Articles | Volume 12, issue 5
https://doi.org/10.5194/gmd-12-1909-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-12-1909-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
14 May 2019
Model description paper |
| 14 May 2019
| 14 May 2019
The Met Office Unified Model Global Atmosphere 7.0/7.1 and JULES Global Land 7.0 configurations
David Walters
CORRESPONDING AUTHOR
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
Anthony J. Baran
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
School of Physics, Astronomy and Mathematics, University of Hertfordshire, Hatfield, AL10 9AB, UK
Ian Boutle
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
Malcolm Brooks
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
Paul Earnshaw
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
John Edwards
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
Kalli Furtado
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
Peter Hill
Department of Meteorology, University of Reading, Reading, RG6 6BB, UK
Adrian Lock
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
James Manners
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
Cyril Morcrette
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
Jane Mulcahy
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
Claudio Sanchez
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
Chris Smith
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
Rachel Stratton
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
Warren Tennant
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
Lorenzo Tomassini
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
Kwinten Van Weverberg
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
Simon Vosper
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
Martin Willett
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
Jo Browse
Centre for Geography, Society and the Environment, University of Exeter – Penryn Campus, Cornwall, TR10 9EZ, UK
Andrew Bushell
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
Kenneth Carslaw
School of Earth and Environment, University of Leeds, Leeds, LS2 9JT, UK
Mohit Dalvi
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
Richard Essery
School of Geosciences, University of Edinburgh, Edinburgh, EH8 9XP, UK
Nicola Gedney
Met Office, Joint Centre for Hydrometeorological Research, Maclean Building, Wallingford, OX10 8BB, UK
Steven Hardiman
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
Ben Johnson
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
Colin Johnson
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
Andy Jones
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
Colin Jones
National Centre for Atmospheric Science, University of Leeds, Leeds, LS2 9JT, UK
Graham Mann
School of Earth and Environment, University of Leeds, Leeds, LS2 9JT, UK
National Centre for Atmospheric Science, University of Leeds, Leeds, LS2 9JT, UK
Sean Milton
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
Heather Rumbold
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
Alistair Sellar
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
Masashi Ujiie
Numerical Prediction Division, Japan Meteorological Agency, 1-3-4 Otemachi, Chiyoda-ku, Tokyo 100-8122, Japan
Michael Whitall
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
Keith Williams
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
Mohamed Zerroukat
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
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Pratapaditya Ghosh, Ian Boutle, Paul Field, Adrian Hill, Marie Mazoyer, Katherine J. Evans, Salil Mahajan, Hyun-Gyu Kang, Min Xu, Wei Zhang, and Hamish Gordon
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Masaru Yoshioka, Daniel P. Grosvenor, Ben B. B. Booth, Colin P. Morice, and Ken S. Carslaw
Atmos. Chem. Phys., 24, 13681–13692, https://doi.org/10.5194/acp-24-13681-2024, https://doi.org/10.5194/acp-24-13681-2024, 2024
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A 2020 regulation has reduced sulfur emissions from shipping by about 80 %, leading to a decrease in atmospheric aerosols that have a cooling effect primarily by affecting cloud properties and amounts. Our climate model simulations predict a global temperature increase of 0.04 K over the next 3 decades as a result, which could contribute to surpassing the Paris Agreement's 1.5 °C target. Reduced aerosols may have also contributed to the recent temperature spikes.
Georgina J. Woolley, Nick Rutter, Leanne Wake, Vincent Vionnet, Chris Derksen, Richard Essery, Philip Marsh, Rosamond Tutton, Branden Walker, Matthieu Lafaysse, and David Pritchard
The Cryosphere, 18, 5685–5711, https://doi.org/10.5194/tc-18-5685-2024, https://doi.org/10.5194/tc-18-5685-2024, 2024
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Parameterisations of Arctic snow processes were implemented into the multi-physics ensemble version of the snow model Crocus (embedded within the Soil, Vegetation, and Snow version 2 land surface model) and evaluated at an Arctic tundra site. Optimal combinations of parameterisations that improved the simulation of density and specific surface area featured modifications that raise wind speeds to increase compaction in surface layers, prevent snowdrift, and increase viscosity in basal layers.
Bettina K. Gier, Manuel Schlund, Pierre Friedlingstein, Chris D. Jones, Colin Jones, Sönke Zaehle, and Veronika Eyring
Biogeosciences, 21, 5321–5360, https://doi.org/10.5194/bg-21-5321-2024, https://doi.org/10.5194/bg-21-5321-2024, 2024
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This study investigates present-day carbon cycle variables in CMIP5 and CMIP6 simulations. Overall, CMIP6 models perform better but also show many remaining biases. A significant improvement in the simulation of photosynthesis in models with a nitrogen cycle is found, with only small differences between emission- and concentration-based simulations. Thus, we recommend using emission-driven simulations in CMIP7 by default and including the nitrogen cycle in all future carbon cycle models.
Benjamin M. Sanderson, Ben B. B. Booth, John Dunne, Veronika Eyring, Rosie A. Fisher, Pierre Friedlingstein, Matthew J. Gidden, Tomohiro Hajima, Chris D. Jones, Colin G. Jones, Andrew King, Charles D. Koven, David M. Lawrence, Jason Lowe, Nadine Mengis, Glen P. Peters, Joeri Rogelj, Chris Smith, Abigail C. Snyder, Isla R. Simpson, Abigail L. S. Swann, Claudia Tebaldi, Tatiana Ilyina, Carl-Friedrich Schleussner, Roland Séférian, Bjørn H. Samset, Detlef van Vuuren, and Sönke Zaehle
Geosci. Model Dev., 17, 8141–8172, https://doi.org/10.5194/gmd-17-8141-2024, https://doi.org/10.5194/gmd-17-8141-2024, 2024
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We discuss how, in order to provide more relevant guidance for climate policy, coordinated climate experiments should adopt a greater focus on simulations where Earth system models are provided with carbon emissions from fossil fuels together with land use change instructions, rather than past approaches that have largely focused on experiments with prescribed atmospheric carbon dioxide concentrations. We discuss how these goals might be achieved in coordinated climate modeling experiments.
Mike Bush, David L. A. Flack, Huw W. Lewis, Sylvia I. Bohnenstengel, Chris J. Short, Charmaine Franklin, Adrian P. Lock, Martin Best, Paul Field, Anne McCabe, Kwinten Van Weverberg, Segolene Berthou, Ian Boutle, Jennifer K. Brooke, Seb Cole, Shaun Cooper, Gareth Dow, John Edwards, Anke Finnenkoetter, Kalli Furtado, Kate Halladay, Kirsty Hanley, Margaret A. Hendry, Adrian Hill, Aravindakshan Jayakumar, Richard W. Jones, Humphrey Lean, Joshua C. K. Lee, Andy Malcolm, Marion Mittermaier, Saji Mohandas, Stuart Moore, Cyril Morcrette, Rachel North, Aurore Porson, Susan Rennie, Nigel Roberts, Belinda Roux, Claudio Sanchez, Chun-Hsu Su, Simon Tucker, Simon Vosper, David Walters, James Warner, Stuart Webster, Mark Weeks, Jonathan Wilkinson, Michael Whitall, Keith D. Williams, and Hugh Zhang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-201, https://doi.org/10.5194/gmd-2024-201, 2024
Revised manuscript accepted for GMD
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RAL configurations define settings for the Unified Model atmosphere and Joint UK Land Environment Simulator. The third version of the Regional Atmosphere and Land (RAL3) science configuration for kilometre and sub-km scale modelling represents a major advance compared to previous versions (RAL2) by delivering a common science definition for applications in tropical and mid-latitude regions. RAL3 has more realistic precipitation distributions and improved representation of clouds and visibility.
Yunqian Zhu, Hideharu Akiyoshi, Valentina Aquila, Elisabeth Asher, Ewa M. Bednarz, Slimane Bekki, Christoph Brühl, Amy H. Butler, Parker Case, Simon Chabrillat, Gabriel Chiodo, Margot Clyne, Lola Falletti, Peter R. Colarco, Eric Fleming, Andrin Jörimann, Mahesh Kovilakam, Gerbrand Koren, Ales Kuchar, Nicolas Lebas, Qing Liang, Cheng-Cheng Liu, Graham Mann, Michael Manyin, Marion Marchand, Olaf Morgenstern, Paul Newman, Luke D. Oman, Freja F. Østerstrøm, Yifeng Peng, David Plummer, Ilaria Quaglia, William Randel, Samuel Rémy, Takashi Sekiya, Stephen Steenrod, Timofei Sukhodolov, Simone Tilmes, Kostas Tsigaridis, Rei Ueyama, Daniele Visioni, Xinyue Wang, Shingo Watanabe, Yousuke Yamashita, Pengfei Yu, Wandi Yu, Jun Zhang, and Zhihong Zhuo
EGUsphere, https://doi.org/10.5194/egusphere-2024-3412, https://doi.org/10.5194/egusphere-2024-3412, 2024
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To understand the climate impact of the 2022 Hunga volcanic eruption, we developed a climate model-observation comparison project. The paper describes the protocols and models that participate in the experiments. We designed several experiments to achieve our goal of this activity: 1. evaluate the climate model performance; 2. understand the Earth system responses to this eruption.
Jeonggyu Kim, Sungmin Park, Greg M. McFarquhar, Anthony J. Baran, Joo Wan Cha, Kyoungmi Lee, Seoung Soo Lee, Chang Hoon Jung, Kyo-Sun Sunny Lim, and Junshik Um
Atmos. Chem. Phys., 24, 12707–12726, https://doi.org/10.5194/acp-24-12707-2024, https://doi.org/10.5194/acp-24-12707-2024, 2024
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We developed idealized models to represent the shapes of ice particles found in deep convective clouds and calculated their single-scattering properties. By comparing these results with in situ measurements, we discovered that a mixture of shape models matches in situ measurements more closely than single-form models or aggregate models. This finding has important implications for enhancing the simulation of single-scattering properties of ice crystals in deep convective clouds.
Philip J. Rasch, Haruki Hirasawa, Mingxuan Wu, Sarah J. Doherty, Robert Wood, Hailong Wang, Andy Jones, James Haywood, and Hansi Singh
Geosci. Model Dev., 17, 7963–7994, https://doi.org/10.5194/gmd-17-7963-2024, https://doi.org/10.5194/gmd-17-7963-2024, 2024
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We introduce a protocol to compare computer climate simulations to better understand a proposed strategy intended to counter warming and climate impacts from greenhouse gas increases. This slightly changes clouds in six ocean regions to reflect more sunlight and cool the Earth. Example changes in clouds and climate are shown for three climate models. Cloud changes differ between the models, but precipitation and surface temperature changes are similar when their cooling effects are made similar.
Claudio Sánchez, Suzanne Gray, Ambrogio Volonté, Florian Pantillon, Ségolène Berthou, and Silvio Davolio
Weather Clim. Dynam., 5, 1429–1455, https://doi.org/10.5194/wcd-5-1429-2024, https://doi.org/10.5194/wcd-5-1429-2024, 2024
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Medicane Ianos was a very intense cyclone that led to harmful impacts over Greece. We explore what processes are important for the forecasting of Medicane Ianos, with the use of the Met Office weather model. There was a preceding precipitation event before Ianos’s birth, whose energetics generated a bubble in the tropopause. This bubble created the necessary conditions for Ianos to emerge and strengthen, and the processes are enhanced in simulations with a warmer Mediterranean Sea.
Natalie G. Ratcliffe, Claire L. Ryder, Nicolas Bellouin, Stephanie Woodward, Anthony Jones, Ben Johnson, Lisa-Maria Wieland, Maximilian Dollner, Josef Gasteiger, and Bernadett Weinzierl
Atmos. Chem. Phys., 24, 12161–12181, https://doi.org/10.5194/acp-24-12161-2024, https://doi.org/10.5194/acp-24-12161-2024, 2024
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Large mineral dust particles are more abundant in the atmosphere than expected and have different impacts on the environment than small particles, which are better represented in climate models. We use aircraft measurements to assess a climate model representation of large-dust transport. We find that the model underestimates the amount of large dust at all stages of transport and that fast removal of the large particles increases this underestimation with distance from the Sahara.
Colin G. Jones, Fanny Adloff, Ben B. B. Booth, Peter M. Cox, Veronika Eyring, Pierre Friedlingstein, Katja Frieler, Helene T. Hewitt, Hazel A. Jeffery, Sylvie Joussaume, Torben Koenigk, Bryan N. Lawrence, Eleanor O'Rourke, Malcolm J. Roberts, Benjamin M. Sanderson, Roland Séférian, Samuel Somot, Pier Luigi Vidale, Detlef van Vuuren, Mario Acosta, Mats Bentsen, Raffaele Bernardello, Richard Betts, Ed Blockley, Julien Boé, Tom Bracegirdle, Pascale Braconnot, Victor Brovkin, Carlo Buontempo, Francisco Doblas-Reyes, Markus Donat, Italo Epicoco, Pete Falloon, Sandro Fiore, Thomas Frölicher, Neven S. Fučkar, Matthew J. Gidden, Helge F. Goessling, Rune Grand Graversen, Silvio Gualdi, José M. Gutiérrez, Tatiana Ilyina, Daniela Jacob, Chris D. Jones, Martin Juckes, Elizabeth Kendon, Erik Kjellström, Reto Knutti, Jason Lowe, Matthew Mizielinski, Paola Nassisi, Michael Obersteiner, Pierre Regnier, Romain Roehrig, David Salas y Mélia, Carl-Friedrich Schleussner, Michael Schulz, Enrico Scoccimarro, Laurent Terray, Hannes Thiemann, Richard A. Wood, Shuting Yang, and Sönke Zaehle
Earth Syst. Dynam., 15, 1319–1351, https://doi.org/10.5194/esd-15-1319-2024, https://doi.org/10.5194/esd-15-1319-2024, 2024
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We propose a number of priority areas for the international climate research community to address over the coming decade. Advances in these areas will both increase our understanding of past and future Earth system change, including the societal and environmental impacts of this change, and deliver significantly improved scientific support to international climate policy, such as future IPCC assessments and the UNFCCC Global Stocktake.
Xinyue Shao, Minghuai Wang, Xinyi Dong, Yaman Liu, Wenxiang Shen, Stephen R. Arnold, Leighton A. Regayre, Meinrat O. Andreae, Mira L. Pöhlker, Duseong S. Jo, Man Yue, and Ken S. Carslaw
Atmos. Chem. Phys., 24, 11365–11389, https://doi.org/10.5194/acp-24-11365-2024, https://doi.org/10.5194/acp-24-11365-2024, 2024
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Highly oxygenated organic molecules (HOMs) play an important role in atmospheric new particle formation (NPF). By semi-explicitly coupling the chemical mechanism of HOMs and a comprehensive nucleation scheme in a global climate model, the updated model shows better agreement with measurements of nucleation rate, growth rate, and NPF event frequency. Our results reveal that HOM-driven NPF leads to a considerable increase in particle and cloud condensation nuclei burden globally.
Richard Essery, Giulia Mazzotti, Sarah Barr, Tobias Jonas, Tristan Quaife, and Nick Rutter
EGUsphere, https://doi.org/10.5194/egusphere-2024-2546, https://doi.org/10.5194/egusphere-2024-2546, 2024
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How forests influence accumulation and melt of snow on the ground is of long-standing interest, but uncertainty remains in how best to model forest snow processes. We developed the Flexible Snow Model version 2 to quantify these uncertainties. In a first model demonstration, how unloading of intercepted snow from the forest canopy is represented is responsible for the largest uncertainty. Global mapping of forest distribution is also likely to be a large source of uncertainty in existing models.
Cecile B. Menard, Sirpa Rasmus, Ioanna Merkouriadi, Gianpaolo Balsamo, Annett Bartsch, Chris Derksen, Florent Domine, Marie Dumont, Dorothee Ehrich, Richard Essery, Bruce C. Forbes, Gerhard Krinner, David Lawrence, Glen Liston, Heidrun Matthes, Nick Rutter, Melody Sandells, Martin Schneebeli, and Sari Stark
The Cryosphere, 18, 4671–4686, https://doi.org/10.5194/tc-18-4671-2024, https://doi.org/10.5194/tc-18-4671-2024, 2024
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Computer models, like those used in climate change studies, are written by modellers who have to decide how best to construct the models in order to satisfy the purpose they serve. Using snow modelling as an example, we examine the process behind the decisions to understand what motivates or limits modellers in their decision-making. We find that the context in which research is undertaken is often more crucial than scientific limitations. We argue for more transparency in our research practice.
Florian Pantillon, Silvio Davolio, Elenio Avolio, Carlos Calvo-Sancho, Diego Saul Carrió, Stavros Dafis, Emanuele Silvio Gentile, Juan Jesus Gonzalez-Aleman, Suzanne Gray, Mario Marcello Miglietta, Platon Patlakas, Ioannis Pytharoulis, Didier Ricard, Antonio Ricchi, Claudio Sanchez, and Emmanouil Flaounas
Weather Clim. Dynam., 5, 1187–1205, https://doi.org/10.5194/wcd-5-1187-2024, https://doi.org/10.5194/wcd-5-1187-2024, 2024
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Cyclone Ianos of September 2020 was a high-impact but poorly predicted medicane (Mediterranean hurricane). A community effort of numerical modelling provides robust results to improve prediction. It is found that the representation of local thunderstorms controlled the interaction of Ianos with a jet stream at larger scales and its subsequent evolution. The results help us understand the peculiar dynamics of medicanes and provide guidance for the next generation of weather and climate models.
Melody Sandells, Nick Rutter, Kirsty Wivell, Richard Essery, Stuart Fox, Chawn Harlow, Ghislain Picard, Alexandre Roy, Alain Royer, and Peter Toose
The Cryosphere, 18, 3971–3990, https://doi.org/10.5194/tc-18-3971-2024, https://doi.org/10.5194/tc-18-3971-2024, 2024
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Satellite microwave observations are used for weather forecasting. In Arctic regions this is complicated by natural emission from snow. By simulating airborne observations from in situ measurements of snow, this study shows how snow properties affect the signal within the atmosphere. Fresh snowfall between flights changed airborne measurements. Good knowledge of snow layering and structure can be used to account for the effects of snow and could unlock these data to improve forecasts.
Jacob Perez, Amanda C. Maycock, Stephen D. Griffiths, Steven C. Hardiman, and Christine M. McKenna
Weather Clim. Dynam., 5, 1061–1078, https://doi.org/10.5194/wcd-5-1061-2024, https://doi.org/10.5194/wcd-5-1061-2024, 2024
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This study assesses existing methods for identifying the position and tilt of the North Atlantic eddy-driven jet, proposing a new feature-based approach. The new method overcomes limitations of other methods, offering a more robust characterisation. Contrary to prior findings, the distribution of daily latitudes shows no distinct multi-modal structure, challenging the notion of preferred jet stream latitudes or regimes. This research enhances our understanding of North Atlantic dynamics.
Richard J. Pope, Fiona M. O'Connor, Mohit Dalvi, Brian J. Kerridge, Richard Siddans, Barry G. Latter, Brice Barret, Eric Le Flochmoen, Anne Boynard, Martyn P. Chipperfield, Wuhu Feng, Matilda A. Pimlott, Sandip S. Dhomse, Christian Retscher, Catherine Wespes, and Richard Rigby
Atmos. Chem. Phys., 24, 9177–9195, https://doi.org/10.5194/acp-24-9177-2024, https://doi.org/10.5194/acp-24-9177-2024, 2024
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Ozone is a potent air pollutant in the lower troposphere, with adverse impacts on human health. Satellite records of tropospheric ozone currently show large-scale inconsistencies in long-term trends. Our detailed study of the potential factors (e.g. satellite errors, where the satellite can observe ozone) potentially driving these inconsistencies found that, in North America, Europe, and East Asia, the underlying trends are typically small with large uncertainties.
Alkiviadis Kalisoras, Aristeidis K. Georgoulias, Dimitris Akritidis, Robert J. Allen, Vaishali Naik, Chaincy Kuo, Sophie Szopa, Pierre Nabat, Dirk Olivié, Twan van Noije, Philippe Le Sager, David Neubauer, Naga Oshima, Jane Mulcahy, Larry W. Horowitz, and Prodromos Zanis
Atmos. Chem. Phys., 24, 7837–7872, https://doi.org/10.5194/acp-24-7837-2024, https://doi.org/10.5194/acp-24-7837-2024, 2024
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Effective radiative forcing (ERF) is a metric for estimating how human activities and natural agents change the energy flow into and out of the Earth’s climate system. We investigate the anthropogenic aerosol ERF, and we estimate the contribution of individual processes to the total ERF using simulations from Earth system models within the Coupled Model Intercomparison Project Phase 6 (CMIP6). Our findings highlight that aerosol–cloud interactions drive ERF variability during the last 150 years.
Karina McCusker, Anthony J. Baran, Chris Westbrook, Stuart Fox, Patrick Eriksson, Richard Cotton, Julien Delanoë, and Florian Ewald
Atmos. Meas. Tech., 17, 3533–3552, https://doi.org/10.5194/amt-17-3533-2024, https://doi.org/10.5194/amt-17-3533-2024, 2024
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Polarised radiative transfer simulations are performed using an atmospheric model based on in situ measurements. These are compared to large polarisation measurements to explore whether such measurements can provide information on cloud ice, e.g. particle shape and orientation. We find that using oriented particle models with shapes based on imagery generally allows for accurate simulations. However, results are sensitive to shape assumptions such as the choice of single crystals or aggregates.
Marielle Saunois, Adrien Martinez, Benjamin Poulter, Zhen Zhang, Peter Raymond, Pierre Regnier, Joseph G. Canadell, Robert B. Jackson, Prabir K. Patra, Philippe Bousquet, Philippe Ciais, Edward J. Dlugokencky, Xin Lan, George H. Allen, David Bastviken, David J. Beerling, Dmitry A. Belikov, Donald R. Blake, Simona Castaldi, Monica Crippa, Bridget R. Deemer, Fraser Dennison, Giuseppe Etiope, Nicola Gedney, Lena Höglund-Isaksson, Meredith A. Holgerson, Peter O. Hopcroft, Gustaf Hugelius, Akihito Ito, Atul K. Jain, Rajesh Janardanan, Matthew S. Johnson, Thomas Kleinen, Paul Krummel, Ronny Lauerwald, Tingting Li, Xiangyu Liu, Kyle C. McDonald, Joe R. Melton, Jens Mühle, Jurek Müller, Fabiola Murguia-Flores, Yosuke Niwa, Sergio Noce, Shufen Pan, Robert J. Parker, Changhui Peng, Michel Ramonet, William J. Riley, Gerard Rocher-Ros, Judith A. Rosentreter, Motoki Sasakawa, Arjo Segers, Steven J. Smith, Emily H. Stanley, Joel Thanwerdas, Hanquin Tian, Aki Tsuruta, Francesco N. Tubiello, Thomas S. Weber, Guido van der Werf, Doug E. Worthy, Yi Xi, Yukio Yoshida, Wenxin Zhang, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-115, https://doi.org/10.5194/essd-2024-115, 2024
Revised manuscript accepted for ESSD
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Methane (CH4) is the second most important human-influenced greenhouse gas in terms of climate forcing after carbon dioxide (CO2). A consortium of multi-disciplinary scientists synthesize and update the budget of the sources and sinks of CH4. This edition benefits from important progresses in estimating emissions from lakes and ponds, reservoirs, and streams and rivers. For the 2010s decade, global CH4 emissions are estimated at 575 Tg CH4 yr-1, including ~65 % from anthropogenic sources.
Julien Meloche, Melody Sandells, Henning Löwe, Nick Rutter, Richard Essery, Ghislain Picard, Randall K. Scharien, Alexandre Langlois, Matthias Jaggi, Josh King, Peter Toose, Jérôme Bouffard, Alessandro Di Bella, and Michele Scagliola
EGUsphere, https://doi.org/10.5194/egusphere-2024-1583, https://doi.org/10.5194/egusphere-2024-1583, 2024
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Sea ice thickness is essential for climate studies. Radar altimetry has provided sea ice thickness measurement, but uncertainty arises from interaction of the signal with the snow cover. Therefore, modelling the signal interaction with the snow is necessary to improve retrieval. A radar model was used to simulate the radar signal from the snow-covered sea ice. This work paved the way to improved physical algorithm to retrieve snow depth and sea ice thickness for radar altimeter missions.
Jean-Paul Vernier, Thomas J. Aubry, Claudia Timmreck, Anja Schmidt, Lieven Clarisse, Fred Prata, Nicolas Theys, Andrew T. Prata, Graham Mann, Hyundeok Choi, Simon Carn, Richard Rigby, Susan C. Loughlin, and John A. Stevenson
Atmos. Chem. Phys., 24, 5765–5782, https://doi.org/10.5194/acp-24-5765-2024, https://doi.org/10.5194/acp-24-5765-2024, 2024
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The 2019 Raikoke eruption (Kamchatka, Russia) generated one of the largest emissions of particles and gases into the stratosphere since the 1991 Mt. Pinatubo eruption. The Volcano Response (VolRes) initiative, an international effort, provided a platform for the community to share information about this eruption and assess its climate impact. The eruption led to a minor global surface cooling of 0.02 °C in 2020 which is negligible relative to warming induced by human greenhouse gas emissions.
Christina V. Brodowsky, Timofei Sukhodolov, Gabriel Chiodo, Valentina Aquila, Slimane Bekki, Sandip S. Dhomse, Michael Höpfner, Anton Laakso, Graham W. Mann, Ulrike Niemeier, Giovanni Pitari, Ilaria Quaglia, Eugene Rozanov, Anja Schmidt, Takashi Sekiya, Simone Tilmes, Claudia Timmreck, Sandro Vattioni, Daniele Visioni, Pengfei Yu, Yunqian Zhu, and Thomas Peter
Atmos. Chem. Phys., 24, 5513–5548, https://doi.org/10.5194/acp-24-5513-2024, https://doi.org/10.5194/acp-24-5513-2024, 2024
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The aerosol layer is an essential part of the climate system. We characterize the sulfur budget in a volcanically quiescent (background) setting, with a special focus on the sulfate aerosol layer using, for the first time, a multi-model approach. The aim is to identify weak points in the representation of the atmospheric sulfur budget in an intercomparison of nine state-of-the-art coupled global circulation models.
Emma Howard, Steven Woolnough, Nicholas Klingaman, Daniel Shipley, Claudio Sanchez, Simon C. Peatman, Cathryn E. Birch, and Adrian J. Matthews
Geosci. Model Dev., 17, 3815–3837, https://doi.org/10.5194/gmd-17-3815-2024, https://doi.org/10.5194/gmd-17-3815-2024, 2024
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This paper describes a coupled atmosphere–mixed-layer ocean simulation setup that will be used to study weather processes in Southeast Asia. The set-up has been used to compare high-resolution simulations, which are able to partially resolve storms, to coarser simulations, which cannot. We compare the model performance at representing variability of rainfall and sea surface temperatures across length scales between the coarse and fine models.
Victoria R. Dutch, Nick Rutter, Leanne Wake, Oliver Sonnentag, Gabriel Hould Gosselin, Melody Sandells, Chris Derksen, Branden Walker, Gesa Meyer, Richard Essery, Richard Kelly, Phillip Marsh, Julia Boike, and Matteo Detto
Biogeosciences, 21, 825–841, https://doi.org/10.5194/bg-21-825-2024, https://doi.org/10.5194/bg-21-825-2024, 2024
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We undertake a sensitivity study of three different parameters on the simulation of net ecosystem exchange (NEE) during the snow-covered non-growing season at an Arctic tundra site. Simulations are compared to eddy covariance measurements, with near-zero NEE simulated despite observed CO2 release. We then consider how to parameterise the model better in Arctic tundra environments on both sub-seasonal timescales and cumulatively throughout the snow-covered non-growing season.
Atabek Umirbekov, Richard Essery, and Daniel Müller
Geosci. Model Dev., 17, 911–929, https://doi.org/10.5194/gmd-17-911-2024, https://doi.org/10.5194/gmd-17-911-2024, 2024
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We present a parsimonious snow model which simulates snow mass without the need for extensive calibration. The model is based on a machine learning algorithm that has been trained on diverse set of daily observations of snow accumulation or melt, along with corresponding climate and topography data. We validated the model using in situ data from numerous new locations. The model provides a promising solution for accurate snow mass estimation across regions where in situ data are limited.
Rolf Müller, Ulrich Pöschl, Thomas Koop, Thomas Peter, and Ken Carslaw
Atmos. Chem. Phys., 23, 15445–15453, https://doi.org/10.5194/acp-23-15445-2023, https://doi.org/10.5194/acp-23-15445-2023, 2023
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Paul J. Crutzen was a pioneer in atmospheric sciences and a kind-hearted, humorous person with empathy for the private lives of his colleagues and students. He made fundamental scientific contributions to a wide range of scientific topics in all parts of the atmosphere. Paul was among the founders of the journal Atmospheric Chemistry and Physics. His work will continue to be a guide for generations of scientists and environmental policymakers to come.
Jim M. Haywood, Andy Jones, Anthony C. Jones, Paul Halloran, and Philip J. Rasch
Atmos. Chem. Phys., 23, 15305–15324, https://doi.org/10.5194/acp-23-15305-2023, https://doi.org/10.5194/acp-23-15305-2023, 2023
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The difficulties in ameliorating global warming and the associated climate change via conventional mitigation are well documented, with all climate model scenarios exceeding 1.5 °C above the preindustrial level in the near future. There is therefore a growing interest in geoengineering to reflect a greater proportion of sunlight back to space and offset some of the global warming. We use a state-of-the-art Earth-system model to investigate two of the most prominent geoengineering strategies.
Lee de Mora, Ranjini Swaminathan, Richard P. Allan, Jerry C. Blackford, Douglas I. Kelley, Phil Harris, Chris D. Jones, Colin G. Jones, Spencer Liddicoat, Robert J. Parker, Tristan Quaife, Jeremy Walton, and Andrew Yool
Earth Syst. Dynam., 14, 1295–1315, https://doi.org/10.5194/esd-14-1295-2023, https://doi.org/10.5194/esd-14-1295-2023, 2023
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We investigate the flux of carbon from the atmosphere into the land surface and ocean for multiple models and over a range of future scenarios. We did this by comparing simulations after the same change in the global-mean near-surface temperature. Using this method, we show that the choice of scenario can impact the carbon allocation to the land, ocean, and atmosphere. Scenarios with higher emissions reach the same warming levels sooner, but also with relatively more carbon in the atmosphere.
Hamza Ahsan, Hailong Wang, Jingbo Wu, Mingxuan Wu, Steven J. Smith, Susanne Bauer, Harrison Suchyta, Dirk Olivié, Gunnar Myhre, Hitoshi Matsui, Huisheng Bian, Jean-François Lamarque, Ken Carslaw, Larry Horowitz, Leighton Regayre, Mian Chin, Michael Schulz, Ragnhild Bieltvedt Skeie, Toshihiko Takemura, and Vaishali Naik
Atmos. Chem. Phys., 23, 14779–14799, https://doi.org/10.5194/acp-23-14779-2023, https://doi.org/10.5194/acp-23-14779-2023, 2023
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We examine the impact of the assumed effective height of SO2 injection, SO2 and BC emission seasonality, and the assumed fraction of SO2 emissions injected as SO4 on climate and chemistry model results. We find that the SO2 injection height has a large impact on surface SO2 concentrations and, in some models, radiative flux. These assumptions are a
hiddensource of inter-model variability and may be leading to bias in some climate model results.
Jean Emmanuel Sicart, Victor Ramseyer, Ghislain Picard, Laurent Arnaud, Catherine Coulaud, Guilhem Freche, Damien Soubeyrand, Yves Lejeune, Marie Dumont, Isabelle Gouttevin, Erwan Le Gac, Frédéric Berger, Jean-Matthieu Monnet, Laurent Borgniet, Éric Mermin, Nick Rutter, Clare Webster, and Richard Essery
Earth Syst. Sci. Data, 15, 5121–5133, https://doi.org/10.5194/essd-15-5121-2023, https://doi.org/10.5194/essd-15-5121-2023, 2023
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Forests strongly modify the accumulation, metamorphism and melting of snow in midlatitude and high-latitude regions. Two field campaigns during the winters 2016–17 and 2017–18 were conducted in a coniferous forest in the French Alps to study interactions between snow and vegetation. This paper presents the field site, instrumentation and collection methods. The observations include forest characteristics, meteorology, snow cover and snow interception by the canopy during precipitation events.
Matthew Henry, Jim Haywood, Andy Jones, Mohit Dalvi, Alice Wells, Daniele Visioni, Ewa M. Bednarz, Douglas G. MacMartin, Walker Lee, and Mari R. Tye
Atmos. Chem. Phys., 23, 13369–13385, https://doi.org/10.5194/acp-23-13369-2023, https://doi.org/10.5194/acp-23-13369-2023, 2023
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Solar climate interventions, such as injecting sulfur in the stratosphere, may be used to offset some of the adverse impacts of global warming. We use two independently developed Earth system models to assess the uncertainties around stratospheric sulfur injections. The injection locations and amounts are optimized to maintain the same pattern of surface temperature. While both models show reduced warming, the change in rainfall patterns (even without sulfur injections) is uncertain.
Kirsty Wivell, Stuart Fox, Melody Sandells, Chawn Harlow, Richard Essery, and Nick Rutter
The Cryosphere, 17, 4325–4341, https://doi.org/10.5194/tc-17-4325-2023, https://doi.org/10.5194/tc-17-4325-2023, 2023
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Satellite microwave observations improve weather forecasts, but to use these observations in the Arctic, snow emission must be known. This study uses airborne and in situ snow observations to validate emissivity simulations for two- and three-layer snowpacks at key frequencies for weather prediction. We assess the impact of thickness, grain size and density in key snow layers, which will help inform development of physical snow models that provide snow profile input to emissivity simulations.
Denis E. Sergeev, Nathan J. Mayne, Thomas Bendall, Ian A. Boutle, Alex Brown, Iva Kavčič, James Kent, Krisztian Kohary, James Manners, Thomas Melvin, Enrico Olivier, Lokesh K. Ragta, Ben Shipway, Jon Wakelin, Nigel Wood, and Mohamed Zerroukat
Geosci. Model Dev., 16, 5601–5626, https://doi.org/10.5194/gmd-16-5601-2023, https://doi.org/10.5194/gmd-16-5601-2023, 2023
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Three-dimensional climate models are one of the best tools we have to study planetary atmospheres. Here, we apply LFRic-Atmosphere, a new model developed by the Met Office, to seven different scenarios for terrestrial planetary climates, including four for the exoplanet TRAPPIST-1e, a primary target for future observations. LFRic-Atmosphere reproduces these scenarios within the spread of the existing models across a range of key climatic variables, justifying its use in future exoplanet studies.
Leighton A. Regayre, Lucia Deaconu, Daniel P. Grosvenor, David M. H. Sexton, Christopher Symonds, Tom Langton, Duncan Watson-Paris, Jane P. Mulcahy, Kirsty J. Pringle, Mark Richardson, Jill S. Johnson, John W. Rostron, Hamish Gordon, Grenville Lister, Philip Stier, and Ken S. Carslaw
Atmos. Chem. Phys., 23, 8749–8768, https://doi.org/10.5194/acp-23-8749-2023, https://doi.org/10.5194/acp-23-8749-2023, 2023
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Aerosol forcing of Earth’s energy balance has persisted as a major cause of uncertainty in climate simulations over generations of climate model development. We show that structural deficiencies in a climate model are exposed by comprehensively exploring parametric uncertainty and that these deficiencies limit how much the model uncertainty can be reduced through observational constraint. This provides a future pathway towards building models with greater physical realism and lower uncertainty.
Camilla Mathison, Eleanor Burke, Andrew J. Hartley, Douglas I. Kelley, Chantelle Burton, Eddy Robertson, Nicola Gedney, Karina Williams, Andy Wiltshire, Richard J. Ellis, Alistair A. Sellar, and Chris D. Jones
Geosci. Model Dev., 16, 4249–4264, https://doi.org/10.5194/gmd-16-4249-2023, https://doi.org/10.5194/gmd-16-4249-2023, 2023
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This paper describes and evaluates a new modelling methodology to quantify the impacts of climate change on water, biomes and the carbon cycle. We have created a new configuration and set-up for the JULES-ES land surface model, driven by bias-corrected historical and future climate model output provided by the Inter-Sectoral Impacts Model Intercomparison Project (ISIMIP). This allows us to compare projections of the impacts of climate change across multiple impact models and multiple sectors.
Chenwei Fang, Jim M. Haywood, Ju Liang, Ben T. Johnson, Ying Chen, and Bin Zhu
Atmos. Chem. Phys., 23, 8341–8368, https://doi.org/10.5194/acp-23-8341-2023, https://doi.org/10.5194/acp-23-8341-2023, 2023
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The responses of Asian summer monsoon duration and intensity to air pollution mitigation are identified given the net-zero future. We show that reducing scattering aerosols makes the rainy season longer and stronger across South Asia and East Asia but that absorbing aerosol reduction has the opposite effect. Our results hint at distinct monsoon responses to emission controls that target different aerosols.
Christian Ferrarin, Florian Pantillon, Silvio Davolio, Marco Bajo, Mario Marcello Miglietta, Elenio Avolio, Diego S. Carrió, Ioannis Pytharoulis, Claudio Sanchez, Platon Patlakas, Juan Jesús González-Alemán, and Emmanouil Flaounas
Nat. Hazards Earth Syst. Sci., 23, 2273–2287, https://doi.org/10.5194/nhess-23-2273-2023, https://doi.org/10.5194/nhess-23-2273-2023, 2023
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The combined use of meteorological and ocean models enabled the analysis of extreme sea conditions driven by Medicane Ianos, which hit the western coast of Greece on 18 September 2020, flooding and damaging the coast. The large spread associated with the ensemble highlighted the high model uncertainty in simulating such an extreme weather event. The different simulations have been used for outlining hazard scenarios that represent a fundamental component of the coastal risk assessment.
Daniel P. Grosvenor and Kenneth S. Carslaw
Atmos. Chem. Phys., 23, 6743–6773, https://doi.org/10.5194/acp-23-6743-2023, https://doi.org/10.5194/acp-23-6743-2023, 2023
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We determine what causes long-term trends in short-wave (SW) radiative fluxes in two climate models. A positive trend occurs between 1850 and 1970 (increasing SW reflection) and a negative trend between 1970 and 2014; the pre-1970 positive trend is mainly driven by an increase in cloud droplet number concentrations due to increases in aerosol, and the 1970–2014 trend is driven by a decrease in cloud fraction, which we attribute to changes in clouds caused by greenhouse gas-induced warming.
Ernesto Reyes-Villegas, Douglas Lowe, Jill S. Johnson, Kenneth S. Carslaw, Eoghan Darbyshire, Michael Flynn, James D. Allan, Hugh Coe, Ying Chen, Oliver Wild, Scott Archer-Nicholls, Alex Archibald, Siddhartha Singh, Manish Shrivastava, Rahul A. Zaveri, Vikas Singh, Gufran Beig, Ranjeet Sokhi, and Gordon McFiggans
Atmos. Chem. Phys., 23, 5763–5782, https://doi.org/10.5194/acp-23-5763-2023, https://doi.org/10.5194/acp-23-5763-2023, 2023
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Organic aerosols (OAs), their sources and their processes remain poorly understood. The volatility basis set (VBS) approach, implemented in air quality models such as WRF-Chem, can be a useful tool to describe primary OA (POA) production and aging. However, the main disadvantage is its complexity. We used a Gaussian process simulator to reproduce model results and to estimate the sources of model uncertainty. We do this by comparing the outputs with OA observations made at Delhi, India, in 2018.
George Manville, Thomas G. Bell, Jane P. Mulcahy, Rafel Simó, Martí Galí, Anoop S. Mahajan, Shrivardhan Hulswar, and Paul R. Halloran
Biogeosciences, 20, 1813–1828, https://doi.org/10.5194/bg-20-1813-2023, https://doi.org/10.5194/bg-20-1813-2023, 2023
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We present the first global investigation of controls on seawater dimethylsulfide (DMS) spatial variability over scales of up to 100 km. Sea surface height anomalies, density, and chlorophyll a help explain almost 80 % of DMS variability. The results suggest that physical and biogeochemical processes play an equally important role in controlling DMS variability. These data provide independent confirmation that existing parameterisations of seawater DMS concentration use appropriate variables.
Xuemei Wang, Hamish Gordon, Daniel P. Grosvenor, Meinrat O. Andreae, and Ken S. Carslaw
Atmos. Chem. Phys., 23, 4431–4461, https://doi.org/10.5194/acp-23-4431-2023, https://doi.org/10.5194/acp-23-4431-2023, 2023
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New particle formation in the upper troposphere is important for the global boundary layer aerosol population, and they can be transported downward in Amazonia. We use a global and a regional model to quantify the number of aerosols that are formed at high altitude and transported downward in a 1000 km region. We find that the majority of the aerosols are from outside the region. This suggests that the 1000 km region is unlikely to be a
closed loopfor aerosol formation, transport and growth.
Edward Gryspeerdt, Adam C. Povey, Roy G. Grainger, Otto Hasekamp, N. Christina Hsu, Jane P. Mulcahy, Andrew M. Sayer, and Armin Sorooshian
Atmos. Chem. Phys., 23, 4115–4122, https://doi.org/10.5194/acp-23-4115-2023, https://doi.org/10.5194/acp-23-4115-2023, 2023
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The impact of aerosols on clouds is one of the largest uncertainties in the human forcing of the climate. Aerosol can increase the concentrations of droplets in clouds, but observational and model studies produce widely varying estimates of this effect. We show that these estimates can be reconciled if only polluted clouds are studied, but this is insufficient to constrain the climate impact of aerosol. The uncertainty in aerosol impact on clouds is currently driven by cases with little aerosol.
Heather S. Rumbold, Richard J. J. Gilham, and Martin J. Best
Geosci. Model Dev., 16, 1875–1886, https://doi.org/10.5194/gmd-16-1875-2023, https://doi.org/10.5194/gmd-16-1875-2023, 2023
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The Joint UK Land Environment Simulator (JULES) uses a tiled representation of land cover but can only model a single dominant soil type within a grid box; hence there is no representation of sub-grid soil heterogeneity. This paper evaluates a new surface–soil tiling scheme in JULES and demonstrates the impacts of the scheme using several soil tiling approaches. Results show that soil tiling has an impact on the water and energy exchanges due to the way vegetation accesses the soil moisture.
Alice F. Wells, Andy Jones, Martin Osborne, Lilly Damany-Pearce, Daniel G. Partridge, and James M. Haywood
Atmos. Chem. Phys., 23, 3985–4007, https://doi.org/10.5194/acp-23-3985-2023, https://doi.org/10.5194/acp-23-3985-2023, 2023
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In 2019 the Raikoke volcano erupted explosively, emitting the largest injection of SO2 into the stratosphere since 2011. Observations indicated that a large amount of volcanic ash was also injected. Previous studies have identified that volcanic ash can prolong the lifetime of stratospheric aerosol optical depth, which we explore in UKESM1. Comparisons to observations suggest that including ash in model emission schemes can improve the representation of volcanic plumes in global climate models.
Mike Bush, Ian Boutle, John Edwards, Anke Finnenkoetter, Charmaine Franklin, Kirsty Hanley, Aravindakshan Jayakumar, Huw Lewis, Adrian Lock, Marion Mittermaier, Saji Mohandas, Rachel North, Aurore Porson, Belinda Roux, Stuart Webster, and Mark Weeks
Geosci. Model Dev., 16, 1713–1734, https://doi.org/10.5194/gmd-16-1713-2023, https://doi.org/10.5194/gmd-16-1713-2023, 2023
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Building on the baseline of RAL1, the RAL2 science configuration is used for regional modelling around the UM partnership and in operations at the Met Office. RAL2 has been tested in different parts of the world including Australia, India and the UK. RAL2 increases medium and low cloud amounts in the mid-latitudes compared to RAL1, leading to improved cloud forecasts and a reduced diurnal cycle of screen temperature. There is also a reduction in the frequency of heavier precipitation rates.
Jane P. Mulcahy, Colin G. Jones, Steven T. Rumbold, Till Kuhlbrodt, Andrea J. Dittus, Edward W. Blockley, Andrew Yool, Jeremy Walton, Catherine Hardacre, Timothy Andrews, Alejandro Bodas-Salcedo, Marc Stringer, Lee de Mora, Phil Harris, Richard Hill, Doug Kelley, Eddy Robertson, and Yongming Tang
Geosci. Model Dev., 16, 1569–1600, https://doi.org/10.5194/gmd-16-1569-2023, https://doi.org/10.5194/gmd-16-1569-2023, 2023
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Recent global climate models simulate historical global mean surface temperatures which are too cold, possibly to due to excessive aerosol cooling. This raises questions about the models' ability to simulate important climate processes and reduces confidence in future climate predictions. We present a new version of the UK Earth System Model, which has an improved aerosols simulation and a historical temperature record. Interestingly, the long-term response to CO2 remains largely unchanged.
Ruth Price, Andrea Baccarini, Julia Schmale, Paul Zieger, Ian M. Brooks, Paul Field, and Ken S. Carslaw
Atmos. Chem. Phys., 23, 2927–2961, https://doi.org/10.5194/acp-23-2927-2023, https://doi.org/10.5194/acp-23-2927-2023, 2023
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Arctic clouds can control how much energy is absorbed by the surface or reflected back to space. Using a computer model of the atmosphere we investigated the formation of atmospheric particles that allow cloud droplets to form. We found that particles formed aloft are transported to the lowest part of the Arctic atmosphere and that this is a key source of particles. Our results have implications for the way Arctic clouds will behave in the future as climate change continues to impact the region.
Philip E. Bett, Adam A. Scaife, Steven C. Hardiman, Hazel E. Thornton, Xiaocen Shen, Lin Wang, and Bo Pang
Weather Clim. Dynam., 4, 213–228, https://doi.org/10.5194/wcd-4-213-2023, https://doi.org/10.5194/wcd-4-213-2023, 2023
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Sudden-stratospheric-warming (SSW) events can severely affect the subsequent weather at the surface. We use a large ensemble of climate model hindcasts to investigate features of the climate that make strong impacts more likely through negative NAO conditions. This allows a more robust assessment than using observations alone. Air pressure over the Arctic prior to an SSW and the zonal-mean zonal wind in the lower stratosphere have the strongest relationship with the subsequent NAO response.
Alexander D. James, Finn Pace, Sebastien N. F. Sikora, Graham W. Mann, John M. C. Plane, and Benjamin J. Murray
Atmos. Chem. Phys., 23, 2215–2233, https://doi.org/10.5194/acp-23-2215-2023, https://doi.org/10.5194/acp-23-2215-2023, 2023
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Here, we examine whether several materials of meteoric origin can nucleate crystallisation in stratospheric cloud droplets which would affect ozone depletion. We find that material which could fragment on atmospheric entry without melting is unlikely to be present in high enough concentration in the stratosphere to contribute to observed crystalline clouds. Material which ablates completely then forms a new solid known as meteoric smoke can provide enough nucleation to explain observed clouds.
Danny McCulloch, Denis E. Sergeev, Nathan Mayne, Matthew Bate, James Manners, Ian Boutle, Benjamin Drummond, and Kristzian Kohary
Geosci. Model Dev., 16, 621–657, https://doi.org/10.5194/gmd-16-621-2023, https://doi.org/10.5194/gmd-16-621-2023, 2023
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We present results from the Met Office Unified Model (UM) to study the dry Martian climate. We describe our model set-up conditions and run two scenarios, with radiatively active/inactive dust. We compare both scenarios to results from an existing Mars climate model, the planetary climate model. We find good agreement in winds and air temperatures, but dust amounts differ between models. This study highlights the importance of using the UM for future Mars research.
Yangxin Chen, Duoying Ji, Qian Zhang, John C. Moore, Olivier Boucher, Andy Jones, Thibaut Lurton, Michael J. Mills, Ulrike Niemeier, Roland Séférian, and Simone Tilmes
Earth Syst. Dynam., 14, 55–79, https://doi.org/10.5194/esd-14-55-2023, https://doi.org/10.5194/esd-14-55-2023, 2023
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Solar geoengineering has been proposed as a way of counteracting the warming effects of increasing greenhouse gases by reflecting solar radiation. This work shows that solar geoengineering can slow down the northern-high-latitude permafrost degradation but cannot preserve the permafrost ecosystem as that under a climate of the same warming level without solar geoengineering.
Ilaria Quaglia, Claudia Timmreck, Ulrike Niemeier, Daniele Visioni, Giovanni Pitari, Christina Brodowsky, Christoph Brühl, Sandip S. Dhomse, Henning Franke, Anton Laakso, Graham W. Mann, Eugene Rozanov, and Timofei Sukhodolov
Atmos. Chem. Phys., 23, 921–948, https://doi.org/10.5194/acp-23-921-2023, https://doi.org/10.5194/acp-23-921-2023, 2023
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The last very large explosive volcanic eruption we have measurements for is the eruption of Mt. Pinatubo in 1991. It is therefore often used as a benchmark for climate models' ability to reproduce these kinds of events. Here, we compare available measurements with the results from multiple experiments conducted with climate models interactively simulating the aerosol cloud formation.
Daniele Visioni, Ewa M. Bednarz, Walker R. Lee, Ben Kravitz, Andy Jones, Jim M. Haywood, and Douglas G. MacMartin
Atmos. Chem. Phys., 23, 663–685, https://doi.org/10.5194/acp-23-663-2023, https://doi.org/10.5194/acp-23-663-2023, 2023
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The paper constitutes Part 1 of a study performing a first systematic inter-model comparison of the atmospheric responses to stratospheric sulfate aerosol injections (SAIs) at various latitudes as simulated by three state-of-the-art Earth system models. We identify similarities and differences in the modeled aerosol burden, investigate the differences in the aerosol approaches between the models, and ultimately show the differences produced in surface climate, temperature and precipitation.
Ewa M. Bednarz, Daniele Visioni, Ben Kravitz, Andy Jones, James M. Haywood, Jadwiga Richter, Douglas G. MacMartin, and Peter Braesicke
Atmos. Chem. Phys., 23, 687–709, https://doi.org/10.5194/acp-23-687-2023, https://doi.org/10.5194/acp-23-687-2023, 2023
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Building on Part 1 of this two-part study, we demonstrate the role of biases in climatological circulation and specific aspects of model microphysics in driving the differences in simulated sulfate distributions amongst three Earth system models. We then characterize the simulated changes in stratospheric and free-tropospheric temperatures, ozone, water vapor, and large-scale circulation, elucidating the role of the above aspects in the surface responses discussed in Part 1.
Esteban Alonso-González, Kristoffer Aalstad, Mohamed Wassim Baba, Jesús Revuelto, Juan Ignacio López-Moreno, Joel Fiddes, Richard Essery, and Simon Gascoin
Geosci. Model Dev., 15, 9127–9155, https://doi.org/10.5194/gmd-15-9127-2022, https://doi.org/10.5194/gmd-15-9127-2022, 2022
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Snow cover plays an important role in many processes, but its monitoring is a challenging task. The alternative is usually to simulate the snowpack, and to improve these simulations one of the most promising options is to fuse simulations with available observations (data assimilation). In this paper we present MuSA, a data assimilation tool which facilitates the implementation of snow monitoring initiatives, allowing the assimilation of a wide variety of remotely sensed snow cover information.
Robert J. Parker, Chris Wilson, Edward Comyn-Platt, Garry Hayman, Toby R. Marthews, A. Anthony Bloom, Mark F. Lunt, Nicola Gedney, Simon J. Dadson, Joe McNorton, Neil Humpage, Hartmut Boesch, Martyn P. Chipperfield, Paul I. Palmer, and Dai Yamazaki
Biogeosciences, 19, 5779–5805, https://doi.org/10.5194/bg-19-5779-2022, https://doi.org/10.5194/bg-19-5779-2022, 2022
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Wetlands are the largest natural source of methane, one of the most important climate gases. The JULES land surface model simulates these emissions. We use satellite data to evaluate how well JULES reproduces the methane seasonal cycle over different tropical wetlands. It performs well for most regions; however, it struggles for some African wetlands influenced heavily by river flooding. We explain the reasons for these deficiencies and highlight how future development will improve these areas.
Leighton A. Regayre, Lucia Deaconu, Daniel P. Grosvenor, David Sexton, Christopher C. Symonds, Tom Langton, Duncan Watson-Paris, Jane P. Mulcahy, Kirsty J. Pringle, Mark Richardson, Jill S. Johnson, John Rostron, Hamish Gordon, Grenville Lister, Philip Stier, and Ken S. Carslaw
EGUsphere, https://doi.org/10.5194/egusphere-2022-1330, https://doi.org/10.5194/egusphere-2022-1330, 2022
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We show that potential structural deficiencies in a climate model can be exposed by comprehensively exploring its parametric uncertainty, and that these deficiencies limit how much the model uncertainty can be reduced through observational constraint. Combined consideration of parametric and structural uncertainties provides a future pathway towards building models that have greater physical realism and lower uncertainty.
Stephanie Woodward, Alistair A. Sellar, Yongming Tang, Marc Stringer, Andrew Yool, Eddy Robertson, and Andy Wiltshire
Atmos. Chem. Phys., 22, 14503–14528, https://doi.org/10.5194/acp-22-14503-2022, https://doi.org/10.5194/acp-22-14503-2022, 2022
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We describe the dust scheme in the UKESM1 Earth system model and show generally good agreement with observations. Comparing with the closely related HadGEM3-GC3.1 model, we show that dust differences are not only due to inter-model differences but also to the dust size distribution. Under climate change, HadGEM3-GC3.1 dust hardly changes, but UKESM1 dust decreases because that model includes the vegetation response which, in our models, has a bigger impact on dust than climate change itself.
Juan-Carlos Antuña-Marrero, Graham W. Mann, John Barnes, Abel Calle, Sandip S. Dhomse, Victoria E. Cachorro-Revilla, Terry Deshler, Li Zhengyao, Nimmi Sharma, and Louis Elterman
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-272, https://doi.org/10.5194/essd-2022-272, 2022
Revised manuscript not accepted
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Tropospheric and stratospheric aerosol extinction profiles observations from a searchlight at New Mexico, US, were rescued and re-calibrated. Spanning between December 1963 and 1964, they measured the volcanic aerosols from the 1963 Agung eruption. Contemporary and state of the art information were used in the re-calibration. A unique and until the present forgotten/ignored dataset, it contributes current observational and modelling research on the impact of major volcanic eruptions on climate.
Victoria R. Dutch, Nick Rutter, Leanne Wake, Melody Sandells, Chris Derksen, Branden Walker, Gabriel Hould Gosselin, Oliver Sonnentag, Richard Essery, Richard Kelly, Phillip Marsh, Joshua King, and Julia Boike
The Cryosphere, 16, 4201–4222, https://doi.org/10.5194/tc-16-4201-2022, https://doi.org/10.5194/tc-16-4201-2022, 2022
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Measurements of the properties of the snow and soil were compared to simulations of the Community Land Model to see how well the model represents snow insulation. Simulations underestimated snow thermal conductivity and wintertime soil temperatures. We test two approaches to reduce the transfer of heat through the snowpack and bring simulated soil temperatures closer to measurements, with an alternative parameterisation of snow thermal conductivity being more appropriate.
Antony Siahaan, Robin S. Smith, Paul R. Holland, Adrian Jenkins, Jonathan M. Gregory, Victoria Lee, Pierre Mathiot, Antony J. Payne, Jeff K. Ridley, and Colin G. Jones
The Cryosphere, 16, 4053–4086, https://doi.org/10.5194/tc-16-4053-2022, https://doi.org/10.5194/tc-16-4053-2022, 2022
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The UK Earth System Model is the first to fully include interactions of the atmosphere and ocean with the Antarctic Ice Sheet. Under the low-greenhouse-gas SSP1–1.9 (Shared Socioeconomic Pathway) scenario, the ice sheet remains stable over the 21st century. Under the strong-greenhouse-gas SSP5–8.5 scenario, the model predicts strong increases in melting of large ice shelves and snow accumulation on the surface. The dominance of accumulation leads to a sea level fall at the end of the century.
Ville Leinonen, Harri Kokkola, Taina Yli-Juuti, Tero Mielonen, Thomas Kühn, Tuomo Nieminen, Simo Heikkinen, Tuuli Miinalainen, Tommi Bergman, Ken Carslaw, Stefano Decesari, Markus Fiebig, Tareq Hussein, Niku Kivekäs, Radovan Krejci, Markku Kulmala, Ari Leskinen, Andreas Massling, Nikos Mihalopoulos, Jane P. Mulcahy, Steffen M. Noe, Twan van Noije, Fiona M. O'Connor, Colin O'Dowd, Dirk Olivie, Jakob B. Pernov, Tuukka Petäjä, Øyvind Seland, Michael Schulz, Catherine E. Scott, Henrik Skov, Erik Swietlicki, Thomas Tuch, Alfred Wiedensohler, Annele Virtanen, and Santtu Mikkonen
Atmos. Chem. Phys., 22, 12873–12905, https://doi.org/10.5194/acp-22-12873-2022, https://doi.org/10.5194/acp-22-12873-2022, 2022
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We provide the first extensive comparison of detailed aerosol size distribution trends between in situ observations from Europe and five different earth system models. We investigated aerosol modes (nucleation, Aitken, and accumulation) separately and were able to show the differences between measured and modeled trends and especially their seasonal patterns. The differences in model results are likely due to complex effects of several processes instead of certain specific model features.
Juha Lemmetyinen, Juval Cohen, Anna Kontu, Juho Vehviläinen, Henna-Reetta Hannula, Ioanna Merkouriadi, Stefan Scheiblauer, Helmut Rott, Thomas Nagler, Elisabeth Ripper, Kelly Elder, Hans-Peter Marshall, Reinhard Fromm, Marc Adams, Chris Derksen, Joshua King, Adriano Meta, Alex Coccia, Nick Rutter, Melody Sandells, Giovanni Macelloni, Emanuele Santi, Marion Leduc-Leballeur, Richard Essery, Cecile Menard, and Michael Kern
Earth Syst. Sci. Data, 14, 3915–3945, https://doi.org/10.5194/essd-14-3915-2022, https://doi.org/10.5194/essd-14-3915-2022, 2022
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The manuscript describes airborne, dual-polarised X and Ku band synthetic aperture radar (SAR) data collected over several campaigns over snow-covered terrain in Finland, Austria and Canada. Colocated snow and meteorological observations are also presented. The data are meant for science users interested in investigating X/Ku band radar signatures from natural environments in winter conditions.
Qirui Zhong, Nick Schutgens, Guido van der Werf, Twan van Noije, Kostas Tsigaridis, Susanne E. Bauer, Tero Mielonen, Alf Kirkevåg, Øyvind Seland, Harri Kokkola, Ramiro Checa-Garcia, David Neubauer, Zak Kipling, Hitoshi Matsui, Paul Ginoux, Toshihiko Takemura, Philippe Le Sager, Samuel Rémy, Huisheng Bian, Mian Chin, Kai Zhang, Jialei Zhu, Svetlana G. Tsyro, Gabriele Curci, Anna Protonotariou, Ben Johnson, Joyce E. Penner, Nicolas Bellouin, Ragnhild B. Skeie, and Gunnar Myhre
Atmos. Chem. Phys., 22, 11009–11032, https://doi.org/10.5194/acp-22-11009-2022, https://doi.org/10.5194/acp-22-11009-2022, 2022
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Aerosol optical depth (AOD) errors for biomass burning aerosol (BBA) are evaluated in 18 global models against satellite datasets. Notwithstanding biases in satellite products, they allow model evaluations. We observe large and diverse model biases due to errors in BBA. Further interpretations of AOD diversities suggest large biases exist in key processes for BBA which require better constraining. These results can contribute to further model improvement and development.
Amy H. Peace, Ben B. B. Booth, Leighton A. Regayre, Ken S. Carslaw, David M. H. Sexton, Céline J. W. Bonfils, and John W. Rostron
Earth Syst. Dynam., 13, 1215–1232, https://doi.org/10.5194/esd-13-1215-2022, https://doi.org/10.5194/esd-13-1215-2022, 2022
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Anthropogenic aerosol emissions have been linked to driving climate responses such as shifts in the location of tropical rainfall. However, the interaction of aerosols with climate remains one of the most uncertain aspects of climate modelling and limits our ability to predict future climate change. We use an ensemble of climate model simulations to investigate what impact the large uncertainty in how aerosols interact with climate has on predicting future tropical rainfall shifts.
Alexander D. Harrison, Daniel O'Sullivan, Michael P. Adams, Grace C. E. Porter, Edmund Blades, Cherise Brathwaite, Rebecca Chewitt-Lucas, Cassandra Gaston, Rachel Hawker, Ovid O. Krüger, Leslie Neve, Mira L. Pöhlker, Christopher Pöhlker, Ulrich Pöschl, Alberto Sanchez-Marroquin, Andrea Sealy, Peter Sealy, Mark D. Tarn, Shanice Whitehall, James B. McQuaid, Kenneth S. Carslaw, Joseph M. Prospero, and Benjamin J. Murray
Atmos. Chem. Phys., 22, 9663–9680, https://doi.org/10.5194/acp-22-9663-2022, https://doi.org/10.5194/acp-22-9663-2022, 2022
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The formation of ice in clouds fundamentally alters cloud properties; hence it is important we understand the special aerosol particles that can nucleate ice when immersed in supercooled cloud droplets. In this paper we show that African desert dust that has travelled across the Atlantic to the Caribbean nucleates ice much less well than we might have expected.
Patrick Le Moigne, Eric Bazile, Anning Cheng, Emanuel Dutra, John M. Edwards, William Maurel, Irina Sandu, Olivier Traullé, Etienne Vignon, Ayrton Zadra, and Weizhong Zheng
The Cryosphere, 16, 2183–2202, https://doi.org/10.5194/tc-16-2183-2022, https://doi.org/10.5194/tc-16-2183-2022, 2022
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This paper describes an intercomparison of snow models, of varying complexity, used for numerical weather prediction or academic research. The results show that the simplest models are, under certain conditions, able to reproduce the surface temperature just as well as the most complex models. Moreover, the diversity of surface parameters of the models has a strong impact on the temporal variability of the components of the simulated surface energy balance.
Juan Manuel Castillo, Huw W. Lewis, Akhilesh Mishra, Ashis Mitra, Jeff Polton, Ashley Brereton, Andrew Saulter, Alex Arnold, Segolene Berthou, Douglas Clark, Julia Crook, Ananda Das, John Edwards, Xiangbo Feng, Ankur Gupta, Sudheer Joseph, Nicholas Klingaman, Imranali Momin, Christine Pequignet, Claudio Sanchez, Jennifer Saxby, and Maria Valdivieso da Costa
Geosci. Model Dev., 15, 4193–4223, https://doi.org/10.5194/gmd-15-4193-2022, https://doi.org/10.5194/gmd-15-4193-2022, 2022
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A new environmental modelling system has been developed to represent the effect of feedbacks between atmosphere, land, and ocean in the Indian region. Different approaches to simulating tropical cyclones Titli and Fani are demonstrated. It is shown that results are sensitive to the way in which the ocean response to cyclone evolution is captured in the system. Notably, we show how a more rigorous formulation for the near-surface energy budget can be included when air–sea coupling is included.
Jim M. Haywood, Andy Jones, Ben T. Johnson, and William McFarlane Smith
Atmos. Chem. Phys., 22, 6135–6150, https://doi.org/10.5194/acp-22-6135-2022, https://doi.org/10.5194/acp-22-6135-2022, 2022
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Simulations are presented investigating the influence of moderately absorbing aerosol in the stratosphere to combat the impacts of climate change. A number of detrimental impacts are noted compared to sulfate aerosol, including (i) reduced cooling efficiency, (ii) increased deficits in global precipitation, (iii) delays in the recovery of the stratospheric ozone hole, and (iv) disruption of the stratospheric circulation and the wintertime storm tracks that impact European precipitation.
Noah D. Smith, Eleanor J. Burke, Kjetil Schanke Aas, Inge H. J. Althuizen, Julia Boike, Casper Tai Christiansen, Bernd Etzelmüller, Thomas Friborg, Hanna Lee, Heather Rumbold, Rachael H. Turton, Sebastian Westermann, and Sarah E. Chadburn
Geosci. Model Dev., 15, 3603–3639, https://doi.org/10.5194/gmd-15-3603-2022, https://doi.org/10.5194/gmd-15-3603-2022, 2022
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The Arctic has large areas of small mounds that are caused by ice lifting up the soil. Snow blown by wind gathers in hollows next to these mounds, insulating them in winter. The hollows tend to be wetter, and thus the soil absorbs more heat in summer. The warm wet soil in the hollows decomposes, releasing methane. We have made a model of this, and we have tested how it behaves and whether it looks like sites in Scandinavia and Siberia. Sometimes we get more methane than a model without mounds.
Ming Li, Husi Letu, Yiran Peng, Hiroshi Ishimoto, Yanluan Lin, Takashi Y. Nakajima, Anthony J. Baran, Zengyuan Guo, Yonghui Lei, and Jiancheng Shi
Atmos. Chem. Phys., 22, 4809–4825, https://doi.org/10.5194/acp-22-4809-2022, https://doi.org/10.5194/acp-22-4809-2022, 2022
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To build on the previous investigations of the Voronoi model in the remote sensing retrievals of ice cloud products, this paper developed an ice cloud parameterization scheme based on the single-scattering properties of the Voronoi model and evaluate it through simulations with the Community Integrated Earth System Model (CIESM). Compared with four representative ice cloud schemes, results show that the Voronoi model has good capabilities of ice cloud modeling in the climate model.
Simone Tilmes, Daniele Visioni, Andy Jones, James Haywood, Roland Séférian, Pierre Nabat, Olivier Boucher, Ewa Monica Bednarz, and Ulrike Niemeier
Atmos. Chem. Phys., 22, 4557–4579, https://doi.org/10.5194/acp-22-4557-2022, https://doi.org/10.5194/acp-22-4557-2022, 2022
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This study assesses the impacts of climate interventions, using stratospheric sulfate aerosol and solar dimming on stratospheric ozone, based on three Earth system models with interactive stratospheric chemistry. The climate interventions have been applied to a high emission (baseline) scenario in order to reach global surface temperatures of a medium emission scenario. We find significant increases and decreases in total column ozone, depending on regions and seasons.
Davide Zanchettin, Claudia Timmreck, Myriam Khodri, Anja Schmidt, Matthew Toohey, Manabu Abe, Slimane Bekki, Jason Cole, Shih-Wei Fang, Wuhu Feng, Gabriele Hegerl, Ben Johnson, Nicolas Lebas, Allegra N. LeGrande, Graham W. Mann, Lauren Marshall, Landon Rieger, Alan Robock, Sara Rubinetti, Kostas Tsigaridis, and Helen Weierbach
Geosci. Model Dev., 15, 2265–2292, https://doi.org/10.5194/gmd-15-2265-2022, https://doi.org/10.5194/gmd-15-2265-2022, 2022
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This paper provides metadata and first analyses of the volc-pinatubo-full experiment of CMIP6-VolMIP. Results from six Earth system models reveal significant differences in radiative flux anomalies that trace back to different implementations of volcanic forcing. Surface responses are in contrast overall consistent across models, reflecting the large spread due to internal variability. A second phase of VolMIP shall consider both aspects toward improved protocol for volc-pinatubo-full.
Andy Jones, Jim M. Haywood, Adam A. Scaife, Olivier Boucher, Matthew Henry, Ben Kravitz, Thibaut Lurton, Pierre Nabat, Ulrike Niemeier, Roland Séférian, Simone Tilmes, and Daniele Visioni
Atmos. Chem. Phys., 22, 2999–3016, https://doi.org/10.5194/acp-22-2999-2022, https://doi.org/10.5194/acp-22-2999-2022, 2022
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Simulations by six Earth-system models of geoengineering by introducing sulfuric acid aerosols into the tropical stratosphere are compared. A robust impact on the northern wintertime North Atlantic Oscillation is found, exacerbating precipitation reduction over parts of southern Europe. In contrast, the models show no consistency with regard to impacts on the Quasi-Biennial Oscillation, although results do indicate a risk that the oscillation could become locked into a permanent westerly phase.
Adam A. Scaife, Mark P. Baldwin, Amy H. Butler, Andrew J. Charlton-Perez, Daniela I. V. Domeisen, Chaim I. Garfinkel, Steven C. Hardiman, Peter Haynes, Alexey Yu Karpechko, Eun-Pa Lim, Shunsuke Noguchi, Judith Perlwitz, Lorenzo Polvani, Jadwiga H. Richter, John Scinocca, Michael Sigmond, Theodore G. Shepherd, Seok-Woo Son, and David W. J. Thompson
Atmos. Chem. Phys., 22, 2601–2623, https://doi.org/10.5194/acp-22-2601-2022, https://doi.org/10.5194/acp-22-2601-2022, 2022
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Great progress has been made in computer modelling and simulation of the whole climate system, including the stratosphere. Since the late 20th century we also gained a much clearer understanding of how the stratosphere interacts with the lower atmosphere. The latest generation of numerical prediction systems now explicitly represents the stratosphere and its interaction with surface climate, and here we review its role in long-range predictions and projections from weeks to decades ahead.
Penelope Maher and Paul Earnshaw
Geosci. Model Dev., 15, 1177–1194, https://doi.org/10.5194/gmd-15-1177-2022, https://doi.org/10.5194/gmd-15-1177-2022, 2022
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Climate models do a pretty good job. But they are far from perfect. Fixing these imperfections is really hard because the models are complicated. One way to make progress is to create simpler models: think impressionism rather than realism in the art world. We changed the Met Office model to be intentionally simple and it still does a pretty good job. This will help to identify sources of model imperfections, develop new methods and improve our understanding of how the climate works.
Sandip S. Dhomse, Martyn P. Chipperfield, Wuhu Feng, Ryan Hossaini, Graham W. Mann, Michelle L. Santee, and Mark Weber
Atmos. Chem. Phys., 22, 903–916, https://doi.org/10.5194/acp-22-903-2022, https://doi.org/10.5194/acp-22-903-2022, 2022
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Solar flux variations associated with 11-year sunspot cycle is believed to exert important external climate forcing. As largest variations occur at shorter wavelengths such as ultra-violet part of the solar spectrum, associated changes in stratospheric ozone are thought to provide direct evidence for solar climate interaction. Until now, most of the studies reported double-peak structured solar cycle signal (SCS), but relatively new satellite data suggest only single-peak-structured SCS.
Ian Boutle, Wayne Angevine, Jian-Wen Bao, Thierry Bergot, Ritthik Bhattacharya, Andreas Bott, Leo Ducongé, Richard Forbes, Tobias Goecke, Evelyn Grell, Adrian Hill, Adele L. Igel, Innocent Kudzotsa, Christine Lac, Bjorn Maronga, Sami Romakkaniemi, Juerg Schmidli, Johannes Schwenkel, Gert-Jan Steeneveld, and Benoît Vié
Atmos. Chem. Phys., 22, 319–333, https://doi.org/10.5194/acp-22-319-2022, https://doi.org/10.5194/acp-22-319-2022, 2022
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Fog forecasting is one of the biggest problems for numerical weather prediction. By comparing many models used for fog forecasting with others used for fog research, we hoped to help guide forecast improvements. We show some key processes that, if improved, will help improve fog forecasting, such as how water is deposited on the ground. We also showed that research models were not themselves a suitable baseline for comparison, and we discuss what future observations are required to improve them.
Jie Zhang, Kalli Furtado, Steven T. Turnock, Jane P. Mulcahy, Laura J. Wilcox, Ben B. Booth, David Sexton, Tongwen Wu, Fang Zhang, and Qianxia Liu
Atmos. Chem. Phys., 21, 18609–18627, https://doi.org/10.5194/acp-21-18609-2021, https://doi.org/10.5194/acp-21-18609-2021, 2021
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The CMIP6 ESMs systematically underestimate TAS anomalies in the NH midlatitudes, especially from 1960 to 1990. The anomalous cooling is concurrent in time and space with anthropogenic SO2 emissions. The spurious drop in TAS is attributed to the overestimated aerosol concentrations. The aerosol forcing sensitivity cannot well explain the inter-model spread of PHC biases. And the cloud-amount term accounts for most of the inter-model spread in aerosol forcing sensitivity.
Catherine Hardacre, Jane P. Mulcahy, Richard J. Pope, Colin G. Jones, Steven T. Rumbold, Can Li, Colin Johnson, and Steven T. Turnock
Atmos. Chem. Phys., 21, 18465–18497, https://doi.org/10.5194/acp-21-18465-2021, https://doi.org/10.5194/acp-21-18465-2021, 2021
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We investigate UKESM1's ability to represent the sulfur (S) cycle in the recent historical period. The S cycle is a key driver of historical radiative forcing. Earth system models such as UKESM1 should represent the S cycle well so that we can have confidence in their projections of future climate. We compare UKESM1 to observations of sulfur compounds, finding that the model generally performs well. We also identify areas for UKESM1’s development, focussing on how SO2 is removed from the air.
Rachel E. Hawker, Annette K. Miltenberger, Jill S. Johnson, Jonathan M. Wilkinson, Adrian A. Hill, Ben J. Shipway, Paul R. Field, Benjamin J. Murray, and Ken S. Carslaw
Atmos. Chem. Phys., 21, 17315–17343, https://doi.org/10.5194/acp-21-17315-2021, https://doi.org/10.5194/acp-21-17315-2021, 2021
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We find that ice-nucleating particles (INPs), aerosols that can initiate the freezing of cloud droplets, cause substantial changes to the properties of radiatively important convectively generated anvil cirrus. The number concentration of INPs had a large effect on ice crystal number concentration while the INP temperature dependence controlled ice crystal size and cloud fraction. The results indicate information on INP number and source is necessary for the representation of cloud glaciation.
Anthony C. Jones, Adrian Hill, Samuel Remy, N. Luke Abraham, Mohit Dalvi, Catherine Hardacre, Alan J. Hewitt, Ben Johnson, Jane P. Mulcahy, and Steven T. Turnock
Atmos. Chem. Phys., 21, 15901–15927, https://doi.org/10.5194/acp-21-15901-2021, https://doi.org/10.5194/acp-21-15901-2021, 2021
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Ammonium nitrate is hard to model because it forms and evaporates rapidly. One approach is to relate its equilibrium concentration to temperature, humidity, and the amount of nitric acid and ammonia gases. Using this approach, we limit the rate at which equilibrium is reached using various condensation rates in a climate model. We show that ammonium nitrate concentrations are highly sensitive to the condensation rate. Our results will help improve the representation of nitrate in climate models.
Charles J. R. Williams, Alistair A. Sellar, Xin Ren, Alan M. Haywood, Peter Hopcroft, Stephen J. Hunter, William H. G. Roberts, Robin S. Smith, Emma J. Stone, Julia C. Tindall, and Daniel J. Lunt
Clim. Past, 17, 2139–2163, https://doi.org/10.5194/cp-17-2139-2021, https://doi.org/10.5194/cp-17-2139-2021, 2021
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Computer simulations of the geological past are an important tool to improve our understanding of climate change. We present results from a simulation of the mid-Pliocene (approximately 3 million years ago) using the latest version of the UK’s climate model. The simulation reproduces temperatures as expected and shows some improvement relative to previous versions of the same model. The simulation is, however, arguably too warm when compared to other models and available observations.
Heather Guy, Ian M. Brooks, Ken S. Carslaw, Benjamin J. Murray, Von P. Walden, Matthew D. Shupe, Claire Pettersen, David D. Turner, Christopher J. Cox, William D. Neff, Ralf Bennartz, and Ryan R. Neely III
Atmos. Chem. Phys., 21, 15351–15374, https://doi.org/10.5194/acp-21-15351-2021, https://doi.org/10.5194/acp-21-15351-2021, 2021
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We present the first full year of surface aerosol number concentration measurements from the central Greenland Ice Sheet. Aerosol concentrations here have a distinct seasonal cycle from those at lower-altitude Arctic sites, which is driven by large-scale atmospheric circulation. Our results can be used to help understand the role aerosols might play in Greenland surface melt through the modification of cloud properties. This is crucial in a rapidly changing region where observations are sparse.
Mao Xiao, Christopher R. Hoyle, Lubna Dada, Dominik Stolzenburg, Andreas Kürten, Mingyi Wang, Houssni Lamkaddam, Olga Garmash, Bernhard Mentler, Ugo Molteni, Andrea Baccarini, Mario Simon, Xu-Cheng He, Katrianne Lehtipalo, Lauri R. Ahonen, Rima Baalbaki, Paulus S. Bauer, Lisa Beck, David Bell, Federico Bianchi, Sophia Brilke, Dexian Chen, Randall Chiu, António Dias, Jonathan Duplissy, Henning Finkenzeller, Hamish Gordon, Victoria Hofbauer, Changhyuk Kim, Theodore K. Koenig, Janne Lampilahti, Chuan Ping Lee, Zijun Li, Huajun Mai, Vladimir Makhmutov, Hanna E. Manninen, Ruby Marten, Serge Mathot, Roy L. Mauldin, Wei Nie, Antti Onnela, Eva Partoll, Tuukka Petäjä, Joschka Pfeifer, Veronika Pospisilova, Lauriane L. J. Quéléver, Matti Rissanen, Siegfried Schobesberger, Simone Schuchmann, Yuri Stozhkov, Christian Tauber, Yee Jun Tham, António Tomé, Miguel Vazquez-Pufleau, Andrea C. Wagner, Robert Wagner, Yonghong Wang, Lena Weitz, Daniela Wimmer, Yusheng Wu, Chao Yan, Penglin Ye, Qing Ye, Qiaozhi Zha, Xueqin Zhou, Antonio Amorim, Ken Carslaw, Joachim Curtius, Armin Hansel, Rainer Volkamer, Paul M. Winkler, Richard C. Flagan, Markku Kulmala, Douglas R. Worsnop, Jasper Kirkby, Neil M. Donahue, Urs Baltensperger, Imad El Haddad, and Josef Dommen
Atmos. Chem. Phys., 21, 14275–14291, https://doi.org/10.5194/acp-21-14275-2021, https://doi.org/10.5194/acp-21-14275-2021, 2021
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Experiments at CLOUD show that in polluted environments new particle formation (NPF) is largely driven by the formation of sulfuric acid–base clusters, stabilized by amines, high ammonia concentrations or lower temperatures. While oxidation products of aromatics can nucleate, they play a minor role in urban NPF. Our experiments span 4 orders of magnitude variation of observed NPF rates in ambient conditions. We provide a framework based on NPF and growth rates to interpret ambient observations.
Marta Abalos, Natalia Calvo, Samuel Benito-Barca, Hella Garny, Steven C. Hardiman, Pu Lin, Martin B. Andrews, Neal Butchart, Rolando Garcia, Clara Orbe, David Saint-Martin, Shingo Watanabe, and Kohei Yoshida
Atmos. Chem. Phys., 21, 13571–13591, https://doi.org/10.5194/acp-21-13571-2021, https://doi.org/10.5194/acp-21-13571-2021, 2021
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The stratospheric Brewer–Dobson circulation (BDC), responsible for transporting mass, tracers and heat globally in the stratosphere, is evaluated in a set of state-of-the-art climate models. The acceleration of the BDC in response to increasing greenhouse gases is most robust in the lower stratosphere. At higher levels, the well-known inconsistency between model and observational BDC trends can be partly reconciled by accounting for limited sampling and large uncertainties in the observations.
Juan-Carlos Antuña-Marrero, Graham W. Mann, John Barnes, Albeht Rodríguez-Vega, Sarah Shallcross, Sandip S. Dhomse, Giorgio Fiocco, and Gerald W. Grams
Earth Syst. Sci. Data, 13, 4407–4423, https://doi.org/10.5194/essd-13-4407-2021, https://doi.org/10.5194/essd-13-4407-2021, 2021
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The first multi-year stratospheric aerosol lidar dataset was recovered and recalibrated. The vertical profile dataset, January 1964 to August 1965 at Lexington, MA, and July to August 1964 at Fairbanks, AK, provides info on volcanic forcing after the 1963 Agung eruption. Applying two-way transmittance correction to the original dataset reveals data variations, with corrected stratospheric aerosol optical depth (sAOD) highest in 1965 with the highest 532 nm sAOD peak at 0.07 in March 1965.
Bjorn Stevens, Sandrine Bony, David Farrell, Felix Ament, Alan Blyth, Christopher Fairall, Johannes Karstensen, Patricia K. Quinn, Sabrina Speich, Claudia Acquistapace, Franziska Aemisegger, Anna Lea Albright, Hugo Bellenger, Eberhard Bodenschatz, Kathy-Ann Caesar, Rebecca Chewitt-Lucas, Gijs de Boer, Julien Delanoë, Leif Denby, Florian Ewald, Benjamin Fildier, Marvin Forde, Geet George, Silke Gross, Martin Hagen, Andrea Hausold, Karen J. Heywood, Lutz Hirsch, Marek Jacob, Friedhelm Jansen, Stefan Kinne, Daniel Klocke, Tobias Kölling, Heike Konow, Marie Lothon, Wiebke Mohr, Ann Kristin Naumann, Louise Nuijens, Léa Olivier, Robert Pincus, Mira Pöhlker, Gilles Reverdin, Gregory Roberts, Sabrina Schnitt, Hauke Schulz, A. Pier Siebesma, Claudia Christine Stephan, Peter Sullivan, Ludovic Touzé-Peiffer, Jessica Vial, Raphaela Vogel, Paquita Zuidema, Nicola Alexander, Lyndon Alves, Sophian Arixi, Hamish Asmath, Gholamhossein Bagheri, Katharina Baier, Adriana Bailey, Dariusz Baranowski, Alexandre Baron, Sébastien Barrau, Paul A. Barrett, Frédéric Batier, Andreas Behrendt, Arne Bendinger, Florent Beucher, Sebastien Bigorre, Edmund Blades, Peter Blossey, Olivier Bock, Steven Böing, Pierre Bosser, Denis Bourras, Pascale Bouruet-Aubertot, Keith Bower, Pierre Branellec, Hubert Branger, Michal Brennek, Alan Brewer, Pierre-Etienne Brilouet, Björn Brügmann, Stefan A. Buehler, Elmo Burke, Ralph Burton, Radiance Calmer, Jean-Christophe Canonici, Xavier Carton, Gregory Cato Jr., Jude Andre Charles, Patrick Chazette, Yanxu Chen, Michal T. Chilinski, Thomas Choularton, Patrick Chuang, Shamal Clarke, Hugh Coe, Céline Cornet, Pierre Coutris, Fleur Couvreux, Susanne Crewell, Timothy Cronin, Zhiqiang Cui, Yannis Cuypers, Alton Daley, Gillian M. Damerell, Thibaut Dauhut, Hartwig Deneke, Jean-Philippe Desbios, Steffen Dörner, Sebastian Donner, Vincent Douet, Kyla Drushka, Marina Dütsch, André Ehrlich, Kerry Emanuel, Alexandros Emmanouilidis, Jean-Claude Etienne, Sheryl Etienne-Leblanc, Ghislain Faure, Graham Feingold, Luca Ferrero, Andreas Fix, Cyrille Flamant, Piotr Jacek Flatau, Gregory R. Foltz, Linda Forster, Iulian Furtuna, Alan Gadian, Joseph Galewsky, Martin Gallagher, Peter Gallimore, Cassandra Gaston, Chelle Gentemann, Nicolas Geyskens, Andreas Giez, John Gollop, Isabelle Gouirand, Christophe Gourbeyre, Dörte de Graaf, Geiske E. de Groot, Robert Grosz, Johannes Güttler, Manuel Gutleben, Kashawn Hall, George Harris, Kevin C. Helfer, Dean Henze, Calvert Herbert, Bruna Holanda, Antonio Ibanez-Landeta, Janet Intrieri, Suneil Iyer, Fabrice Julien, Heike Kalesse, Jan Kazil, Alexander Kellman, Abiel T. Kidane, Ulrike Kirchner, Marcus Klingebiel, Mareike Körner, Leslie Ann Kremper, Jan Kretzschmar, Ovid Krüger, Wojciech Kumala, Armin Kurz, Pierre L'Hégaret, Matthieu Labaste, Tom Lachlan-Cope, Arlene Laing, Peter Landschützer, Theresa Lang, Diego Lange, Ingo Lange, Clément Laplace, Gauke Lavik, Rémi Laxenaire, Caroline Le Bihan, Mason Leandro, Nathalie Lefevre, Marius Lena, Donald Lenschow, Qiang Li, Gary Lloyd, Sebastian Los, Niccolò Losi, Oscar Lovell, Christopher Luneau, Przemyslaw Makuch, Szymon Malinowski, Gaston Manta, Eleni Marinou, Nicholas Marsden, Sebastien Masson, Nicolas Maury, Bernhard Mayer, Margarette Mayers-Als, Christophe Mazel, Wayne McGeary, James C. McWilliams, Mario Mech, Melina Mehlmann, Agostino Niyonkuru Meroni, Theresa Mieslinger, Andreas Minikin, Peter Minnett, Gregor Möller, Yanmichel Morfa Avalos, Caroline Muller, Ionela Musat, Anna Napoli, Almuth Neuberger, Christophe Noisel, David Noone, Freja Nordsiek, Jakub L. Nowak, Lothar Oswald, Douglas J. Parker, Carolyn Peck, Renaud Person, Miriam Philippi, Albert Plueddemann, Christopher Pöhlker, Veronika Pörtge, Ulrich Pöschl, Lawrence Pologne, Michał Posyniak, Marc Prange, Estefanía Quiñones Meléndez, Jule Radtke, Karim Ramage, Jens Reimann, Lionel Renault, Klaus Reus, Ashford Reyes, Joachim Ribbe, Maximilian Ringel, Markus Ritschel, Cesar B. Rocha, Nicolas Rochetin, Johannes Röttenbacher, Callum Rollo, Haley Royer, Pauline Sadoulet, Leo Saffin, Sanola Sandiford, Irina Sandu, Michael Schäfer, Vera Schemann, Imke Schirmacher, Oliver Schlenczek, Jerome Schmidt, Marcel Schröder, Alfons Schwarzenboeck, Andrea Sealy, Christoph J. Senff, Ilya Serikov, Samkeyat Shohan, Elizabeth Siddle, Alexander Smirnov, Florian Späth, Branden Spooner, M. Katharina Stolla, Wojciech Szkółka, Simon P. de Szoeke, Stéphane Tarot, Eleni Tetoni, Elizabeth Thompson, Jim Thomson, Lorenzo Tomassini, Julien Totems, Alma Anna Ubele, Leonie Villiger, Jan von Arx, Thomas Wagner, Andi Walther, Ben Webber, Manfred Wendisch, Shanice Whitehall, Anton Wiltshire, Allison A. Wing, Martin Wirth, Jonathan Wiskandt, Kevin Wolf, Ludwig Worbes, Ethan Wright, Volker Wulfmeyer, Shanea Young, Chidong Zhang, Dongxiao Zhang, Florian Ziemen, Tobias Zinner, and Martin Zöger
Earth Syst. Sci. Data, 13, 4067–4119, https://doi.org/10.5194/essd-13-4067-2021, https://doi.org/10.5194/essd-13-4067-2021, 2021
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The EUREC4A field campaign, designed to test hypothesized mechanisms by which clouds respond to warming and benchmark next-generation Earth-system models, is presented. EUREC4A comprised roughly 5 weeks of measurements in the downstream winter trades of the North Atlantic – eastward and southeastward of Barbados. It was the first campaign that attempted to characterize the full range of processes and scales influencing trade wind clouds.
Ramiro Checa-Garcia, Yves Balkanski, Samuel Albani, Tommi Bergman, Ken Carslaw, Anne Cozic, Chris Dearden, Beatrice Marticorena, Martine Michou, Twan van Noije, Pierre Nabat, Fiona M. O'Connor, Dirk Olivié, Joseph M. Prospero, Philippe Le Sager, Michael Schulz, and Catherine Scott
Atmos. Chem. Phys., 21, 10295–10335, https://doi.org/10.5194/acp-21-10295-2021, https://doi.org/10.5194/acp-21-10295-2021, 2021
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Thousands of tons of dust are emitted into the atmosphere every year, producing important impacts on the Earth system. However, current global climate models are not yet able to reproduce dust emissions, transport and depositions with the desirable accuracy. Our study analyses five different Earth system models to report aspects to be improved to reproduce better available observations, increase the consistency between models and therefore decrease the current uncertainties.
Daniele Visioni, Douglas G. MacMartin, Ben Kravitz, Olivier Boucher, Andy Jones, Thibaut Lurton, Michou Martine, Michael J. Mills, Pierre Nabat, Ulrike Niemeier, Roland Séférian, and Simone Tilmes
Atmos. Chem. Phys., 21, 10039–10063, https://doi.org/10.5194/acp-21-10039-2021, https://doi.org/10.5194/acp-21-10039-2021, 2021
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A new set of simulations is used to investigate commonalities, differences and sources of uncertainty when simulating the injection of SO2 in the stratosphere in order to mitigate the effects of climate change (solar geoengineering). The models differ in how they simulate the aerosols and how they spread around the stratosphere, resulting in differences in projected regional impacts. Overall, however, the models agree that aerosols have the potential to mitigate the warming produced by GHGs.
Josué Bock, Martine Michou, Pierre Nabat, Manabu Abe, Jane P. Mulcahy, Dirk J. L. Olivié, Jörg Schwinger, Parvadha Suntharalingam, Jerry Tjiputra, Marco van Hulten, Michio Watanabe, Andrew Yool, and Roland Séférian
Biogeosciences, 18, 3823–3860, https://doi.org/10.5194/bg-18-3823-2021, https://doi.org/10.5194/bg-18-3823-2021, 2021
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In this study we analyse surface ocean dimethylsulfide (DMS) concentration and flux to the atmosphere from four CMIP6 Earth system models over the historical and ssp585 simulations.
Our analysis of contemporary (1980–2009) climatologies shows that models better reproduce observations in mid to high latitudes. The models disagree on the sign of the trend of the global DMS flux from 1980 onwards. The models agree on a positive trend of DMS over polar latitudes following sea-ice retreat dynamics.
Andrew Yool, Julien Palmiéri, Colin G. Jones, Lee de Mora, Till Kuhlbrodt, Ekatarina E. Popova, A. J. George Nurser, Joel Hirschi, Adam T. Blaker, Andrew C. Coward, Edward W. Blockley, and Alistair A. Sellar
Geosci. Model Dev., 14, 3437–3472, https://doi.org/10.5194/gmd-14-3437-2021, https://doi.org/10.5194/gmd-14-3437-2021, 2021
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The ocean plays a key role in modulating the Earth’s climate. Understanding this role is critical when using models to project future climate change. Consequently, it is necessary to evaluate their realism against the ocean's observed state. Here we validate UKESM1, a new Earth system model, focusing on the realism of its ocean physics and circulation, as well as its biological cycles and productivity. While we identify biases, generally the model performs well over a wide range of properties.
Anna B. Harper, Karina E. Williams, Patrick C. McGuire, Maria Carolina Duran Rojas, Debbie Hemming, Anne Verhoef, Chris Huntingford, Lucy Rowland, Toby Marthews, Cleiton Breder Eller, Camilla Mathison, Rodolfo L. B. Nobrega, Nicola Gedney, Pier Luigi Vidale, Fred Otu-Larbi, Divya Pandey, Sebastien Garrigues, Azin Wright, Darren Slevin, Martin G. De Kauwe, Eleanor Blyth, Jonas Ardö, Andrew Black, Damien Bonal, Nina Buchmann, Benoit Burban, Kathrin Fuchs, Agnès de Grandcourt, Ivan Mammarella, Lutz Merbold, Leonardo Montagnani, Yann Nouvellon, Natalia Restrepo-Coupe, and Georg Wohlfahrt
Geosci. Model Dev., 14, 3269–3294, https://doi.org/10.5194/gmd-14-3269-2021, https://doi.org/10.5194/gmd-14-3269-2021, 2021
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We evaluated 10 representations of soil moisture stress in the JULES land surface model against site observations of GPP and latent heat flux. Increasing the soil depth and plant access to deep soil moisture improved many aspects of the simulations, and we recommend these settings in future work using JULES. In addition, using soil matric potential presents the opportunity to include parameters specific to plant functional type to further improve modeled fluxes.
Neil P. Hindley, Corwin J. Wright, Alan M. Gadian, Lars Hoffmann, John K. Hughes, David R. Jackson, John C. King, Nicholas J. Mitchell, Tracy Moffat-Griffin, Andrew C. Moss, Simon B. Vosper, and Andrew N. Ross
Atmos. Chem. Phys., 21, 7695–7722, https://doi.org/10.5194/acp-21-7695-2021, https://doi.org/10.5194/acp-21-7695-2021, 2021
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One limitation of numerical atmospheric models is spatial resolution. For atmospheric gravity waves (GWs) generated over small mountainous islands, the driving effect of these waves on atmospheric circulations can be underestimated. Here we use a specialised high-resolution model over South Georgia island to compare simulated stratospheric GWs to colocated 3-D satellite observations. We find reasonable model agreement with observations, with some GW amplitudes much larger than expected.
Garry D. Hayman, Edward Comyn-Platt, Chris Huntingford, Anna B. Harper, Tom Powell, Peter M. Cox, William Collins, Christopher Webber, Jason Lowe, Stephen Sitch, Joanna I. House, Jonathan C. Doelman, Detlef P. van Vuuren, Sarah E. Chadburn, Eleanor Burke, and Nicola Gedney
Earth Syst. Dynam., 12, 513–544, https://doi.org/10.5194/esd-12-513-2021, https://doi.org/10.5194/esd-12-513-2021, 2021
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We model greenhouse gas emission scenarios consistent with limiting global warming to either 1.5 or 2 °C above pre-industrial levels. We quantify the effectiveness of methane emission control and land-based mitigation options regionally. Our results highlight the importance of reducing methane emissions for realistic emission pathways that meet the global warming targets. For land-based mitigation, growing bioenergy crops on existing agricultural land is preferable to replacing forests.
Rachel E. Hawker, Annette K. Miltenberger, Jonathan M. Wilkinson, Adrian A. Hill, Ben J. Shipway, Zhiqiang Cui, Richard J. Cotton, Ken S. Carslaw, Paul R. Field, and Benjamin J. Murray
Atmos. Chem. Phys., 21, 5439–5461, https://doi.org/10.5194/acp-21-5439-2021, https://doi.org/10.5194/acp-21-5439-2021, 2021
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The impact of aerosols on clouds is a large source of uncertainty for future climate projections. Our results show that the radiative properties of a complex convective cloud field in the Saharan outflow region are sensitive to the temperature dependence of ice-nucleating particle concentrations. This means that differences in the aerosol source or composition, for the same aerosol size distribution, can cause differences in the outgoing radiation from regions dominated by tropical convection.
Ananth Ranjithkumar, Hamish Gordon, Christina Williamson, Andrew Rollins, Kirsty Pringle, Agnieszka Kupc, Nathan Luke Abraham, Charles Brock, and Ken Carslaw
Atmos. Chem. Phys., 21, 4979–5014, https://doi.org/10.5194/acp-21-4979-2021, https://doi.org/10.5194/acp-21-4979-2021, 2021
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The effect aerosols have on climate can be better understood by studying their vertical and spatial distribution throughout the atmosphere. We use observation data from the ATom campaign and evaluate the vertical profile of aerosol number concentration, sulfur dioxide and condensation sink using the UKESM (UK Earth System Model). We identify uncertainties in key atmospheric processes that help improve their theoretical representation in global climate models.
Ben Kravitz, Douglas G. MacMartin, Daniele Visioni, Olivier Boucher, Jason N. S. Cole, Jim Haywood, Andy Jones, Thibaut Lurton, Pierre Nabat, Ulrike Niemeier, Alan Robock, Roland Séférian, and Simone Tilmes
Atmos. Chem. Phys., 21, 4231–4247, https://doi.org/10.5194/acp-21-4231-2021, https://doi.org/10.5194/acp-21-4231-2021, 2021
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This study investigates multi-model response to idealized geoengineering (high CO2 with solar reduction) across two different generations of climate models. We find that, with the exception of a few cases, the results are unchanged between the different generations. This gives us confidence that broad conclusions about the response to idealized geoengineering are robust.
Margot Clyne, Jean-Francois Lamarque, Michael J. Mills, Myriam Khodri, William Ball, Slimane Bekki, Sandip S. Dhomse, Nicolas Lebas, Graham Mann, Lauren Marshall, Ulrike Niemeier, Virginie Poulain, Alan Robock, Eugene Rozanov, Anja Schmidt, Andrea Stenke, Timofei Sukhodolov, Claudia Timmreck, Matthew Toohey, Fiona Tummon, Davide Zanchettin, Yunqian Zhu, and Owen B. Toon
Atmos. Chem. Phys., 21, 3317–3343, https://doi.org/10.5194/acp-21-3317-2021, https://doi.org/10.5194/acp-21-3317-2021, 2021
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This study finds how and why five state-of-the-art global climate models with interactive stratospheric aerosols differ when simulating the aftermath of large volcanic injections as part of the Model Intercomparison Project on the climatic response to Volcanic forcing (VolMIP). We identify and explain the consequences of significant disparities in the underlying physics and chemistry currently in some of the models, which are problems likely not unique to the models participating in this study.
Claudia Tebaldi, Kevin Debeire, Veronika Eyring, Erich Fischer, John Fyfe, Pierre Friedlingstein, Reto Knutti, Jason Lowe, Brian O'Neill, Benjamin Sanderson, Detlef van Vuuren, Keywan Riahi, Malte Meinshausen, Zebedee Nicholls, Katarzyna B. Tokarska, George Hurtt, Elmar Kriegler, Jean-Francois Lamarque, Gerald Meehl, Richard Moss, Susanne E. Bauer, Olivier Boucher, Victor Brovkin, Young-Hwa Byun, Martin Dix, Silvio Gualdi, Huan Guo, Jasmin G. John, Slava Kharin, YoungHo Kim, Tsuyoshi Koshiro, Libin Ma, Dirk Olivié, Swapna Panickal, Fangli Qiao, Xinyao Rong, Nan Rosenbloom, Martin Schupfner, Roland Séférian, Alistair Sellar, Tido Semmler, Xiaoying Shi, Zhenya Song, Christian Steger, Ronald Stouffer, Neil Swart, Kaoru Tachiiri, Qi Tang, Hiroaki Tatebe, Aurore Voldoire, Evgeny Volodin, Klaus Wyser, Xiaoge Xin, Shuting Yang, Yongqiang Yu, and Tilo Ziehn
Earth Syst. Dynam., 12, 253–293, https://doi.org/10.5194/esd-12-253-2021, https://doi.org/10.5194/esd-12-253-2021, 2021
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We present an overview of CMIP6 ScenarioMIP outcomes from up to 38 participating ESMs according to the new SSP-based scenarios. Average temperature and precipitation projections according to a wide range of forcings, spanning a wider range than the CMIP5 projections, are documented as global averages and geographic patterns. Times of crossing various warming levels are computed, together with benefits of mitigation for selected pairs of scenarios. Comparisons with CMIP5 are also discussed.
Kamalika Sengupta, Kirsty Pringle, Jill S. Johnson, Carly Reddington, Jo Browse, Catherine E. Scott, and Ken Carslaw
Atmos. Chem. Phys., 21, 2693–2723, https://doi.org/10.5194/acp-21-2693-2021, https://doi.org/10.5194/acp-21-2693-2021, 2021
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Global models consistently underestimate atmospheric secondary organic aerosol (SOA), which has significant climatic implications. We use a perturbed parameter model ensemble and ground-based observations to reduce the uncertainty in modelling SOA formation from oxidation of volatile organic compounds. We identify plausible parameter spaces for the yields of extremely low-volatility, low-volatility, and semi-volatile organic compounds based on model–observation match for three key model outputs.
Bijoy Thompson, Claudio Sanchez, Boon Chong Peter Heng, Rajesh Kumar, Jianyu Liu, Xiang-Yu Huang, and Pavel Tkalich
Geosci. Model Dev., 14, 1081–1100, https://doi.org/10.5194/gmd-14-1081-2021, https://doi.org/10.5194/gmd-14-1081-2021, 2021
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This article describes the development and ocean forecast evaluation of an atmosphere–ocean coupled prediction system for the Maritime Continent domain, which includes the eastern Indian and western Pacific oceans. The coupled system comprises regional configurations of the atmospheric model MetUM and ocean model NEMO, coupled using the OASIS3-MCT libraries. The model forecast deviation of selected fields relative to observations is within acceptable error limits of operational forecast models.
Jacob W. Smith, Peter H. Haynes, Amanda C. Maycock, Neal Butchart, and Andrew C. Bushell
Atmos. Chem. Phys., 21, 2469–2489, https://doi.org/10.5194/acp-21-2469-2021, https://doi.org/10.5194/acp-21-2469-2021, 2021
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This paper informs realistic simulation of stratospheric water vapour by clearly attributing each of the two key influences on water vapour entry to the stratosphere. Presenting modified trajectory models, the results of this paper show temperatures dominate on annual and inter-annual variations; however, transport has a significant effect in reducing the annual cycle maximum. Furthermore, sub-seasonal variations in temperature have an important overall influence.
Fiona M. O'Connor, N. Luke Abraham, Mohit Dalvi, Gerd A. Folberth, Paul T. Griffiths, Catherine Hardacre, Ben T. Johnson, Ron Kahana, James Keeble, Byeonghyeon Kim, Olaf Morgenstern, Jane P. Mulcahy, Mark Richardson, Eddy Robertson, Jeongbyn Seo, Sungbo Shim, João C. Teixeira, Steven T. Turnock, Jonny Williams, Andrew J. Wiltshire, Stephanie Woodward, and Guang Zeng
Atmos. Chem. Phys., 21, 1211–1243, https://doi.org/10.5194/acp-21-1211-2021, https://doi.org/10.5194/acp-21-1211-2021, 2021
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This paper calculates how changes in emissions and/or concentrations of different atmospheric constituents since the pre-industrial era have altered the Earth's energy budget at the present day using a metric called effective radiative forcing. The impact of land use change is also assessed. We find that individual contributions do not add linearly, and different Earth system interactions can affect the magnitude of the calculated effective radiative forcing.
Andy Jones, Jim M. Haywood, Anthony C. Jones, Simone Tilmes, Ben Kravitz, and Alan Robock
Atmos. Chem. Phys., 21, 1287–1304, https://doi.org/10.5194/acp-21-1287-2021, https://doi.org/10.5194/acp-21-1287-2021, 2021
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Two different methods of simulating a geoengineering scenario are compared using data from two different Earth system models. One method is very idealised while the other includes details of a plausible mechanism. The results from both models agree that the idealised approach does not capture an impact found when detailed modelling is included, namely that geoengineering induces a positive phase of the North Atlantic Oscillation which leads to warmer, wetter winters in northern Europe.
Gillian Thornhill, William Collins, Dirk Olivié, Ragnhild B. Skeie, Alex Archibald, Susanne Bauer, Ramiro Checa-Garcia, Stephanie Fiedler, Gerd Folberth, Ada Gjermundsen, Larry Horowitz, Jean-Francois Lamarque, Martine Michou, Jane Mulcahy, Pierre Nabat, Vaishali Naik, Fiona M. O'Connor, Fabien Paulot, Michael Schulz, Catherine E. Scott, Roland Séférian, Chris Smith, Toshihiko Takemura, Simone Tilmes, Kostas Tsigaridis, and James Weber
Atmos. Chem. Phys., 21, 1105–1126, https://doi.org/10.5194/acp-21-1105-2021, https://doi.org/10.5194/acp-21-1105-2021, 2021
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We find that increased temperatures affect aerosols and reactive gases by changing natural emissions and their rates of removal from the atmosphere. Changing the composition of these species in the atmosphere affects the radiative budget of the climate system and therefore amplifies or dampens the climate response of climate models of the Earth system. This study found that the largest effect is a dampening of climate change as warmer temperatures increase the emissions of cooling aerosols.
Jim M. Haywood, Steven J. Abel, Paul A. Barrett, Nicolas Bellouin, Alan Blyth, Keith N. Bower, Melissa Brooks, Ken Carslaw, Haochi Che, Hugh Coe, Michael I. Cotterell, Ian Crawford, Zhiqiang Cui, Nicholas Davies, Beth Dingley, Paul Field, Paola Formenti, Hamish Gordon, Martin de Graaf, Ross Herbert, Ben Johnson, Anthony C. Jones, Justin M. Langridge, Florent Malavelle, Daniel G. Partridge, Fanny Peers, Jens Redemann, Philip Stier, Kate Szpek, Jonathan W. Taylor, Duncan Watson-Parris, Robert Wood, Huihui Wu, and Paquita Zuidema
Atmos. Chem. Phys., 21, 1049–1084, https://doi.org/10.5194/acp-21-1049-2021, https://doi.org/10.5194/acp-21-1049-2021, 2021
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Every year, the seasonal cycle of biomass burning from agricultural practices in Africa creates a huge plume of smoke that travels many thousands of kilometres over the Atlantic Ocean. This study provides an overview of a measurement campaign called the cloud–aerosol–radiation interaction and forcing for year 2017 (CLARIFY-2017) and documents the rationale, deployment strategy, observations, and key results from the campaign which utilized the heavily equipped FAAM atmospheric research aircraft.
Gillian D. Thornhill, William J. Collins, Ryan J. Kramer, Dirk Olivié, Ragnhild B. Skeie, Fiona M. O'Connor, Nathan Luke Abraham, Ramiro Checa-Garcia, Susanne E. Bauer, Makoto Deushi, Louisa K. Emmons, Piers M. Forster, Larry W. Horowitz, Ben Johnson, James Keeble, Jean-Francois Lamarque, Martine Michou, Michael J. Mills, Jane P. Mulcahy, Gunnar Myhre, Pierre Nabat, Vaishali Naik, Naga Oshima, Michael Schulz, Christopher J. Smith, Toshihiko Takemura, Simone Tilmes, Tongwen Wu, Guang Zeng, and Jie Zhang
Atmos. Chem. Phys., 21, 853–874, https://doi.org/10.5194/acp-21-853-2021, https://doi.org/10.5194/acp-21-853-2021, 2021
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This paper is a study of how different constituents in the atmosphere, such as aerosols and gases like methane and ozone, affect the energy balance in the atmosphere. Different climate models were run using the same inputs to allow an easy comparison of the results and to understand where the models differ. We found the effect of aerosols is to reduce warming in the atmosphere, but this effect varies between models. Reactions between gases are also important in affecting climate.
Benjamin J. Murray, Kenneth S. Carslaw, and Paul R. Field
Atmos. Chem. Phys., 21, 665–679, https://doi.org/10.5194/acp-21-665-2021, https://doi.org/10.5194/acp-21-665-2021, 2021
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The balance between the amounts of ice and supercooled water in clouds over the world's oceans strongly influences how much these clouds can dampen or amplify global warming. Aerosol particles which catalyse ice formation can dramatically reduce the amount of supercooled water in clouds; hence we argue that we need a concerted effort to improve our understanding of these ice-nucleating particles if we are to improve our predictions of climate change.
Jane P. Mulcahy, Colin Johnson, Colin G. Jones, Adam C. Povey, Catherine E. Scott, Alistair Sellar, Steven T. Turnock, Matthew T. Woodhouse, Nathan Luke Abraham, Martin B. Andrews, Nicolas Bellouin, Jo Browse, Ken S. Carslaw, Mohit Dalvi, Gerd A. Folberth, Matthew Glover, Daniel P. Grosvenor, Catherine Hardacre, Richard Hill, Ben Johnson, Andy Jones, Zak Kipling, Graham Mann, James Mollard, Fiona M. O'Connor, Julien Palmiéri, Carly Reddington, Steven T. Rumbold, Mark Richardson, Nick A. J. Schutgens, Philip Stier, Marc Stringer, Yongming Tang, Jeremy Walton, Stephanie Woodward, and Andrew Yool
Geosci. Model Dev., 13, 6383–6423, https://doi.org/10.5194/gmd-13-6383-2020, https://doi.org/10.5194/gmd-13-6383-2020, 2020
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Aerosols are an important component of the Earth system. Here, we comprehensively document and evaluate the aerosol schemes as implemented in the physical and Earth system models, HadGEM3-GC3.1 and UKESM1. This study provides a useful characterisation of the aerosol climatology in both models, facilitating the understanding of the numerous aerosol–climate interaction studies that will be conducted for CMIP6 and beyond.
Richard Essery, Hyungjun Kim, Libo Wang, Paul Bartlett, Aaron Boone, Claire Brutel-Vuilmet, Eleanor Burke, Matthias Cuntz, Bertrand Decharme, Emanuel Dutra, Xing Fang, Yeugeniy Gusev, Stefan Hagemann, Vanessa Haverd, Anna Kontu, Gerhard Krinner, Matthieu Lafaysse, Yves Lejeune, Thomas Marke, Danny Marks, Christoph Marty, Cecile B. Menard, Olga Nasonova, Tomoko Nitta, John Pomeroy, Gerd Schädler, Vladimir Semenov, Tatiana Smirnova, Sean Swenson, Dmitry Turkov, Nander Wever, and Hua Yuan
The Cryosphere, 14, 4687–4698, https://doi.org/10.5194/tc-14-4687-2020, https://doi.org/10.5194/tc-14-4687-2020, 2020
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Climate models are uncertain in predicting how warming changes snow cover. This paper compares 22 snow models with the same meteorological inputs. Predicted trends agree with observations at four snow research sites: winter snow cover does not start later, but snow now melts earlier in spring than in the 1980s at two of the sites. Cold regions where snow can last until late summer are predicted to be particularly sensitive to warming because the snow then melts faster at warmer times of year.
Daniel P. Grosvenor and Kenneth S. Carslaw
Atmos. Chem. Phys., 20, 15681–15724, https://doi.org/10.5194/acp-20-15681-2020, https://doi.org/10.5194/acp-20-15681-2020, 2020
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Particles arising from human activity interact with clouds and affect how much of the Sun's energy is reflected away. Lack of understanding about how to represent this in models leads to large uncertainties in climate predictions. We quantify cloud responses to particles in the latest UK Met Office climate model over the North Atlantic Ocean, showing that, in contrast to suggestions elsewhere, increases in cloud coverage and thickness are important over large areas.
Steven T. Turnock, Robert J. Allen, Martin Andrews, Susanne E. Bauer, Makoto Deushi, Louisa Emmons, Peter Good, Larry Horowitz, Jasmin G. John, Martine Michou, Pierre Nabat, Vaishali Naik, David Neubauer, Fiona M. O'Connor, Dirk Olivié, Naga Oshima, Michael Schulz, Alistair Sellar, Sungbo Shim, Toshihiko Takemura, Simone Tilmes, Kostas Tsigaridis, Tongwen Wu, and Jie Zhang
Atmos. Chem. Phys., 20, 14547–14579, https://doi.org/10.5194/acp-20-14547-2020, https://doi.org/10.5194/acp-20-14547-2020, 2020
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A first assessment is made of the historical and future changes in air pollutants from models participating in the 6th Coupled Model Intercomparison Project (CMIP6). Substantial benefits to future air quality can be achieved in future scenarios that implement measures to mitigate climate and involve reductions in air pollutant emissions, particularly methane. However, important differences are shown between models in the future regional projection of air pollutants under the same scenario.
Juan-Carlos Antuña-Marrero, Graham W. Mann, Philippe Keckhut, Sergey Avdyushin, Bruno Nardi, and Larry W. Thomason
Earth Syst. Sci. Data, 12, 2843–2851, https://doi.org/10.5194/essd-12-2843-2020, https://doi.org/10.5194/essd-12-2843-2020, 2020
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We report the recovery of lidar measurements of the 1991 Pinatubo eruption. Two Soviet ships crossing the tropical Atlantic in July–September 1991 and January–February 1992 measured the vertical profile of the Pinatubo cloud at different points in its spatio-temporal evolution. The datasets provide valuable new information on the eruption's impacts on climate, with the SAGE-II satellite measurements not able to measure most of the lower half of the Pinatubo cloud in the tropics in this period.
Sandip S. Dhomse, Graham W. Mann, Juan Carlos Antuña Marrero, Sarah E. Shallcross, Martyn P. Chipperfield, Kenneth S. Carslaw, Lauren Marshall, N. Luke Abraham, and Colin E. Johnson
Atmos. Chem. Phys., 20, 13627–13654, https://doi.org/10.5194/acp-20-13627-2020, https://doi.org/10.5194/acp-20-13627-2020, 2020
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We confirm downward adjustment of SO2 emission to simulate the Pinatubo aerosol cloud with aerosol microphysics models. Similar adjustment is also needed to simulate the El Chichón and Agung volcanic cloud, indicating potential missing removal or vertical redistribution process in models. Important inhomogeneities in the CMIP6 forcing datasets after Agung and El Chichón eruptions are difficult to reconcile. Quasi-biennial oscillation plays an important role in modifying stratospheric warming.
Rachel L. Tunnicliffe, Anita L. Ganesan, Robert J. Parker, Hartmut Boesch, Nicola Gedney, Benjamin Poulter, Zhen Zhang, Jošt V. Lavrič, David Walter, Matthew Rigby, Stephan Henne, Dickon Young, and Simon O'Doherty
Atmos. Chem. Phys., 20, 13041–13067, https://doi.org/10.5194/acp-20-13041-2020, https://doi.org/10.5194/acp-20-13041-2020, 2020
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This study quantifies Brazil’s emissions of a potent atmospheric greenhouse gas, methane. This is in the field of atmospheric modelling and uses remotely sensed data and surface measurements of methane concentrations as well as an atmospheric transport model to interpret the data. Because of Brazil’s large emissions from wetlands, agriculture and biomass burning, these emissions affect global methane concentrations and thus are of global significance.
Debbie O'Sullivan, Franco Marenco, Claire L. Ryder, Yaswant Pradhan, Zak Kipling, Ben Johnson, Angela Benedetti, Melissa Brooks, Matthew McGill, John Yorks, and Patrick Selmer
Atmos. Chem. Phys., 20, 12955–12982, https://doi.org/10.5194/acp-20-12955-2020, https://doi.org/10.5194/acp-20-12955-2020, 2020
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Mineral dust is an important component of the climate system, and we assess how well it is predicted by two operational models. We flew an aircraft in the dust layers in the eastern Atlantic, and we also make use of satellites. We show that models predict the dust layer too low and that it predicts the particles to be too small. We believe that these discrepancies may be overcome if models can be constrained with operational observations of dust vertical and size-resolved distribution.
Hamish Gordon, Paul R. Field, Steven J. Abel, Paul Barrett, Keith Bower, Ian Crawford, Zhiqiang Cui, Daniel P. Grosvenor, Adrian A. Hill, Jonathan Taylor, Jonathan Wilkinson, Huihui Wu, and Ken S. Carslaw
Atmos. Chem. Phys., 20, 10997–11024, https://doi.org/10.5194/acp-20-10997-2020, https://doi.org/10.5194/acp-20-10997-2020, 2020
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The Met Office's Unified Model is widely used both for weather forecasting and climate prediction. We present the first version of the model in which both aerosol and cloud particle mass and number concentrations are allowed to evolve separately and independently, which is important for studying how aerosols affect weather and climate. We test the model against aircraft observations near Ascension Island in the Atlantic, focusing on how aerosols can "activate" to become cloud droplets.
Lee de Mora, Alistair A. Sellar, Andrew Yool, Julien Palmieri, Robin S. Smith, Till Kuhlbrodt, Robert J. Parker, Jeremy Walton, Jeremy C. Blackford, and Colin G. Jones
Geosci. Commun., 3, 263–278, https://doi.org/10.5194/gc-3-263-2020, https://doi.org/10.5194/gc-3-263-2020, 2020
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We use time series data from the first United Kingdom Earth System Model (UKESM1) to create six procedurally generated musical pieces for piano. Each of the six pieces help to explain either a scientific principle or a practical aspect of Earth system modelling. We describe the methods that were used to create these pieces, discuss the limitations of this pilot study and list several approaches to extend and expand upon this work.
Leighton A. Regayre, Julia Schmale, Jill S. Johnson, Christian Tatzelt, Andrea Baccarini, Silvia Henning, Masaru Yoshioka, Frank Stratmann, Martin Gysel-Beer, Daniel P. Grosvenor, and Ken S. Carslaw
Atmos. Chem. Phys., 20, 10063–10072, https://doi.org/10.5194/acp-20-10063-2020, https://doi.org/10.5194/acp-20-10063-2020, 2020
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The amount of energy reflected back into space because of man-made particles is highly uncertain. Processes related to naturally occurring particles cause most of the uncertainty, but these processes are poorly constrained by present-day measurements. We show that measurements over the Southern Ocean, far from pollution sources, efficiently reduce climate model uncertainties. Our results pave the way to designing experiments and measurement campaigns that reduce this uncertainty even further.
Jill S. Johnson, Leighton A. Regayre, Masaru Yoshioka, Kirsty J. Pringle, Steven T. Turnock, Jo Browse, David M. H. Sexton, John W. Rostron, Nick A. J. Schutgens, Daniel G. Partridge, Dantong Liu, James D. Allan, Hugh Coe, Aijun Ding, David D. Cohen, Armand Atanacio, Ville Vakkari, Eija Asmi, and Ken S. Carslaw
Atmos. Chem. Phys., 20, 9491–9524, https://doi.org/10.5194/acp-20-9491-2020, https://doi.org/10.5194/acp-20-9491-2020, 2020
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We use over 9000 monthly aggregated grid-box measurements of aerosol to constrain the uncertainty in the HadGEM3-UKCA climate model. Measurements of AOD, PM2.5, particle number concentrations, sulfate and organic mass concentrations are compared to 1 million
variantsof the model using an implausibility metric. Despite many compensating effects in the model, the procedure constrains the probability distributions of many parameters, and direct radiative forcing uncertainty is reduced by 34 %.
Lawrence Mudryk, María Santolaria-Otín, Gerhard Krinner, Martin Ménégoz, Chris Derksen, Claire Brutel-Vuilmet, Mike Brady, and Richard Essery
The Cryosphere, 14, 2495–2514, https://doi.org/10.5194/tc-14-2495-2020, https://doi.org/10.5194/tc-14-2495-2020, 2020
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We analyze how well updated state-of-the-art climate models reproduce observed historical snow cover extent and snow mass and how they project that these quantities will change up to the year 2100. Overall the updated models better represent historical snow extent than previous models, and they simulate stronger historical trends in snow extent and snow mass. They project that spring snow extent will decrease by 8 % for each degree Celsius that the global surface air temperature increases.
Veronika Eyring, Lisa Bock, Axel Lauer, Mattia Righi, Manuel Schlund, Bouwe Andela, Enrico Arnone, Omar Bellprat, Björn Brötz, Louis-Philippe Caron, Nuno Carvalhais, Irene Cionni, Nicola Cortesi, Bas Crezee, Edouard L. Davin, Paolo Davini, Kevin Debeire, Lee de Mora, Clara Deser, David Docquier, Paul Earnshaw, Carsten Ehbrecht, Bettina K. Gier, Nube Gonzalez-Reviriego, Paul Goodman, Stefan Hagemann, Steven Hardiman, Birgit Hassler, Alasdair Hunter, Christopher Kadow, Stephan Kindermann, Sujan Koirala, Nikolay Koldunov, Quentin Lejeune, Valerio Lembo, Tomas Lovato, Valerio Lucarini, François Massonnet, Benjamin Müller, Amarjiit Pandde, Núria Pérez-Zanón, Adam Phillips, Valeriu Predoi, Joellen Russell, Alistair Sellar, Federico Serva, Tobias Stacke, Ranjini Swaminathan, Verónica Torralba, Javier Vegas-Regidor, Jost von Hardenberg, Katja Weigel, and Klaus Zimmermann
Geosci. Model Dev., 13, 3383–3438, https://doi.org/10.5194/gmd-13-3383-2020, https://doi.org/10.5194/gmd-13-3383-2020, 2020
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The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool designed to improve comprehensive and routine evaluation of earth system models (ESMs) participating in the Coupled Model Intercomparison Project (CMIP). It has undergone rapid development since the first release in 2016 and is now a well-tested tool that provides end-to-end provenance tracking to ensure reproducibility.
Prodromos Zanis, Dimitris Akritidis, Aristeidis K. Georgoulias, Robert J. Allen, Susanne E. Bauer, Olivier Boucher, Jason Cole, Ben Johnson, Makoto Deushi, Martine Michou, Jane Mulcahy, Pierre Nabat, Dirk Olivié, Naga Oshima, Adriana Sima, Michael Schulz, Toshihiko Takemura, and Konstantinos Tsigaridis
Atmos. Chem. Phys., 20, 8381–8404, https://doi.org/10.5194/acp-20-8381-2020, https://doi.org/10.5194/acp-20-8381-2020, 2020
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In this work, we use Coupled Model Intercomparison Project Phase 6 (CMIP6) simulations from 10 Earth system models (ESMs) and general circulation models (GCMs) to study the fast climate responses on pre-industrial climate, due to present-day aerosols. All models carried out two sets of simulations: a control experiment with all forcings set to the year 1850 and a perturbation experiment with all forcings identical to the control, except for aerosols with precursor emissions set to the year 2014.
Marielle Saunois, Ann R. Stavert, Ben Poulter, Philippe Bousquet, Josep G. Canadell, Robert B. Jackson, Peter A. Raymond, Edward J. Dlugokencky, Sander Houweling, Prabir K. Patra, Philippe Ciais, Vivek K. Arora, David Bastviken, Peter Bergamaschi, Donald R. Blake, Gordon Brailsford, Lori Bruhwiler, Kimberly M. Carlson, Mark Carrol, Simona Castaldi, Naveen Chandra, Cyril Crevoisier, Patrick M. Crill, Kristofer Covey, Charles L. Curry, Giuseppe Etiope, Christian Frankenberg, Nicola Gedney, Michaela I. Hegglin, Lena Höglund-Isaksson, Gustaf Hugelius, Misa Ishizawa, Akihiko Ito, Greet Janssens-Maenhout, Katherine M. Jensen, Fortunat Joos, Thomas Kleinen, Paul B. Krummel, Ray L. Langenfelds, Goulven G. Laruelle, Licheng Liu, Toshinobu Machida, Shamil Maksyutov, Kyle C. McDonald, Joe McNorton, Paul A. Miller, Joe R. Melton, Isamu Morino, Jurek Müller, Fabiola Murguia-Flores, Vaishali Naik, Yosuke Niwa, Sergio Noce, Simon O'Doherty, Robert J. Parker, Changhui Peng, Shushi Peng, Glen P. Peters, Catherine Prigent, Ronald Prinn, Michel Ramonet, Pierre Regnier, William J. Riley, Judith A. Rosentreter, Arjo Segers, Isobel J. Simpson, Hao Shi, Steven J. Smith, L. Paul Steele, Brett F. Thornton, Hanqin Tian, Yasunori Tohjima, Francesco N. Tubiello, Aki Tsuruta, Nicolas Viovy, Apostolos Voulgarakis, Thomas S. Weber, Michiel van Weele, Guido R. van der Werf, Ray F. Weiss, Doug Worthy, Debra Wunch, Yi Yin, Yukio Yoshida, Wenxin Zhang, Zhen Zhang, Yuanhong Zhao, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data, 12, 1561–1623, https://doi.org/10.5194/essd-12-1561-2020, https://doi.org/10.5194/essd-12-1561-2020, 2020
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Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. We have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. This is the second version of the review dedicated to the decadal methane budget, integrating results of top-down and bottom-up estimates.
Dominik Stolzenburg, Mario Simon, Ananth Ranjithkumar, Andreas Kürten, Katrianne Lehtipalo, Hamish Gordon, Sebastian Ehrhart, Henning Finkenzeller, Lukas Pichelstorfer, Tuomo Nieminen, Xu-Cheng He, Sophia Brilke, Mao Xiao, António Amorim, Rima Baalbaki, Andrea Baccarini, Lisa Beck, Steffen Bräkling, Lucía Caudillo Murillo, Dexian Chen, Biwu Chu, Lubna Dada, António Dias, Josef Dommen, Jonathan Duplissy, Imad El Haddad, Lukas Fischer, Loic Gonzalez Carracedo, Martin Heinritzi, Changhyuk Kim, Theodore K. Koenig, Weimeng Kong, Houssni Lamkaddam, Chuan Ping Lee, Markus Leiminger, Zijun Li, Vladimir Makhmutov, Hanna E. Manninen, Guillaume Marie, Ruby Marten, Tatjana Müller, Wei Nie, Eva Partoll, Tuukka Petäjä, Joschka Pfeifer, Maxim Philippov, Matti P. Rissanen, Birte Rörup, Siegfried Schobesberger, Simone Schuchmann, Jiali Shen, Mikko Sipilä, Gerhard Steiner, Yuri Stozhkov, Christian Tauber, Yee Jun Tham, António Tomé, Miguel Vazquez-Pufleau, Andrea C. Wagner, Mingyi Wang, Yonghong Wang, Stefan K. Weber, Daniela Wimmer, Peter J. Wlasits, Yusheng Wu, Qing Ye, Marcel Zauner-Wieczorek, Urs Baltensperger, Kenneth S. Carslaw, Joachim Curtius, Neil M. Donahue, Richard C. Flagan, Armin Hansel, Markku Kulmala, Jos Lelieveld, Rainer Volkamer, Jasper Kirkby, and Paul M. Winkler
Atmos. Chem. Phys., 20, 7359–7372, https://doi.org/10.5194/acp-20-7359-2020, https://doi.org/10.5194/acp-20-7359-2020, 2020
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Sulfuric acid is a major atmospheric vapour for aerosol formation. If new particles grow fast enough, they can act as cloud droplet seeds or affect air quality. In a controlled laboratory set-up, we demonstrate that van der Waals forces enhance growth from sulfuric acid. We disentangle the effects of ammonia, ions and particle hydration, presenting a complete picture of sulfuric acid growth from molecular clusters onwards. In a climate model, we show its influence on the global aerosol budget.
William T. Morgan, James D. Allan, Stéphane Bauguitte, Eoghan Darbyshire, Michael J. Flynn, James Lee, Dantong Liu, Ben Johnson, Jim Haywood, Karla M. Longo, Paulo E. Artaxo, and Hugh Coe
Atmos. Chem. Phys., 20, 5309–5326, https://doi.org/10.5194/acp-20-5309-2020, https://doi.org/10.5194/acp-20-5309-2020, 2020
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We flew a large atmospheric research aircraft across a number of different environments in the Amazon basin during the 2012 biomass burning season. Smoke from fires builds up and has a significant impact on weather, climate, health and natural ecosystems. Our goal was to quantify changes in the properties of the smoke emitted by fires as it is transported through the atmosphere. We found that the major control on the properties of the smoke was due to differences in the fires themselves.
Minchao Wu, Grigory Nikulin, Erik Kjellström, Danijel Belušić, Colin Jones, and David Lindstedt
Earth Syst. Dynam., 11, 377–394, https://doi.org/10.5194/esd-11-377-2020, https://doi.org/10.5194/esd-11-377-2020, 2020
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Regional Climate Models constitute a downscaling tool to provide high-resolution data for impact and adaptation studies. However, there is no unique definition of the added value of downscaling as it depends on many factors. We investigate the impact of spatial resolution and model formulation on downscaled rainfall in Africa. Our results show that improvements in downscaled rainfall compared to the driving reanalysis are often related to model formulation and not always to higher resolution.
Mike Bush, Tom Allen, Caroline Bain, Ian Boutle, John Edwards, Anke Finnenkoetter, Charmaine Franklin, Kirsty Hanley, Humphrey Lean, Adrian Lock, James Manners, Marion Mittermaier, Cyril Morcrette, Rachel North, Jon Petch, Chris Short, Simon Vosper, David Walters, Stuart Webster, Mark Weeks, Jonathan Wilkinson, Nigel Wood, and Mohamed Zerroukat
Geosci. Model Dev., 13, 1999–2029, https://doi.org/10.5194/gmd-13-1999-2020, https://doi.org/10.5194/gmd-13-1999-2020, 2020
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In this paper we define the first Regional Atmosphere and Land (RAL) science configuration for kilometre-scale modelling using the Unified Model (UM) as the basis for the atmosphere and the Joint UK Land Environment Simulator (JULES) for the land. RAL1 defines the science configuration of the dynamics and physics schemes of the atmosphere and land. This configuration will provide a model baseline for any future weather or climate model developments to be described against.
Alexander T. Archibald, Fiona M. O'Connor, Nathan Luke Abraham, Scott Archer-Nicholls, Martyn P. Chipperfield, Mohit Dalvi, Gerd A. Folberth, Fraser Dennison, Sandip S. Dhomse, Paul T. Griffiths, Catherine Hardacre, Alan J. Hewitt, Richard S. Hill, Colin E. Johnson, James Keeble, Marcus O. Köhler, Olaf Morgenstern, Jane P. Mulcahy, Carlos Ordóñez, Richard J. Pope, Steven T. Rumbold, Maria R. Russo, Nicholas H. Savage, Alistair Sellar, Marc Stringer, Steven T. Turnock, Oliver Wild, and Guang Zeng
Geosci. Model Dev., 13, 1223–1266, https://doi.org/10.5194/gmd-13-1223-2020, https://doi.org/10.5194/gmd-13-1223-2020, 2020
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Here we present a description and evaluation of the UKCA stratosphere–troposphere chemistry scheme (StratTrop vn 1.0) implemented in the UK Earth System Model (UKESM1). UKCA StratTrop represents a substantial step forward compared to previous versions of UKCA. We show here that it is fully suited to the challenges of representing interactions in a coupled Earth system model and identify key areas and components for future development that will make it even better in the future.
Mattia Righi, Bouwe Andela, Veronika Eyring, Axel Lauer, Valeriu Predoi, Manuel Schlund, Javier Vegas-Regidor, Lisa Bock, Björn Brötz, Lee de Mora, Faruk Diblen, Laura Dreyer, Niels Drost, Paul Earnshaw, Birgit Hassler, Nikolay Koldunov, Bill Little, Saskia Loosveldt Tomas, and Klaus Zimmermann
Geosci. Model Dev., 13, 1179–1199, https://doi.org/10.5194/gmd-13-1179-2020, https://doi.org/10.5194/gmd-13-1179-2020, 2020
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This paper describes the second major release of ESMValTool, a community diagnostic and performance metrics tool for the evaluation of Earth system models. This new version features a brand new design, with an improved interface and a revised preprocessor. It takes advantage of state-of-the-art computational libraries and methods to deploy efficient and user-friendly data processing, improving the performance over its predecessor by more than a factor of 30.
Constanze Wellmann, Andrew I. Barrett, Jill S. Johnson, Michael Kunz, Bernhard Vogel, Ken S. Carslaw, and Corinna Hoose
Atmos. Chem. Phys., 20, 2201–2219, https://doi.org/10.5194/acp-20-2201-2020, https://doi.org/10.5194/acp-20-2201-2020, 2020
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Severe hailstorms may cause damage to buildings and crops. Thus, the forecast of numerical weather prediction (NWP) models should be as reliable as possible.
Using statistical emulation, we identify those model input parameters describing environmental conditions and cloud microphysics which lead to large uncertainties in the prediction of deep convection. We find that the impact of the input parameters on the uncertainty depends on the considered output variable.
Thomas J. Fauchez, Martin Turbet, Eric T. Wolf, Ian Boutle, Michael J. Way, Anthony D. Del Genio, Nathan J. Mayne, Konstantinos Tsigaridis, Ravi K. Kopparapu, Jun Yang, Francois Forget, Avi Mandell, and Shawn D. Domagal Goldman
Geosci. Model Dev., 13, 707–716, https://doi.org/10.5194/gmd-13-707-2020, https://doi.org/10.5194/gmd-13-707-2020, 2020
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Atmospheric characterization of rocky exoplanets orbiting within the habitable zone of nearby M dwarf stars is around the corner with the James Webb Space Telescope (JWST), expected to be launch in 2021.
Global climate models (GCMs) are powerful tools to model exoplanet atmospheres and to predict their habitability. However, intrinsic differences between the models can lead to various predictions. This paper presents an experiment protocol to evaluate these differences.
Andrew J. Wiltshire, Maria Carolina Duran Rojas, John M. Edwards, Nicola Gedney, Anna B. Harper, Andrew J. Hartley, Margaret A. Hendry, Eddy Robertson, and Kerry Smout-Day
Geosci. Model Dev., 13, 483–505, https://doi.org/10.5194/gmd-13-483-2020, https://doi.org/10.5194/gmd-13-483-2020, 2020
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We present the Global Land (GL) configuration of the Joint UK Land Environment Simulator (JULES). JULES-GL7 can be used to simulate the exchange of heat, water and momentum over land and is therefore applicable for helping understand past and future changes, and forms the land component of the HadGEM3-GC3.1 climate model. The configuration is freely available subject to licence restrictions.
Laura E. Revell, Stefanie Kremser, Sean Hartery, Mike Harvey, Jane P. Mulcahy, Jonny Williams, Olaf Morgenstern, Adrian J. McDonald, Vidya Varma, Leroy Bird, and Alex Schuddeboom
Atmos. Chem. Phys., 19, 15447–15466, https://doi.org/10.5194/acp-19-15447-2019, https://doi.org/10.5194/acp-19-15447-2019, 2019
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Aerosols over the Southern Ocean consist primarily of sea salt and sulfate, yet are seasonally biased in our model. We test three sulfate chemistry schemes to investigate DMS oxidation, which forms sulfate aerosol. Simulated cloud droplet number concentrations improve using more complex sulfate chemistry. We also show that a new sea spray aerosol source function, developed from measurements made on a recent Southern Ocean research voyage, improves the model's simulation of aerosol optical depth.
Xiaoqi Xu, Chunsong Lu, Yangang Liu, Wenhua Gao, Yuan Wang, Yueming Cheng, Shi Luo, and Kwinten Van Weverberg
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2019-1063, https://doi.org/10.5194/acp-2019-1063, 2019
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A typical summer plateau precipitation event was simulated with the WRF model by introducing different parameterizations of liquid-phase microphysical processes and found that the low resolution is one reason responsible for the overprediction of precipitation over the Tibet Plateau. The inaccurate parameterization of accretion is another reason. It is critical to consider rain and cloud drop sizes in accretion parameterizations, which can suppress artificial accretion when drops are too small.
Nick Rutter, Melody J. Sandells, Chris Derksen, Joshua King, Peter Toose, Leanne Wake, Tom Watts, Richard Essery, Alexandre Roy, Alain Royer, Philip Marsh, Chris Larsen, and Matthew Sturm
The Cryosphere, 13, 3045–3059, https://doi.org/10.5194/tc-13-3045-2019, https://doi.org/10.5194/tc-13-3045-2019, 2019
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Impact of natural variability in Arctic tundra snow microstructural characteristics on the capacity to estimate snow water equivalent (SWE) from Ku-band radar was assessed. Median values of metrics quantifying snow microstructure adequately characterise differences between snowpack layers. Optimal estimates of SWE required microstructural values slightly less than the measured median but tolerated natural variability for accurate estimation of SWE in shallow snowpacks.
Duncan Watson-Parris, Nick Schutgens, Carly Reddington, Kirsty J. Pringle, Dantong Liu, James D. Allan, Hugh Coe, Ken S. Carslaw, and Philip Stier
Atmos. Chem. Phys., 19, 11765–11790, https://doi.org/10.5194/acp-19-11765-2019, https://doi.org/10.5194/acp-19-11765-2019, 2019
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The vertical distribution of aerosol in the atmosphere affects its ability to act as cloud condensation nuclei and changes the amount of sunlight it absorbs or reflects. Common global measurements of aerosol provide no information about this vertical distribution. Using a global collection of in situ aircraft measurements to compare with an aerosol–climate model (ECHAM-HAM), we explore the key processes controlling this distribution and find that wet removal plays a key role.
Franziska Glassmeier, Fabian Hoffmann, Jill S. Johnson, Takanobu Yamaguchi, Ken S. Carslaw, and Graham Feingold
Atmos. Chem. Phys., 19, 10191–10203, https://doi.org/10.5194/acp-19-10191-2019, https://doi.org/10.5194/acp-19-10191-2019, 2019
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The climatic relevance of aerosol–cloud interactions depends on the sensitivity of the radiative effect of clouds to certain cloud properties. We derive the dependence of cloud fraction, cloud albedo, and the relative cloud radiative effect on the number of cloud droplets and on liquid water path from a large set of detailed simulations of stratocumulus clouds.
Christoph Heinze, Veronika Eyring, Pierre Friedlingstein, Colin Jones, Yves Balkanski, William Collins, Thierry Fichefet, Shuang Gao, Alex Hall, Detelina Ivanova, Wolfgang Knorr, Reto Knutti, Alexander Löw, Michael Ponater, Martin G. Schultz, Michael Schulz, Pier Siebesma, Joao Teixeira, George Tselioudis, and Martin Vancoppenolle
Earth Syst. Dynam., 10, 379–452, https://doi.org/10.5194/esd-10-379-2019, https://doi.org/10.5194/esd-10-379-2019, 2019
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Earth system models for producing climate projections under given forcings include additional processes and feedbacks that traditional physical climate models do not consider. We present an overview of climate feedbacks for key Earth system components and discuss the evaluation of these feedbacks. The target group for this article includes generalists with a background in natural sciences and an interest in climate change as well as experts working in interdisciplinary climate research.
George S. Fanourgakis, Maria Kanakidou, Athanasios Nenes, Susanne E. Bauer, Tommi Bergman, Ken S. Carslaw, Alf Grini, Douglas S. Hamilton, Jill S. Johnson, Vlassis A. Karydis, Alf Kirkevåg, John K. Kodros, Ulrike Lohmann, Gan Luo, Risto Makkonen, Hitoshi Matsui, David Neubauer, Jeffrey R. Pierce, Julia Schmale, Philip Stier, Kostas Tsigaridis, Twan van Noije, Hailong Wang, Duncan Watson-Parris, Daniel M. Westervelt, Yang Yang, Masaru Yoshioka, Nikos Daskalakis, Stefano Decesari, Martin Gysel-Beer, Nikos Kalivitis, Xiaohong Liu, Natalie M. Mahowald, Stelios Myriokefalitakis, Roland Schrödner, Maria Sfakianaki, Alexandra P. Tsimpidi, Mingxuan Wu, and Fangqun Yu
Atmos. Chem. Phys., 19, 8591–8617, https://doi.org/10.5194/acp-19-8591-2019, https://doi.org/10.5194/acp-19-8591-2019, 2019
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Effects of aerosols on clouds are important for climate studies but are among the largest uncertainties in climate projections. This study evaluates the skill of global models to simulate aerosol, cloud condensation nuclei (CCN) and cloud droplet number concentrations (CDNCs). Model results show reduced spread in CDNC compared to CCN due to the negative correlation between the sensitivities of CDNC to aerosol number concentration (air pollution) and updraft velocity (atmospheric dynamics).
Jonathan W. Taylor, Sophie L. Haslett, Keith Bower, Michael Flynn, Ian Crawford, James Dorsey, Tom Choularton, Paul J. Connolly, Valerian Hahn, Christiane Voigt, Daniel Sauer, Régis Dupuy, Joel Brito, Alfons Schwarzenboeck, Thierry Bourriane, Cyrielle Denjean, Phil Rosenberg, Cyrille Flamant, James D. Lee, Adam R. Vaughan, Peter G. Hill, Barbara Brooks, Valéry Catoire, Peter Knippertz, and Hugh Coe
Atmos. Chem. Phys., 19, 8503–8522, https://doi.org/10.5194/acp-19-8503-2019, https://doi.org/10.5194/acp-19-8503-2019, 2019
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Low-level clouds cover a wide area of southern West Africa (SWA) and play an important role in the region's climate, reflecting sunlight away from the surface. We performed aircraft measurements of aerosols and clouds over SWA during the 2016 summer monsoon and found pollution, and polluted clouds, across the whole region. Smoke from biomass burning in Central Africa is transported to West Africa, causing a polluted background which limits the effect of local pollution on cloud properties.
Jamie M. Kelly, Ruth M. Doherty, Fiona M. O'Connor, Graham W. Mann, Hugh Coe, and Dantong Liu
Geosci. Model Dev., 12, 2539–2569, https://doi.org/10.5194/gmd-12-2539-2019, https://doi.org/10.5194/gmd-12-2539-2019, 2019
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This study develops the representation of secondary organic aerosol (SOA) within a global chemistry–climate model (UKCA). Both dry and wet deposition within the UKCA model are extended to consider precursors of SOA. The oxidation mechanism describing SOA formation is also extended by adding a reaction intermediate, with SOA yields that are dependent on oxidant concentrations.
Huw W. Lewis, John Siddorn, Juan Manuel Castillo Sanchez, Jon Petch, John M. Edwards, and Tim Smyth
Ocean Sci., 15, 761–778, https://doi.org/10.5194/os-15-761-2019, https://doi.org/10.5194/os-15-761-2019, 2019
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Oceans are modified at the surface by winds and by the exchange of heat with the atmosphere. The effect of changing atmospheric information that is available to drive an ocean model of north-west Europe, which can simulate small-scale details of the ocean state, is tested. We show that simulated temperatures agree better with observations located near the coast around the south-west UK when using data from a high-resolution atmospheric model, and when atmosphere and ocean feedbacks are included.
Huw W. Lewis, Juan Manuel Castillo Sanchez, Alex Arnold, Joachim Fallmann, Andrew Saulter, Jennifer Graham, Mike Bush, John Siddorn, Tamzin Palmer, Adrian Lock, John Edwards, Lucy Bricheno, Alberto Martínez-de la Torre, and James Clark
Geosci. Model Dev., 12, 2357–2400, https://doi.org/10.5194/gmd-12-2357-2019, https://doi.org/10.5194/gmd-12-2357-2019, 2019
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In the real world the atmosphere, oceans and land surface are closely interconnected, and yet the prediction systems used for weather and ocean forecasting tend to treat them in isolation. This paper describes the third version of a regional modelling system which aims to represent the feedback processes between sky, sea and land. The main innovation introduced in this version enables waves to affect the underlying ocean. Coupled results from four different month-long simulations are analysed.
Zongbo Shi, Tuan Vu, Simone Kotthaus, Roy M. Harrison, Sue Grimmond, Siyao Yue, Tong Zhu, James Lee, Yiqun Han, Matthias Demuzere, Rachel E. Dunmore, Lujie Ren, Di Liu, Yuanlin Wang, Oliver Wild, James Allan, W. Joe Acton, Janet Barlow, Benjamin Barratt, David Beddows, William J. Bloss, Giulia Calzolai, David Carruthers, David C. Carslaw, Queenie Chan, Lia Chatzidiakou, Yang Chen, Leigh Crilley, Hugh Coe, Tie Dai, Ruth Doherty, Fengkui Duan, Pingqing Fu, Baozhu Ge, Maofa Ge, Daobo Guan, Jacqueline F. Hamilton, Kebin He, Mathew Heal, Dwayne Heard, C. Nicholas Hewitt, Michael Hollaway, Min Hu, Dongsheng Ji, Xujiang Jiang, Rod Jones, Markus Kalberer, Frank J. Kelly, Louisa Kramer, Ben Langford, Chun Lin, Alastair C. Lewis, Jie Li, Weijun Li, Huan Liu, Junfeng Liu, Miranda Loh, Keding Lu, Franco Lucarelli, Graham Mann, Gordon McFiggans, Mark R. Miller, Graham Mills, Paul Monk, Eiko Nemitz, Fionna O'Connor, Bin Ouyang, Paul I. Palmer, Carl Percival, Olalekan Popoola, Claire Reeves, Andrew R. Rickard, Longyi Shao, Guangyu Shi, Dominick Spracklen, David Stevenson, Yele Sun, Zhiwei Sun, Shu Tao, Shengrui Tong, Qingqing Wang, Wenhua Wang, Xinming Wang, Xuejun Wang, Zifang Wang, Lianfang Wei, Lisa Whalley, Xuefang Wu, Zhijun Wu, Pinhua Xie, Fumo Yang, Qiang Zhang, Yanli Zhang, Yuanhang Zhang, and Mei Zheng
Atmos. Chem. Phys., 19, 7519–7546, https://doi.org/10.5194/acp-19-7519-2019, https://doi.org/10.5194/acp-19-7519-2019, 2019
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APHH-Beijing is a collaborative international research programme to study the sources, processes and health effects of air pollution in Beijing. This introduction to the special issue provides an overview of (i) the APHH-Beijing programme, (ii) the measurement and modelling activities performed as part of it and (iii) the air quality and meteorological conditions during joint intensive field campaigns as a core activity within APHH-Beijing.
Stephanie Fiedler, Stefan Kinne, Wan Ting Katty Huang, Petri Räisänen, Declan O'Donnell, Nicolas Bellouin, Philip Stier, Joonas Merikanto, Twan van Noije, Risto Makkonen, and Ulrike Lohmann
Atmos. Chem. Phys., 19, 6821–6841, https://doi.org/10.5194/acp-19-6821-2019, https://doi.org/10.5194/acp-19-6821-2019, 2019
Kuldeep Sharma, Sushant Kumar, Raghavendra Ashrit, Sean Milton, Ashis K. Mitra, and Ekkattil N. Rajagopal
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2019-65, https://doi.org/10.5194/gmd-2019-65, 2019
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This study is based on the long record (2007–2018) of UM model's real time rainfall forecasts over India to highlight the improved skill of forecasts over orographic regions of India. Some of these improvements are attributed to the increased horizontal and vertical resolutions as well as improved physics parameterization schemes while major credit to the substantial improvements in weather forecasting goes to the sophisticated data assimilation systems which utilizes satellite data.
Eoghan Darbyshire, William T. Morgan, James D. Allan, Dantong Liu, Michael J. Flynn, James R. Dorsey, Sebastian J. O'Shea, Douglas Lowe, Kate Szpek, Franco Marenco, Ben T. Johnson, Stephane Bauguitte, Jim M. Haywood, Joel F. Brito, Paulo Artaxo, Karla M. Longo, and Hugh Coe
Atmos. Chem. Phys., 19, 5771–5790, https://doi.org/10.5194/acp-19-5771-2019, https://doi.org/10.5194/acp-19-5771-2019, 2019
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A novel analysis of aerosol and gas-phase vertical profiles shows a marked regional pollution contrast: composition is driven by the fire regime and vertical distribution is driven by thermodynamics. These drivers ought to be well represented in simulations to ensure realistic prediction of climate and air quality impacts. The BC : CO ratio in haze and plumes increases with altitude – long-range transport or fire stage coupled to plume dynamics may be responsible. Further enquiry is advocated.
Jennifer K. Brooke, R. Chawn Harlow, Russell L. Scott, Martin J. Best, John M. Edwards, Jean-Claude Thelen, and Mark Weeks
Geosci. Model Dev., 12, 1703–1724, https://doi.org/10.5194/gmd-12-1703-2019, https://doi.org/10.5194/gmd-12-1703-2019, 2019
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This paper evaluates a significant cold land surface temperature bias in semi-arid regions in the Met Office Unified Model when compared with satellite observations. Sparse vegetation canopies are not well represented in ancillary datasets, in particular regions of cold bias are correlated with low bare soil cover fractions. The study demonstrates the difficulties in modelling land surface temperatures that match state-of-the-art satellite retrievals required for operational data assimilation.
Stuart Fox, Jana Mendrok, Patrick Eriksson, Robin Ekelund, Sebastian J. O'Shea, Keith N. Bower, Anthony J. Baran, R. Chawn Harlow, and Juliet C. Pickering
Atmos. Meas. Tech., 12, 1599–1617, https://doi.org/10.5194/amt-12-1599-2019, https://doi.org/10.5194/amt-12-1599-2019, 2019
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Airborne observations of ice clouds are used to validate radiative transfer simulations using a state-of-the-art database of cloud ice optical properties. Simulations at these wavelengths are required to make use of future satellite instruments such as the Ice Cloud Imager. We show that they can generally reproduce observed cloud signals, but for a given total ice mass there is considerable sensitivity to the cloud microphysics, including the particle shape and distribution of ice mass.
Gerhard Krinner, Chris Derksen, Richard Essery, Mark Flanner, Stefan Hagemann, Martyn Clark, Alex Hall, Helmut Rott, Claire Brutel-Vuilmet, Hyungjun Kim, Cécile B. Ménard, Lawrence Mudryk, Chad Thackeray, Libo Wang, Gabriele Arduini, Gianpaolo Balsamo, Paul Bartlett, Julia Boike, Aaron Boone, Frédérique Chéruy, Jeanne Colin, Matthias Cuntz, Yongjiu Dai, Bertrand Decharme, Jeff Derry, Agnès Ducharne, Emanuel Dutra, Xing Fang, Charles Fierz, Josephine Ghattas, Yeugeniy Gusev, Vanessa Haverd, Anna Kontu, Matthieu Lafaysse, Rachel Law, Dave Lawrence, Weiping Li, Thomas Marke, Danny Marks, Martin Ménégoz, Olga Nasonova, Tomoko Nitta, Masashi Niwano, John Pomeroy, Mark S. Raleigh, Gerd Schaedler, Vladimir Semenov, Tanya G. Smirnova, Tobias Stacke, Ulrich Strasser, Sean Svenson, Dmitry Turkov, Tao Wang, Nander Wever, Hua Yuan, Wenyan Zhou, and Dan Zhu
Geosci. Model Dev., 11, 5027–5049, https://doi.org/10.5194/gmd-11-5027-2018, https://doi.org/10.5194/gmd-11-5027-2018, 2018
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This paper provides an overview of a coordinated international experiment to determine the strengths and weaknesses in how climate models treat snow. The models will be assessed at point locations using high-quality reference measurements and globally using satellite-derived datasets. How well climate models simulate snow-related processes is important because changing snow cover is an important part of the global climate system and provides an important freshwater resource for human use.
Gary Lloyd, Thomas W. Choularton, Keith N. Bower, Martin W. Gallagher, Jonathan Crosier, Sebastian O'Shea, Steven J. Abel, Stuart Fox, Richard Cotton, and Ian A. Boutle
Atmos. Chem. Phys., 18, 17191–17206, https://doi.org/10.5194/acp-18-17191-2018, https://doi.org/10.5194/acp-18-17191-2018, 2018
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The work deals with cold weather outbreaks at high latitudes that often bring severe weather such as heavy snow, lightning and high winds but are poorly forecast by weather models. Here we made measurements of these events and the clouds associated with them using a research aircraft. We found that the properties of these clouds were often very different to what the models predicted, and these results can potentially be used to bring significant improvement to the forecasting of these events.
Meng Si, Victoria E. Irish, Ryan H. Mason, Jesús Vergara-Temprado, Sarah J. Hanna, Luis A. Ladino, Jacqueline D. Yakobi-Hancock, Corinne L. Schiller, Jeremy J. B. Wentzell, Jonathan P. D. Abbatt, Ken S. Carslaw, Benjamin J. Murray, and Allan K. Bertram
Atmos. Chem. Phys., 18, 15669–15685, https://doi.org/10.5194/acp-18-15669-2018, https://doi.org/10.5194/acp-18-15669-2018, 2018
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Using the concentrations of ice-nucleating particles (INPs) and total aerosol particles measured at three coastal marine sites, the ice-nucleating ability of aerosol particles on a per number basis and a per surface-area basis were determined as a function of size. The ice-nucleating ability was strongly dependent on size, with larger particles being more efficient. This type of information can help determine the sources of INPs and constrain the future modelling of INPs and mixed-phase clouds.
Hamish Gordon, Paul R. Field, Steven J. Abel, Mohit Dalvi, Daniel P. Grosvenor, Adrian A. Hill, Ben T. Johnson, Annette K. Miltenberger, Masaru Yoshioka, and Ken S. Carslaw
Atmos. Chem. Phys., 18, 15261–15289, https://doi.org/10.5194/acp-18-15261-2018, https://doi.org/10.5194/acp-18-15261-2018, 2018
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Smoke from African fires is frequently transported across the Atlantic Ocean, where it interacts with clouds. We simulate the interaction of the smoke with the clouds, and the consequences of this for the solar radiation the clouds reflect. The simulations use a new regional configuration of the UK Met Office climate model. Our simulations indicate that the properties of the clouds, in particular their height and reflectivity, and the fractional cloud cover, are strongly affected by the smoke.
Lee de Mora, Andrew Yool, Julien Palmieri, Alistair Sellar, Till Kuhlbrodt, Ekaterina Popova, Colin Jones, and J. Icarus Allen
Geosci. Model Dev., 11, 4215–4240, https://doi.org/10.5194/gmd-11-4215-2018, https://doi.org/10.5194/gmd-11-4215-2018, 2018
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Climate change is expected to have a significant impact on the Earth's weather, ice caps, land surface, and ocean. Computer models of the Earth system are the only tools available to make predictions about how the climate may change in the future. However, in order to trust the model predictions, we must first demonstrate that the models have a realistic description of the past. The BGC-val toolkit was built to rapidly and simply evaluate the behaviour of models of the Earth's oceans.
Ben Kravitz, Philip J. Rasch, Hailong Wang, Alan Robock, Corey Gabriel, Olivier Boucher, Jason N. S. Cole, Jim Haywood, Duoying Ji, Andy Jones, Andrew Lenton, John C. Moore, Helene Muri, Ulrike Niemeier, Steven Phipps, Hauke Schmidt, Shingo Watanabe, Shuting Yang, and Jin-Ho Yoon
Atmos. Chem. Phys., 18, 13097–13113, https://doi.org/10.5194/acp-18-13097-2018, https://doi.org/10.5194/acp-18-13097-2018, 2018
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Marine cloud brightening has been proposed as a means of geoengineering/climate intervention, or deliberately altering the climate system to offset anthropogenic climate change. In idealized simulations that highlight contrasts between land and ocean, we find that the globe warms, including the ocean due to transport of heat from land. This study reinforces that no net energy input into the Earth system does not mean that temperature will necessarily remain unchanged.
Jill S. Johnson, Leighton A. Regayre, Masaru Yoshioka, Kirsty J. Pringle, Lindsay A. Lee, David M. H. Sexton, John W. Rostron, Ben B. B. Booth, and Kenneth S. Carslaw
Atmos. Chem. Phys., 18, 13031–13053, https://doi.org/10.5194/acp-18-13031-2018, https://doi.org/10.5194/acp-18-13031-2018, 2018
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We estimate the uncertainty in an aerosol–climate model that has been tuned to match several common types of observations. We used a large set of model simulations and built emulators so that we could generate 4 million “variants” of our climate model. Even after using nine aerosol and cloud observations to constrain the model, the uncertainty remains large. We conclude that estimates of aerosol forcing from multi-model studies are likely to be more uncertain than currently estimated.
Nathan Luke Abraham, Alexander T. Archibald, Paul Cresswell, Sam Cusworth, Mohit Dalvi, David Matthews, Steven Wardle, and Stuart Whitehouse
Geosci. Model Dev., 11, 3647–3657, https://doi.org/10.5194/gmd-11-3647-2018, https://doi.org/10.5194/gmd-11-3647-2018, 2018
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Using a virtual machine environment, a low-resolution configuration of the United Kingdom Chemistry and Aerosols (UKCA) composition-climate model has been developed. This configuration, while not suitable for long simulations, is an excellent test-bed for new model developments and can be used to train new users in how to use UKCA. This work was motivated by the desire to improve the usability of UKCA, and to encourage more users to become involved with the code development process.
Blanca Ayarzagüena, Lorenzo M. Polvani, Ulrike Langematz, Hideharu Akiyoshi, Slimane Bekki, Neal Butchart, Martin Dameris, Makoto Deushi, Steven C. Hardiman, Patrick Jöckel, Andrew Klekociuk, Marion Marchand, Martine Michou, Olaf Morgenstern, Fiona M. O'Connor, Luke D. Oman, David A. Plummer, Laura Revell, Eugene Rozanov, David Saint-Martin, John Scinocca, Andrea Stenke, Kane Stone, Yousuke Yamashita, Kohei Yoshida, and Guang Zeng
Atmos. Chem. Phys., 18, 11277–11287, https://doi.org/10.5194/acp-18-11277-2018, https://doi.org/10.5194/acp-18-11277-2018, 2018
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Stratospheric sudden warmings (SSWs) are natural major disruptions of the polar stratospheric circulation that also affect surface weather. In the literature there are conflicting claims as to whether SSWs will change in the future. The confusion comes from studies using different models and methods. Here we settle the question by analysing 12 models with a consistent methodology, to show that no robust changes in frequency and other features are expected over the 21st century.
Robin G. Stevens, Katharina Loewe, Christopher Dearden, Antonios Dimitrelos, Anna Possner, Gesa K. Eirund, Tomi Raatikainen, Adrian A. Hill, Benjamin J. Shipway, Jonathan Wilkinson, Sami Romakkaniemi, Juha Tonttila, Ari Laaksonen, Hannele Korhonen, Paul Connolly, Ulrike Lohmann, Corinna Hoose, Annica M. L. Ekman, Ken S. Carslaw, and Paul R. Field
Atmos. Chem. Phys., 18, 11041–11071, https://doi.org/10.5194/acp-18-11041-2018, https://doi.org/10.5194/acp-18-11041-2018, 2018
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We perform a model intercomparison of summertime high Arctic clouds. Observed concentrations of aerosol particles necessary for cloud formation fell to extremely low values, coincident with a transition from cloudy to nearly cloud-free conditions. Previous analyses have suggested that at these low concentrations, the radiative properties of the clouds are determined primarily by these particle concentrations. The model results strongly support this hypothesis.
Angela Benedetti, Jeffrey S. Reid, Peter Knippertz, John H. Marsham, Francesca Di Giuseppe, Samuel Rémy, Sara Basart, Olivier Boucher, Ian M. Brooks, Laurent Menut, Lucia Mona, Paolo Laj, Gelsomina Pappalardo, Alfred Wiedensohler, Alexander Baklanov, Malcolm Brooks, Peter R. Colarco, Emilio Cuevas, Arlindo da Silva, Jeronimo Escribano, Johannes Flemming, Nicolas Huneeus, Oriol Jorba, Stelios Kazadzis, Stefan Kinne, Thomas Popp, Patricia K. Quinn, Thomas T. Sekiyama, Taichu Tanaka, and Enric Terradellas
Atmos. Chem. Phys., 18, 10615–10643, https://doi.org/10.5194/acp-18-10615-2018, https://doi.org/10.5194/acp-18-10615-2018, 2018
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Numerical prediction of aerosol particle properties has become an important activity at many research and operational weather centers. This development is due to growing interest from a diverse set of stakeholders, such as air quality regulatory bodies, aviation authorities, solar energy plant managers, climate service providers, and health professionals. This paper describes the advances in the field and sets out requirements for observations for the sustainability of these activities.
Leighton A. Regayre, Jill S. Johnson, Masaru Yoshioka, Kirsty J. Pringle, David M. H. Sexton, Ben B. B. Booth, Lindsay A. Lee, Nicolas Bellouin, and Kenneth S. Carslaw
Atmos. Chem. Phys., 18, 9975–10006, https://doi.org/10.5194/acp-18-9975-2018, https://doi.org/10.5194/acp-18-9975-2018, 2018
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We sample uncertainty in one climate model by perturbing aerosol and physical atmosphere parameters. Our uncertainty is comparable to multi-model studies. Atmospheric parameters cause most of the top-of-atmosphere flux uncertainty; uncertainty in aerosol forcing is mostly caused by aerosols: both are important. The strongest aerosol forcings are inconsistent with top-of-atmosphere flux observations. Better constraint requires observations that share causes of uncertainty with aerosol forcing.
Claudia Timmreck, Graham W. Mann, Valentina Aquila, Rene Hommel, Lindsay A. Lee, Anja Schmidt, Christoph Brühl, Simon Carn, Mian Chin, Sandip S. Dhomse, Thomas Diehl, Jason M. English, Michael J. Mills, Ryan Neely, Jianxiong Sheng, Matthew Toohey, and Debra Weisenstein
Geosci. Model Dev., 11, 2581–2608, https://doi.org/10.5194/gmd-11-2581-2018, https://doi.org/10.5194/gmd-11-2581-2018, 2018
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The paper describes the experimental design of the Interactive Stratospheric Aerosol Model Intercomparison Project (ISA-MIP). ISA-MIP will improve understanding of stratospheric aerosol processes, chemistry, and dynamics and constrain climate impacts of background aerosol variability and small and large volcanic eruptions. It will help to asses the stratospheric aerosol contribution to the early 21st century global warming hiatus period and the effects from hypothetical geoengineering schemes.
Sandip S. Dhomse, Douglas Kinnison, Martyn P. Chipperfield, Ross J. Salawitch, Irene Cionni, Michaela I. Hegglin, N. Luke Abraham, Hideharu Akiyoshi, Alex T. Archibald, Ewa M. Bednarz, Slimane Bekki, Peter Braesicke, Neal Butchart, Martin Dameris, Makoto Deushi, Stacey Frith, Steven C. Hardiman, Birgit Hassler, Larry W. Horowitz, Rong-Ming Hu, Patrick Jöckel, Beatrice Josse, Oliver Kirner, Stefanie Kremser, Ulrike Langematz, Jared Lewis, Marion Marchand, Meiyun Lin, Eva Mancini, Virginie Marécal, Martine Michou, Olaf Morgenstern, Fiona M. O'Connor, Luke Oman, Giovanni Pitari, David A. Plummer, John A. Pyle, Laura E. Revell, Eugene Rozanov, Robyn Schofield, Andrea Stenke, Kane Stone, Kengo Sudo, Simone Tilmes, Daniele Visioni, Yousuke Yamashita, and Guang Zeng
Atmos. Chem. Phys., 18, 8409–8438, https://doi.org/10.5194/acp-18-8409-2018, https://doi.org/10.5194/acp-18-8409-2018, 2018
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We analyse simulations from the Chemistry-Climate Model Initiative (CCMI) to estimate the return dates of the stratospheric ozone layer from depletion by anthropogenic chlorine and bromine. The simulations from 20 models project that global column ozone will return to 1980 values in 2047 (uncertainty range 2042–2052). Return dates in other regions vary depending on factors related to climate change and importance of chlorine and bromine. Column ozone in the tropics may continue to decline.
Ian Boutle, Jeremy Price, Innocent Kudzotsa, Harri Kokkola, and Sami Romakkaniemi
Atmos. Chem. Phys., 18, 7827–7840, https://doi.org/10.5194/acp-18-7827-2018, https://doi.org/10.5194/acp-18-7827-2018, 2018
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Aerosol processes are a key mechanism in the development of fog. Poor representation of aerosol–fog interaction can result in large biases in fog forecasts, such as surface temperatures which are too high and fog which is too deep and long lived. A relatively simple representation of aerosol–fog interaction can actually lead to significant improvements in forecasting. Aerosol–fog interaction can have a large effect on the climate system but is poorly represented in climate models.
Jamie M. Kelly, Ruth M. Doherty, Fiona M. O'Connor, and Graham W. Mann
Atmos. Chem. Phys., 18, 7393–7422, https://doi.org/10.5194/acp-18-7393-2018, https://doi.org/10.5194/acp-18-7393-2018, 2018
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The global secondary organic aerosol (SOA) budget is highly uncertain with global models typically underpredicting observed SOA concentrations. Using a global chemistry-climate model, the impacts of biogenic, anthropogenic, and biomass burning VOC emissions on the global SOA budget and model agreement with observed SOA concentrations are quantified.
Amy K. Hodgson, William T. Morgan, Sebastian O'Shea, Stéphane Bauguitte, James D. Allan, Eoghan Darbyshire, Michael J. Flynn, Dantong Liu, James Lee, Ben Johnson, Jim M. Haywood, Karla M. Longo, Paulo E. Artaxo, and Hugh Coe
Atmos. Chem. Phys., 18, 5619–5638, https://doi.org/10.5194/acp-18-5619-2018, https://doi.org/10.5194/acp-18-5619-2018, 2018
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We flew a large atmospheric research aircraft across a number of different biomass burning environments in the Amazon Basin in September and October 2012. In this paper, we focus on smoke sampled very close to fresh fires (only 600–900 m above the fires and smoke that was 4–6 min old) to examine the chemical components that make up the smoke and their abundance. We found substantial differences in the emitted smoke that are due to the fuel type and combustion processes driving the fires.
Gillian D. Thornhill, Claire L. Ryder, Eleanor J. Highwood, Len C. Shaffrey, and Ben T. Johnson
Atmos. Chem. Phys., 18, 5321–5342, https://doi.org/10.5194/acp-18-5321-2018, https://doi.org/10.5194/acp-18-5321-2018, 2018
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We investigated the impact on the regional climate of different amounts of smoke emission (aerosol) from the burning of vegetation in South America using a climate model. We looked at differences between high and low smoke emissions and found impacts from the higher smoke emissions on the amount of cloud cover, solar radiation reaching the surface, wind patterns and rainfall. This means the local climate may be affected if there is more deforestation and more smoke from burning of vegetation.
Jake J. Gristey, J. Christine Chiu, Robert J. Gurney, Cyril J. Morcrette, Peter G. Hill, Jacqueline E. Russell, and Helen E. Brindley
Atmos. Chem. Phys., 18, 5129–5145, https://doi.org/10.5194/acp-18-5129-2018, https://doi.org/10.5194/acp-18-5129-2018, 2018
Neal Butchart, James A. Anstey, Kevin Hamilton, Scott Osprey, Charles McLandress, Andrew C. Bushell, Yoshio Kawatani, Young-Ha Kim, Francois Lott, John Scinocca, Timothy N. Stockdale, Martin Andrews, Omar Bellprat, Peter Braesicke, Chiara Cagnazzo, Chih-Chieh Chen, Hye-Yeong Chun, Mikhail Dobrynin, Rolando R. Garcia, Javier Garcia-Serrano, Lesley J. Gray, Laura Holt, Tobias Kerzenmacher, Hiroaki Naoe, Holger Pohlmann, Jadwiga H. Richter, Adam A. Scaife, Verena Schenzinger, Federico Serva, Stefan Versick, Shingo Watanabe, Kohei Yoshida, and Seiji Yukimoto
Geosci. Model Dev., 11, 1009–1032, https://doi.org/10.5194/gmd-11-1009-2018, https://doi.org/10.5194/gmd-11-1009-2018, 2018
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This paper documents the numerical experiments to be used in phase 1 of the Stratosphere–troposphere Processes And their Role in Climate (SPARC) Quasi-Biennial Oscillation initiative (QBOi), which was set up to improve the representation of the QBO and tropical stratospheric variability in global climate models.
Esteban Alonso-González, J. Ignacio López-Moreno, Simon Gascoin, Matilde García-Valdecasas Ojeda, Alba Sanmiguel-Vallelado, Francisco Navarro-Serrano, Jesús Revuelto, Antonio Ceballos, María Jesús Esteban-Parra, and Richard Essery
Earth Syst. Sci. Data, 10, 303–315, https://doi.org/10.5194/essd-10-303-2018, https://doi.org/10.5194/essd-10-303-2018, 2018
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We present a new daily gridded snow depth and snow water equivalent database over the Iberian Peninsula from 1980 to 2014 structured in common elevation bands. The data have proved their consistency with in situ observations and remote sensing data (MODIS). The presented dataset may be useful for many applications, including land management, hydrometeorological studies, phenology of flora and fauna, winter tourism and risk management.
Lauren Marshall, Anja Schmidt, Matthew Toohey, Ken S. Carslaw, Graham W. Mann, Michael Sigl, Myriam Khodri, Claudia Timmreck, Davide Zanchettin, William T. Ball, Slimane Bekki, James S. A. Brooke, Sandip Dhomse, Colin Johnson, Jean-Francois Lamarque, Allegra N. LeGrande, Michael J. Mills, Ulrike Niemeier, James O. Pope, Virginie Poulain, Alan Robock, Eugene Rozanov, Andrea Stenke, Timofei Sukhodolov, Simone Tilmes, Kostas Tsigaridis, and Fiona Tummon
Atmos. Chem. Phys., 18, 2307–2328, https://doi.org/10.5194/acp-18-2307-2018, https://doi.org/10.5194/acp-18-2307-2018, 2018
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We use four global aerosol models to compare the simulated sulfate deposition from the 1815 Mt. Tambora eruption to ice core records. Inter-model volcanic sulfate deposition differs considerably. Volcanic sulfate deposited on polar ice sheets is used to estimate the atmospheric sulfate burden and subsequently radiative forcing of historic eruptions. Our results suggest that deriving such relationships from model simulations may be associated with greater uncertainties than previously thought.
Camilla W. Stjern, Helene Muri, Lars Ahlm, Olivier Boucher, Jason N. S. Cole, Duoying Ji, Andy Jones, Jim Haywood, Ben Kravitz, Andrew Lenton, John C. Moore, Ulrike Niemeier, Steven J. Phipps, Hauke Schmidt, Shingo Watanabe, and Jón Egill Kristjánsson
Atmos. Chem. Phys., 18, 621–634, https://doi.org/10.5194/acp-18-621-2018, https://doi.org/10.5194/acp-18-621-2018, 2018
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Marine cloud brightening (MCB) has been proposed to help limit global warming. We present here the first multi-model assessment of idealized MCB simulations from the Geoengineering Model Intercomparison Project. While all models predict a global cooling as intended, there is considerable spread between the models both in terms of radiative forcing and the climate response, largely linked to the substantial differences in the models' representation of clouds.
Axel Lauer, Colin Jones, Veronika Eyring, Martin Evaldsson, Stefan Hagemann, Jarmo Mäkelä, Gill Martin, Romain Roehrig, and Shiyu Wang
Earth Syst. Dynam., 9, 33–67, https://doi.org/10.5194/esd-9-33-2018, https://doi.org/10.5194/esd-9-33-2018, 2018
Huw W. Lewis, Juan Manuel Castillo Sanchez, Jennifer Graham, Andrew Saulter, Jorge Bornemann, Alex Arnold, Joachim Fallmann, Chris Harris, David Pearson, Steven Ramsdale, Alberto Martínez-de la Torre, Lucy Bricheno, Eleanor Blyth, Victoria A. Bell, Helen Davies, Toby R. Marthews, Clare O'Neill, Heather Rumbold, Enda O'Dea, Ashley Brereton, Karen Guihou, Adrian Hines, Momme Butenschon, Simon J. Dadson, Tamzin Palmer, Jason Holt, Nick Reynard, Martin Best, John Edwards, and John Siddorn
Geosci. Model Dev., 11, 1–42, https://doi.org/10.5194/gmd-11-1-2018, https://doi.org/10.5194/gmd-11-1-2018, 2018
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In the real world the atmosphere, oceans and land surface are closely interconnected, and yet prediction systems tend to treat them in isolation. Those feedbacks are often illustrated in natural hazards, such as when strong winds lead to large waves and coastal damage, or when prolonged rainfall leads to saturated ground and high flowing rivers. For the first time, we have attempted to represent some of the feedbacks between sky, sea and land within a high-resolution forecast system for the UK.
Yoko Tsushima, Florent Brient, Stephen A. Klein, Dimitra Konsta, Christine C. Nam, Xin Qu, Keith D. Williams, Steven C. Sherwood, Kentaroh Suzuki, and Mark D. Zelinka
Geosci. Model Dev., 10, 4285–4305, https://doi.org/10.5194/gmd-10-4285-2017, https://doi.org/10.5194/gmd-10-4285-2017, 2017
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Cloud feedback is the largest uncertainty associated with estimates of climate sensitivity. Diagnostics have been developed to evaluate cloud processes in climate models. For this understanding to be reflected in better estimates of cloud feedbacks, it is vital to continue to develop such tools and to exploit them fully during the model development process. Code repositories have been created to store and document the programs which will allow climate modellers to compute these diagnostics.
Lars Ahlm, Andy Jones, Camilla W. Stjern, Helene Muri, Ben Kravitz, and Jón Egill Kristjánsson
Atmos. Chem. Phys., 17, 13071–13087, https://doi.org/10.5194/acp-17-13071-2017, https://doi.org/10.5194/acp-17-13071-2017, 2017
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We present results from coordinated simulations with three Earth system models focusing on the response of Earth’s radiation balance to the injection of sea salt particles. We find that in most regions the effective radiative forcing by the injected particles is equally large in cloudy and clear-sky conditions, suggesting a more important role of the aerosol direct effect in sea spray climate engineering than previously thought.
Lucy S. Neal, Mohit Dalvi, Gerd Folberth, Rachel N. McInnes, Paul Agnew, Fiona M. O'Connor, Nicholas H. Savage, and Marie Tilbee
Geosci. Model Dev., 10, 3941–3962, https://doi.org/10.5194/gmd-10-3941-2017, https://doi.org/10.5194/gmd-10-3941-2017, 2017
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This paper concerns aspects of downscaling global atmospheric composition and chemistry model predictions on the continental and UK national scale. A two-step nested model configuration was developed and used to simulate UK air quality for a 5-year period under present-day conditions. The results show some benefits associated with higher-resolution modelling for primary emitted pollutants, but also highlight the importance of consistency between the nested models.
Marielle Saunois, Philippe Bousquet, Ben Poulter, Anna Peregon, Philippe Ciais, Josep G. Canadell, Edward J. Dlugokencky, Giuseppe Etiope, David Bastviken, Sander Houweling, Greet Janssens-Maenhout, Francesco N. Tubiello, Simona Castaldi, Robert B. Jackson, Mihai Alexe, Vivek K. Arora, David J. Beerling, Peter Bergamaschi, Donald R. Blake, Gordon Brailsford, Lori Bruhwiler, Cyril Crevoisier, Patrick Crill, Kristofer Covey, Christian Frankenberg, Nicola Gedney, Lena Höglund-Isaksson, Misa Ishizawa, Akihiko Ito, Fortunat Joos, Heon-Sook Kim, Thomas Kleinen, Paul Krummel, Jean-François Lamarque, Ray Langenfelds, Robin Locatelli, Toshinobu Machida, Shamil Maksyutov, Joe R. Melton, Isamu Morino, Vaishali Naik, Simon O'Doherty, Frans-Jan W. Parmentier, Prabir K. Patra, Changhui Peng, Shushi Peng, Glen P. Peters, Isabelle Pison, Ronald Prinn, Michel Ramonet, William J. Riley, Makoto Saito, Monia Santini, Ronny Schroeder, Isobel J. Simpson, Renato Spahni, Atsushi Takizawa, Brett F. Thornton, Hanqin Tian, Yasunori Tohjima, Nicolas Viovy, Apostolos Voulgarakis, Ray Weiss, David J. Wilton, Andy Wiltshire, Doug Worthy, Debra Wunch, Xiyan Xu, Yukio Yoshida, Bowen Zhang, Zhen Zhang, and Qiuan Zhu
Atmos. Chem. Phys., 17, 11135–11161, https://doi.org/10.5194/acp-17-11135-2017, https://doi.org/10.5194/acp-17-11135-2017, 2017
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Following the Global Methane Budget 2000–2012 published in Saunois et al. (2016), we use the same dataset of bottom-up and top-down approaches to discuss the variations in methane emissions over the period 2000–2012. The changes in emissions are discussed both in terms of trends and quasi-decadal changes. The ensemble gathered here allows us to synthesise the robust changes in terms of regional and sectorial contributions to the increasing methane emissions.
Chris Huntingford, Hui Yang, Anna Harper, Peter M. Cox, Nicola Gedney, Eleanor J. Burke, Jason A. Lowe, Garry Hayman, William J. Collins, Stephen M. Smith, and Edward Comyn-Platt
Earth Syst. Dynam., 8, 617–626, https://doi.org/10.5194/esd-8-617-2017, https://doi.org/10.5194/esd-8-617-2017, 2017
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Recent UNFCCC climate meetings have placed much emphasis on constraining global warming to remain below 2 °C. The 2015 Paris meeting went further and gave an aspiration to fulfil a 1.5 °C threshold. We provide a flexible set of algebraic global temperature profiles that stabilise to either target. This will potentially allow the climate research community to estimate local climatic implications for these temperature profiles, along with emissions trajectories to fulfil them.
Keith D. Williams and Alejandro Bodas-Salcedo
Geosci. Model Dev., 10, 2547–2566, https://doi.org/10.5194/gmd-10-2547-2017, https://doi.org/10.5194/gmd-10-2547-2017, 2017
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The simulation of cloud is problematic for general circulation models. As clouds come in differing types, areal coverage, altitude and reflectivity, it is possible for a model to appear to perform well against a particular observational dataset through a compensation of errors. Here we evaluate a model's cloud simulation against a range of observational datasets, globally and across weather–climate timescales, in order to provide a comprehensive assessment.
David Walters, Ian Boutle, Malcolm Brooks, Thomas Melvin, Rachel Stratton, Simon Vosper, Helen Wells, Keith Williams, Nigel Wood, Thomas Allen, Andrew Bushell, Dan Copsey, Paul Earnshaw, John Edwards, Markus Gross, Steven Hardiman, Chris Harris, Julian Heming, Nicholas Klingaman, Richard Levine, James Manners, Gill Martin, Sean Milton, Marion Mittermaier, Cyril Morcrette, Thomas Riddick, Malcolm Roberts, Claudio Sanchez, Paul Selwood, Alison Stirling, Chris Smith, Dan Suri, Warren Tennant, Pier Luigi Vidale, Jonathan Wilkinson, Martin Willett, Steve Woolnough, and Prince Xavier
Geosci. Model Dev., 10, 1487–1520, https://doi.org/10.5194/gmd-10-1487-2017, https://doi.org/10.5194/gmd-10-1487-2017, 2017
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Global Atmosphere (GA) configurations of the Unified Model (UM) and Global Land (GL) configurations of JULES are developed for use in any global atmospheric modelling application.
We describe a recent iteration of these configurations: GA6/GL6. This includes ENDGame: a new dynamical core designed to improve the model's accuracy, stability and scalability. GA6 is now operational in a variety of Met Office and UM collaborators applications and hence its documentation is important.
We describe a recent iteration of these configurations: GA6/GL6. This includes ENDGame: a new dynamical core designed to improve the model's accuracy, stability and scalability. GA6 is now operational in a variety of Met Office and UM collaborators applications and hence its documentation is important.
Steven C. Hardiman, Neal Butchart, Fiona M. O'Connor, and Steven T. Rumbold
Geosci. Model Dev., 10, 1209–1232, https://doi.org/10.5194/gmd-10-1209-2017, https://doi.org/10.5194/gmd-10-1209-2017, 2017
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HadGEM3-ES is improved, with respect to the previous model, in 10 of the 14 metrics considered. A significant bias in stratospheric water vapour is reduced, allowing more accurate simulation of water vapour and ozone concentrations in the stratosphere. Dynamics are found to influence the spatial structure of the simulated ozone hole and the area of polar stratospheric clouds. This research was carried out as part of involvement in the Chemistry-Climate Model Initiative (CCM-I).
Jesús Vergara-Temprado, Benjamin J. Murray, Theodore W. Wilson, Daniel O'Sullivan, Jo Browse, Kirsty J. Pringle, Karin Ardon-Dryer, Allan K. Bertram, Susannah M. Burrows, Darius Ceburnis, Paul J. DeMott, Ryan H. Mason, Colin D. O'Dowd, Matteo Rinaldi, and Ken S. Carslaw
Atmos. Chem. Phys., 17, 3637–3658, https://doi.org/10.5194/acp-17-3637-2017, https://doi.org/10.5194/acp-17-3637-2017, 2017
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We quantify the importance in the atmosphere of different aerosol components to contribute to global ice-nucleating particles concentrations (INPs). The aim is to improve the way atmospheric cloud-ice processes are represented in climate models so they will be able to make better predictions in the future. We found that a kind of dust (K-feldspar), together with marine organic aerosols, can help to improve the representation of INPs and explain most of their observations.
Céline Planche, Graham W. Mann, Kenneth S. Carslaw, Mohit Dalvi, John H. Marsham, and Paul R. Field
Atmos. Chem. Phys., 17, 3371–3384, https://doi.org/10.5194/acp-17-3371-2017, https://doi.org/10.5194/acp-17-3371-2017, 2017
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A convection-permitting limited area model with prognostic aerosol microphysics is applied to investigate how concentrations of cloud condensation nuclei (CCN) in the marine boundary layer are affected by high-resolution dynamical and thermodynamic fields at sub-climate model scale. We gain new insight into the way primary sea-salt and secondary sulfate particles contribute to the overall CCN variance, and find a marked difference in the variability of super- and sub-micron CCN.
Olaf Morgenstern, Michaela I. Hegglin, Eugene Rozanov, Fiona M. O'Connor, N. Luke Abraham, Hideharu Akiyoshi, Alexander T. Archibald, Slimane Bekki, Neal Butchart, Martyn P. Chipperfield, Makoto Deushi, Sandip S. Dhomse, Rolando R. Garcia, Steven C. Hardiman, Larry W. Horowitz, Patrick Jöckel, Beatrice Josse, Douglas Kinnison, Meiyun Lin, Eva Mancini, Michael E. Manyin, Marion Marchand, Virginie Marécal, Martine Michou, Luke D. Oman, Giovanni Pitari, David A. Plummer, Laura E. Revell, David Saint-Martin, Robyn Schofield, Andrea Stenke, Kane Stone, Kengo Sudo, Taichu Y. Tanaka, Simone Tilmes, Yousuke Yamashita, Kohei Yoshida, and Guang Zeng
Geosci. Model Dev., 10, 639–671, https://doi.org/10.5194/gmd-10-639-2017, https://doi.org/10.5194/gmd-10-639-2017, 2017
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We present a review of the make-up of 20 models participating in the Chemistry–Climate Model Initiative (CCMI). In comparison to earlier such activities, most of these models comprise a whole-atmosphere chemistry, and several of them include an interactive ocean module. This makes them suitable for studying the interactions of tropospheric air quality, stratospheric ozone, and climate. The paper lays the foundation for other studies using the CCMI simulations for scientific analysis.
Melody Sandells, Richard Essery, Nick Rutter, Leanne Wake, Leena Leppänen, and Juha Lemmetyinen
The Cryosphere, 11, 229–246, https://doi.org/10.5194/tc-11-229-2017, https://doi.org/10.5194/tc-11-229-2017, 2017
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This study looks at a wide range of options for simulating sensor signals for satellite monitoring of water stored as snow, though an ensemble of 1323 coupled snow evolution and microwave scattering models. The greatest improvements will be made with better computer simulations of how the snow microstructure changes, followed by how the microstructure scatters radiation at microwave frequencies. Snow compaction should also be considered in systems to monitor snow mass from space.
Marielle Saunois, Philippe Bousquet, Ben Poulter, Anna Peregon, Philippe Ciais, Josep G. Canadell, Edward J. Dlugokencky, Giuseppe Etiope, David Bastviken, Sander Houweling, Greet Janssens-Maenhout, Francesco N. Tubiello, Simona Castaldi, Robert B. Jackson, Mihai Alexe, Vivek K. Arora, David J. Beerling, Peter Bergamaschi, Donald R. Blake, Gordon Brailsford, Victor Brovkin, Lori Bruhwiler, Cyril Crevoisier, Patrick Crill, Kristofer Covey, Charles Curry, Christian Frankenberg, Nicola Gedney, Lena Höglund-Isaksson, Misa Ishizawa, Akihiko Ito, Fortunat Joos, Heon-Sook Kim, Thomas Kleinen, Paul Krummel, Jean-François Lamarque, Ray Langenfelds, Robin Locatelli, Toshinobu Machida, Shamil Maksyutov, Kyle C. McDonald, Julia Marshall, Joe R. Melton, Isamu Morino, Vaishali Naik, Simon O'Doherty, Frans-Jan W. Parmentier, Prabir K. Patra, Changhui Peng, Shushi Peng, Glen P. Peters, Isabelle Pison, Catherine Prigent, Ronald Prinn, Michel Ramonet, William J. Riley, Makoto Saito, Monia Santini, Ronny Schroeder, Isobel J. Simpson, Renato Spahni, Paul Steele, Atsushi Takizawa, Brett F. Thornton, Hanqin Tian, Yasunori Tohjima, Nicolas Viovy, Apostolos Voulgarakis, Michiel van Weele, Guido R. van der Werf, Ray Weiss, Christine Wiedinmyer, David J. Wilton, Andy Wiltshire, Doug Worthy, Debra Wunch, Xiyan Xu, Yukio Yoshida, Bowen Zhang, Zhen Zhang, and Qiuan Zhu
Earth Syst. Sci. Data, 8, 697–751, https://doi.org/10.5194/essd-8-697-2016, https://doi.org/10.5194/essd-8-697-2016, 2016
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An accurate assessment of the methane budget is important to understand the atmospheric methane concentrations and trends and to provide realistic pathways for climate change mitigation. The various and diffuse sources of methane as well and its oxidation by a very short lifetime radical challenge this assessment. We quantify the methane sources and sinks as well as their uncertainties based on both bottom-up and top-down approaches provided by a broad international scientific community.
Ben T. Johnson, James M. Haywood, Justin M. Langridge, Eoghan Darbyshire, William T. Morgan, Kate Szpek, Jennifer K. Brooke, Franco Marenco, Hugh Coe, Paulo Artaxo, Karla M. Longo, Jane P. Mulcahy, Graham W. Mann, Mohit Dalvi, and Nicolas Bellouin
Atmos. Chem. Phys., 16, 14657–14685, https://doi.org/10.5194/acp-16-14657-2016, https://doi.org/10.5194/acp-16-14657-2016, 2016
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Biomass burning is a large source of carbonaceous aerosols, which scatter and absorb solar radiation, and modify cloud properties. We evaluate the simulation of biomass burning aerosol processes and properties in the HadGEM3 climate model using observations, including those from the South American Biomass Burning Analysis. We find that modelled aerosol optical depths are underestimated unless aerosol emissions (Global Fire Emission Database v3) are increased by a factor of 1.6–2.0.
François Benduhn, Graham W. Mann, Kirsty J. Pringle, David O. Topping, Gordon McFiggans, and Kenneth S. Carslaw
Geosci. Model Dev., 9, 3875–3906, https://doi.org/10.5194/gmd-9-3875-2016, https://doi.org/10.5194/gmd-9-3875-2016, 2016
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We present a new mathematical formalism that serves to represent exchanges of inorganic matter between the atmosphere gas phase and the aerosol aqueous phase. In a global modelling framework, taking into account these processes may help represent many important features more accurately, such as the formation of cloud droplets or the radiative properties of the atmosphere. The formalism strives to keep an appropriate balance between accuracy and computation efficiency requirements.
Husi Letu, Hiroshi Ishimoto, Jerome Riedi, Takashi Y. Nakajima, Laurent C.-Labonnote, Anthony J. Baran, Takashi M. Nagao, and Miho Sekiguchi
Atmos. Chem. Phys., 16, 12287–12303, https://doi.org/10.5194/acp-16-12287-2016, https://doi.org/10.5194/acp-16-12287-2016, 2016
Zarashpe Z. Kapadia, Dominick V. Spracklen, Steve R. Arnold, Duncan J. Borman, Graham W. Mann, Kirsty J. Pringle, Sarah A. Monks, Carly L. Reddington, François Benduhn, Alexandru Rap, Catherine E. Scott, Edward W. Butt, and Masaru Yoshioka
Atmos. Chem. Phys., 16, 10521–10541, https://doi.org/10.5194/acp-16-10521-2016, https://doi.org/10.5194/acp-16-10521-2016, 2016
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Using a coupled tropospheric chemistry-aerosol microphysics model this research paper investigates the effect of variations in aviation fuel sulfur content (FSC) on surface PM2.5 concentrations, increases in aviation-induced premature mortalities, low-level cloud condensation nuclei and radiative effect.
When investigating the climatic impact of variations in FSC the ozone direct radiative effect, aerosol direct radiative effect and aerosol cloud albedo effect are quantified.
When investigating the climatic impact of variations in FSC the ozone direct radiative effect, aerosol direct radiative effect and aerosol cloud albedo effect are quantified.
Davide Zanchettin, Myriam Khodri, Claudia Timmreck, Matthew Toohey, Anja Schmidt, Edwin P. Gerber, Gabriele Hegerl, Alan Robock, Francesco S. R. Pausata, William T. Ball, Susanne E. Bauer, Slimane Bekki, Sandip S. Dhomse, Allegra N. LeGrande, Graham W. Mann, Lauren Marshall, Michael Mills, Marion Marchand, Ulrike Niemeier, Virginie Poulain, Eugene Rozanov, Angelo Rubino, Andrea Stenke, Kostas Tsigaridis, and Fiona Tummon
Geosci. Model Dev., 9, 2701–2719, https://doi.org/10.5194/gmd-9-2701-2016, https://doi.org/10.5194/gmd-9-2701-2016, 2016
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Simulating volcanically-forced climate variability is a challenging task for climate models. The Model Intercomparison Project on the climatic response to volcanic forcing (VolMIP) – an endorsed contribution to CMIP6 – defines a protocol for idealized volcanic-perturbation experiments to improve comparability of results across different climate models. This paper illustrates the design of VolMIP's experiments and describes the aerosol forcing input datasets to be used.
Richard Essery, Anna Kontu, Juha Lemmetyinen, Marie Dumont, and Cécile B. Ménard
Geosci. Instrum. Method. Data Syst., 5, 219–227, https://doi.org/10.5194/gi-5-219-2016, https://doi.org/10.5194/gi-5-219-2016, 2016
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Physically based models that predict the properties of snow on the ground are used in many applications, but meteorological input data required by these models are hard to obtain in cold regions. Monitoring at the Sodankyla research station allows construction of model input and evaluation datasets covering several years for the first time in the Arctic. The data are used to show that a sophisticated snow model developed for warmer and wetter sites can perform well in very different conditions.
Richard J. Keane, Robert S. Plant, and Warren J. Tennant
Geosci. Model Dev., 9, 1921–1935, https://doi.org/10.5194/gmd-9-1921-2016, https://doi.org/10.5194/gmd-9-1921-2016, 2016
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A widely studied stochastic deep convection scheme is evaluated over an extended forecasting period for the first time. It is found to significantly improve the probabilistic forecast for weakly forced cases – which tend to be less predictable – and to be comparable to a well-tuned reference scheme for strongly forced cases. A newly developed verification metric is applied to provide evidence that the improved probabilistic forecast is in large part due to the stochasticity of the scheme.
Veronika Eyring, Mattia Righi, Axel Lauer, Martin Evaldsson, Sabrina Wenzel, Colin Jones, Alessandro Anav, Oliver Andrews, Irene Cionni, Edouard L. Davin, Clara Deser, Carsten Ehbrecht, Pierre Friedlingstein, Peter Gleckler, Klaus-Dirk Gottschaldt, Stefan Hagemann, Martin Juckes, Stephan Kindermann, John Krasting, Dominik Kunert, Richard Levine, Alexander Loew, Jarmo Mäkelä, Gill Martin, Erik Mason, Adam S. Phillips, Simon Read, Catherine Rio, Romain Roehrig, Daniel Senftleben, Andreas Sterl, Lambertus H. van Ulft, Jeremy Walton, Shiyu Wang, and Keith D. Williams
Geosci. Model Dev., 9, 1747–1802, https://doi.org/10.5194/gmd-9-1747-2016, https://doi.org/10.5194/gmd-9-1747-2016, 2016
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A community diagnostics and performance metrics tool for the evaluation of Earth system models (ESMs) in CMIP has been developed that allows for routine comparison of single or multiple models, either against predecessor versions or against observations.
N. Huneeus, S. Basart, S. Fiedler, J.-J. Morcrette, A. Benedetti, J. Mulcahy, E. Terradellas, C. Pérez García-Pando, G. Pejanovic, S. Nickovic, P. Arsenovic, M. Schulz, E. Cuevas, J. M. Baldasano, J. Pey, S. Remy, and B. Cvetkovic
Atmos. Chem. Phys., 16, 4967–4986, https://doi.org/10.5194/acp-16-4967-2016, https://doi.org/10.5194/acp-16-4967-2016, 2016
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Five dust models are evaluated regarding their performance in predicting an intense Saharan dust outbreak affecting western and northern Europe (NE). Models predict the onset and evolution of the event for all analysed lead times. On average, differences among the models are larger than differences in lead times for each model. The models tend to underestimate the long-range transport towards NE. This is partly due to difficulties in simulating the vertical dust distribution and horizontal wind.
Anthony C. Jones, James M. Haywood, and Andy Jones
Atmos. Chem. Phys., 16, 2843–2862, https://doi.org/10.5194/acp-16-2843-2016, https://doi.org/10.5194/acp-16-2843-2016, 2016
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In this paper we assess the potential climatic impacts of geoengineering with sulfate, black carbon and titania injection strategies. We find that black carbon injection results in severe stratospheric warming and precipitation impacts, and therefore black carbon is unsuitable for geoengineering purposes. As the injection rates and climatic impacts for titania are close to those for sulfate, there appears little benefit of using titania when compared to injection of sulfur dioxide.
Sarah S. Thompson, Bernd Kulessa, Richard L. H. Essery, and Martin P. Lüthi
The Cryosphere, 10, 433–444, https://doi.org/10.5194/tc-10-433-2016, https://doi.org/10.5194/tc-10-433-2016, 2016
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We show that strong electrical self-potential fields are generated in melting in in situ snowpacks at Rhone Glacier and Jungfraujoch Glacier, Switzerland. We conclude that the electrical self-potential method is a promising snow and firn hydrology sensor, owing to its suitability for sensing lateral and vertical liquid water flows directly and minimally invasively, complementing established observational programs and monitoring autonomously at a low cost.
Zak Kipling, Philip Stier, Colin E. Johnson, Graham W. Mann, Nicolas Bellouin, Susanne E. Bauer, Tommi Bergman, Mian Chin, Thomas Diehl, Steven J. Ghan, Trond Iversen, Alf Kirkevåg, Harri Kokkola, Xiaohong Liu, Gan Luo, Twan van Noije, Kirsty J. Pringle, Knut von Salzen, Michael Schulz, Øyvind Seland, Ragnhild B. Skeie, Toshihiko Takemura, Kostas Tsigaridis, and Kai Zhang
Atmos. Chem. Phys., 16, 2221–2241, https://doi.org/10.5194/acp-16-2221-2016, https://doi.org/10.5194/acp-16-2221-2016, 2016
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The vertical distribution of atmospheric aerosol is an important factor in its effects on climate. In this study we use a sophisticated model of the many interacting processes affecting aerosol in the atmosphere to show that the vertical distribution is typically dominated by only a few of these processes. Constraining these physical processes may help to reduce the large differences between models. However, the important processes are not always the same for different types of aerosol.
Franco Marenco, Ben Johnson, Justin M. Langridge, Jane Mulcahy, Angela Benedetti, Samuel Remy, Luke Jones, Kate Szpek, Jim Haywood, Karla Longo, and Paulo Artaxo
Atmos. Chem. Phys., 16, 2155–2174, https://doi.org/10.5194/acp-16-2155-2016, https://doi.org/10.5194/acp-16-2155-2016, 2016
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A widespread and persistent smoke layer was observed in the Amazon
region during the biomass burning season, spanning a distance of 2200 km
and a period of 14 days. The larger smoke content was typically found
in elevated layers, from 1–1.5 km to 4–6 km.
Measurements have been compared to model predictions, and the latter
were able to reproduce the general features of the smoke layer, but
with some differences which are analysed and described in the paper.
R. Essery
Geosci. Model Dev., 8, 3867–3876, https://doi.org/10.5194/gmd-8-3867-2015, https://doi.org/10.5194/gmd-8-3867-2015, 2015
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Models of snow on the ground need to represent processes of solar radiation absorption, heat conduction, liquid water movement and compaction in snow and transfers of heat from the atmosphere. There are many such models in use, but their wide range in complexity makes it hard to understand how differences in process representations determine differences in predictions. Processes in the factorial snow model can be switched on or off independently, allowing highly controlled numerical experiments.
C. E. Scott, D. V. Spracklen, J. R. Pierce, I. Riipinen, S. D. D'Andrea, A. Rap, K. S. Carslaw, P. M. Forster, P. Artaxo, M. Kulmala, L. V. Rizzo, E. Swietlicki, G. W. Mann, and K. J. Pringle
Atmos. Chem. Phys., 15, 12989–13001, https://doi.org/10.5194/acp-15-12989-2015, https://doi.org/10.5194/acp-15-12989-2015, 2015
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To understand the radiative effects of biogenic secondary organic aerosol (SOA) it is necessary to consider the manner in which it is distributed across the existing aerosol size distribution. We explore the importance of the approach taken by global-scale models to do this, when calculating the direct radiative effect (DRE) & first aerosol indirect effect (AIE) due to biogenic SOA. This choice has little effect on the DRE, but a substantial impact on the magnitude and even sign of the first AIE
S. R. Kolusu, J. H. Marsham, J. Mulcahy, B. Johnson, C. Dunning, M. Bush, and D. V. Spracklen
Atmos. Chem. Phys., 15, 12251–12266, https://doi.org/10.5194/acp-15-12251-2015, https://doi.org/10.5194/acp-15-12251-2015, 2015
B. Kravitz, A. Robock, S. Tilmes, O. Boucher, J. M. English, P. J. Irvine, A. Jones, M. G. Lawrence, M. MacCracken, H. Muri, J. C. Moore, U. Niemeier, S. J. Phipps, J. Sillmann, T. Storelvmo, H. Wang, and S. Watanabe
Geosci. Model Dev., 8, 3379–3392, https://doi.org/10.5194/gmd-8-3379-2015, https://doi.org/10.5194/gmd-8-3379-2015, 2015
S. T. Turnock, D. V. Spracklen, K. S. Carslaw, G. W. Mann, M. T. Woodhouse, P. M. Forster, J. Haywood, C. E. Johnson, M. Dalvi, N. Bellouin, and A. Sanchez-Lorenzo
Atmos. Chem. Phys., 15, 9477–9500, https://doi.org/10.5194/acp-15-9477-2015, https://doi.org/10.5194/acp-15-9477-2015, 2015
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We evaluate HadGEM3-UKCA over Europe for the period 1960-2009 against observations of aerosol mass and number, aerosol optical depth (AOD) and surface solar radiation (SSR). The model underestimates aerosol mass and number but is less biased if compared to AOD and SSR. Observed trends in aerosols are well simulated by the model and necessary for reproducing the observed increase in SSR since 1990. European all-sky top of atmosphere aerosol radiative forcing increased by > 3 Wm-2 from 1970 to 2009.
S. E. Chadburn, E. J. Burke, R. L. H. Essery, J. Boike, M. Langer, M. Heikenfeld, P. M. Cox, and P. Friedlingstein
The Cryosphere, 9, 1505–1521, https://doi.org/10.5194/tc-9-1505-2015, https://doi.org/10.5194/tc-9-1505-2015, 2015
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In this paper we use a global land-surface model to study the dynamics of Arctic permafrost. We examine the impact of new and improved processes in the model, namely soil depth and resolution, organic soils, moss and the representation of snow. These improvements make the simulated soil temperatures and thaw depth significantly more realistic. Simulations under future climate scenarios show that permafrost thaws more slowly in the new model version, but still a large amount is lost by 2100.
S. Fuzzi, U. Baltensperger, K. Carslaw, S. Decesari, H. Denier van der Gon, M. C. Facchini, D. Fowler, I. Koren, B. Langford, U. Lohmann, E. Nemitz, S. Pandis, I. Riipinen, Y. Rudich, M. Schaap, J. G. Slowik, D. V. Spracklen, E. Vignati, M. Wild, M. Williams, and S. Gilardoni
Atmos. Chem. Phys., 15, 8217–8299, https://doi.org/10.5194/acp-15-8217-2015, https://doi.org/10.5194/acp-15-8217-2015, 2015
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Particulate matter (PM) constitutes one of the most challenging problems both for air quality and climate change policies. This paper reviews the most recent scientific results on the issue and the policy needs that have driven much of the increase in monitoring and mechanistic research over the last 2 decades. The synthesis reveals many new processes and developments in the science underpinning climate-PM interactions and the effects of PM on human health and the environment.
J. G. L. Rae, H. T. Hewitt, A. B. Keen, J. K. Ridley, A. E. West, C. M. Harris, E. C. Hunke, and D. N. Walters
Geosci. Model Dev., 8, 2221–2230, https://doi.org/10.5194/gmd-8-2221-2015, https://doi.org/10.5194/gmd-8-2221-2015, 2015
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The paper presents a new sea ice configuration, GSI6.0, in the Met Office coupled atmosphere-ocean-ice model. Differences in the sea ice from a previous configuration (GSI4.0) are explained in the context of a previously published sensitivity study. In summer, Arctic sea ice is thicker and more extensive than in GSI4.0, bringing it closer to the observationally derived data sets. In winter, the Arctic ice is thicker but less extensive than in GSI4.0.
A. Franchin, S. Ehrhart, J. Leppä, T. Nieminen, S. Gagné, S. Schobesberger, D. Wimmer, J. Duplissy, F. Riccobono, E. M. Dunne, L. Rondo, A. Downard, F. Bianchi, A. Kupc, G. Tsagkogeorgas, K. Lehtipalo, H. E. Manninen, J. Almeida, A. Amorim, P. E. Wagner, A. Hansel, J. Kirkby, A. Kürten, N. M. Donahue, V. Makhmutov, S. Mathot, A. Metzger, T. Petäjä, R. Schnitzhofer, M. Sipilä, Y. Stozhkov, A. Tomé, V.-M. Kerminen, K. Carslaw, J. Curtius, U. Baltensperger, and M. Kulmala
Atmos. Chem. Phys., 15, 7203–7216, https://doi.org/10.5194/acp-15-7203-2015, https://doi.org/10.5194/acp-15-7203-2015, 2015
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The ion-ion recombination coefficient was measured at different temperatures, relative humidities and concentrations of ozone and sulfur dioxide. The experiments were carried out using the CLOUD chamber at CERN.
We observed a strong dependency on temperature and on relative humidity, which has not been reported previously. No dependency of the ion-ion recombination coefficient on ozone concentration was observed and a weak variation with sulfur dioxide concentration was also observed.
M. A. Thomas, M. Kahnert, C. Andersson, H. Kokkola, U. Hansson, C. Jones, J. Langner, and A. Devasthale
Geosci. Model Dev., 8, 1885–1898, https://doi.org/10.5194/gmd-8-1885-2015, https://doi.org/10.5194/gmd-8-1885-2015, 2015
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We have showed that a coupled modelling system is beneficial in the sense that more complex processes can be included to better represent the aerosol processes starting from their formation, their interactions with clouds and provide better estimate of radiative forcing. Using this model set up, we estimated an annual mean 'indirect' radiative forcing of -0.64W/m2. This means that aerosols, solely by their capability of altering the microphysical properties of clouds can cool the Earth system.
K. D. Williams, C. M. Harris, A. Bodas-Salcedo, J. Camp, R. E. Comer, D. Copsey, D. Fereday, T. Graham, R. Hill, T. Hinton, P. Hyder, S. Ineson, G. Masato, S. F. Milton, M. J. Roberts, D. P. Rowell, C. Sanchez, A. Shelly, B. Sinha, D. N. Walters, A. West, T. Woollings, and P. K. Xavier
Geosci. Model Dev., 8, 1509–1524, https://doi.org/10.5194/gmd-8-1509-2015, https://doi.org/10.5194/gmd-8-1509-2015, 2015
S. Chadburn, E. Burke, R. Essery, J. Boike, M. Langer, M. Heikenfeld, P. Cox, and P. Friedlingstein
Geosci. Model Dev., 8, 1493–1508, https://doi.org/10.5194/gmd-8-1493-2015, https://doi.org/10.5194/gmd-8-1493-2015, 2015
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Permafrost, ground that is frozen for 2 or more years, is found extensively in the Arctic. It stores large quantities of carbon, which may be released under climate warming, so it is important to include it in climate models. Here we improve the representation of permafrost in a climate model land-surface scheme, both in the numerical representation of soil and snow, and by adding the effects of organic soils and moss. Site simulations show significantly improved soil temperature and thaw depth.
A. J. Baran, K. Furtado, L.-C. Labonnote, S. Havemann, J.-C. Thelen, and F. Marenco
Atmos. Chem. Phys., 15, 1105–1127, https://doi.org/10.5194/acp-15-1105-2015, https://doi.org/10.5194/acp-15-1105-2015, 2015
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The relationship between the shape of cirrus scattering phase functions and the atmospheric state is investigated using space-based multi-angle remote sensing measurements and high-resolution numerical weather prediction model output of the relative humidity field with respect to ice (RHi). It is found that on a pixel-by-pixel basis, the most featureless phase functions are generally associated with RHi>1, whilst for RHi<1, a unique model phase function could not be assigned to the pixel.
W. R. Sessions, J. S. Reid, A. Benedetti, P. R. Colarco, A. da Silva, S. Lu, T. Sekiyama, T. Y. Tanaka, J. M. Baldasano, S. Basart, M. E. Brooks, T. F. Eck, M. Iredell, J. A. Hansen, O. C. Jorba, H.-M. H. Juang, P. Lynch, J.-J. Morcrette, S. Moorthi, J. Mulcahy, Y. Pradhan, M. Razinger, C. B. Sampson, J. Wang, and D. L. Westphal
Atmos. Chem. Phys., 15, 335–362, https://doi.org/10.5194/acp-15-335-2015, https://doi.org/10.5194/acp-15-335-2015, 2015
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M. C. Wyant, C. S. Bretherton, R. Wood, G. R. Carmichael, A. Clarke, J. Fast, R. George, W. I. Gustafson Jr., C. Hannay, A. Lauer, Y. Lin, J.-J. Morcrette, J. Mulcahy, P. E. Saide, S. N. Spak, and Q. Yang
Atmos. Chem. Phys., 15, 153–172, https://doi.org/10.5194/acp-15-153-2015, https://doi.org/10.5194/acp-15-153-2015, 2015
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Simulations from a group of GCMs, forecast models, and regional models are compared with aircraft and ship observations of the marine boundary layer (MBL) in the southeast Pacific region during the VOCALS-REx field campaign of October-November 2008. Gradients of cloud, aerosol, and chemical properties in and above the MBL extending from the Peruvian coast westward along 20 degrees south are compared during the period.
T. R. Marthews, S. J. Dadson, B. Lehner, S. Abele, and N. Gedney
Hydrol. Earth Syst. Sci., 19, 91–104, https://doi.org/10.5194/hess-19-91-2015, https://doi.org/10.5194/hess-19-91-2015, 2015
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Modelling land surface water flow is of critical importance in the context of climate change predictions. Many approaches are based on the popular hydrology model TOPMODEL, and the most important parameter of this model is the well-known topographic index. Here we present new, higher-resolution parameter maps of the topographic index, which are ideal for land surface modelling applications and show important improvements on the previous standard maps from HYDRO1k.
E. M. Blyth, R. Oliver, and N. Gedney
Biogeosciences Discuss., https://doi.org/10.5194/bgd-11-17967-2014, https://doi.org/10.5194/bgd-11-17967-2014, 2014
Revised manuscript has not been submitted
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By studying patterns of soil carbon in the Northern Latitudes alongside vegetation, soil temperatures and wetlands, it is apparent that the main cause of high values of soil carbon is the presence of saturated soils (wetlands). This link can only be modelled if the wetlands are assumed to completely suppress soil respiration. It is important to be able to model wetlands and their effect on soil carbon if we are to understand the long term future of the soil-carbon store in Northern Latitudes.
G. D. Hayman, F. M. O'Connor, M. Dalvi, D. B. Clark, N. Gedney, C. Huntingford, C. Prigent, M. Buchwitz, O. Schneising, J. P. Burrows, C. Wilson, N. Richards, and M. Chipperfield
Atmos. Chem. Phys., 14, 13257–13280, https://doi.org/10.5194/acp-14-13257-2014, https://doi.org/10.5194/acp-14-13257-2014, 2014
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Globally, wetlands are a major source of methane, which is the second most important greenhouse gas. We find the JULES wetland methane scheme to perform well in general, although there is a tendency for it to overpredict emissions in the tropics and underpredict them in northern latitudes. Our study highlights novel uses of satellite data as a major tool to constrain land-atmosphere methane flux models in a warming world.
J. Brito, L. V. Rizzo, W. T. Morgan, H. Coe, B. Johnson, J. Haywood, K. Longo, S. Freitas, M. O. Andreae, and P. Artaxo
Atmos. Chem. Phys., 14, 12069–12083, https://doi.org/10.5194/acp-14-12069-2014, https://doi.org/10.5194/acp-14-12069-2014, 2014
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This paper details the physical--chemical characteristics of aerosols in a region strongly impacted by biomass burning in the western part of the Brazilian Amazon region. For such, a large suite of state-of-the-art instruments for realtime analysis was deployed at a ground site. Among the key findings, we observe the strong prevalence of organic aerosols associated to fire emissions, with important climate effects, and indications of its very fast processing in the atmosphere.
E. W. Blockley, M. J. Martin, A. J. McLaren, A. G. Ryan, J. Waters, D. J. Lea, I. Mirouze, K. A. Peterson, A. Sellar, and D. Storkey
Geosci. Model Dev., 7, 2613–2638, https://doi.org/10.5194/gmd-7-2613-2014, https://doi.org/10.5194/gmd-7-2613-2014, 2014
S. S. Dhomse, K. M. Emmerson, G. W. Mann, N. Bellouin, K. S. Carslaw, M. P. Chipperfield, R. Hommel, N. L. Abraham, P. Telford, P. Braesicke, M. Dalvi, C. E. Johnson, F. O'Connor, O. Morgenstern, J. A. Pyle, T. Deshler, J. M. Zawodny, and L. W. Thomason
Atmos. Chem. Phys., 14, 11221–11246, https://doi.org/10.5194/acp-14-11221-2014, https://doi.org/10.5194/acp-14-11221-2014, 2014
K. Tsigaridis, N. Daskalakis, M. Kanakidou, P. J. Adams, P. Artaxo, R. Bahadur, Y. Balkanski, S. E. Bauer, N. Bellouin, A. Benedetti, T. Bergman, T. K. Berntsen, J. P. Beukes, H. Bian, K. S. Carslaw, M. Chin, G. Curci, T. Diehl, R. C. Easter, S. J. Ghan, S. L. Gong, A. Hodzic, C. R. Hoyle, T. Iversen, S. Jathar, J. L. Jimenez, J. W. Kaiser, A. Kirkevåg, D. Koch, H. Kokkola, Y. H Lee, G. Lin, X. Liu, G. Luo, X. Ma, G. W. Mann, N. Mihalopoulos, J.-J. Morcrette, J.-F. Müller, G. Myhre, S. Myriokefalitakis, N. L. Ng, D. O'Donnell, J. E. Penner, L. Pozzoli, K. J. Pringle, L. M. Russell, M. Schulz, J. Sciare, Ø. Seland, D. T. Shindell, S. Sillman, R. B. Skeie, D. Spracklen, T. Stavrakou, S. D. Steenrod, T. Takemura, P. Tiitta, S. Tilmes, H. Tost, T. van Noije, P. G. van Zyl, K. von Salzen, F. Yu, Z. Wang, Z. Wang, R. A. Zaveri, H. Zhang, K. Zhang, Q. Zhang, and X. Zhang
Atmos. Chem. Phys., 14, 10845–10895, https://doi.org/10.5194/acp-14-10845-2014, https://doi.org/10.5194/acp-14-10845-2014, 2014
E. Collier, L. I. Nicholson, B. W. Brock, F. Maussion, R. Essery, and A. B. G. Bush
The Cryosphere, 8, 1429–1444, https://doi.org/10.5194/tc-8-1429-2014, https://doi.org/10.5194/tc-8-1429-2014, 2014
J. Browse, K. S. Carslaw, G. W. Mann, C. E. Birch, S. R. Arnold, and C. Leck
Atmos. Chem. Phys., 14, 7543–7557, https://doi.org/10.5194/acp-14-7543-2014, https://doi.org/10.5194/acp-14-7543-2014, 2014
R. E. L. West, P. Stier, A. Jones, C. E. Johnson, G. W. Mann, N. Bellouin, D. G. Partridge, and Z. Kipling
Atmos. Chem. Phys., 14, 6369–6393, https://doi.org/10.5194/acp-14-6369-2014, https://doi.org/10.5194/acp-14-6369-2014, 2014
C. B. Ménard, R. Essery, and J. Pomeroy
Hydrol. Earth Syst. Sci., 18, 2375–2392, https://doi.org/10.5194/hess-18-2375-2014, https://doi.org/10.5194/hess-18-2375-2014, 2014
G. W. Mann, K. S. Carslaw, C. L. Reddington, K. J. Pringle, M. Schulz, A. Asmi, D. V. Spracklen, D. A. Ridley, M. T. Woodhouse, L. A. Lee, K. Zhang, S. J. Ghan, R. C. Easter, X. Liu, P. Stier, Y. H. Lee, P. J. Adams, H. Tost, J. Lelieveld, S. E. Bauer, K. Tsigaridis, T. P. C. van Noije, A. Strunk, E. Vignati, N. Bellouin, M. Dalvi, C. E. Johnson, T. Bergman, H. Kokkola, K. von Salzen, F. Yu, G. Luo, A. Petzold, J. Heintzenberg, A. Clarke, J. A. Ogren, J. Gras, U. Baltensperger, U. Kaminski, S. G. Jennings, C. D. O'Dowd, R. M. Harrison, D. C. S. Beddows, M. Kulmala, Y. Viisanen, V. Ulevicius, N. Mihalopoulos, V. Zdimal, M. Fiebig, H.-C. Hansson, E. Swietlicki, and J. S. Henzing
Atmos. Chem. Phys., 14, 4679–4713, https://doi.org/10.5194/acp-14-4679-2014, https://doi.org/10.5194/acp-14-4679-2014, 2014
J. P. Mulcahy, D. N. Walters, N. Bellouin, and S. F. Milton
Atmos. Chem. Phys., 14, 4749–4778, https://doi.org/10.5194/acp-14-4749-2014, https://doi.org/10.5194/acp-14-4749-2014, 2014
C. Jiao, M. G. Flanner, Y. Balkanski, S. E. Bauer, N. Bellouin, T. K. Berntsen, H. Bian, K. S. Carslaw, M. Chin, N. De Luca, T. Diehl, S. J. Ghan, T. Iversen, A. Kirkevåg, D. Koch, X. Liu, G. W. Mann, J. E. Penner, G. Pitari, M. Schulz, Ø. Seland, R. B. Skeie, S. D. Steenrod, P. Stier, T. Takemura, K. Tsigaridis, T. van Noije, Y. Yun, and K. Zhang
Atmos. Chem. Phys., 14, 2399–2417, https://doi.org/10.5194/acp-14-2399-2014, https://doi.org/10.5194/acp-14-2399-2014, 2014
D. N. Walters, K. D. Williams, I. A. Boutle, A. C. Bushell, J. M. Edwards, P. R. Field, A. P. Lock, C. J. Morcrette, R. A. Stratton, J. M. Wilkinson, M. R. Willett, N. Bellouin, A. Bodas-Salcedo, M. E. Brooks, D. Copsey, P. D. Earnshaw, S. C. Hardiman, C. M. Harris, R. C. Levine, C. MacLachlan, J. C. Manners, G. M. Martin, S. F. Milton, M. D. Palmer, M. J. Roberts, J. M. Rodríguez, W. J. Tennant, and P. L. Vidale
Geosci. Model Dev., 7, 361–386, https://doi.org/10.5194/gmd-7-361-2014, https://doi.org/10.5194/gmd-7-361-2014, 2014
C. E. Scott, A. Rap, D. V. Spracklen, P. M. Forster, K. S. Carslaw, G. W. Mann, K. J. Pringle, N. Kivekäs, M. Kulmala, H. Lihavainen, and P. Tunved
Atmos. Chem. Phys., 14, 447–470, https://doi.org/10.5194/acp-14-447-2014, https://doi.org/10.5194/acp-14-447-2014, 2014
M. Yoshida, J. M. Haywood, T. Yokohata, H. Murakami, and T. Nakajima
Atmos. Chem. Phys., 13, 10827–10845, https://doi.org/10.5194/acp-13-10827-2013, https://doi.org/10.5194/acp-13-10827-2013, 2013
L. A. Lee, K. J. Pringle, C. L. Reddington, G. W. Mann, P. Stier, D. V. Spracklen, J. R. Pierce, and K. S. Carslaw
Atmos. Chem. Phys., 13, 8879–8914, https://doi.org/10.5194/acp-13-8879-2013, https://doi.org/10.5194/acp-13-8879-2013, 2013
F. Jégou, G. Berthet, C. Brogniez, J.-B. Renard, P. François, J. M. Haywood, A. Jones, Q. Bourgeois, T. Lurton, F. Auriol, S. Godin-Beekmann, C. Guimbaud, G. Krysztofiak, B. Gaubicher, M. Chartier, L. Clarisse, C. Clerbaux, J. Y. Balois, C. Verwaerde, and D. Daugeron
Atmos. Chem. Phys., 13, 6533–6552, https://doi.org/10.5194/acp-13-6533-2013, https://doi.org/10.5194/acp-13-6533-2013, 2013
Z. Kipling, P. Stier, J. P. Schwarz, A. E. Perring, J. R. Spackman, G. W. Mann, C. E. Johnson, and P. J. Telford
Atmos. Chem. Phys., 13, 5969–5986, https://doi.org/10.5194/acp-13-5969-2013, https://doi.org/10.5194/acp-13-5969-2013, 2013
C. L. Reddington, G. McMeeking, G. W. Mann, H. Coe, M. G. Frontoso, D. Liu, M. Flynn, D. V. Spracklen, and K. S. Carslaw
Atmos. Chem. Phys., 13, 4917–4939, https://doi.org/10.5194/acp-13-4917-2013, https://doi.org/10.5194/acp-13-4917-2013, 2013
N. Bellouin, G. W. Mann, M. T. Woodhouse, C. Johnson, K. S. Carslaw, and M. Dalvi
Atmos. Chem. Phys., 13, 3027–3044, https://doi.org/10.5194/acp-13-3027-2013, https://doi.org/10.5194/acp-13-3027-2013, 2013
M. T. Woodhouse, G. W. Mann, K. S. Carslaw, and O. Boucher
Atmos. Chem. Phys., 13, 2723–2733, https://doi.org/10.5194/acp-13-2723-2013, https://doi.org/10.5194/acp-13-2723-2013, 2013
H. F. Dacre, A. L. M. Grant, and B. T. Johnson
Atmos. Chem. Phys., 13, 1277–1291, https://doi.org/10.5194/acp-13-1277-2013, https://doi.org/10.5194/acp-13-1277-2013, 2013
E. M. Dunne, L. A. Lee, C. L. Reddington, and K. S. Carslaw
Atmos. Chem. Phys., 12, 11573–11587, https://doi.org/10.5194/acp-12-11573-2012, https://doi.org/10.5194/acp-12-11573-2012, 2012
Related subject area
Climate and Earth system modeling
ZEMBA v1.0: an energy and moisture balance climate model to investigate Quaternary climate
Development and evaluation of a new 4DEnVar-based weakly coupled ocean data assimilation system in E3SMv2
TemDeep: a self-supervised framework for temporal downscaling of atmospheric fields at arbitrary time resolutions
The ensemble consistency test: from CESM to MPAS and beyond
Presentation, calibration and testing of the DCESS II Earth system model of intermediate complexity (version 1.0)
Synthesizing global carbon–nitrogen coupling effects – the MAGICC coupled carbon–nitrogen cycle model v1.0
Historical trends and controlling factors of isoprene emissions in CMIP6 Earth system models
Investigating carbon and nitrogen conservation in reported CMIP6 Earth system model data
From weather data to river runoff: using spatiotemporal convolutional networks for discharge forecasting
A Fortran–Python interface for integrating machine learning parameterization into earth system models
A rapid-application emissions-to-impacts tool for scenario assessment: Probabilistic Regional Impacts from Model patterns and Emissions (PRIME)
The DOE E3SM version 2.1: overview and assessment of the impacts of parameterized ocean submesoscales
WRF-ELM v1.0: a regional climate model to study land–atmosphere interactions over heterogeneous land use regions
Modeling commercial-scale CO2 storage in the gas hydrate stability zone with PFLOTRAN v6.0
DiuSST: a conceptual model of diurnal warm layers for idealized atmospheric simulations with interactive sea surface temperature
High-Resolution Model Intercomparison Project phase 2 (HighResMIP2) towards CMIP7
T&C-CROP: representing mechanistic crop growth with a terrestrial biosphere model (T&C, v1.5) – model formulation and validation
An updated non-intrusive, multi-scale, and flexible coupling interface in WRF 4.6.0
Monitoring and benchmarking Earth system model simulations with ESMValTool v2.12.0
The Earth Science Box Modeling Toolkit (ESBMTK 0.14.0.11): a Python library for research and teaching
CropSuite v1.0 – a comprehensive open-source crop suitability model considering climate variability for climate impact assessment
ICON ComIn – the ICON Community Interface (ComIn version 0.1.0, with ICON version 2024.01-01)
Using feature importance as an exploratory data analysis tool on Earth system models
A new metrics framework for quantifying and intercomparing atmospheric rivers in observations, reanalyses, and climate models
The real challenges for climate and weather modelling on its way to sustained exascale performance: a case study using ICON (v2.6.6)
Improving the representation of major Indian crops in the Community Land Model version 5.0 (CLM5) using site-scale crop data
Evaluation of CORDEX ERA5-forced NARCliM2.0 regional climate models over Australia using the Weather Research and Forecasting (WRF) model version 4.1.2
Design, evaluation, and future projections of the NARCliM2.0 CORDEX-CMIP6 Australasia regional climate ensemble
The Detection and Attribution Model Intercomparison Project (DAMIP v2.0) contribution to CMIP7
Amending the algorithm of aerosol–radiation interactions in WRF-Chem (v4.4)
The very-high-resolution configuration of the EC-Earth global model for HighResMIP
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Multi-year simulations at kilometre scale with the Integrated Forecasting System coupled to FESOM2.5 and NEMOv3.4
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CARIB12: a regional Community Earth System Model/Modular Ocean Model 6 configuration of the Caribbean Sea
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ISOM 1.0: a fully mesoscale-resolving idealized Southern Ocean model and the diversity of multiscale eddy interactions
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Daniel F. J. Gunning, Kerim H. Nisancioglu, Emilie Capron, and Roderik S. W. van de Wal
Geosci. Model Dev., 18, 2479–2508, https://doi.org/10.5194/gmd-18-2479-2025, https://doi.org/10.5194/gmd-18-2479-2025, 2025
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This work documents the first results from ZEMBA: an energy balance model of the climate system. The model is a computationally efficient tool designed to study the response of climate to changes in the Earth's orbit. We demonstrate that ZEMBA reproduces many features of the Earth's climate for both the pre-industrial period and the Earth's most recent cold extreme – the Last Glacial Maximum. We intend to develop ZEMBA further and investigate the glacial cycles of the last 2.5 million years.
Pengfei Shi, L. Ruby Leung, and Bin Wang
Geosci. Model Dev., 18, 2443–2460, https://doi.org/10.5194/gmd-18-2443-2025, https://doi.org/10.5194/gmd-18-2443-2025, 2025
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Improving climate predictions has significant socio-economic impacts. In this study, we develop and apply a new weakly coupled ocean data assimilation (WCODA) system to a coupled climate model. The WCODA system improves simulations of ocean temperature and salinity across many global regions. This system is meant to advance our understanding of the ocean's role in climate predictability.
Liwen Wang, Qian Li, Qi Lv, Xuan Peng, and Wei You
Geosci. Model Dev., 18, 2427–2442, https://doi.org/10.5194/gmd-18-2427-2025, https://doi.org/10.5194/gmd-18-2427-2025, 2025
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Our research presents a novel deep learning approach called "TemDeep" for downscaling atmospheric variables at arbitrary time resolutions based on temporal coherence. Results show that our method can accurately recover evolution details superior to other methods, reaching 53.7 % in the restoration rate. Our findings are important for advancing weather forecasting models and enabling more precise and reliable predictions to support disaster preparedness, agriculture, and sustainable development.
Teo Price-Broncucia, Allison Baker, Dorit Hammerling, Michael Duda, and Rebecca Morrison
Geosci. Model Dev., 18, 2349–2372, https://doi.org/10.5194/gmd-18-2349-2025, https://doi.org/10.5194/gmd-18-2349-2025, 2025
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The ensemble consistency test (ECT) and its ultrafast variant (UF-ECT) have become powerful tools in the development community for the identification of unwanted changes in the Community Earth System Model (CESM). We develop a generalized setup framework to enable easy adoption of the ECT approach for other model developers and communities. This framework specifies test parameters to accurately characterize model variability and balance test sensitivity and computational cost.
Esteban Fernández Villanueva and Gary Shaffer
Geosci. Model Dev., 18, 2161–2192, https://doi.org/10.5194/gmd-18-2161-2025, https://doi.org/10.5194/gmd-18-2161-2025, 2025
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We describe, calibrate and test the Danish Center for Earth System Science (DCESS) II model, a new, broad, adaptable and fast Earth system model. DCESS II is designed for global simulations over timescales of years to millions of years using limited computer resources like a personal computer. With its flexibility and comprehensive treatment of the global carbon cycle, DCESS II is a useful, computationally friendly tool for simulations of past climates as well as for future Earth system projections.
Gang Tang, Zebedee Nicholls, Alexander Norton, Sönke Zaehle, and Malte Meinshausen
Geosci. Model Dev., 18, 2193–2230, https://doi.org/10.5194/gmd-18-2193-2025, https://doi.org/10.5194/gmd-18-2193-2025, 2025
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We studied carbon–nitrogen coupling in Earth system models by developing a global carbon–nitrogen cycle model (CNit v1.0) within the widely used emulator MAGICC. CNit effectively reproduced the global carbon–nitrogen cycle dynamics observed in complex models. Our results show persistent nitrogen limitations on plant growth (net primary production) from 1850 to 2100, suggesting that nitrogen deficiency may constrain future land carbon sequestration.
Ngoc Thi Nhu Do, Kengo Sudo, Akihiko Ito, Louisa K. Emmons, Vaishali Naik, Kostas Tsigaridis, Øyvind Seland, Gerd A. Folberth, and Douglas I. Kelley
Geosci. Model Dev., 18, 2079–2109, https://doi.org/10.5194/gmd-18-2079-2025, https://doi.org/10.5194/gmd-18-2079-2025, 2025
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Understanding historical isoprene emission changes is important for predicting future climate, but trends and their controlling factors remain uncertain. This study shows that long-term isoprene trends vary among Earth system models mainly due to partially incorporating CO2 effects and land cover changes rather than to climate. Future models that refine these factors’ effects on isoprene emissions, along with long-term observations, are essential for better understanding plant–climate interactions.
Gang Tang, Zebedee Nicholls, Chris Jones, Thomas Gasser, Alexander Norton, Tilo Ziehn, Alejandro Romero-Prieto, and Malte Meinshausen
Geosci. Model Dev., 18, 2111–2136, https://doi.org/10.5194/gmd-18-2111-2025, https://doi.org/10.5194/gmd-18-2111-2025, 2025
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We analyzed carbon and nitrogen mass conservation in data from various Earth system models. Our findings reveal significant discrepancies between flux and pool size data, where cumulative imbalances can reach hundreds of gigatons of carbon or nitrogen. These imbalances appear primarily due to missing or inconsistently reported fluxes – especially for land-use and fire emissions. To enhance data quality, we recommend that future climate data protocols address this issue at the reporting stage.
Florian Börgel, Sven Karsten, Karoline Rummel, and Ulf Gräwe
Geosci. Model Dev., 18, 2005–2019, https://doi.org/10.5194/gmd-18-2005-2025, https://doi.org/10.5194/gmd-18-2005-2025, 2025
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Forecasting river runoff, which is crucial for managing water resources and understanding climate impacts, can be challenging. This study introduces a new method using convolutional long short-term memory (ConvLSTM) networks, a machine learning model that processes spatial and temporal data. Focusing on the Baltic Sea region, our model uses weather data as input to predict daily river runoff for 97 rivers.
Tao Zhang, Cyril Morcrette, Meng Zhang, Wuyin Lin, Shaocheng Xie, Ye Liu, Kwinten Van Weverberg, and Joana Rodrigues
Geosci. Model Dev., 18, 1917–1928, https://doi.org/10.5194/gmd-18-1917-2025, https://doi.org/10.5194/gmd-18-1917-2025, 2025
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Earth system models (ESMs) struggle with the uncertainties associated with parameterizing subgrid physics. Machine learning (ML) algorithms offer a solution by learning the important relationships and features from high-resolution models. To incorporate ML parameterizations into ESMs, we develop a Fortran–Python interface that allows for calling Python functions within Fortran-based ESMs. Through two case studies, this interface demonstrates its feasibility, modularity, and effectiveness.
Camilla Mathison, Eleanor J. Burke, Gregory Munday, Chris D. Jones, Chris J. Smith, Norman J. Steinert, Andy J. Wiltshire, Chris Huntingford, Eszter Kovacs, Laila K. Gohar, Rebecca M. Varney, and Douglas McNeall
Geosci. Model Dev., 18, 1785–1808, https://doi.org/10.5194/gmd-18-1785-2025, https://doi.org/10.5194/gmd-18-1785-2025, 2025
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We present PRIME (Probabilistic Regional Impacts from Model patterns and Emissions), which is designed to take new emissions scenarios and rapidly provide regional impact information. PRIME allows large ensembles to be run on multi-centennial timescales, including the analysis of many important variables for impact assessments. Our evaluation shows that PRIME reproduces the climate response for known scenarios, providing confidence in using PRIME for novel scenarios.
Katherine M. Smith, Alice M. Barthel, LeAnn M. Conlon, Luke P. Van Roekel, Anthony Bartoletti, Jean-Christophe Golaz, Chengzhu Zhang, Carolyn Branecky Begeman, James J. Benedict, Gautam Bisht, Yan Feng, Walter Hannah, Bryce E. Harrop, Nicole Jeffery, Wuyin Lin, Po-Lun Ma, Mathew E. Maltrud, Mark R. Petersen, Balwinder Singh, Qi Tang, Teklu Tesfa, Jonathan D. Wolfe, Shaocheng Xie, Xue Zheng, Karthik Balaguru, Oluwayemi Garuba, Peter Gleckler, Aixue Hu, Jiwoo Lee, Ben Moore-Maley, and Ana C. Ordoñez
Geosci. Model Dev., 18, 1613–1633, https://doi.org/10.5194/gmd-18-1613-2025, https://doi.org/10.5194/gmd-18-1613-2025, 2025
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Version 2.1 of the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) adds the Fox-Kemper et al. (2011) mixed-layer eddy parameterization, which restratifies the ocean surface layer through an overturning streamfunction. Results include surface layer bias reduction in temperature, salinity, and sea ice extent in the North Atlantic; a small strengthening of the Atlantic meridional overturning circulation; and improvements to many atmospheric climatological variables.
Huilin Huang, Yun Qian, Gautam Bisht, Jiali Wang, Tirthankar Chakraborty, Dalei Hao, Jianfeng Li, Travis Thurber, Balwinder Singh, Zhao Yang, Ye Liu, Pengfei Xue, William J. Sacks, Ethan Coon, and Robert Hetland
Geosci. Model Dev., 18, 1427–1443, https://doi.org/10.5194/gmd-18-1427-2025, https://doi.org/10.5194/gmd-18-1427-2025, 2025
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We integrate the E3SM Land Model (ELM) with the WRF model through the Lightweight Infrastructure for Land Atmosphere Coupling (LILAC) Earth System Modeling Framework (ESMF). This framework includes a top-level driver, LILAC, for variable communication between WRF and ELM and ESMF caps for ELM initialization, execution, and finalization. The LILAC–ESMF framework maintains the integrity of the ELM's source code structure and facilitates the transfer of future ELM model developments to WRF-ELM.
Michael Nole, Jonah Bartrand, Fawz Naim, and Glenn Hammond
Geosci. Model Dev., 18, 1413–1425, https://doi.org/10.5194/gmd-18-1413-2025, https://doi.org/10.5194/gmd-18-1413-2025, 2025
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Safe carbon dioxide (CO2) storage is likely to be critical for mitigating some of the most severe effects of climate change. We present a simulation framework for modeling CO2 storage beneath the seafloor, where CO2 can form a solid. This can aid in permanent CO2 storage for long periods of time. Our models show what a commercial-scale CO2 injection would look like in a marine environment. We discuss what would need to be considered when designing a subsea CO2 injection.
Reyk Börner, Jan O. Haerter, and Romain Fiévet
Geosci. Model Dev., 18, 1333–1356, https://doi.org/10.5194/gmd-18-1333-2025, https://doi.org/10.5194/gmd-18-1333-2025, 2025
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The daily cycle of sea surface temperature (SST) impacts clouds above the ocean and could influence the clustering of thunderstorms linked to extreme rainfall and hurricanes. However, daily SST variability is often poorly represented in modeling studies of how clouds cluster. We present a simple, wind-responsive model of upper-ocean temperature for use in atmospheric simulations. Evaluating the model against observations, we show that it performs significantly better than common slab models.
Malcolm J. Roberts, Kevin A. Reed, Qing Bao, Joseph J. Barsugli, Suzana J. Camargo, Louis-Philippe Caron, Ping Chang, Cheng-Ta Chen, Hannah M. Christensen, Gokhan Danabasoglu, Ivy Frenger, Neven S. Fučkar, Shabeh ul Hasson, Helene T. Hewitt, Huanping Huang, Daehyun Kim, Chihiro Kodama, Michael Lai, Lai-Yung Ruby Leung, Ryo Mizuta, Paulo Nobre, Pablo Ortega, Dominique Paquin, Christopher D. Roberts, Enrico Scoccimarro, Jon Seddon, Anne Marie Treguier, Chia-Ying Tu, Paul A. Ullrich, Pier Luigi Vidale, Michael F. Wehner, Colin M. Zarzycki, Bosong Zhang, Wei Zhang, and Ming Zhao
Geosci. Model Dev., 18, 1307–1332, https://doi.org/10.5194/gmd-18-1307-2025, https://doi.org/10.5194/gmd-18-1307-2025, 2025
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HighResMIP2 is a model intercomparison project focusing on high-resolution global climate models, that is, those with grid spacings of 25 km or less in the atmosphere and ocean, using simulations of decades to a century in length. We are proposing an update of our simulation protocol to make the models more applicable to key questions for climate variability and hazard in present-day and future projections and to build links with other communities to provide more robust climate information.
Jordi Buckley Paules, Simone Fatichi, Bonnie Warring, and Athanasios Paschalis
Geosci. Model Dev., 18, 1287–1305, https://doi.org/10.5194/gmd-18-1287-2025, https://doi.org/10.5194/gmd-18-1287-2025, 2025
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We present and validate enhancements to the process-based T&C model aimed at improving its representation of crop growth and management practices. The updated model, T&C-CROP, enables applications such as analysing the hydrological and carbon storage impacts of land use transitions (e.g. conversions between crops, forests, and pastures) and optimizing irrigation and fertilization strategies in response to climate change.
Sébastien Masson, Swen Jullien, Eric Maisonnave, David Gill, Guillaume Samson, Mathieu Le Corre, and Lionel Renault
Geosci. Model Dev., 18, 1241–1263, https://doi.org/10.5194/gmd-18-1241-2025, https://doi.org/10.5194/gmd-18-1241-2025, 2025
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This article details a new feature we implemented in the popular regional atmospheric model WRF. This feature allows for data exchange between WRF and any other model (e.g. an ocean model) using the coupling library Ocean–Atmosphere–Sea–Ice–Soil Model Coupling Toolkit (OASIS3-MCT). This coupling interface is designed to be non-intrusive, flexible and modular. It also offers the possibility of taking into account the nested zooms used in WRF or in the models with which it is coupled.
Axel Lauer, Lisa Bock, Birgit Hassler, Patrick Jöckel, Lukas Ruhe, and Manuel Schlund
Geosci. Model Dev., 18, 1169–1188, https://doi.org/10.5194/gmd-18-1169-2025, https://doi.org/10.5194/gmd-18-1169-2025, 2025
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Earth system models are important tools to improve our understanding of current climate and to project climate change. Thus, it is crucial to understand possible shortcomings in the models. New features of the ESMValTool software package allow one to compare and visualize a model's performance with respect to reproducing observations in the context of other climate models in an easy and user-friendly way. We aim to help model developers assess and monitor climate simulations more efficiently.
Ulrich G. Wortmann, Tina Tsan, Mahrukh Niazi, Irene A. Ma, Ruben Navasardyan, Magnus-Roland Marun, Bernardo S. Chede, Jingwen Zhong, and Morgan Wolfe
Geosci. Model Dev., 18, 1155–1167, https://doi.org/10.5194/gmd-18-1155-2025, https://doi.org/10.5194/gmd-18-1155-2025, 2025
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The Earth Science Box Modeling Toolkit (ESBMTK) is a user-friendly Python library that simplifies the creation of models to study earth system processes, such as the carbon cycle and ocean chemistry. It enhances learning by emphasizing concepts over programming and is accessible to students and researchers alike. By automating complex calculations and promoting code clarity, ESBMTK accelerates model development while improving reproducibility and the usability of scientific research.
Florian Zabel, Matthias Knüttel, and Benjamin Poschlod
Geosci. Model Dev., 18, 1067–1087, https://doi.org/10.5194/gmd-18-1067-2025, https://doi.org/10.5194/gmd-18-1067-2025, 2025
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CropSuite is a new open-source crop suitability model. It provides a GUI and a wide range of options, including a spatial downscaling of climate data. We apply CropSuite to 48 staple and opportunity crops at a 1 km spatial resolution in Africa. We find that climate variability significantly impacts suitable areas but also affects optimal sowing dates and multiple cropping potential. The results provide valuable information for climate impact assessments, adaptation, and land-use planning.
Kerstin Hartung, Bastian Kern, Nils-Arne Dreier, Jörn Geisbüsch, Mahnoosh Haghighatnasab, Patrick Jöckel, Astrid Kerkweg, Wilton Jaciel Loch, Florian Prill, and Daniel Rieger
Geosci. Model Dev., 18, 1001–1015, https://doi.org/10.5194/gmd-18-1001-2025, https://doi.org/10.5194/gmd-18-1001-2025, 2025
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The ICOsahedral Non-hydrostatic (ICON) model system Community Interface (ComIn) library supports connecting third-party modules to the ICON model. Third-party modules can range from simple diagnostic Python scripts to full chemistry models. ComIn offers a low barrier for code extensions to ICON, provides multi-language support (Fortran, C/C++, and Python), and reduces the migration effort in response to new ICON releases. This paper presents the ComIn design principles and a range of use cases.
Daniel Ries, Katherine Goode, Kellie McClernon, and Benjamin Hillman
Geosci. Model Dev., 18, 1041–1065, https://doi.org/10.5194/gmd-18-1041-2025, https://doi.org/10.5194/gmd-18-1041-2025, 2025
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Machine learning has advanced research in the climate science domain, but its models are difficult to understand. In order to understand the impacts and consequences of climate interventions such as stratospheric aerosol injection, complex models are often necessary. We use a case study to illustrate how we can understand the inner workings of a complex model. We present this technique as an exploratory tool that can be used to quickly discover and assess relationships in complex climate data.
Bo Dong, Paul Ullrich, Jiwoo Lee, Peter Gleckler, Kristin Chang, and Travis A. O'Brien
Geosci. Model Dev., 18, 961–976, https://doi.org/10.5194/gmd-18-961-2025, https://doi.org/10.5194/gmd-18-961-2025, 2025
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A metrics package designed for easy analysis of atmospheric river (AR) characteristics and statistics is presented. The tool is efficient for diagnosing systematic AR bias in climate models and useful for evaluating new AR characteristics in model simulations. In climate models, landfalling AR precipitation shows dry biases globally, and AR tracks are farther poleward (equatorward) in the North and South Atlantic (South Pacific and Indian Ocean).
Panagiotis Adamidis, Erik Pfister, Hendryk Bockelmann, Dominik Zobel, Jens-Olaf Beismann, and Marek Jacob
Geosci. Model Dev., 18, 905–919, https://doi.org/10.5194/gmd-18-905-2025, https://doi.org/10.5194/gmd-18-905-2025, 2025
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In this paper, we investigated performance indicators of the climate model ICON (ICOsahedral Nonhydrostatic) on different compute architectures to answer the question of how to generate high-resolution climate simulations. Evidently, it is not enough to use more computing units of the conventionally used architectures; higher memory throughput is the most promising approach. More potential can be gained from single-node optimization rather than simply increasing the number of compute nodes.
Kangari Narender Reddy, Somnath Baidya Roy, Sam S. Rabin, Danica L. Lombardozzi, Gudimetla Venkateswara Varma, Ruchira Biswas, and Devavat Chiru Naik
Geosci. Model Dev., 18, 763–785, https://doi.org/10.5194/gmd-18-763-2025, https://doi.org/10.5194/gmd-18-763-2025, 2025
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The study aimed to improve the representation of wheat and rice in a land model for the Indian region. The modified model performed significantly better than the default model in simulating crop phenology, yield, and carbon, water, and energy fluxes compared to observations. The study highlights the need for global land models to use region-specific crop parameters for accurately simulating vegetation processes and land surface processes.
Giovanni Di Virgilio, Fei Ji, Eugene Tam, Jason P. Evans, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Yue Li, and Matthew L. Riley
Geosci. Model Dev., 18, 703–724, https://doi.org/10.5194/gmd-18-703-2025, https://doi.org/10.5194/gmd-18-703-2025, 2025
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We evaluate the skill in simulating the Australian climate of some of the latest generation of regional climate models. We show when and where the models simulate this climate with high skill versus model limitations. We show how new models perform relative to the previous-generation models, assessing how model design features may underlie key performance improvements. This work is of national and international relevance as it can help guide the use and interpretation of climate projections.
Giovanni Di Virgilio, Jason P. Evans, Fei Ji, Eugene Tam, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Stephen White, Yue Li, Moutassem El Rafei, Rishav Goyal, Matthew L. Riley, and Jyothi Lingala
Geosci. Model Dev., 18, 671–702, https://doi.org/10.5194/gmd-18-671-2025, https://doi.org/10.5194/gmd-18-671-2025, 2025
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We introduce new climate models that simulate Australia’s future climate at regional scales, including at an unprecedented resolution of 4 km for 1950–2100. We describe the model design process used to create these new climate models. We show how the new models perform relative to previous-generation models and compare their climate projections. This work is of national and international relevance as it can help guide climate model design and the use and interpretation of climate projections.
Nathan P. Gillett, Isla R. Simpson, Gabi Hegerl, Reto Knutti, Dann Mitchell, Aurélien Ribes, Hideo Shiogama, Dáithí Stone, Claudia Tebaldi, Piotr Wolski, Wenxia Zhang, and Vivek K. Arora
EGUsphere, https://doi.org/10.5194/egusphere-2024-4086, https://doi.org/10.5194/egusphere-2024-4086, 2025
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Climate model simulations of the response to human and natural influences together, natural climate influences alone, and greenhouse gases alone, among others, are key to quantifying human influence on the climate. The last set of such coordinated simulations underpinned key findings in the last Intergovernmental Panel on Climate Change (IPCC) report. Here we propose a new set of such simulations to be used in the next generation of attribution studies, and to underpin the next IPCC report.
Jiawang Feng, Chun Zhao, Qiuyan Du, Zining Yang, and Chen Jin
Geosci. Model Dev., 18, 585–603, https://doi.org/10.5194/gmd-18-585-2025, https://doi.org/10.5194/gmd-18-585-2025, 2025
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In this study, we improved the calculation of how aerosols in the air interact with radiation in WRF-Chem. The original model used a simplified method, but we developed a more accurate approach. We found that this method significantly changes the properties of the estimated aerosols and their effects on radiation, especially for dust aerosols. It also impacts the simulated weather conditions. Our work highlights the importance of correctly representing aerosol–radiation interactions in models.
Eduardo Moreno-Chamarro, Thomas Arsouze, Mario Acosta, Pierre-Antoine Bretonnière, Miguel Castrillo, Eric Ferrer, Amanda Frigola, Daria Kuznetsova, Eneko Martin-Martinez, Pablo Ortega, and Sergi Palomas
Geosci. Model Dev., 18, 461–482, https://doi.org/10.5194/gmd-18-461-2025, https://doi.org/10.5194/gmd-18-461-2025, 2025
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We present the high-resolution model version of the EC-Earth global climate model to contribute to HighResMIP. The combined model resolution is about 10–15 km in both the ocean and atmosphere, which makes it one of the finest ever used to complete historical and scenario simulations. This model is compared with two lower-resolution versions, with a 100 km and a 25 km grid. The three models are compared with observations to study the improvements thanks to the increased resolution.
Catherine Guiavarc'h, David Storkey, Adam T. Blaker, Ed Blockley, Alex Megann, Helene Hewitt, Michael J. Bell, Daley Calvert, Dan Copsey, Bablu Sinha, Sophia Moreton, Pierre Mathiot, and Bo An
Geosci. Model Dev., 18, 377–403, https://doi.org/10.5194/gmd-18-377-2025, https://doi.org/10.5194/gmd-18-377-2025, 2025
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The Global Ocean and Sea Ice configuration version 9 (GOSI9) is the new UK hierarchy of model configurations based on the Nucleus for European Modelling of the Ocean (NEMO) and available at three resolutions. It will be used for various applications, e.g. weather forecasting and climate prediction. It improves upon the previous version by reducing global temperature and salinity biases and enhancing the representation of Arctic sea ice and the Antarctic Circumpolar Current.
Andy Richling, Jens Grieger, and Henning W. Rust
Geosci. Model Dev., 18, 361–375, https://doi.org/10.5194/gmd-18-361-2025, https://doi.org/10.5194/gmd-18-361-2025, 2025
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The performance of weather and climate prediction systems is variable in time and space. It is of interest how this performance varies in different situations. We provide a decomposition of a skill score (a measure of forecast performance) as a tool for detailed assessment of performance variability to support model development or forecast improvement. The framework is exemplified with decadal forecasts to assess the impact of different ocean states in the North Atlantic on temperature forecast.
Maria R. Russo, Sadie L. Bartholomew, David Hassell, Alex M. Mason, Erica Neininger, A. James Perman, David A. J. Sproson, Duncan Watson-Parris, and Nathan Luke Abraham
Geosci. Model Dev., 18, 181–191, https://doi.org/10.5194/gmd-18-181-2025, https://doi.org/10.5194/gmd-18-181-2025, 2025
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Observational data and modelling capabilities have expanded in recent years, but there are still barriers preventing these two data sources from being used in synergy. Proper comparison requires generating, storing, and handling a large amount of data. This work describes the first step in the development of a new set of software tools, the VISION toolkit, which can enable the easy and efficient integration of observational and model data required for model evaluation.
Bijan Fallah, Masoud Rostami, Emmanuele Russo, Paula Harder, Christoph Menz, Peter Hoffmann, Iulii Didovets, and Fred F. Hattermann
Geosci. Model Dev., 18, 161–180, https://doi.org/10.5194/gmd-18-161-2025, https://doi.org/10.5194/gmd-18-161-2025, 2025
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We tried to contribute to a local climate change impact study in central Asia, a region that is water-scarce and vulnerable to global climate change. We use regional models and machine learning to produce reliable local data from global climate models. We find that regional models show more realistic and detailed changes in heavy precipitation than global climate models. Our work can help assess the future risks of extreme events and plan adaptation strategies in central Asia.
Manuel Schlund, Bouwe Andela, Jörg Benke, Ruth Comer, Birgit Hassler, Emma Hogan, Peter Kalverla, Axel Lauer, Bill Little, Saskia Loosveldt Tomas, Francesco Nattino, Patrick Peglar, Valeriu Predoi, Stef Smeets, Stephen Worsley, Martin Yeo, and Klaus Zimmermann
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-236, https://doi.org/10.5194/gmd-2024-236, 2025
Revised manuscript accepted for GMD
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The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool for the evaluation of Earth system models. Here, we describe recent significant improvements of ESMValTool’s computational efficiency including parallel, out-of-core, and distributed computing. Evaluations with the enhanced version of ESMValTool are faster, use less computational resources, and can handle input data larger than the available memory.
Thomas Rackow, Xabier Pedruzo-Bagazgoitia, Tobias Becker, Sebastian Milinski, Irina Sandu, Razvan Aguridan, Peter Bechtold, Sebastian Beyer, Jean Bidlot, Souhail Boussetta, Willem Deconinck, Michail Diamantakis, Peter Dueben, Emanuel Dutra, Richard Forbes, Rohit Ghosh, Helge F. Goessling, Ioan Hadade, Jan Hegewald, Thomas Jung, Sarah Keeley, Lukas Kluft, Nikolay Koldunov, Aleksei Koldunov, Tobias Kölling, Josh Kousal, Christian Kühnlein, Pedro Maciel, Kristian Mogensen, Tiago Quintino, Inna Polichtchouk, Balthasar Reuter, Domokos Sármány, Patrick Scholz, Dmitry Sidorenko, Jan Streffing, Birgit Sützl, Daisuke Takasuka, Steffen Tietsche, Mirco Valentini, Benoît Vannière, Nils Wedi, Lorenzo Zampieri, and Florian Ziemen
Geosci. Model Dev., 18, 33–69, https://doi.org/10.5194/gmd-18-33-2025, https://doi.org/10.5194/gmd-18-33-2025, 2025
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Detailed global climate model simulations have been created based on a numerical weather prediction model, offering more accurate spatial detail down to the scale of individual cities ("kilometre-scale") and a better understanding of climate phenomena such as atmospheric storms, whirls in the ocean, and cracks in sea ice. The new model aims to provide globally consistent information on local climate change with greater precision, benefiting environmental planning and local impact modelling.
Yilin Fang, Hoang Viet Tran, and L. Ruby Leung
Geosci. Model Dev., 18, 19–32, https://doi.org/10.5194/gmd-18-19-2025, https://doi.org/10.5194/gmd-18-19-2025, 2025
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Hurricanes may worsen water quality in the lower Mississippi River basin (LMRB) by increasing nutrient runoff. We found that runoff parameterizations greatly affect nitrate–nitrogen runoff simulated using an Earth system land model. Our simulations predicted increased nitrogen runoff in the LMRB during Hurricane Ida in 2021, albeit less pronounced than the observations, indicating areas for model improvement to better understand and manage nutrient runoff loss during hurricanes in the region.
Giovanni Seijo-Ellis, Donata Giglio, Gustavo Marques, and Frank Bryan
Geosci. Model Dev., 17, 8989–9021, https://doi.org/10.5194/gmd-17-8989-2024, https://doi.org/10.5194/gmd-17-8989-2024, 2024
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A CESM–MOM6 regional configuration of the Caribbean Sea was developed in response to the rising need for high-resolution models for climate impact studies. The configuration is validated for the period 2000–2020 and improves significant errors in a low-resolution model. Oceanic properties are well represented. Patterns of freshwater associated with the Amazon River are well captured, and the mean flows of ocean waters across multiple passages in the Caribbean Sea agree with observations.
Yan Bo, Hao Liang, Tao Li, and Feng Zhou
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-212, https://doi.org/10.5194/gmd-2024-212, 2024
Revised manuscript accepted for GMD
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This study proposed an advancing framework for modeling regional rice production, water use, and greenhouse gas emissions. The framework integrated a process-based soil-crop model with key physiological effects, a novel model upscaling method, and the NSGA-II multi-objective optimization algorithm at a parallel computing platform. The framework provides a valuable tool for irrigation optimization to deliver co-benefits of ensuring food production, reducing water use and greenhouse gas emissions.
Deifilia To, Julian Quinting, Gholam Ali Hoshyaripour, Markus Götz, Achim Streit, and Charlotte Debus
Geosci. Model Dev., 17, 8873–8884, https://doi.org/10.5194/gmd-17-8873-2024, https://doi.org/10.5194/gmd-17-8873-2024, 2024
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Pangu-Weather is a breakthrough machine learning model in medium-range weather forecasting that considers 3D atmospheric information. We show that using a simpler 2D framework improves robustness, speeds up training, and reduces computational needs by 20 %–30 %. We introduce a training procedure that varies the importance of atmospheric variables over time to speed up training convergence. Decreasing computational demand increases the accessibility of training and working with the model.
Fang Li, Xiang Song, Sandy P. Harrison, Jennifer R. Marlon, Zhongda Lin, L. Ruby Leung, Jörg Schwinger, Virginie Marécal, Shiyu Wang, Daniel S. Ward, Xiao Dong, Hanna Lee, Lars Nieradzik, Sam S. Rabin, and Roland Séférian
Geosci. Model Dev., 17, 8751–8771, https://doi.org/10.5194/gmd-17-8751-2024, https://doi.org/10.5194/gmd-17-8751-2024, 2024
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This study provides the first comprehensive assessment of historical fire simulations from 19 Earth system models in phase 6 of the Coupled Model Intercomparison Project (CMIP6). Most models reproduce global totals, spatial patterns, seasonality, and regional historical changes well but fail to simulate the recent decline in global burned area and underestimate the fire response to climate variability. CMIP6 simulations address three critical issues of phase-5 models.
Seung H. Baek, Paul A. Ullrich, Bo Dong, and Jiwoo Lee
Geosci. Model Dev., 17, 8665–8681, https://doi.org/10.5194/gmd-17-8665-2024, https://doi.org/10.5194/gmd-17-8665-2024, 2024
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We evaluate downscaled products by examining locally relevant co-variances during precipitation events. Common statistical downscaling techniques preserve expected co-variances during convective precipitation (a stationary phenomenon). However, they dampen future intensification of frontal precipitation (a non-stationary phenomenon) captured in global climate models and dynamical downscaling. Our study quantifies a ramification of the stationarity assumption underlying statistical downscaling.
Emmanuel Nyenah, Petra Döll, Daniel S. Katz, and Robert Reinecke
Geosci. Model Dev., 17, 8593–8611, https://doi.org/10.5194/gmd-17-8593-2024, https://doi.org/10.5194/gmd-17-8593-2024, 2024
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Research software is vital for scientific progress but is often developed by scientists with limited skills, time, and funding, leading to challenges in usability and maintenance. Our study across 10 sectors shows strengths in version control, open-source licensing, and documentation while emphasizing the need for containerization and code quality. We recommend workshops; code quality metrics; funding; and following the findable, accessible, interoperable, and reusable (FAIR) standards.
Chris Smith, Donald P. Cummins, Hege-Beate Fredriksen, Zebedee Nicholls, Malte Meinshausen, Myles Allen, Stuart Jenkins, Nicholas Leach, Camilla Mathison, and Antti-Ilari Partanen
Geosci. Model Dev., 17, 8569–8592, https://doi.org/10.5194/gmd-17-8569-2024, https://doi.org/10.5194/gmd-17-8569-2024, 2024
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Climate projections are only useful if the underlying models that produce them are well calibrated and can reproduce observed climate change. We formalise a software package that calibrates the open-source FaIR simple climate model to full-complexity Earth system models. Observations, including historical warming, and assessments of key climate variables such as that of climate sensitivity are used to constrain the model output.
Jingwei Xie, Xi Wang, Hailong Liu, Pengfei Lin, Jiangfeng Yu, Zipeng Yu, Junlin Wei, and Xiang Han
Geosci. Model Dev., 17, 8469–8493, https://doi.org/10.5194/gmd-17-8469-2024, https://doi.org/10.5194/gmd-17-8469-2024, 2024
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We propose the concept of mesoscale ocean direct numerical simulation (MODNS), which should resolve the first baroclinic deformation radius and ensure the numerical dissipative effects do not directly contaminate the mesoscale motions. It can be a benchmark for testing mesoscale ocean large eddy simulation (MOLES) methods in ocean models. We build an idealized Southern Ocean model using MITgcm to generate a type of MODNS. We also illustrate the diversity of multiscale eddy interactions.
Emily Black, John Ellis, and Ross I. Maidment
Geosci. Model Dev., 17, 8353–8372, https://doi.org/10.5194/gmd-17-8353-2024, https://doi.org/10.5194/gmd-17-8353-2024, 2024
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We present General TAMSAT-ALERT, a computationally lightweight and versatile tool for generating ensemble forecasts from time series data. General TAMSAT-ALERT is capable of combining multiple streams of monitoring and meteorological forecasting data into probabilistic hazard assessments. In this way, it complements existing systems and enhances their utility for actionable hazard assessment.
Sarah Schöngart, Lukas Gudmundsson, Mathias Hauser, Peter Pfleiderer, Quentin Lejeune, Shruti Nath, Sonia Isabelle Seneviratne, and Carl-Friedrich Schleussner
Geosci. Model Dev., 17, 8283–8320, https://doi.org/10.5194/gmd-17-8283-2024, https://doi.org/10.5194/gmd-17-8283-2024, 2024
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Precipitation and temperature are two of the most impact-relevant climatic variables. Yet, projecting future precipitation and temperature data under different emission scenarios relies on complex models that are computationally expensive. In this study, we propose a method that allows us to generate monthly means of local precipitation and temperature at low computational costs. Our modelling framework is particularly useful for all downstream applications of climate model data.
Benjamin M. Sanderson, Ben B. B. Booth, John Dunne, Veronika Eyring, Rosie A. Fisher, Pierre Friedlingstein, Matthew J. Gidden, Tomohiro Hajima, Chris D. Jones, Colin G. Jones, Andrew King, Charles D. Koven, David M. Lawrence, Jason Lowe, Nadine Mengis, Glen P. Peters, Joeri Rogelj, Chris Smith, Abigail C. Snyder, Isla R. Simpson, Abigail L. S. Swann, Claudia Tebaldi, Tatiana Ilyina, Carl-Friedrich Schleussner, Roland Séférian, Bjørn H. Samset, Detlef van Vuuren, and Sönke Zaehle
Geosci. Model Dev., 17, 8141–8172, https://doi.org/10.5194/gmd-17-8141-2024, https://doi.org/10.5194/gmd-17-8141-2024, 2024
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We discuss how, in order to provide more relevant guidance for climate policy, coordinated climate experiments should adopt a greater focus on simulations where Earth system models are provided with carbon emissions from fossil fuels together with land use change instructions, rather than past approaches that have largely focused on experiments with prescribed atmospheric carbon dioxide concentrations. We discuss how these goals might be achieved in coordinated climate modeling experiments.
Peter Berg, Thomas Bosshard, Denica Bozhinova, Lars Bärring, Joakim Löw, Carolina Nilsson, Gustav Strandberg, Johan Södling, Johan Thuresson, Renate Wilcke, and Wei Yang
Geosci. Model Dev., 17, 8173–8179, https://doi.org/10.5194/gmd-17-8173-2024, https://doi.org/10.5194/gmd-17-8173-2024, 2024
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When bias adjusting climate model data using quantile mapping, one needs to prescribe what to do at the tails of the distribution, where a larger data range is likely encountered outside of the calibration period. The end result is highly dependent on the method used. We show that, to avoid discontinuities in the time series, one needs to exclude data in the calibration range to also activate the extrapolation functionality in that time period.
Cited articles
Abdul-Razzak, H. and Ghan, S. J.: A parameterization of aerosol activation: 2.
Multiple aerosol types, J. Geophys. Res., 105, 6837–6844,
https://doi.org/10.1029/1999JD901161, 2000. a
Abel, S. J. and Boutle, I. A.: An improved representation of the raindrop size
distribution for single-moment microphysics schemes, Q. J. Roy. Meteorol. Soc.,
138, 2151–2162, https://doi.org/10.1002/qj.1949, 2012. a
Abel, S. J. and Shipway, B. J.: A comparison of cloud-resolving model
simulations of trade wind cumulus with aircraft observations taken during
RICO, Q. J. Roy. Meteorol. Soc., 133, 781–794, https://doi.org/10.1002/qj.55, 2007. a
Adler, R. F., Huffman, G. J., Chang, A., Ferraro, R., Xie, P.-P., Janowiak, J.,
Rudolf, B., Schneider, U., Curtis, S., Bolvin, D., Gruber, A., Susskind, J.,
Arkin, P., and Nelkin, E.: The version-2 Global Precipitation Climatology
Project (GPCP) monthly precipitation analysis (1979–present), J.
Hydrometeor., 4, 1147–1167,
https://doi.org/10.1175/1525-7541(2003)004<1147:TVGPCP>2.0.CO;2, 2003. a, b
Allan, R. and Ansell, T.: A new globally complete monthly historical gridded
mean sea level pressure dataset (HadSLP2): 1850–2004, J. Climate, 19,
5816–5842, https://doi.org/10.1175/JCLI3937.1, 2006. a
Allen, G., Coe, H., Clarke, A., Bretherton, C., Wood, R., Abel, S. J.,
Barrett, P., Brown, P., George, R., Freitag, S., McNaughton, C., Howell, S.,
Shank, L., Kapustin, V., Brekhovskikh, V., Kleinman, L., Lee, Y.-N.,
Springston, S., Toniazzo, T., Krejci, R., Fochesatto, J., Shaw, G., Krecl,
P., Brooks, B., McMeeking, G., Bower, K. N., Williams, P. I., Crosier, J.,
Crawford, I., Connolly, P., Allan, J. D., Covert, D., Bandy, A. R., Russell,
L. M., Trembath, J., Bart, M., McQuaid, J. B., Wang, J., and Chand, D.: South
East Pacific atmospheric composition and variability sampled along 20∘ S
during VOCALS-REx, Atmos. Chem. Phys., 11, 5237–5262,
https://doi.org/10.5194/acp-11-5237-2011, 2011. a
Amundsen, D. S., Tremblin, P., Manners, J., Baraffe, I., and Mayne, N. J.:
Treatment of overlapping gaseous absorption with the correlated-k method in
hot Jupiter and brown dwarf atmosphere models, Astron. Astrophys.,
598, A97, https://doi.org/10.1051/0004-6361/201629322, 2017. a
Anderson, E. A.: A point energy and mass balance model of a snow cover, Tech.
Rep. NWQ 19, NOAA, Office of Hydrology, National Weather Service, Silver
Spring, MD, USA, available at:
https://repository.library.noaa.gov/view/noaa/6392
(last access: 4 April 2019), 1976. a
Andres, R. J. and Kasgnoc, A. D.: A time-averaged inventory of subaerial
volcanic sulfur emissions, J. Geophys. Res., 103, 25251–25261,
https://doi.org/10.1029/98JD02091, 1998. a
Arakawa, A. and Lamb, V. R.: Computational design of the basic dynamic
processes of the UCLA general circulation model, Methods Comput. Phys., 17,
173–265, 1977. a
Asmi, A., Wiedensohler, A., Laj, P., Fjaeraa, A.-M., Sellegri, K., Birmili,
W., Weingartner, E., Baltensperger, U., Zdimal, V., Zikova, N., Putaud,
J.-P., Marinoni, A., Tunved, P., Hansson, H.-C., Fiebig, M., Kivekäs, N.,
Lihavainen, H., Asmi, E., Ulevicius, V., Aalto, P. P., Swietlicki, E.,
Kristensson, A., Mihalopoulos, N., Kalivitis, N., Kalapov, I., Kiss, G., de
Leeuw, G., Henzing, B., Harrison, R. M., Beddows, D., O'Dowd, C., Jennings,
S. G., Flentje, H., Weinhold, K., Meinhardt, F., Ries, L., and Kulmala, M.:
Number size distributions and seasonality of submicron particles in Europe
2008–2009, Atmos. Chem. Phys., 11, 5505–5538,
https://doi.org/10.5194/acp-11-5505-2011, 2011. a
Asmi, E., Kondratyev, V., Brus, D., Laurila, T., Lihavainen, H., Backman, J.,
Vakkari, V., Aurela, M., Hatakka, J., Viisanen, Y., Uttal, T., Ivakhov, V.,
and Makshtas, A.: Aerosol size distribution seasonal characteristics measured
in Tiksi, Russian Arctic, Atmos. Chem. Phys., 16, 1271–1287,
https://doi.org/10.5194/acp-16-1271-2016, 2016. a
Bain, C. L., Williams, K. D., Milton, S. F., and Heming, J. T.: Objective
tracking of African Easterly Waves in Met Office models, Q. J. Roy.
Meteorol. Soc., 140, 47–57, https://doi.org/10.1002/qj.2110, 2013. a
Baran, A. J. and Labonnote, L.-C.: A self-consistent scattering model for
cirrus. I: the solar region, Q. J. Roy. Meteorol. Soc., 133, 1899–1912,
https://doi.org/10.1002/qj.164, 2007. a
Baran, A. J., Hill, P., Furtado, K., Field, P., and Manners, J.: A coupled
cloud physics-radiation parameterization of the bulk optical properties of
cirrus and its impact on the Met Office Unified Model Global Atmosphere 5.0
configuration, J. Climate, 27, 7725–7752, https://doi.org/10.1175/JCLI-D-13-00700.1,
2014. a, b
Baran, A. J., Hill, P., Walters, D., Hardman, S. C., Furtado, K., Field, P. R.,
and Manners, J.: The impact of two coupled cirrus microphysics-radiation
parameterizations on the temperature and specific humidity biases in the
tropical tropopause layer in a climate model, J. Climate, 29, 5299–5316,
https://doi.org/10.1175/JCLI-D-15-0821.1, 2016. a, b, c, d, e, f
Barker, H. and Li, Z.: Improved simulation of clear-sky radiative transfer in
the CCC-GCM, J. Climate, 8, 2213–2223,
https://doi.org/10.1175/1520-0442(1995)008<2213:ISOCSS>2.0.CO;2, 1995. a
Bates, T. S., Huebert, B. J., Gras, J. L., Griffiths, F. B., and Durkee, P.
A.: title = International Global Atmospheric Chemistry (IGAC), project's
first, Aerosol Characterization Experiment (ACE 1): overview, J. Geophys. Res.-Atmos.,
103, 16297–16318, https://doi.org/10.1029/97JD03741, 1998. a
Bates, T. S., Quinn, P. K., Coffman, D. J.,
Johnson, J. E., Miller, T. L., Covert, D. S.,
Wiedensohler, A., Leinert, S., Nowak, A., and Neusüss, C.:
Regional physical and chemical properties of the marine
boundary layer aerosol across the Atlantic during Aerosols99: An
overview, J. Geophys. Res.-Atmos., 106, 20767–20782, https://doi.org/10.1029/2000JD900578,
2001. a
Bates, T. S., Quinn, P. K., Coffman, D. J., Covert, D. S., Miller, T. L.,
Johnson, J. E., Carmichael, G. R., Guazzotti, S. A., Sodeman, D. A., Prather, K. A.,
Rivera, M., Russell, L. M., and and Merrill, J. T.: Marine boundary layer
dust and pollution transport associated with the passage of a frontal system
over eastern Asia, J. Geophys. Res., 109, D19S19, https://doi.org/10.1029/2003JD004094,
2004. a
Bates, T. S., Quinn, P. K., Coffman, D. J., Johnson, J. E., and
Middlebrook, A. M.: The Dominance of Organic Aerosols in the Marine
Boundary Layer over the Gulf of Maine during NEAQS 2002 and their Role in
Aerosol Light Scattering, J. Geophys. Res., 110, D18202,
https://doi.org/10.1029/2005JD005797, 2005. a
Bates, T. S., Quinn, P. K., Coffman, D., Schulz, K.,
Covert, D. S., Johnson, J. E., Williams, E. J., Lerner, B. M.,
Angevine, W. M., Tucker, S. C., Brewer, W. A., and Stohl, A.:
Boundary layer aerosol chemistry during TexAQS/GoMACCS 2006: Insights into
aerosol sources and transformation processes, J. Geophys. Res.-Atmos.,
113, D7, https://doi.org/10.1029/2008JD010023, 2008. a
Batjes, N. H.: Harmonized soil profile data for applications at global and
continental scales: updates to the WISE database, Soil Use Manage., 25,
124–127, https://doi.org/10.1111/j.1475-2743.2009.00202.x, 2009. a
Bazile, E., Couvreux, F., Le Moigne, P., Genthon, C., Traullé, O., Maurel,
W., Barral, H., Canut, G., Holtslag(4), A. A. M., and Svensson, G.:
available at: http://www.umr-cnrm.fr/aladin/meshtml/GABLS4/GABLS4.html
(last access: 25 October 2017), 2014. a
Beare, R. J.: The role of shear in the morning transition boundary layer,
Bound.-Lay. Meteorol., 129, 395–410, https://doi.org/10.1007/s10546-008-9324-8, 2008. a
Beljaars, A. C. M. and Holtslag, A. A. M.: Flux parametrization over land
surfaces for atmospheric models, J. Appl. Meteorol., 30, 327–341,
https://doi.org/10.1175/1520-0450(1991)030<0327:FPOLSF>2.0.CO;2, 1991. a
Bellouin, N., Rae, J., Jones, A., Johnson, C., Haywood, J., and Boucher, O.:
Aerosol forcing in the Climate Model Intercomparison Project (CMIP5)
simulations by HadGEM2-ES and the role of ammonium nitrate, J. Geophys.
Res., 116, D20206, https://doi.org/10.1029/2011JD016074, 2011. a, b, c
Bellouin, N., Mann, G. W., Woodhouse, M. T., Johnson, C., Carslaw, K. S., and
Dalvi, M.: Impact of the modal aerosol scheme GLOMAP-mode on aerosol
forcing in the Hadley Centre Global Environmental Model, Atmos. Chem.
Phys., 13, 3027–3044, https://doi.org/10.5194/acp-13-3027-2013, 2013. a, b
Bengtsson, L. and Körich, H.: Impact of a stochastic parametrization of
cumulus convection, using cellular automata, in a mesoscale ensemble
prediction system, Q. J. Roy. Meteorol. Soc., 142, 1150–1159,
https://doi.org/10.1002/qj.2720, 2016. a
Bengtsson, L., Steinheimer, M., Bechtold, P., and Geleyn, J. F.: A stochastic
parametrization for deep convection using cellular automata, Q. J. Roy.
Meteorol. Soc., 139, 1533–1543, https://doi.org/10.1002/qj.2108, 2013. a
Berner, J., Jung, T., and Palmer, T. N.: Systematic error model error: the
impact of increased horizontal resolution versus improved stochastic and
deterministic parameterizations, J. Climate, 66, 603–626,
https://doi.org/10.1175/JCLI-D-11-00297.1, 2012. a
Berrisford, P., Dee, D., Fielding, K., Fuentes, M., Kållberg, P.,
Kobayashi, S., and Uppala, S.: The ERA-Interim archive, Tech. Rep. 1, ERA
report series, ECMWF, Reading, UK, 2009. a
Best, M. J.: Representing urban areas within operational numerical weather
prediction models, Bound.-Lay. Meteorol., 114, 91–109,
https://doi.org/10.1007/s10546-004-4834-5, 2005. a
Best, M. J., Pryor, M., Clark, D. B., Rooney, G. G., Essery, R. L. H.,
Ménard, C. B., Edwards, J. M., Hendry, M. A., Gedney, N., Mercado, L. M.,
Sitch, S., Blyth, E., Boucher, O., Cox, P. M., Grimmond, C. S. B., and
Harding, R. J.: The Joint UK Land Environment Simulator (JULES), model
description – Part 1: Energy and water fluxes, Geosci. Model Dev., 4,
677–699, https://doi.org/10.5194/gmd-4-677-2011, 2011. a, b, c, d, e
Beven, K. J. and Kirkby, M. J.: A physically based, variable contributing area
model of basin hydrology, Hydrol. Sci. Bull., 24, 43–69,
https://doi.org/10.1080/02626667909491834, 1979. a
Birch, C. E., Roberts, M. J., Garcia-Carreras, L., Ackerley, D., Reeder, M. J.,
Lock, A. P., and Schiemann, R.: Sea-breeze dynamics and convection
initiation: The influence of convective parameterization in weather and
climate model biases, J. Climate, 28, 8093–8108,
https://doi.org/10.1175/JCLI-D-14-00850.1, 2015. a
Bodas-Salcedo, A., Webb, M. J., Brooks, M. E., Ringer, M. A., Williams, K. D.,
Milton, S. F., and Wilson, D. R.: Evaluating cloud systems in the Met
Office global forecast model using simulated CloudSat radar
reflectivities, J. Geophys. Res., 113, D00A13, https://doi.org/10.1029/2007JD009620,
2008. a
Bodas-Salcedo, A., Williams, K. D., Field, P. R., and Lock, A. P.: The surface
downwelling solar radiation surplus over the Southern Ocean in the Met Office
model: the role of midlatitude cyclone clouds, J. Climate, 25, 7467–7486,
https://doi.org/10.1175/JCLI-D-11-00702.1, 2012. a
Bodas-Salcedo, A., Williams, K. D., Ringer, M. A., Beau, I., Cole, J. N. S.,
Dufresne, J.-L., Koshiro, T., Stevens, B., Wang, Z., and Yokohata, T.:
Origins of the solar radiation biases over the Southern Ocean in CFMIP2
models, J. Climate, 27, 41–56, https://doi.org/10.1175/JCLI-D-13-00169.1, 2014. a
Bond, T. C. and Bergstrom, R. W.: Light Absorption by Carbonaceous Particles:
An Investigative Review, Aerosol Sci. Technol., 40, 27–67,
https://doi.org/10.1080/02786820500421521, 2006. a
Bond, T. C., Doherty, S. J., Fahey, D. W., Forster, P. M., Berntsen, T.,
DeAngelo, B. J., Flanner, M. G., Ghan, S., Kärcher, B., Koch, D., Kinne, S.,
Kondo, Y., Quinn, P. K., Sarofim, M. C., Schultz, M. G., Schulz, M.,
Venkataraman, C., Zhang, H., Zhang, S., Bellouin, N., Guttikunda, S. K.,
Hopke, P. K., Jacobson, M. Z., Kaiser, J. W., Klimont, Z., Lohmann, U.,
Schwarz, J. P., Shindell, D., Storelvmo, T., Warren, S. G., and Zender,
C. S.: Bounding the role of black carbon in the climate system: A scientific
assessment, J. Geophys. Res.-Atmos., 11, 5380–5552,
https://doi.org/10.1002/jgrd.50171, 2013. a
Bosilovich, M. G.: NASA's modern era retrospective-analysis for research
and applications: Integrating Earth observations, Earthzine,
available at: https://earthzine.org/nasas-modern-era-retrospective-analysis/
(last access: 4 April 2019), 2008. a
Boutle, I., Price, J., Kudzotsa, I., Kokkola, H., and Romakkaniemi, S.:
Aerosol-fog interaction and the transition to well-mixed radiation fog,
Atmos. Chem. Phys., 18, 7827–7840, https://doi.org/10.5194/acp-18-7827-2018, 2018. a
Boutle, I. A. and Abel, S. J.: Microphysical controls on the stratocumulus
topped boundary-layer structure during VOCALS-REx, Atmos. Chem. Phys., 12,
2849–2863, https://doi.org/10.5194/acp-12-2849-2012, 2012. a
Boutle, I. A., Abel, S. J., Hill, P. G., and Morcrette, C. J.: Spatial
variability of liquid cloud and rain: observations and microphysical effects,
Q. J. Roy. Meteorol. Soc., 140, 583–594, https://doi.org/10.1002/qj.2140,
2014a. a, b, c, d
Boutle, I. A., Eyre, J. E. J., and Lock, A. P.: Seamless stratocumulus
simulation across the turbulent gray zone, Mon. Weather Rev., 142,
1655–1668, https://doi.org/10.1175/MWR-D-13-00229.1, 2014b. a
Bowler, N. E., Arribas, A., Mylne, K. R., Robertson, K. B., and Beare, S. E.:
The MOGREPS short-range ensemble prediction system, Q. J. Roy. Meteorol.
Soc., 134, 703–722, https://doi.org/10.1002/qj.234, 2008. a
Bowler, N. E., Arribas, A., Beare, S. E., and Mylne, K. R.: The local ETKF
and SKEB: upgrades to the MOGREPS short-range ensemble prediction system,
Q. J. Roy. Meteorol. Soc., 135, 767–776, https://doi.org/10.1002/qj.394, 2009. a
Bowler, N. E., Clayton, A. M., Jardak, M., Lee, E., Lorenc, A. C., Piccolo, C.,
Pring, S. R., Wlasak, M. A., Barker, D. M., Inverarity, G. W., and Swinbank,
R.: Inflation and localization tests in the development of an ensemble of
4D-ensemble variational assimilations, Q. J. Roy. Meteorol. Soc., 143,
1280–1302, https://doi.org/10.1002/qj.3004, 2017. a
Brohan, P., Kennedy, J. J., Harris, I., Tett, S. F. B., and Jones, P. D.:
Uncertainty estimates in regional and global observed temperature changes: a
new dataset from 1850, J. Geophys. Res., 111, D12106,
https://doi.org/10.1029/2005JD006548, 2006. a
Brown, A., Milton, S., Cullen, M., Golding, B., Mitchell, J., and Shelly, A.:
Unified modeling and prediction of weather and climate: a 25 year journey,
B. Am. Meteorol. Soc., 93, 1865–1877, https://doi.org/10.1175/BAMS-D-12-00018.1,
2012. a
Brown, A. R.: The sensitivity of large-eddy simulations of shallow cumulus
convection to resolution and sub-grid model, Q. J. Roy. Meteorol. Soc., 125,
469–482, https://doi.org/10.1002/qj.49712555405, 1999. a
Brown, A. R., Beare, R. J., Edwards, J. M., Lock, A. P., Keogh, S. J., Milton,
S. F., and Walters, D. N.: Upgrades to the boundary-layer scheme in the Met
Office numerical weather prediction model, Bound.-Lay. Meteorol., 128,
117–132, https://doi.org/10.1007/s10546-008-9275-0, 2008. a, b
Burke, E. J., Dankers, R., Jones, C. D., and Wiltshire, A. J.: A retrospective
analysis of pan Arctic permafrost using the JULES land surface model,
Clim. Dynam., 41, 1025–1038, https://doi.org/10.1007/s00382-012-1648-x, 2013. a
Bushell, A. C., Wilson, D. R., and Gregory, D.: A description of cloud
production by non-uniformly distributed processes, Q. J. Roy. Meteorol. Soc.,
129, 1435–1455, https://doi.org/10.1256/qj.01.110, 2003. a
Calonne, N., Flin, F., Morin, S., Lesaffre, B., Rolland du Roscoat, S., and
Geindreau, C.: Numerical and experimental investigations of the effective
thermal conductivity of snow, Geophys. Res. Lett., 38, L23501,
https://doi.org/10.1029/2011GL049234, 2011. a
Chang, R. Y.-W., Leck, C., Graus, M., Müller, M., Paatero, J., Burkhart, J.
F., Stohl, A., Orr, L. H., Hayden, K., Li, S.-M., Hansel, A., Tjernström, M.,
Leaitch, W. R., and Abbatt, J. P. D.: Aerosol composition and sources in the
central Arctic Ocean during ASCOS, Atmos. Chem. Phys., 11, 10619–10636,
https://doi.org/10.5194/acp-11-10619-2011, 2011. a
Charney, J. G. and Phillips, N. A.: Numerical integration of the
quasi-geostrophic equations for barotropic and simple baroclinic flows, J.
Meteorol., 10, 71–99,
https://doi.org/10.1175/1520-0469(1953)010<0071:NIOTQG>2.0.CO;2, 1953. a
Charnock, H.: Wind stress on a water surface, Q. J. Roy. Meteorol. Soc., 81,
639–640, https://doi.org/10.1002/qj.49708135027, 1955. a
Cionni, I., Eyring, V., Lamarque, J. F., Randel, W. J., Stevenson, D. S., Wu,
F., Bodeker, G. E., Shepherd, T. G., Shindell, D. T., and Waugh, D. W.: Ozone
database in support of CMIP5 simulations: results and corresponding
radiative forcing, Atmos. Chem. Phys., 11, 11267–11292,
https://doi.org/10.5194/acp-11-11267-2011, 2011. a
Clarke, A. D., Varner, J. L., Eisele,
F., Mauldin, R. L., Tanner, D., and Litchy, M.: Particle
production in the remote marine atmosphere: Cloud outflow and subsidence
during ACE 1, J. Geophys. Res.-Atmos., 103, 16397–16409,
https://doi.org/10.1029/97JD02987, = 1998. a
Clark, D. B., Mercado, L. M., Sitch, S., Jones, C. D., Gedney, N., Best, M. J.,
Pryor, M., Rooney, G. G., Essery, R. L. H., Blyth, E., Boucher, O., Cox,
P. M., and Harding, R. J.: The Joint UK Land Environment Simulator (JULES),
model description – Part 2: Carbon fluxes and vegetation, Geosci. Model
Dev., 4, 701–722, https://doi.org/10.5194/gmd-4-701-2011, 2011. a, b
Clayton, A. M., Lorenc, A. C., and Barker, D. M.: Operational implementation of
a hybrid ensemble/4D-Var global data assimilation system at the Met
Office, Q. J. Roy. Meteorol. Soc., 139, 1445–1461, https://doi.org/10.1002/qj.2054,
2013. a
Cotton, R. J., Field, P. R., Ulanowski, Z., Kaye, P. H., Hirst, E., Greenaway,
R. S., Crawford, I., Crosier, J., and Dorsey, J.: The effective density of
small ice particles obtained from in situ aircraft observations of
mid-latitude cirrus, Q. J. Roy. Meteorol. Soc., 139, 1923–1934,
https://doi.org/10.1002/qj.2058, 2013. a, b
Cox, C. and Munk, W.: Measurement of the Roughness of the Sea Surface from
Photographs of the Sun's Glitter, J. Opt. Soc. Am., 44, 838–850,
https://doi.org/10.1364/JOSA.44.000838, 1954. a
Cusack, S., Slingo, A., Edwards, J. M., and Wild, M.: The radiative impact of a
simple aerosol climatology on the Hadley Centre atmospheric GCM, Q. J. Roy.
Meteorol. Soc., 124, 2517–2526, https://doi.org/10.1002/qj.49712455117, 1998. a
Daumont, D., Brion, J., Charbonnier, J., and Malicet, J.: Ozone UV
spectroscopy I: Absorption cross-sections at room temperature, J. Atmos.
Chem., 15, 145–155, https://doi.org/10.1007/BF00053756, 1992. a
Dawson, A. and Palmer, T. N.: Simulating weather regimes: impact of model
resolution and stochastic parameterization, Clim. Dynam., 44, 2177–2193,
https://doi.org/10.1007/s00382-014-2238-x, 2015. a
Derbyshire, S. H., Maidens, A. V., Milton, S. F., Stratton, R. A., and Willett,
M. R.: Adaptive detrainment in a convective parametrization, Q. J. Roy.
Meteorol. Soc., 137, 1856–1871, https://doi.org/10.1002/qj.875, 2011. a, b, c
DeWitt, H. L., Coffman, D. J., Schulz, K. J.,
Alan Brewer, W., Bates, T. S., and Quinn, P. K.:
Atmospheric aerosol properties over the equatorial Indian Ocean and the
impact of the Madden–Julian Oscillation, J. Geophys. Res.-Atmos., 118,
5736–5749, https://doi.org/10.1002/jgrd.50419, 2013. a
Dharssi, I., Vidale, P. L., Verhoef, A., Macpherson, B., Jones, C., and Best,
M.: New soil physical properties implemented in the Unified Model at PS18,
Tech. Rep. 528, Forecasting R&D, Met Office, Exeter, UK, 2009. a
Doblas-Reyes, F. J., Weisheimer, A., Déqué, M., Keenlyside, N., McVean, M.,
Murphy, J. M., Rogel, P., Smith, D., and Palmer, T. N.: Addressing model
uncertainty in seasonal and annual dynamical seasonal forecasts, Q. J. Roy.
Meteorol. Soc., 135, 1538–1559, https://doi.org/10.1002/qj.464, 2009. a
Donelan, M. A., Dobson, F. W., Smith, S. D., and Anderson, R. J.: On the
dependence of sea surface roughness on wave development, J. Phys. Oceanogr.,
23, 2143–2149, https://doi.org/10.1175/1520-0485(1993)023<2143:OTDOSS>2.0.CO;2,
1993. a
Dyer, A. J. and Hicks, B. B.: Flux-gradient relationships in the constant flux
layer, Q. J. Roy. Meteorol. Soc., 96, 715–721, https://doi.org/10.1002/qj.49709641012,
1970. a
EBAS: http://ebas.nilu.no, last access: 12 March 2019. a
Eckermann, S. D.: Explicitly stochastic parameterization of nonorographic
gravity wave drag, J. Atmos. Sci., 68, 1749–1765,
https://doi.org/10.1175/2011JAS3684.1, 2011. a
Edson, J. B.: Review of air-sea transfer processes, in: ECMWF workshop on
atmosphere-ocean interactions, Reading, UK, 10–12
November, 2008, 7–24, European Centre for Medium-Range Weather
Forecasts, 2009. a
Edson, J. B., Jampana, V., Weller, R. A., Biggore, S. P., Plueddemann, A. J.,
Fairall, C. W., Miller, S. D., Mahrt, L., Vickers, D., and Hersbach, H.: On
the exchange of momentum over the open ocean, J. Phys. Oceanogr., 43,
1589–1610, https://doi.org/10.1175/JPO-D-12-0173.1, 2013. a
Edwards, J. M.: Efficient calculation of infrared fluxes and cooling rates
using the two-stream equations, J. Atmos. Sci., 53, 1921–1932,
https://doi.org/10.1175/1520-0469(1996)053<1921:ECOIFA>2.0.CO;2, 1996. a
Edwards, J. M. and Slingo, A.: Studies with a flexible new radiation code. I:
Choosing a configuration for a large-scale model, Q. J. Roy. Meteorol. Soc.,
122, 689–719, https://doi.org/10.1002/qj.49712253107, 1996. a, b
Essery, R., Pomeroy, J., Parviainen, J., and Storck, P.: Sublimation of snow
from coniferous forests in a climate model, J. Climate, 16, 1855–1864,
https://doi.org/10.1175/1520-0442(2003)016<1855:SOSFCF>2.0.CO;2,
2003a. a
Essery, R. L. H., Best, M. J., Betts, R. A., Cox, P. M., and Taylor, C. M.:
Explicit representation of subgrid heterogeneity in a GCM land surface
scheme, J. Hydrometeor., 4, 530–543,
https://doi.org/10.1175/1525-7541(2003)004<0530:EROSHI>2.0.CO;2,
2003b. a
Eyring, V., Bony, S., Meehl, G. A., Senior, C., Stevens, B., and Stouffer, R.
J. Taylor, K. E.: Overview of the Coupled Model Intercomparison Project
Phase 6 (CMIP6) experimental design and organisation, Geosci. Model Dev.
Discuss., 8, 10539–10583, https://doi.org/10.5194/gmdd-8-10539-2015, 2015. a
Fairall, C. W., Bradley, E. F., Hare, J. E., Grachev, A. A., and Edson, J. B.:
Bulk parameterization of air-sea fluxes: updates and verification for the
COARE algorithm, J. Climate, 16, 571–591,
https://doi.org/10.1175/1520-0442(2003)016<0571:BPOASF>2.0.CO;2, 2003. a
Falloon, P. D. and Betts, R. A.: The impact of climate change on global river
flow in HadGEM1 simulations, Atmos. Sci. Lett., 7, 62–68,
https://doi.org/10.1002/asl.133, 2006. a
Fenn, M. A., Browell, E. V., Butler, C. F., Grant, W. B., Kooi, S. A.,
Clayton, M. B., Gregory, G. L., Newell, R. E., Zhu, Y., Dibb, J. E.,
Fuelberg, H. E., Anderson, B. E., Bandy, A. R., Blake,
D. R., Bradshaw, J. D., Heikes, B. G., Sachse, G. W., Sandholm, S. T.,
Singh, H. B., Talbot, R. W., and Thornton, D. C.: Ozone and aerosol
distributions and air mass characteristics over the South Pacific during
the burning season, J. Geophys. Res.-Atmos., 104, 16197–16212,
https://doi.org/10.1029/1999JD900065, 1999. a
Fiebig, M., Lunder, C. R., and Stohl, A.: Tracing
biomass burning aerosol from South America to Troll Research Station,
Antarctica, Geophys. Res. Lett., 36, L14815, https://doi.org/10.1029/2009GL038531,
2009. a
Field, P. R., Heymsfield, A. J., and Bansemer, A.: Snow Size Distribution
Parameterization for Midlatitude and Tropical Ice Clouds, J. Atmos. Sci., 64,
4346–4365, https://doi.org/10.1175/2007JAS2344.1, 2007. a, b
Field, P. R., Hill, A. A., Furtado, K., and Korolev, A.: Mixed-phase clouds in
a turbulent environment. Part 2: Analytic treatment, Q. J. Roy. Meteorol. Soc.,
140, 870–880, https://doi.org/10.1002/qj.2175, 2014. a, b
Ford, D. A., Edwards, K. P., Lea, D., Barciela, R. M., Martin, M. J., and
Demaria, J.: Assimilating GlobColour ocean colour data into a
pre-operational physical-biogeochemical model, Ocean Sci., 8, 751–771,
https://doi.org/10.5194/os-8-751-2012, 2012. a, b
Fritsch, J. M. and Chappell, C. F.: Numerical prediction of convectively driven
mesoscale pressure systems. Part I: convective parameterization, J.
Atmos. Sci., 37, 1722–1733,
https://doi.org/10.1175/1520-0469(1980)037<1722:NPOCDM>2.0.CO;2, 1980. a
Frossard, A. A., Shaw, P. M., Russell, L. M., Kroll, J. H., Canagartna, M.,
Worsnop, D., Quinn, P. K., and Bates, T. S.: Springtime Arctic haze
contributions of submicron organic particles from European and Asian combustion
sources, J. Geophys. Res., 116, D05205, https://doi.org/10.1029/2010JD015178, 2011. a
Furtado, K., Field, P. R., Cotton, R., and Baran, A. J.: The sensitivity of
simulated high clouds to ice crystal fall speed, shape and size distribution,
Q. J. Roy. Meteorol. Soc., 141, 1546–1559, https://doi.org/10.1002/qj.2457, 2015. a, b
Furtado, K., Field, P. R., Boutle, I. A., Morcrette, C. J., and Wilkinson,
J. M.: A physically based subgrid parameterization for the production and
maintenance of mixed-phase clouds in a general circulation model, J. Atmos.
Sci., 73, 279–291, https://doi.org/10.1175/JAS-D-15-0021.1, 2016. a, b, c, d
Gallet, J.-C., Domine, F., Arnaud, L., Picard, G., and Savarino, J.: Vertical
profile of the specific surface area and density of the snow at Dome C and on
a transect to Dumont D'Urville, Antarctica – albedo calculations and
comparison to remote sensing products, The Cryosphere, 5, 631–649,
https://doi.org/10.5194/tc-5-631-2011, 2011. a
Garcia-Carreras, L., J., P. D., Marsham, J. H., Rosenberg, P. D., Brooks,
I. M., Lock, A. P., Marenco, F., McQuaid, J. B., and Hobby, M.: The turbulent
structure and diurnal growth of the Saharan atmospheric boundary layer, J.
Atmos. Sci., 72, 693–713, https://doi.org/10.1175/JAS-D-13-0384.1, 2015. a
Gedney, N. and Cox, P. M.: The sensitivity of global climate model simulations
to the representation of soil moisture heterogeneity, J. Hydrometeor., 4,
1265–1275, https://doi.org/10.1175/1525-7541(2003)004<1265:TSOGCM>2.0.CO;2, 2003. a
Godfrey, J. S. and Beljaars, A. C. M.: On the turbulent fluxes of buoyancy,
heat and moisture at the air-sea interface at low wind speeds, J. Geophys.
Res., 96, 22043–22048, https://doi.org/10.1029/91JC02015, 1991. a
Gorshelev, V., Serdyuchenko, A., Weber, M., Chehade, W., and Burrows, J. P.:
High spectral resolution ozone absorption cross-sections – Part 1:
Measurements, data analysis and comparison with previous measurements around
293 K, Atmos. Meas. Tech., 7, 609–624, https://doi.org/10.5194/amt-7-609-2014, 2014. a
Grant, A. L. M.: Cloud-base fluxes in the cumulus-capped boundary layer, Q. J.
Roy. Meteorol. Soc., 127, 407–421, https://doi.org/10.1002/qj.49712757209, 2001. a, b
Grant, A. L. M. and Brown, A. R.: A similarity hypothesis for shallow-cumulus
transports, Q. J. Roy. Meteorol. Soc., 125, 1913–1936,
https://doi.org/10.1002/qj.49712555802, 1999. a
Grant, A. L. M. and Lock, A. P.: The turbulent kinetic energy budget for
shallow cumulus convection, Q. J. Roy. Meteorol. Soc., 130, 401–422,
https://doi.org/10.1256/qj.03.50, 2004. a, b
Gregory, D. and Allen, S.: The effect of convective downdraughts upon NWP and
climate simulations, in: Ninth conference on numerical weather prediction,
Denver, Colorado, 122–123, 1991. a
Gregory, D. and Rowntree, P. R.: A massflux convection scheme with
representation of cloud ensemble characteristics and stability dependent
closure, Mon. Weather Rev., 118, 1483–1506,
https://doi.org/10.1175/1520-0493(1990)118<1483:AMFCSW>2.0.CO;2, 1990. a, b, c
Gregory, D., Kershaw, R., and Inness, P. M.: Parametrization of momentum
transport by convection II: Tests in single-column and general
circulation models, Q. J. Roy. Meteorol. Soc., 123, 1153–1183,
https://doi.org/10.1002/qj.49712354103, 1997. a
Hardiman, S. C., Boutle, I. A., Bushell, A. C., Butchart, N., Cullen, M. J. P.,
Field, P. R., Furtado, K., Manners, J. C., Milton, S. F., Morcrette, C.,
O'Connor, F. M., Shipway, B. J., Smith, C., Walters, D. N., Willett, M. R.,
Williams, K. D., Wood, N., Abraham, N. L., Keeble, J., Maycock, A. C.,
Thuburn, J., and Woodhouse, M. T.: Processes controlling tropical tropopause
temperature and stratospheric water vapor in climate models, J. Climate, 28,
6516–6535, https://doi.org/10.1175/JCLI-D-15-0075.1, 2015. a, b, c, d, e, f, g, h
Hastings, D. A., Dunbar, P. K., Elphingstone, G. M., Bootz, M., Murakami, H.,
Maruyama, H., Masaharu, H., Holland, P., Payne, J., Bryant, N. A., Logan,
T. L., Muller, J.-P., Schreier, G., and MacDonald, J. S.: The Global Land
One-kilometer Base Elevation (GLOBE) Digital Elevation Model, Version 1.0,
Digital data base on the World Wide Web,
available at: http://www.ngdc.noaa.gov/mgg/topo/globe.html (last access:
25 October 2017), 1999. a
Hawkins, L. N., Russell, L. M., Covert, D. S., Quinn, P. K., and Bates, T.
S.: Carboxylic acids, sulfates, and organosulfates in processed
continental organic aerosol over the Southeast
Pacific Ocean during VOCALS-REx 2008 J. Geophys. Res.,
115, D132012010, https://doi.org/10.1029/2009JD013276, 2010. a
Hill, A. A., Field, P. R., Furtado, K., Korolev, A., and Shipway, B. J.:
Mixed-phase clouds in a turbulent environment. Part 1: Large-eddy simulation
experiments, Q. J. Roy. Meteorol. Soc., 140, 855–869, https://doi.org/10.1002/qj.2177,
2014. a
Hill, A. A., Shipway, B. J., and Boutle, I. A.: How sensitive are
aerosol-precipitation interactions to the warm rain representation?, J. Adv.
Model. Earth Syst., 7, 987–1004, https://doi.org/10.1002/2014MS000422, 2015. a
Hill, P. G., Manners, J., and Petch, J. C.: Reducing noise associated with the
Monte Carlo Independent Column Approximation for weather forecasting
models, Q. J. Roy. Meteorol. Soc., 137, 219–228, https://doi.org/10.1002/qj.732, 2011. a, b
Hill, P. G., Hogan, R. J., Manners, J., and Petch, J. C.: Parametrizing the
horizontal inhomogeneity of ice water content using CloudSat data products,
Q. J. Roy. Meteorol. Soc., 138, 1784–1793, https://doi.org/10.1002/qj.1893, 2012. a
Hogan, R. J. and Illingworth, A. J.: Parameterizing ice cloud inhomogeneity and
the overlap of inhomogeneities using cloud radar data, J. Atmos. Sci., 60,
756–767, https://doi.org/10.1175/1520-0469(2003)060<0756:PICIAT>2.0.CO;2, 2003. a
Holben, B. N., Tanre, D., Smirnov, A., Eck, T. F., Slutsker, I., Abuhassan, N.,
Newcomb, W. W., Schafer, J., Chatenet, B., Lavenue, F., Kaufman, Y. J.,
Castle, J. V., Setzer, A., Markham, B., Clark, D., Frouin, R., Halthore, R.,
Karnieli, A., O'Neill, N. T., Pietras, C., Pinker, R. T., Voss, K., and
Zibordi, G.: An emerging ground-based aerosol climatology: Aerosol Optical
Depth from AERONET, J. Geophys. Res., 106, 12067–12097,
https://doi.org/10.1029/2001JD900014, 2001. a
Holtslag, A. A. M. and Moeng, C.-H.: Eddy diffusivity and countergradient
transport in the convective atmospheric boundary layer, J. Atmos. Sci., 48,
1690–1698, https://doi.org/10.1175/1520-0469(1991)048<1690:EDACTI>2.0.CO;2, 1991. a
Houldcroft, C., Grey, W., Barnsley, M., Taylor, C., Los, S., and North, P.: New
vegetation albedo parameters and global fields of background albedo derived
from MODIS for use in a climate model, J. Hydrometeorol., 10,
183–198, https://doi.org/10.1175/2008JHM1021.1, 2008. a
Hourdin, F., Mauritsen, T., Gettelman, A., Golaz, J.-C., Balaji, V., Duan, Q.,
Folini, D., Ji, D., Klocke, D., Qian, Y., Rauser, F., Rio, C., Tomassini, L.,
Watanabe, M., and Williamson, D.: The art and science of climate model
tuning, B. Am. Meteorol. Soc., 98, 589–602,
https://doi.org/10.1175/BAMS-D-15-00135.1, 2017. a
Huebert, B. J., Bates, T., Russell, P. B.,
Shi, G., Kim, Y. J., Kawamura, K., Carmichael, G.,
and Nakajima, T.: An overview of ACE-Asia: Strategies for
quantifying the relationships between Asian aerosols and their climatic
impacts, journal = ”J Geophys Res Atmos.”, volume = 108, pages = D23,
doi = 10.1029/2003JD003550, 2003. a
Hudson, J. G. and Noble, S.: CCN and cloud
droplet concentrations at a remote ocean site, Geophys. Res. Lett., 36,
L13812 https://doi.org/10.1029/2009GL038465, 2009. a
Hyder, P., Edwards, J. M., Allan, R. P., Hewitt, H. T., Bracegirdle, T. J.,
Gregory, J. M., Wood, R. A., Meijers, A. J. S., Mulcahy, J., Field, P.,
Furtado, K., Bodas-Salcedo, A., Williams, K. D., Copsey, D., Josey, S. A.,
Liu, C., Roberts, C. D., Sanchez, C., Ridley, J., Thorpe, L., Hardiman, S.
C., Mayer, M., Berry, D. I., and Belcher, S. E.: Critical Southern Ocean
climate model biases traced to atmospheric model cloud errors, Nat. Commun.,
9, 3625, https://doi.org/10.1038/s41467-018-05634-2, 2018. a
Hyvärinen, A.-P., Lihavainen, H., Komppula, M., Panwar, T. S., Sharma, V. P.,
Hooda, R. K., and Viisanen, Y.: Aerosol measurements at the Gual Pahari
EUCAARI station: preliminary results from in-situ measurements, Atmos. Chem.
Phys., 10, 7241–7252, https://doi.org/10.5194/acp-10-7241-2010, 2010. a
Illingworth, A. J., Hogan, R. J., O'Connor, E. J., Bouniol, D., Delanoë,
J., Pelon, J., Protat, A., Brooks, M. E., Gaussiat, N., Wilson, D. R.,
Donovan, D. P., Klein Baltink, H., van Zadelhoff, G.-J., Eastment, J. D.,
Goddard, J. W. F., Wrench, C. L., Haeffelin, M., Krasnov, O. A.,
Russchenberg, H. W. J., Piriou, J.-M., Vinit, F., Seifert, A., Tompkins,
A. M., and U, W.: Cloudnet-continuous evaluation of cloud profiles in seven
operational models using ground-based observations, B. Am. Meteorol.
Soc., 88, 883–898, https://doi.org/10.1175/BAMS-88-6-883, 2007. a
Inverarity, G. W., Wlasak, M. A., Jardak, M., and Lorenc, A. C.: Deterministic
data assimilation developments – July 2017, Tech. Rep. 625, Forecasting
Research, Met Office, Exeter, UK, 2018. a
IPCC: Climate Change 2013: The Physical Science Basis. Contribution of Working
Group I to the Fifth Assessment Report of the Intergovernmental Panel on
Climate Change, Cambridge University Press, Cambridge, United Kingdom and New
York, NY, USA, https://doi.org/10.1017/CBO9781107415324, 2013. a, b
Jeong, C.-H., Evans, G. J., McGuire, M. L., Chang, R. Y.-W., Abbatt, J. P.
D., Zeromskiene, K., Mozurkewich, M., Li, S.-M., and Leaitch, W. R.: Particle
formation and growth at five rural and urban sites, Atmos. Chem. Phys., 10,
7979–7995, https://doi.org/10.5194/acp-10-7979-2010, 2010. a
Jin, Z., Qiao, Y., Wang, Y., Fang, Y., and Yi, W.: A new parameterization of
spectral and broadband ocean surface albedo, Opt. Expres, 19,
26429–26443, https://doi.org/10.1364/OE.19.026429, 2011. a, b, c
Johansen, O.: Thermal conductivity of soils, Ph.D. thesis, University of
Trondheim, Norway, 1975. a
Kettle, A. J., Andreae, M. O., Amouroux, D., Andreae, T. W., Bates, T. S.,
Berresheim, H., Bingemer, H., Boniforti, R., Curran, M. A. J., DiTullio,
G. R., Helas, G., Jones, G. B., Keller, M. D., Kiene, R. P., Leck, C.,
Levasseur, M., Malin, G., Maspero, M., Matrai, P., McTaggart, A. R.,
Mihalopoulos, N., Nguyen, B. C., Novo, A., Putaud, J. P., Rapsomanikis, S.,
Roberts, G., Schebeske, G., Sharma, S., Simó, R., Staubes, R., Turner,
S., and Uher, G.: A global database of sea surface dimethyl sulfide (DMS)
measurements and a procedure to predict sea surface DMS as a function of
latitude, longitude, and month, Global Biogeochem. Cy., 13, 399–444,
https://doi.org/10.1029/1999GB900004, 1999. a, b
Khairoutdinov, M. and Kogan, Y.: A new cloud physics parameterization in a
large-eddy simulation model of marine stratocumulus, Mon. Weather Rev., 128,
229–243, https://doi.org/10.1175/1520-0493(2000)128<0229:ANCPPI>2.0.CO;2, 2000. a, b
Klein, S. A., McCoy, R. B., Morrison, H., Ackerman, A. S., Avramov, A., Boer,
G. d., Chen, M., Cole, J. N. S., Del Genio, A. D., Falk, M., Foster, M. J.,
Fridlind, A., Golaz, J.-C., Hashino, T., Harrington, J. Y., Hoose, C.,
Khairoutdinov, M. F., Larson, V. E., Liu, X., Luo, Y., McFarquhar, G. M.,
Menon, S., Neggers, R. A. J., Park, S., Poellot, M. R., Schmidt, J. M.,
Sednev, I., Shipway, B. J., Shupe, M. D., Spangenberg, D. A., Sud, Y. C.,
Turner, D. D., Veron, D. E., Salzen, K. v., Walker, G. K., Wang, Z., Wolf,
A. B., Xie, S., Xu, K.-M., Yang, F., and Zhang, G.: Intercomparison of model
simulations of mixed-phase clouds observed during the ARM mixed-phase
arctic cloud experiment. I: single-layer cloud, Q. J. Roy. Meteorol. Soc.,
135, 979–1002, https://doi.org/10.1002/qj.416, 2009. a
Lamarque, J.-F., Bond, T. C., Eyring, V., Granier, C., Heil, A., Klimont, Z.,
Lee, D., Liousse, C., Mieville, A., Owen, B., Schultz, M. G., Shindell, D.,
Smith, S. J., Stehfest, E., Van Aardenne, J., Cooper, O. R., Kainuma, M.,
Mahowald, N., McConnell, J. R., Naik, V., Riahi, K., and van Vuuren, D. P.:
Historical (1850–2000) gridded anthropogenic and biomass burning emissions
of reactive gases and aerosols: methodology and application, Atmos. Chem.
Phys., 10, 7017–7039, https://doi.org/10.5194/acp-10-7017-2010, 2010. a
Lana, A., Bell, T. G., Simó, R., Vallina, S. M., Ballabrera-Poy, J.,
Kettle, A. J., Dachs, J., Bopp, L., Saltzman, E. S., Stefels, J., Johnson,
J. E., and Liss, P. S.: An updated climatology of surface dimethlysulfide
concentrations and emission fluxes in the global ocean, Global Biogeochem.
Cy., 25, GB1004, https://doi.org/10.1029/2010GB003850, 2011. a
Leaitch, W. R., Sharma, S., Huang, L.,
Toom–Sauntry, D., Chivulescu, A., Macdonald,
A. M., von Salzen, K., Pierce, J. R.,
Bertram, A. K., Schroder, J. C., Shantz,
N. C., Chang, R. Y.-W., and Norman, A.-L.:
Dimethyl sulfide control of the clean summertime Arctic
aerosol and cloud, Elem. Sci. Anth., 1, 17,
https://doi.org/10.12952/journal.elementa.000017, 2013. a
Lean, J., Rottman, G., Harder, J., and Kopp, G.: SORCE Contributions to New
Understanding of Global Change and Solar Variability, in: The Solar Radiation
and Climate Experiment (SORCE): Mission Description and Early Results,
edited by: Rottman, G., Woods, T., and George, V., 27–53, Springer New
York, New York, NY, https://doi.org/10.1007/0-387-37625-9_3, 2005. a
Legates, D. R. and Willmott, C. J.: Mean seasonal and spatial variability in
global surface air temperature, Theor. Appl. Climatol., 41, 11–21,
https://doi.org/10.1007/BF00866198, 1990a. a
Legates, D. R. and Willmott, C. J.: Mean seasonal and spatial variability in
gauge-corrected, global precipitation, Int. J. Climatol., 10, 111–127,
https://doi.org/10.1002/joc.3370100202, 1990b. a
Lewis, E. R. and Teixeira, J.: Dispelling clouds of uncertainty, Eos, 96,
https://doi.org/10.1029/2015EO031303, 2015. a
Liu, Y., Daum, P. H., Guo, H., and Peng, Y.: Dispersion bias, dispersion
effect, and the aerosol-cloud conundrum, Environ. Res. Lett., 3, 045021,
https://doi.org/10.1088/1748-9326/3/4/045021, 2008. a
Lock, A. P.: The numerical representation of entrainment in parametrizations of
boundary layer turbulent mixing, Mon. Weather Rev., 129, 1148–1163,
https://doi.org/10.1175/1520-0493(2001)129<1148:TNROEI>2.0.CO;2, 2001. a
Lock, A. P., Brown, A. R., Bush, M. R., Martin, G. M., and Smith, R. N. B.: A
new boundary layer mixing scheme. Part I: Scheme description and
single-column model tests, Mon. Weather Rev., 128, 3187–3199,
https://doi.org/10.1175/1520-0493(2000)128<3187:ANBLMS>2.0.CO;2, 2000. a, b
Loeb, N. G., Wielicki, B. A., Doelling, D. R., Smith, G. L., Keyes, D. F.,
Kato, S., Manalo-Smith, N., and Wong, T.: Toward optimal closure of the
Earth's top-of-atmosphere radiation budget, J. Climate, 22, 748–766,
https://doi.org/10.1175/2008JCLI2637.1, 2009. a, b
Long, C. N. and McFarlane, S. A.: Quantification
of the Impact of Nauru Island on ARM Measurements, J. Appl.
Meteorol. Climatol., 51, 628–636, https://doi.org/10.1175/JAMC-D-11-0174.1, 2012. a
Lott, F. and Miller, M. J.: A new subgrid-scale orographic drag
parametrization: Its formulation and testing, Q. J. Roy. Meteorol. Soc., 123,
101–127, https://doi.org/10.1002/qj.49712353704, 1997. a
Loveland, T. R., Reed, B. C., Brown, J. F., Ohlen, D. O., Zhu, Z., Yang, L.,
and Merchant, J. W.: Development of a global land cover characteristics
database and IGBP DISCover from 1 km AVHRR data, Int. J. Remote Sens.,
21, 1303–1330, https://doi.org/10.1080/014311600210191, 2000. a, b, c
MacKay, M. D. and Bartlett, P. A.: Estimating canopy snow unloading timescales
from daily observations of albedo and preciptation, Geophys. Res. Lett., 33,
L19405, https://doi.org/10.1029/2006GL027521, 2006. a
MacLachlan, C., Arribas, A., Peterson, K. A., Maidens, A., Fereday, D., Scaife,
A. A., Gordon, M., Vellinga, M., Williams, A., Comer, R. E., Camp, J.,
Xavier, P., and Madec, G.: Global Seasonal forecast system version 5
(GloSea5): a high-resolution seasonal forecast system, Q. J. Roy. Meteorol.
Soc., 141, https://doi.org/10.1002/qj.2396, 2014. a
Madden, R. A. and Julian, P. R.: Detection of a 40–50 day oscillation in the
zonal wind in the tropical Pacific, J. Atmos. Sci., 28, 702–708,
https://doi.org/10.1175/1520-0469(1971)028<0702:DOADOI>2.0.CO;2, 1971. a
Malicet, J., Daumont, D., Charbonnier, J., Parisse, C., Chakir, A., and Brion,
J.: Ozone UV spectroscopy. II. Absorption cross-sections and temperature
dependence, J. Atmos. Chem., 21, 263–273, https://doi.org/10.1007/BF00696758, 1995. a
Mann, G. W., Carslaw, K. S., Spracklen, D. V., Ridley, D. A., Manktelow, P. T.,
Chipperfield, M. P., Pickering, S. J., and Johnson, C. E.: Description and
evaluation of GLOMAP-mode: a modal global aerosol microphysics model for
the UKCA composition-climate model, Geosci. Model Dev., 3, 519–551,
https://doi.org/10.5194/gmd-3-519-2010, 2010. a, b
Manners, J., Thelen, J.-C., Petch, J., Hill, P., and Edwards, J. M.: Two fast
radiative transfer methods to improve the temporal sampling of clouds in
numerical weather prediction and climate models, Q. J. Roy. Meteorol. Soc.,
135, 457–468, https://doi.org/10.1002/qj.956, 2009. a
Manners, J., Vosper, S. B., and Roberts, N.: Radiative transfer over resolved
topographic features for high-resolution weather prediction, Q. J. Roy.
Meteorol. Soc., 138, 720–733, https://doi.org/10.1002/qj.956, 2012. a
Manners, J., Edwards, J. M., Hill, P., and Thelen, J.-C.: SOCRATES (Suite Of
Community RAdiative Transfer codes based on Edwards and Slingo) Technical
Guide, Met Office, UK, available at: https://code.metoffice.gov.uk/trac/socrates
(last access: 25 October 2017), 2015. a
Maritorena, S., d'Andon, O. H. F., Mangin, A., and Siegel, D. A.: Merged
satellite ocean color data products using a bio-optical model:
characteristics, benefits and issues, Remote Sens. Environ., 114, 1791–1804,
https://doi.org/10.1016/j.rse.2010.04.002, 2010. a
Marshall, S. and Oglesby, R. J.: An improved snow hydrology for GCMs. Part 1:
snow cover fraction, albedo, grain size, and age, J. Climate, 10, 21–37,
https://doi.org/10.1007/BF00210334, 1994. a
Marthews, T. R., Dadson, S. J., Lehner, B., Abele, S., and Gedney, N.:
High-resolution global topographic index values, Dataset made available under
the terms of the Open Government Licence, available at:
https://catalogue.ceh.ac.uk/documents/6b0c4358-2bf3-4924-aa8f-793d468b92be
(last access: 25 October 2017), 2015. a
Martin, G. M., Johnson, D. W., and Spice, A.: The measurement and
parameterization of effective radius of droplets in warm stratocumulus
clouds, J. Atmos. Sci., 51, 1823–1942,
https://doi.org/10.1175/1520-0469(1994)051<1823:TMAPOE>2.0.CO;2, 1994. a
Maycock, A. C. and Shine, K. P.: Stratospheric water vapor and climate:
sensitivity to the representation in radiation codes, J. Geophys.
Res.-Atmos., 117, D13102, https://doi.org/10.1029/2012JD017484, 2012. a
McCabe, A. and Brown, A. R.: The role of surface heterogeneity in modelling the
stable boundary layer, Bound.-Lay. Meteorol., 122, 517–534,
https://doi.org/10.1007/s10546-006-9119-8, 2007. a
McNaughton, C. S., Clarke, A. D., Freitag, S., Kapustin, V. N., Kondo, Y.,
Moteki, N., Sahu, L., Takegawa, N., Schwarz, J. P., Spackman, J. R., Watts,
L., Diskin, G., Podolske, J., Holloway, J. S., Wisthaler, A., Mikoviny, T.,
de Gouw, J., Warneke, C., Jimenez, J., Cubison, M., Howell, S. G.,
Middlebrook, A., Bahreini, R., Anderson, B. E., Winstead, E., Thornhill, K.
L., Lack, D., Cozic, J., and Brock, C. A.: Absorbing aerosol in the
troposphere of the Western Arctic during the 2008 ARCTAS/ARCPAC airborne
field campaigns, Atmos. Chem. Phys., 11, 7561–7582,
https://doi.org/10.5194/acp-11-7561-2011, 2011. a
Mercado, L. M., Huntingford, C., Gash, J. H. C., Cox, P. M., and Jogireddy, V.:
Improving the representation of radiative interception and photosynthesis for
climate model applications, Tellus, B59, 553–565,
https://doi.org/10.1111/j.1600-0889.2007.00256.x, 2007. a
Miller, D. A. and White, R. A.: A conterminous United States multilayer soil
characteristics dataset for regional climate and hydrology modeling, Earth
Interact., 2, 1–26, https://doi.org/10.1175/1087-3562(1998)002<0001:ACUSMS>2.3.CO;2, 1998. a
Mlawer, E. J., Payne, V. H., Moncet, J.-L., Delamere, J. S., Alvarado, M. J.,
and Tobin, D. C.: Development and recent evaluation of the MT_CKD model of
continuum absorption, Philos. Trans. R. Soc. Lond. A, 370, 2520–2556,
https://doi.org/10.1098/rsta.2011.0295, 2012. a
Morcrette, C. J.: Improvements to a prognostic cloud scheme through changes to
its cloud erosion parametrization, Atmos. Sci. Let., 13, 95–102,
https://doi.org/10.1002/asl.374, 2012. a
Morgenstern, O., Braesicke, P., O'Connor, F. M., Bushell, A. C., Johnson,
C. E., Osprey, S. M., and Pyle, J. A.: Evaluation of the new UKCA
climate-composition model – Part 1: The stratosphere, Geosci. Model Dev.,
2, 43–57, https://doi.org/10.5194/gmd-2-43-2009, 2009. a
Mulcahy, J. P., Jones, C., Sellar, A., Johnson, B., Boutle, I. A., Jones, A.,
Andrews, T., Rumbold, S. T., Mollard, J., Bellouin, N., Johnson, C. E.,
Williams, K. D., Grosvenor, D. P., and McCoy, D. T.: Improved Aerosol
Processes and Effective Radiative Forcing in HadGEM3 and UKESM1,
JAMES, 10, 2786–2805, https://doi.org/10.1029/2018MS001464, 2018. a, b
Muller, J.-P., López, G., Watson, G., Shane, N., Kennedy, T., Yuen, P.,
Lewis, P., Fischer, J., Guanter, L., Domench, C., Preusker, R., North, P.,
Heckel, A., Danne, O., Krämer, U., Zühlke, M., Brockmann, C., and
Pinnock, S.: The ESA GlobAlbedo project for mapping the Earth's land
surface albedo for 15 years from European sensors, presented at IEEE
Geoscience and Remote Sensing Symposium (IGARSS) 2012, IEEE, Munich,
Germany, 22–27 July 2012,
available at: http://www.mssl.ucl.ac.uk/~pcy/papers/Muller-GlobAlbedo-abstractV4.pdf
(last access: 25 October 2017), 2012. a
Nachtergaele, F., van Velthuizen, H., Verelst, L., Batjes, N., Dijkshoorn, K.,
van Engelen, V., Fischer, G., Jones, A., Montanarella, L., Petri, M.,
Prieler, S., Teixeira, E., Wiberg, D., and Shi, X.: Harmonized World Soil
Database (version 1.0), FAO, Rome, Italy and IIASA, Laxenburg, Austria,
2008. a
Neggers, R. A. J., Ackerman, A. S., Angevine, W. M., Bazile, E., Beau, I.,
Blossey, P. N., Boutle, I. A., de Bruijn, C., Cheng, A., van der Dussen, J.,
Fletcher, J., Dal Gesso, S., Jam, A., Kawai, H., Cheedela, S. K., Larson, V.
E., Lefebvre, M.-P., Lock, A. P., Meyer, N. R., de Roode, S. R., de Rooy, W.,
Sandu, I., Xiao, H., and Xu, K.-M.: Single-Column Model Simulations of
Subtropical Marine Boundary-Layer Cloud Transitions Under Weakening
Inversions, JAMES, 9, 2385–2412, https://doi.org/10.1002/2017MS001064, 2017. a
Nicholls, S.: The dynamics of stratocumulus: Aircraft observations and
comparisons with a mixed layer model, Q. J. Roy. Meteorol. Soc., 110, 783–820,
https://doi.org/10.1002/qj.49711046603, 1984. a
O'Connor, F. M., Johnson, C. E., Morgenstern, O., Abraham, N. L., Braesicke,
P., Dalvi, M., Folberth, G. A., Sanderson, M. G., Telford, P. J.,
Voulgarakis, A., Young, P. J., Zeng, G., Collins, W. J., and Pyle, J. A.:
Evaluation of the new UKCA climate-composition model – Part 2: The
troposphere, Geosci. Model Dev., 7, 41–91, https://doi.org/10.5194/gmd-7-41-2014,
2014. a, b
Oki, T.: Validating the runoff from LSP-SVAT models using a global river
routing network by one degree mesh, in: AMS 13th Conference on
Hydrology, Long Beach, California, 2–7 February 1997, 319–322,
1997. a
Oki, T. and Sud, Y. C.: Design of Total Runoff Integrating Pathways (TRIP)
– A global river channel network, Earth Interact., 2, 1–36,
https://doi.org/10.1175/1087-3562(1998)002<0001:DOTRIP>2.3.CO;2, 1998. a, b
Oreopoulos, L. and Cahalan, R. F.: Cloud inhomogeneity from MODIS, J.
Climate, 18, 5110–5124, https://doi.org/10.1175/JCLI3591.1, 2005. a
Oreopoulos, L., Mlawer, E., Delamere, J., Shippert, T., Cole, J., Fomin, B.,
Iacono, M., Jin, Z., Li, J., Manners, J., Räisänen, P., Rose, F., Zhang,
Y., Wilson, M. J., and Rossow, W. B.: The continual intercomparison of
radiation codes: results from phase I, J. Geophys. Res.-Atmos., 117,
D06118, https://doi.org/10.1029/2011JD016821, 2012. a, b
Palmer, T. N., Buizza, R., Doblas-Reyes, F. J., Jung, T., Leutbecher, M.,
Shutts, G., Steinheimer, M., and A, A. W.: Stochastic parametrization and
model uncertainty, Tech. Rep. 1, ECMWF RD Technical Memorandum, ECMWF,
Reading, UK, 2009. a
Pearson, K. J., Lister, G. M. S., Birch, C. E., Allan, R. P., Hogan, R. J., and
Woolnough, S. J.: Modelling the diurnal cycle of tropical convection across
the “grey zone”, Q. J. Roy. Meteorol. Soc., 140, 491–499,
https://doi.org/10.1002/qj.2145, 2014. a
Pincus, R., Mlawer, E. J., Oreopoulos, L., Ackerman, A. S., Baek, S., Brath,
M., Buehler, S. A., Cady-Pereira, K. E., Cole, J. N. S., Dufresne, J.-L.,
Kelley, M., Li, J., Manners, J., Paynter, D. J., Roehrig, R., Sekiguchi, M.,
and Schwarzkopf, D. M.: Radiative flux and forcing parameterization error in
aerosol-free clear skies, Geophys. Res. Lett., 42, 5485–5492,
https://doi.org/10.1002/2015GL064291, 2015. a
Plant, R. S. and Craig, G. C.: A stochastic parameterization for deep
convection based on equilibrium statistics, J. Atmos. Sci., 65, 87–105,
https://doi.org/10.1175/2007JAS2263.1, 2008. a
Ptashnik, I. V., McPheat, R. A., Shine, K. P., Smith, K. M., and Williams,
R. G.: Water vapor self-continuum absorption in near-infrared windows derived
from laboratory measurements, J. Geophys. Res.-Atmos., 116, D16305,
https://doi.org/10.1029/2011JD015603, 2011. a
Ptashnik, I. V., McPheat, R. A., Shine, K. P., Smith, K. M., and Williams,
R. G.: Water vapour foreign-continuum absorption in near-infrared windows
from laboratory measurements, Philos. Trans. R. Soc. Lond. A, 370,
2557–2577, https://doi.org/10.1098/rsta.2011.0218, 2012. a
Quinn, P. K. and Bates, T. S.: Regional
aerosol properties: Comparisons of boundary layer
measurements from ACE 1, ACE 2, Aerosols99, INDOEX,
ACE Asia, TARFOX, and NEAQS, J. Geophys. Res., 110, D14202,
https://doi.org/10/1024/2004JD004755, 2005. a, b
Quinn, P. K., Bates, T. S., Schulz, K. S., Coffman, D. J., Frossard, A. A.,
Russell, L. M., Keene, W. C., and Kieber, D. J.:
Contribution of sea surface carbon pool to organic matter enrichment
in sea spray aerosol, Nat. Geosci., 7, 228–232, https://doi.org/10.1038/ngeo2092,
2014. a
Quinn, P. K., Bates, T. S., Coffman, D., Onasch, T. B., Worsnop, D.,
Baynard, T., de Gouw, J. A., Goldan, P. D., Kuster, W. C., Williams, E.,
Roberts, J. M., Lerner, B., Stohl, A., Pettersson, A., and Lovejoy, E. R.:
Impacts of sources and aging on submicrometer aerosol properties in the
marine boundary layer across the
Gulf of Maine, J. Geophys. Res., 111, D23S36, https://doi.org/10.1029/2006JD007582, 2006. a
Ramanathan, V., Crutzen, P. J., Lelieveld, J., Mitra, A. P., Althausen, D.,
Anderson, J., Andreae, M. O., Cantrell, W., Cass, G. R., Chung, C. E.,
Clarke, A. D., Coakley, J. A., Collins, W. D., Conant, W. C., Dulac, F.,
Heintzenberg, J., Heymsfield, A. J., Holben, B., Howell, S., Hudson, J.,
Jayaraman, A., Kiehl, J. T., Krishnamurti, T. N., Lubin, D.,
McFarquhar, G., Novakov, T., Ogren, J. A., Podgorny, I. A., Prather, K.,
Priestley, K., Prospero, J. M., Quinn, P. K., Rajeev, K., Rasch, P.,
Rupert, S., Sadourny, R., Satheesh, S. K., Shaw, G. E., Sheridan, P., and
Valero, F. P. J.: Indian Ocean Experiment: An integrated analysis of
the climate forcing and effects of the great Indo-Asian haze,
J. Geophys. Res.-Atmos., 106, 28371–28398, https://doi.org/10.1029/2001JD900133,
2001. a
Raper, J. L., Kleb, M. M., Jacob, D. J., Davis,
D. D., Newell, R. E., Fuelberg, H. E., Bendura,
R. J., Hoell, J. M., and McNeal, R. J.: Pacific
Exploratory Mission in the Tropical Pacific: PEM-Tropics B, March–April
1999, J. Geophys. Res.-Atmos. 106, 32401–32425, https://doi.org/10.1029/2000JD900833,
2001. a
Rashid, H. A. and Hirst, A. C.: Mechanisms of improved rainfall simulation over
the Maritime Continent due to increased horizontal resolution in an AGCM,
Clim. Dynam., 49, 1747–1764, https://doi.org/10.1007/s00382-016-3413-z, 2017. a
Rauber, R. M., Stevens, B., Ochs, H. T., Knight, C., Albrecht, B. A., Blyth,
A. M., Fairall, C. W., Jensen, J. B., Lasher-Trapp, S. G., Mayol-Bracero,
O. L., Vali, G., Anderson, J. R., Baker, B. A., Bandy, A. R., Burnet, E.,
Brenguier, J. L., Brewer, W. A., Brown, P. R. A., Chuang, P., Cotton, W. R.,
Di Girolamo, L., Geerts, B., Gerber, H., Goke, S., Gomes, L., Heikes, B. G.,
Hudson, J. G., Kollias, P., Lawson, R. P., Krueger, S. K., Lenschow, D. H.,
Nuijens, L., O'Sullivan, D. W., Rilling, R. A., Rogers, D. C., Siebesma,
A. P., Snodgrass, E., Stith, J. L., Thornton, D. C., Tucker, S., Twohy,
C. H., and Zuidema, P.: Rain in shallow cumulus over the ocean: the RICO
campaign, B. Am. Meteorol. Soc., 88, 1912–1928,
https://doi.org/10.1175/BAMS-88-12-1912, 2007. a
Reddington, C. L., Carslaw, K. S., Stier, P., Schutgens, N., Coe, H., Liu, D.,
Allan, J., Browse, J., Pringle, K. J., Lee, L. A., Yoshioka, M., Johnson,
J. S., Regayre, L. A., Spracklen, D. V., Mann, G. W., Clarke, A., Hermann,
M., Henning, S., Wex, H., Kristensen, T. B., Leaitch, W. R., Pöschl, U.,
Rose, D., Andreae, M. O., Schmale, J., Kondo, Y., Oshima, N., Schwarz, J. P.,
Nenes, A., Anderson, B., Roberts, G. C., Snider, J. R., Leck, C., Quinn,
P. K., Chi, X., Ding, A., Jimenez, J. L., and Zhang, Q.: The Global Aerosol
Synthesis and Science Project (GASSP): Measurements and modeling to reduce
uncertainty, B. Am. Meteorol. Soc., 98, 1857–1877,
https://doi.org/10.1175/BAMS-D-15-00317.1, 2017. a, b, c
Redelsperger, J.-L., Guichard, F., and Mondon, S.: A parametrization of
mesoscale enhancement of surface fluxes for large-scale models, J. Climate,
13, 402–421, https://doi.org/10.1175/1520-0442(2000)013<0402:APOMEO>2.0.CO;2,
2000. a
Rooney, G. G. and Jones, I. D.: Coupling the 1-D lake model FLake to the
community land-surface model JULES, Boreal Env. Res., 15, 501–512, 2010. a
Rothman, L. S., Gordon, I. E., Babikov, Y., Barbe, A., Chris Benner, D.,
Bernath, P. F., Birk, M., Bizzocchi, L., Boudon, V., Brown, L. R., Campargue,
A., Chance, K., Cohen, E. A., Coudert, L. H., Devi, V. M., Drouin, B. J.,
Fayt, A., Flaud, J.-M., Gamache, R. R., Harrison, J. J., Hartmann, J.-M.,
Hill, C., Hodges, J. T., Jacquemart, D., Jolly, A., Lamouroux, J., Le Roy,
R. J., Li, G., Long, D. A., Lyulin, O. M., Mackie, C. J., Massie, S. T.,
Mikhailenko, S., Müller, H. S. P., Naumenko, O. V., Nikitin, A. V.,
Orphal, J., Perevalov, V., Perrin, A., Polovtseva, E. R., Richard, C., Smith,
M. A. H., Starikova, E., Sung, K., Tashkun, S., Tennyson, J., Toon, G. C.,
Tyuterev, V. G., and Wagner, G.: The HITRAN2012 molecular spectroscopic
database, J. Quant. Spectrosc. Radiat. Transfer, 130, 4–50,
https://doi.org/10.1016/j.jqsrt.2013.07.002, 2013. a
Ryerson, T. B., Andrews, A. E., Angevine, W. M., Bates, T.
S., Brock, C. A., Cairns, B.,Cohen, R. C., Cooper, O. R., de
Gouw, J. A., Fehsenfeld, F. C., Ferrare, R. A., Fischer, M. L.,
Flagan, R. C., Goldstein, A. H., Hair, J. W., Hardesty, R. M.,
Hostetler, C. A., Jimenez, J. L., Langford, A. O., McCauley, E.,
McKeen, S. A., Molina, L. T., Nenes, A., Oltmans, S. J., Parrish,
D. D., Pederson, J. R., Pierce, R. B., Prather, K., Quinn, P. K., Seinfeld, J. H.,
Senff, C. J., Sorooshian, A., Stutz, J.,
Surratt, J. D., Trainer, M., Volkamer, R., Williams, E. J., and
Wofsy, S. C.: The 2010 California Research at the Nexus of air
quality and climate change (CalNex) field study, J. Geophys. Res.-Atmos.,
118, 5830–5866, https://doi.org/10.1002/jgrd.50331, 2013. a
Samanta, A., Ganguly, S., Schull, M. A., Shabanov, N. V., Knyazikhin, Y., and
Myneni, R. B.: Collection 5 MODIS LAI/FPAR Products, Presented at AGU Fall
Meeting, San Francisco, USA, 15–19 December, 2008,
2012. a
Sanchez, C., Williams, K. D., Shutts, G. J., McDonald, R. E., Hinton, T. J.,
Senior, C. A., and Wood, N.: Towards the development of a robust model
hierarchy: investigation of dynamical limitations at low resolution and
possible solutions, Q. J. Roy. Meteorol. Soc., 139, 75–84,
https://doi.org/10.1002/qj.1971, 2013. a
Sayer, A. M., Munchak, L. A., Hsu, N. C., Levy, R. C., Bettenhausen, C., and
M.-J., J.: MODIS Collection 6 aerosol products: Comparison between
Aqua's e-Deep Blue, Dark Target, and “merged” data sets, and usage
recommendations, J. Geophys. Res., 119, 13,965–13,989,
https://doi.org/10.1002/2014JD022453, 2014. a
Scaife, A. A., Butchart, N., Warner, C. D., and Swinbank, R.: Impact of a
spectral gravity wave parametrization on the stratosphere in the Met Office
Unified Model, J. Atmos. Sci., 59, 1473–1489,
https://doi.org/10.1175/1520-0469(2002)059<1473:IOASGW>2.0.CO;2, 2002. a
Schmidt, G. A., Bader, D., Donner, L. J., Elsaesser, G. S., Golaz, J.-C.,
Hannay, C., Molod, A., Neale, R. B., and Saha, S.: Practice and philosophy of
climate model tuning across six US modeling centers, Geosci. Model Dev., 10,
3207–3223, https://doi.org/10.5194/gmd-10-3207-2017, 2017. a
Schutgens, N., Tsyro, S., Gryspeerdt, E., Goto, D., Weigum, N., Schulz, M., and
Stier, P.: On the spatio-temporal representativeness of observations, Atmos.
Chem. Phys., 17, 9761–9780, https://doi.org/10.5194/acp-17-9761-2017, 2017. a
Sellers, P. J.: Canopy reflectance, photosynthesis and reflection, Int. J. Rem.
Sens., 6, 1335–1372, https://doi.org/10.1080/01431168508948283, 1985. a
Serdyuchenko, A., Gorshelev, V., Weber, M., Chehade, W., and Burrows, J. P.:
High spectral resolution ozone absorption cross-sections – Part 2:
temperature dependence, Atmos. Meas. Tech., 7, 625–636,
https://doi.org/10.5194/amt-7-625-2014, 2014. a
Shonk, J. K. P. and Hogan, R. J.: Effect of improving representation of
horizontal and vertical cloud structure on the Earth's radiation budget.
Part II: The global effects, Q. J. Roy. Meteorol. Soc., 136, 1205–1215,
https://doi.org/10.1002/qj.646, 2010. a
Slater, A. G., Lawrence, D. M., and Koven, C. D.: Process-level model
evaluation: A snow and heat transfer metric, The Cryosphere, 11, 989–996,
https://doi.org/10.5194/tc-11-989-2017, 2017. a
Slingo, J. M.: The development and verification of a cloud prediction scheme
for the ECMWF model, Q. J. Roy. Meteorol. Soc., 113, 899–927,
https://doi.org/10.1002/qj.49711347710, 1987. a
Smith, S. D.: Coefficients for sea surface wind stress, heat flux, and wind
profiles as a function of wind speed and temperature, J. Geophys. Res., 93,
15467–15472, https://doi.org/10.1029/JC093iC12p15467, 1988. a
Smith, R. N. B.: A scheme for predicting layer cloud and their water
content in a general circulation model, Q. J. Roy. Meteorol. Soc.,
116, 435–460, https://doi.org/10.1002/qj.49711649210, 1990. a
Soloviev, A. V., Lukas, R., Donelan, M. A., Haus, B. K., and Ginis, I.: The
air-sea interface and surface stress under tropical cyclones, Sci. Rep., 4,
5306, https://doi.org/10.1038/srep0536, 2014. a
Stephens, G. L., L'Ecuyer, T., Forbes, R., Gettlemen, A., Golaz, J.-C.,
Bodas-Salcedo, A., Suzuki, K., Gabriel, P., and Haynes, J.: Dreary state of
precipitation in global models, J. Geophys. Res., 115, D24211,
https://doi.org/10.1029/2010JD014532, 2010. a
Stirling, A. J. and Stratton, R. A.: Entrainment processes in the diurnal cycle
of deep convection over land, Q. J. Roy. Meteorol. Soc., 138, 1135–1149,
https://doi.org/10.1002/qj.1868, 2012. a
Stratton, R. A., Stirling, A., and Derbyshire, S.: Changes and developments to
Convective Momentum Transport (CMT) parametrization based on analysis of
CRM and SCM, Tech. Rep. 530, Forecsating R&D, Met Office, Exeter, UK,
2009. a
Suselj, K., Teixeira, J., and Matheou, G.: Eddy diffusivity/mass flux and
shallow cumulus boundary layer: an updraft PDF multiple mass flux scheme,
J. Atmos. Sci., 69, 1513–1533, https://doi.org/10.1175/JAS-D-11-090.1, 2012. a
Taillandier, A.-S., Domine, F., Simpson, W. R., Sturm, M., and Douglas, T. A.:
Rate of decrease of the specific surface area of dry snow: Isothermal and
temperature gradient conditions, J. Geophys. Res.-Earth Surf., 112, F03003,
https://doi.org/10.1029/2006JF000514, 2007. a
Takahama, S., Schwartz, R. E., Russell, L. M., Macdonald, A. M., Sharma, S.,
and Leaitch, W. R.: Organic functional groups in aerosol particles from
burning and non-burning forest emissions at a high-elevation mountain site,
Atmos. Chem. Phys., 11, 6367–6386, https://doi.org/10.5194/acp-11-6367-2011,
2011. a
Tennant, W. J., Shutts, G. J., Arribas, A., and Thompson, S. A.: Using a
stochastic kinetic energy backscatter scheme to improve MOGREPS
probabilistic forecast skill, Mon. Weather Rev., 139, 1190–1206,
https://doi.org/10.1175/2010MWR3430.1, 2011. a, b, c
Tiedtke, M.: Representation of clouds in large-scale models, Mon. Weather Rev.,
121, 3040–3061, https://doi.org/10.1175/1520-0493(1993)121<3040:ROCILS>2.0.CO;2,
1993. a
Tomassini, L., Parker, D. J., Stirling, A., Bain, C., Senior, C., and Milton,
S.: The interaction between moist diabatic processes and the atmospheric
circulation in African Easterly Wave propagation, Q. J. Roy. Meteorol. Soc.,
143, 3207–3227, https://doi.org/10.1002/qj.3173, 2017. a
Ujiie, M., Willet, M., Walters, D., Bushell, A., and Milton, S.: An improvement
to the melting of precipitation in the Met Office Unified Model's
convection scheme and its impact on the tropical performance, Tech. rep.,
Forecsating R&D, Met Office, Exeter, UK, 2017b. a
Untch, A. and Simmons, A. J.: Increased stratospheric resolution in the ECMWF
forecasting system, ECMWF Newsletter 82, ECMWF, Reading, UK, 1999. a
Uppala, S. M., Kållberg, P. W., Simmons, A. J., Andrae, U., V. Da Costa
Bechtold, Fiorino, M., Gibson, J. K., Haseler, J., Hernandez, A., Kelly,
G. A., Li, X., Onogi, K., Saarinen, S., Sokka, N., Allan, R. P., Andersson,
E., Arpe, K., Balmaseda, M. A., Beljaars, A. C. M., van de Berg, L., Bidlot,
J., Bormann, N., Caires, S., Chevallier, F., Dethof, A., Dragosavac, M.,
Fisher, M., Fuentes, M., Hagemann, S., Hólm, E., Hoskins, B. J., Isaksen,
L., Janssen, P. A. E. M., Jenne, R., Mcnally, A. P., Mahfouf, J.-F.,
Morcrette, J.-J., Rayner, N. A., Saunders, R. W., Simon, P., Sterl, A.,
Trenberth, K. E., Untch, A., Vasiljevic, D., Viterbo, P., and Woollen, J.:
The ERA-40 re-analysis, Q. J. Roy. Meteorol. Soc., 131, 2961–3012,
https://doi.org/10.1256/qj.04.176, 2005. a
Vakkari, V., Beukes, J. P., Laakso, H., Mabaso, D., Pienaar, J. J., Kulmala,
M., and Laakso, L.: Long-term observations of aerosol size distributions in
semi-clean and polluted savannah in South Africa, Atmos. Chem. Phys., 13,
1751–1770, https://doi.org/10.5194/acp-13-1751-2013, 2013. a
van der Werf, G. R., Randerson, J. T., Giglio, L., Collatz, G. J., Mu, M.,
Kasibhatla, P. S., Morton, D. C., DeFries, R. S., Jin, Y., and van Leeuwen,
T. T.: Global fire emissions and the contribution of deforestation, savanna,
forest, agricultural, and peat fires (1997–2009), Atmos. Chem. Phys., 10,
11707–11735, https://doi.org/10.5194/acp-10-11707-2010, 2010. a
van Genuchten, M. T.: A closed-form equation for predicting the hydraulic
conductivity of unsaturated soils, Soil Sci. Soc. Am. J., 44, 892–898,
https://doi.org/10.2136/sssaj1980.03615995004400050002x, 1980. a
Van Weverberg, K., Boutle, I. A., Morcrette, C. J., and Newsom, R. K.: Towards
retrieving critical relative humidity from ground-based remote-sensing
observations, Q. J. Roy. Meteorol. Soc., 142, 2867–2881,
https://doi.org/10.1002/qj.2874, 2016. a, b, c
Vionnet, V., Brun, E., Morin, S., Boone, A., Faroux, S., Moigne, P. L., Martin,
E., and Willemet, J.-M.: The detailed snowpack scheme Crocus and its
implementation in SURFEX v7.2, Geosci. Model Dev., 5, 773–791,
https://doi.org/10.5194/gmd-5-773-2012, 2012. a
Vosper, S. B.: Mountain waves and wakes generated by South Georgia:
implications for drag parametrization, Q. J. Roy. Meteorol. Soc., 141,
2813–2827, https://doi.org/10.1002/qj.2566, 2015. a
Walters, D., Boutle, I., Brooks, M., Melvin, T., Stratton, R., Vosper, S.,
Wells, H., Williams, K., Wood, N., Allen, T., Bushell, A., Copsey, D.,
Earnshaw, P., Edwards, J., Gross, M., Hardiman, S., Harris, C., Heming, J.,
Klingaman, N., Levine, R., Manners, J., Martin, G., Milton, S., Mittermaier,
M., Morcrette, C., Riddick, T., Roberts, M., Sanchez, C., Selwood, P.,
Stirling, A., Smith, C., Suri, D., Tennant, W., Vidale, P. L., Wilkinson, J.,
Willett, M., Woolnough, S., and Xavier, P.: The Met Office Unified Model
Global Atmosphere 6.0/6.1 and JULES Global Land 6.0/6.1 configurations,
Geosci. Model Dev., 10, 1487–1520, https://doi.org/10.5194/gmd-10-1487-2017, 2017. a, b, c, d, e, f, g, h, i
Walters, D. N., Best, M. J., Bushell, A. C., Copsey, D., Edwards, J. M.,
Falloon, P. D., Harris, C. M., Lock, A. P., Manners, J. C., Morcrette, C. J.,
Roberts, M. J., Stratton, R. A., S. Webster, J. M. W., Willett, M. R.,
Boutle, I. A., Earnshaw, P. D., Hill, P. G., MacLachlan, C., Martin, G. M.,
Moufouma-Okia, W., Palmer, M. D., Petch, J. C., Rooney, G. G., Scaife, A. A.,
and Williams, K. D.: The Met Office Unified Model Global Atmosphere 3.0/3.1
and JULES Global Land 3.0/3.1 configurations, Geosci. Model Dev., 4,
919–941, https://doi.org/10.5194/gmd-4-919-2011, 2011. a, b, c, d
Walters, D. N., Williams, K. D., Boutle, I. A., Bushell, A. C., Edwards, J. M.,
Field, P. R., Lock, A. P., Morcrette, C. J., Stratton, R. A., Wilkinson,
J. M., Willett, M. R., Bellouin, N., Bodas-Salcedo, A., Brooks, M. E.,
Copsey, D., Earnshaw, P. D., Harris, C. M., Levine, R. C., MacLachlan, C.,
Manners, J. C., Martin, G. M., Milton, S. F., Palmer, M. D., Roberts, M. J.,
Rodríguez, J. M., Tennant, W. J., and Vidale, P.: The Met Office Unified
Model Global Atmosphere 4.0 and JULES Global Land 4.0 configurations,
Geosci. Model Dev., 7, 361–386, https://doi.org/10.5194/gmd-7-361-2014, 2014. a
Wang, W., Rood, M. J., Carrico,
C. M., Covert, D. S., Quinn, P. K., and Bates, T.
S.: Aerosol optical properties along the northeast coast of North
America during the New England Air Quality Study – Intercontinental
Transport and Chemical Transformation 2004 campaign and the influence of
aerosol composition, J. Geophys. Res.-Atmos., 112, D10, https://doi.org/10.1029/2006JD007579,
2007. a
Warner, C. D. and McIntyre, M. E.: An ultrasimple spectral parametrization
for nonorographic gravity waves, J. Atmos. Sci., 58, 1837–1857,
https://doi.org/10.1175/1520-0469(2001)058<1837:AUSPFN>2.0.CO;2, 2001. a
Weisheimer, A., Palmer, T. N., and Doblas-Reyes, F. J.: Assessment of
representations of model uncertainty in monthly and seasonal forecast
ensembles, Geophys. Res. Lett., 38, L16703, https://doi.org/10.1029/2011GL048123,
2011. a
Weisheimer, A., Cortia, S., Palmer, T., and Vitart, F.: Addressing model error
through atmospheric stochastic physical parametrizations: impact on the
coupled ECMWF seasonal forecasting system, Philos. Trans. R. Soc. Lond. A,
372, 20130290, https://doi.org/10.1098/rsta.2013.0290, 2014. a, b
Wentz, F. J. and Spencer, R. W.: SSM/I rain retrievals within a unified
all-weather ocean algorithm, J. Atmos. Sci., 55, 1613–1627,
https://doi.org/10.1175/1520-0469(1998)055<1613:SIRRWA>2.0.CO;2, note: SSM/I data
are produced by Remote Sensing Systems and sponsored by the NASA Earth
Science MEaSUREs DISCOVER Project, available at: http://www.remss.com (last
access: 25 October 2017), 1998. a
West, R. E. L., Stier, P., Jones, A., Johnson, C. E., Mann, G. W., Bellouin,
N., Partridge, D. G., and Kipling, Z.: The importance of vertical velocity
variability for estimates of the in direct aerosol effects, Atmos. Chem.
Phys., 14, 6369–6393, https://doi.org/10.5194/acp-14-6369-2014, 2014. a, b, c
Williams, K. D. and Bodas-Salcedo, A.: A multi-diagnostic approach to cloud
evaluation, Geosci. Model Dev., 10, 2547–2566,
https://doi.org/10.5194/gmd-10-2547-2017, 2017. a, b
Williams, K. D., Bodas-Salcedo, A., Déqué, M., Fermepin, S., Medeiros, B.,
Watanabe, M., Jakob, C., Klein, S. A., Senior, C. A., and Williamson, D. L.:
The transpose-AMIP ii experiment and its application to the understanding
of Southern Ocean cloud biases in climate models, J. Climate, 26,
3258–3274, https://doi.org/10.1175/JCLI-D-12-00429.1, 2013. a
Williams, K. D., Copsey, D., Blockley, E. W., Bodas-Salcedo, A., Calvert, D.,
Comer, R., Davis, P., Graham, T., Hewitt, H. T., Hill, R., Hyder, P., Ineson,
S., Johns, T. C., Keen, A. B., Lee, R. W., Megann, A., Milton, S. F., Rae, J.
G. L., Roberts, M. J., Scaife, A. A., Schiemann, R., Storkey, D., Thorpe, L.,
Watterson, I. G., Walters, D. N., West, A., Wood, R. A., Woollings, T., and
Xavier, P. K.: The Met Office Global Coupled model 3.0 and 3.1 (GC3.0 and
GC3.1) configurations, JAMES, 10, 357–380,
https://doi.org/10.1002/2017MS001115, 2018. a, b, c
Wilson, D. R. and Ballard, S. P.: A microphysically based precipitation scheme
for the UK Meteorological Office Unified Model, Q. J. Roy. Meteorol. Soc.,
125, 1607–1636, https://doi.org/10.1002/qj.49712555707, 1999. a
Wilson, D. R., Bushell, A. C., Kerr-Munslow, A. M., Price, J. D., and
Morcrette, C. J.: PC2: A prognostic cloud fraction and condensation scheme.
I: Scheme description, Q. J. Roy. Meteorol. Soc., 134, 2093–2107,
https://doi.org/10.1002/qj.333, 2008a. a, b, c
Wilson, D. R., Bushell, A. C., Kerr-Munslow, A. M., Price, J. D., Morcrette,
C. J., and Bodas-Salcedo, A.: PC2: A prognostic cloud fraction and
condensation scheme. II: Climate model simulations, Q. J. Roy. Meteorol. Soc.,
134, 2109–2125, https://doi.org/10.1002/qj.332, 2008b. a
Wlasak, M. A. and Cullen, M. J. P.: Modelling static 3-D spatial background
error covariances – the effect of vertical and horizontal transform order,
Adv. Sci. Res., 11, 63–67, https://doi.org/10.5194/asr-11-63-2014, 2014. a
Wood, N. and Mason, P. J.: The pressure force induced by neutral, turbulent
flow over hills, Q. J. Roy. Meteorol. Soc., 127, 759–777,
https://doi.org/10.1002/qj.49711951402, 1993. a
Wood, N., Diamantakis, M., and Staniforth, A.: A monotonically-damping
second-order-accurate unconditionally-stable numerical scheme for diffusion,
Q. J. Roy. Meteorol. Soc., 133, 1559–1573, https://doi.org/10.1002/qj.116, 2007. a
Wood, N., Staniforth, A., White, A., Allen, T., Diamantakis, M., Gross, M.,
Melvin, T., Smith, C., Vosper, S., Zerroukat, M., and Thuburn, J.: An
inherently mass-conserving semi-implicit semi-Lagrangian discretization of
the deep-atmosphere global non-hydrostatic equations, Q. J. Roy. Meteorol.
Soc., 140, 1505–1520, https://doi.org/10.1002/qj.2235, 2014. a, b
Wood, R., Mechoso, C. R., Bretherton, C. S., Weller, R. A., Huebert, B.,
Straneo, F., Albrecht, B. A., Coe, H., Allen, G., Vaughan, G., Daum, P.,
Fairall, C., Chand, D., Gallardo Klenner, L., Garreaud, R., Grados, C.,
Covert, D. S., Bates, T. S., Krejci, R., Russell, L. M., de Szoeke, S.,
Brewer, A., Yuter, S. E., Springston, S. R., Chaigneau, A., Toniazzo, T.,
Minnis, P., Palikonda, R., Abel, S. J., Brown, W. O. J., Williams, S.,
Fochesatto, J., Brioude, J., and Bower, K. N.: The VAMOS
Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx): goals,
platforms, and field operations, Atmos. Chem. Phys., 11, 627–654,
https://doi.org/10.5194/acp-11-627-2011, 2011. a, b
Xie, P. and Arkin, P. A.: Global precipitation: A 17-year monthly analysis
based on gauge observations, satellite estimates, and numerical model
outputs, B. Am. Meteorol. Soc., 78, 2539–2558,
https://doi.org/10.1175/1520-0477(1997)078<2539:GPAYMA>2.0.CO;2, 1997. a
Yen, Y.-C.: Review of the thermal properties of snow, ice and sea ice, Tech.
Rep. 81-10, Cold Regions Research and Engineering Laboratory, Hanover, NH,
1981. a
Zerroukat, M.: A simple mass conserving semi-Lagrangian scheme for transport
problems, J. Comput. Phys., 229,
9011–9019, https://doi.org/10.1016/j.jcp.2010.08.017, 2010. a
Zerroukat, M. and Allen, T.: On the monotonic and conservative transport on
overset/Yin-Yang grids, J. Comput. Phys., 302, 285–299,
https://doi.org/10.1016/j.jcp.2015.09.006, 2015. a
Zhang, Y. and Klein, S. A.: Factors controlling the vertical extent of
fair-weather shallow cumulus clouds over land: investigation of diurnal-cycle
observations collected at the ARM Southern Great Plains site, J. Atmos.
Sci., 70, 1297–1315, https://doi.org/10.1175/JAS-D-12-0131.1, 2013. a, b
Zhong, W. and Haigh, J. D.: An efficient and accurate correlated-k
parameterization of infrared radiative transfer for
troposphere–stratosphere–mesosphere GCMs, Atmos. Sci. Lett., 1, 125–135,
https://doi.org/10.1006/asle.2000.0022, 2000. a
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Short summary
Global Atmosphere (GA) configurations of the Unified Model (UM) and Global Land (GL) configurations of JULES are developed for use in any global atmospheric modelling application. We describe a recent iteration of these configurations, GA7/GL7, which includes new aerosol and snow schemes and addresses the four critical errors identified in GA6. GA7/GL7 will underpin the UK's contributions to CMIP6, and hence their documentation is important.
Global Atmosphere (GA) configurations of the Unified Model (UM) and Global Land (GL)...
