Articles | Volume 12, issue 4
https://doi.org/10.5194/gmd-12-1703-2019
© 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-12-1703-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
29 Apr 2019
Model evaluation paper |
| 29 Apr 2019
| 29 Apr 2019
Evaluating the Met Office Unified Model land surface temperature in Global Atmosphere/Land 3.1 (GA/L3.1), Global Atmosphere/Land 6.1 (GA/L6.1) and limited area 2.2 km configurations
Jennifer K. Brooke
CORRESPONDING AUTHOR
Met Office, Fitzroy Road, Exeter, EX1 3PB, UK
R. Chawn Harlow
Met Office, Fitzroy Road, Exeter, EX1 3PB, UK
Russell L. Scott
Southwest Watershed Research Center, USDA-ARS, 2000 E. Allen Road,
Tucson, AZ 85719, USA
Martin J. Best
Met Office, Fitzroy Road, Exeter, EX1 3PB, UK
John M. Edwards
Met Office, Fitzroy Road, Exeter, EX1 3PB, UK
Jean-Claude Thelen
Met Office, Fitzroy Road, Exeter, EX1 3PB, UK
Mark Weeks
Met Office, Fitzroy Road, Exeter, EX1 3PB, UK
Related authors
Martin Richard Willett, Melissa Brooks, Andrew Bushell, Paul Earnshaw, Samantha Smith, Lorenzo Tomassini, Martin Best, Ian Boutle, Jennifer Brooke, John M. Edwards, Kalli Furtado, Catherine Hardacre, Andrew J. Hartley, Alan Hewitt, Ben Johnson, Adrian Lock, Andy Malcolm, Jane Mulcahy, Eike Müller, Heather Rumbold, Gabriel G. Rooney, Alistair Sellar, Masashi Ujiie, Annelize van Niekerk, Andy Wiltshire, and Michael Whitall
EGUsphere, https://doi.org/10.5194/egusphere-2025-1829, https://doi.org/10.5194/egusphere-2025-1829, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
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, GA8GL9, which includes improvements to the represenation of convection and other physical processes. GA8GL9 is used for operational weather prediction in the UK and forms the basis for the next GA and GL configuration.
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
Short summary
Short summary
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.
Alban Philibert, Marie Lothon, Julien Amestoy, Pierre-Yves Meslin, Solène Derrien, Yannick Bezombes, Bernard Campistron, Fabienne Lohou, Antoine Vial, Guylaine Canut-Rocafort, Joachim Reuder, and Jennifer K. Brooke
Atmos. Meas. Tech., 17, 1679–1701, https://doi.org/10.5194/amt-17-1679-2024, https://doi.org/10.5194/amt-17-1679-2024, 2024
Short summary
Short summary
We present a new algorithm, CALOTRITON, for the retrieval of the convective boundary layer depth with ultra-high-frequency radar measurements. CALOTRITON is partly based on the principle that the top of the convective boundary layer is associated with an inversion and a decrease in turbulence. It is evaluated using ceilometer and radiosonde data. It is able to qualify the complexity of the vertical structure of the low troposphere and detect internal or residual layers.
Franco Marenco, Claire Ryder, Victor Estellés, Debbie O'Sullivan, Jennifer Brooke, Luke Orgill, Gary Lloyd, and Martin Gallagher
Atmos. Chem. Phys., 18, 17655–17668, https://doi.org/10.5194/acp-18-17655-2018, https://doi.org/10.5194/acp-18-17655-2018, 2018
Short summary
Short summary
The AER-D airborne campaign characterised Saharan dust in the eastern Atlantic. We report an instance of unusual vertical structure of the Saharan Air Layer during an intense event, showing a large radiative impact and correlated with anomalous lightning activity. Moreover, we report a significant presence of giant dust particles. This is important because most models would miss the giant particles. Our findings may change the way we represent dust transport and deposition in the Atlantic.
Claire L. Ryder, Franco Marenco, Jennifer K. Brooke, Victor Estelles, Richard Cotton, Paola Formenti, James B. McQuaid, Hannah C. Price, Dantong Liu, Patrick Ausset, Phil D. Rosenberg, Jonathan W. Taylor, Tom Choularton, Keith Bower, Hugh Coe, Martin Gallagher, Jonathan Crosier, Gary Lloyd, Eleanor J. Highwood, and Benjamin J. Murray
Atmos. Chem. Phys., 18, 17225–17257, https://doi.org/10.5194/acp-18-17225-2018, https://doi.org/10.5194/acp-18-17225-2018, 2018
Short summary
Short summary
Every year, millions of tons of Saharan dust particles are carried across the Atlantic by the wind, where they can affect weather patterns and climate. Their sizes span orders of magnitude, but the largest (over 10 microns – around the width of a human hair) are difficult to measure and few observations exist. Here we show new aircraft observations of large dust particles, finding more than we would expect, and we quantify their properties which allow them to interact with atmospheric radiation.
Dantong Liu, Jonathan W. Taylor, Jonathan Crosier, Nicholas Marsden, Keith N. Bower, Gary Lloyd, Claire L. Ryder, Jennifer K. Brooke, Richard Cotton, Franco Marenco, Alan Blyth, Zhiqiang Cui, Victor Estelles, Martin Gallagher, Hugh Coe, and Tom W. Choularton
Atmos. Chem. Phys., 18, 3817–3838, https://doi.org/10.5194/acp-18-3817-2018, https://doi.org/10.5194/acp-18-3817-2018, 2018
Short summary
Short summary
This article presents measurements of aerosol properties off the coast of west Africa during August 2015. For the first time, an airborne laser-induced incandescence instrument was deployed to measure the hematite content of dust. The single scattering albedo of dust was found to be influenced by the hematite content, but depended on the dust source and potential dust age. This highlights the importance of size-dependent composition in determining the optical properties of dust.
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
Short summary
Short summary
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.
C. L. Ryder, J. B. McQuaid, C. Flamant, P. D. Rosenberg, R. Washington, H. E. Brindley, E. J. Highwood, J. H. Marsham, D. J. Parker, M. C. Todd, J. R. Banks, J. K. Brooke, S. Engelstaedter, V. Estelles, P. Formenti, L. Garcia-Carreras, C. Kocha, F. Marenco, H. Sodemann, C. J. T. Allen, A. Bourdon, M. Bart, C. Cavazos-Guerra, S. Chevaillier, J. Crosier, E. Darbyshire, A. R. Dean, J. R. Dorsey, J. Kent, D. O'Sullivan, K. Schepanski, K. Szpek, J. Trembath, and A. Woolley
Atmos. Chem. Phys., 15, 8479–8520, https://doi.org/10.5194/acp-15-8479-2015, https://doi.org/10.5194/acp-15-8479-2015, 2015
Short summary
Short summary
Measurements of the Saharan atmosphere and of atmospheric mineral dust are lacking but are vital to our understanding of the climate of this region and their impacts further afield. Novel observations were made by the Fennec climate programme during June 2011 and 2012 using ground-based, remote sensing and airborne platforms. Here we describe the airborne observations and the contributions they have made to furthering our understanding of the Saharan climate system.
Martin Richard Willett, Melissa Brooks, Andrew Bushell, Paul Earnshaw, Samantha Smith, Lorenzo Tomassini, Martin Best, Ian Boutle, Jennifer Brooke, John M. Edwards, Kalli Furtado, Catherine Hardacre, Andrew J. Hartley, Alan Hewitt, Ben Johnson, Adrian Lock, Andy Malcolm, Jane Mulcahy, Eike Müller, Heather Rumbold, Gabriel G. Rooney, Alistair Sellar, Masashi Ujiie, Annelize van Niekerk, Andy Wiltshire, and Michael Whitall
EGUsphere, https://doi.org/10.5194/egusphere-2025-1829, https://doi.org/10.5194/egusphere-2025-1829, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
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, GA8GL9, which includes improvements to the represenation of convection and other physical processes. GA8GL9 is used for operational weather prediction in the UK and forms the basis for the next GA and GL configuration.
Gab Abramowitz, Anna Ukkola, Sanaa Hobeichi, Jon Cranko Page, Mathew Lipson, Martin G. De Kauwe, Samuel Green, Claire Brenner, Jonathan Frame, Grey Nearing, Martyn Clark, Martin Best, Peter Anthoni, Gabriele Arduini, Souhail Boussetta, Silvia Caldararu, Kyeungwoo Cho, Matthias Cuntz, David Fairbairn, Craig R. Ferguson, Hyungjun Kim, Yeonjoo Kim, Jürgen Knauer, David Lawrence, Xiangzhong Luo, Sergey Malyshev, Tomoko Nitta, Jerome Ogee, Keith Oleson, Catherine Ottlé, Phillipe Peylin, Patricia de Rosnay, Heather Rumbold, Bob Su, Nicolas Vuichard, Anthony P. Walker, Xiaoni Wang-Faivre, Yunfei Wang, and Yijian Zeng
Biogeosciences, 21, 5517–5538, https://doi.org/10.5194/bg-21-5517-2024, https://doi.org/10.5194/bg-21-5517-2024, 2024
Short summary
Short summary
This paper evaluates land models – computer-based models that simulate ecosystem dynamics; land carbon, water, and energy cycles; and the role of land in the climate system. It uses machine learning and AI approaches to show that, despite the complexity of land models, they do not perform nearly as well as they could given the amount of information they are provided with about the prediction problem.
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
Short summary
Short summary
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.
Jacob A. Nelson, Sophia Walther, Fabian Gans, Basil Kraft, Ulrich Weber, Kimberly Novick, Nina Buchmann, Mirco Migliavacca, Georg Wohlfahrt, Ladislav Šigut, Andreas Ibrom, Dario Papale, Mathias Göckede, Gregory Duveiller, Alexander Knohl, Lukas Hörtnagl, Russell L. Scott, Jiří Dušek, Weijie Zhang, Zayd Mahmoud Hamdi, Markus Reichstein, Sergio Aranda-Barranco, Jonas Ardö, Maarten Op de Beeck, Dave Billesbach, David Bowling, Rosvel Bracho, Christian Brümmer, Gustau Camps-Valls, Shiping Chen, Jamie Rose Cleverly, Ankur Desai, Gang Dong, Tarek S. El-Madany, Eugenie Susanne Euskirchen, Iris Feigenwinter, Marta Galvagno, Giacomo A. Gerosa, Bert Gielen, Ignacio Goded, Sarah Goslee, Christopher Michael Gough, Bernard Heinesch, Kazuhito Ichii, Marcin Antoni Jackowicz-Korczynski, Anne Klosterhalfen, Sara Knox, Hideki Kobayashi, Kukka-Maaria Kohonen, Mika Korkiakoski, Ivan Mammarella, Mana Gharun, Riccardo Marzuoli, Roser Matamala, Stefan Metzger, Leonardo Montagnani, Giacomo Nicolini, Thomas O'Halloran, Jean-Marc Ourcival, Matthias Peichl, Elise Pendall, Borja Ruiz Reverter, Marilyn Roland, Simone Sabbatini, Torsten Sachs, Marius Schmidt, Christopher R. Schwalm, Ankit Shekhar, Richard Silberstein, Maria Lucia Silveira, Donatella Spano, Torbern Tagesson, Gianluca Tramontana, Carlo Trotta, Fabio Turco, Timo Vesala, Caroline Vincke, Domenico Vitale, Enrique R. Vivoni, Yi Wang, William Woodgate, Enrico A. Yepez, Junhui Zhang, Donatella Zona, and Martin Jung
Biogeosciences, 21, 5079–5115, https://doi.org/10.5194/bg-21-5079-2024, https://doi.org/10.5194/bg-21-5079-2024, 2024
Short summary
Short summary
The movement of water, carbon, and energy from the Earth's surface to the atmosphere, or flux, is an important process to understand because it impacts our lives. Here, we outline a method called FLUXCOM-X to estimate global water and CO2 fluxes based on direct measurements from sites around the world. We go on to demonstrate how these new estimates of net CO2 uptake/loss, gross CO2 uptake, total water evaporation, and transpiration from plants compare to previous and independent estimates.
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
Short summary
Short summary
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.
Alban Philibert, Marie Lothon, Julien Amestoy, Pierre-Yves Meslin, Solène Derrien, Yannick Bezombes, Bernard Campistron, Fabienne Lohou, Antoine Vial, Guylaine Canut-Rocafort, Joachim Reuder, and Jennifer K. Brooke
Atmos. Meas. Tech., 17, 1679–1701, https://doi.org/10.5194/amt-17-1679-2024, https://doi.org/10.5194/amt-17-1679-2024, 2024
Short summary
Short summary
We present a new algorithm, CALOTRITON, for the retrieval of the convective boundary layer depth with ultra-high-frequency radar measurements. CALOTRITON is partly based on the principle that the top of the convective boundary layer is associated with an inversion and a decrease in turbulence. It is evaluated using ceilometer and radiosonde data. It is able to qualify the complexity of the vertical structure of the low troposphere and detect internal or residual layers.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Matthew P. Dannenberg, Mallory L. Barnes, William K. Smith, Miriam R. Johnston, Susan K. Meerdink, Xian Wang, Russell L. Scott, and Joel A. Biederman
Biogeosciences, 20, 383–404, https://doi.org/10.5194/bg-20-383-2023, https://doi.org/10.5194/bg-20-383-2023, 2023
Short summary
Short summary
Earth's drylands provide ecosystem services to many people and will likely be strongly affected by climate change, but it is quite challenging to monitor the productivity and water use of dryland plants with satellites. We developed and tested an approach for estimating dryland vegetation activity using machine learning to combine information from multiple satellite sensors. Our approach excelled at estimating photosynthesis and water use largely due to the inclusion of satellite soil moisture.
Mathew Lipson, Sue Grimmond, Martin Best, Winston T. L. Chow, Andreas Christen, Nektarios Chrysoulakis, Andrew Coutts, Ben Crawford, Stevan Earl, Jonathan Evans, Krzysztof Fortuniak, Bert G. Heusinkveld, Je-Woo Hong, Jinkyu Hong, Leena Järvi, Sungsoo Jo, Yeon-Hee Kim, Simone Kotthaus, Keunmin Lee, Valéry Masson, Joseph P. McFadden, Oliver Michels, Wlodzimierz Pawlak, Matthias Roth, Hirofumi Sugawara, Nigel Tapper, Erik Velasco, and Helen Claire Ward
Earth Syst. Sci. Data, 14, 5157–5178, https://doi.org/10.5194/essd-14-5157-2022, https://doi.org/10.5194/essd-14-5157-2022, 2022
Short summary
Short summary
We describe a new openly accessible collection of atmospheric observations from 20 cities around the world, capturing 50 site years. The observations capture local meteorology (temperature, humidity, wind, etc.) and the energy fluxes between the land and atmosphere (e.g. radiation and sensible and latent heat fluxes). These observations can be used to improve our understanding of urban climate processes and to test the accuracy of urban climate models.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Natasha MacBean, Russell L. Scott, Joel A. Biederman, Catherine Ottlé, Nicolas Vuichard, Agnès Ducharne, Thomas Kolb, Sabina Dore, Marcy Litvak, and David J. P. Moore
Hydrol. Earth Syst. Sci., 24, 5203–5230, https://doi.org/10.5194/hess-24-5203-2020, https://doi.org/10.5194/hess-24-5203-2020, 2020
Richard J. Bantges, Helen E. Brindley, Jonathan E. Murray, Alan E. Last, Jacqueline E. Russell, Cathryn Fox, Stuart Fox, Chawn Harlow, Sebastian J. O'Shea, Keith N. Bower, Bryan A. Baum, Ping Yang, Hilke Oetjen, and Juliet C. Pickering
Atmos. Chem. Phys., 20, 12889–12903, https://doi.org/10.5194/acp-20-12889-2020, https://doi.org/10.5194/acp-20-12889-2020, 2020
Short summary
Short summary
Understanding how ice clouds influence the Earth's energy balance remains a key challenge for predicting the future climate. These clouds are ubiquitous and are composed of ice crystals that have complex shapes that are incredibly difficult to model. This work exploits new measurements of the Earth's emitted thermal energy made from instruments flown on board an aircraft to test how well the latest ice cloud models can represent these clouds. Results indicate further developments are required.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Paul C. Stoy, Tarek S. El-Madany, Joshua B. Fisher, Pierre Gentine, Tobias Gerken, Stephen P. Good, Anne Klosterhalfen, Shuguang Liu, Diego G. Miralles, Oscar Perez-Priego, Angela J. Rigden, Todd H. Skaggs, Georg Wohlfahrt, Ray G. Anderson, A. Miriam J. Coenders-Gerrits, Martin Jung, Wouter H. Maes, Ivan Mammarella, Matthias Mauder, Mirco Migliavacca, Jacob A. Nelson, Rafael Poyatos, Markus Reichstein, Russell L. Scott, and Sebastian Wolf
Biogeosciences, 16, 3747–3775, https://doi.org/10.5194/bg-16-3747-2019, https://doi.org/10.5194/bg-16-3747-2019, 2019
Short summary
Short summary
Key findings are the nearly optimal response of T to atmospheric water vapor pressure deficits across methods and scales. Additionally, the notion that T / ET intermittently approaches 1, which is a basis for many partitioning methods, does not hold for certain methods and ecosystems. To better constrain estimates of E and T from combined ET measurements, we propose a combination of independent measurement techniques to better constrain E and T at the ecosystem scale.
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
Short summary
Short summary
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
Short summary
Short summary
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.
David Walters, Anthony J. Baran, Ian Boutle, Malcolm Brooks, Paul Earnshaw, John Edwards, Kalli Furtado, Peter Hill, Adrian Lock, James Manners, Cyril Morcrette, Jane Mulcahy, Claudio Sanchez, Chris Smith, Rachel Stratton, Warren Tennant, Lorenzo Tomassini, Kwinten Van Weverberg, Simon Vosper, Martin Willett, Jo Browse, Andrew Bushell, Kenneth Carslaw, Mohit Dalvi, Richard Essery, Nicola Gedney, Steven Hardiman, Ben Johnson, Colin Johnson, Andy Jones, Colin Jones, Graham Mann, Sean Milton, Heather Rumbold, Alistair Sellar, Masashi Ujiie, Michael Whitall, Keith Williams, and Mohamed Zerroukat
Geosci. Model Dev., 12, 1909–1963, https://doi.org/10.5194/gmd-12-1909-2019, https://doi.org/10.5194/gmd-12-1909-2019, 2019
Short summary
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.
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
Short summary
Short summary
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.
Franco Marenco, Claire Ryder, Victor Estellés, Debbie O'Sullivan, Jennifer Brooke, Luke Orgill, Gary Lloyd, and Martin Gallagher
Atmos. Chem. Phys., 18, 17655–17668, https://doi.org/10.5194/acp-18-17655-2018, https://doi.org/10.5194/acp-18-17655-2018, 2018
Short summary
Short summary
The AER-D airborne campaign characterised Saharan dust in the eastern Atlantic. We report an instance of unusual vertical structure of the Saharan Air Layer during an intense event, showing a large radiative impact and correlated with anomalous lightning activity. Moreover, we report a significant presence of giant dust particles. This is important because most models would miss the giant particles. Our findings may change the way we represent dust transport and deposition in the Atlantic.
Claire L. Ryder, Franco Marenco, Jennifer K. Brooke, Victor Estelles, Richard Cotton, Paola Formenti, James B. McQuaid, Hannah C. Price, Dantong Liu, Patrick Ausset, Phil D. Rosenberg, Jonathan W. Taylor, Tom Choularton, Keith Bower, Hugh Coe, Martin Gallagher, Jonathan Crosier, Gary Lloyd, Eleanor J. Highwood, and Benjamin J. Murray
Atmos. Chem. Phys., 18, 17225–17257, https://doi.org/10.5194/acp-18-17225-2018, https://doi.org/10.5194/acp-18-17225-2018, 2018
Short summary
Short summary
Every year, millions of tons of Saharan dust particles are carried across the Atlantic by the wind, where they can affect weather patterns and climate. Their sizes span orders of magnitude, but the largest (over 10 microns – around the width of a human hair) are difficult to measure and few observations exist. Here we show new aircraft observations of large dust particles, finding more than we would expect, and we quantify their properties which allow them to interact with atmospheric radiation.
Dantong Liu, Jonathan W. Taylor, Jonathan Crosier, Nicholas Marsden, Keith N. Bower, Gary Lloyd, Claire L. Ryder, Jennifer K. Brooke, Richard Cotton, Franco Marenco, Alan Blyth, Zhiqiang Cui, Victor Estelles, Martin Gallagher, Hugh Coe, and Tom W. Choularton
Atmos. Chem. Phys., 18, 3817–3838, https://doi.org/10.5194/acp-18-3817-2018, https://doi.org/10.5194/acp-18-3817-2018, 2018
Short summary
Short summary
This article presents measurements of aerosol properties off the coast of west Africa during August 2015. For the first time, an airborne laser-induced incandescence instrument was deployed to measure the hematite content of dust. The single scattering albedo of dust was found to be influenced by the hematite content, but depended on the dust source and potential dust age. This highlights the importance of size-dependent composition in determining the optical properties of dust.
Jannis von Buttlar, Jakob Zscheischler, Anja Rammig, Sebastian Sippel, Markus Reichstein, Alexander Knohl, Martin Jung, Olaf Menzer, M. Altaf Arain, Nina Buchmann, Alessandro Cescatti, Damiano Gianelle, Gerard Kiely, Beverly E. Law, Vincenzo Magliulo, Hank Margolis, Harry McCaughey, Lutz Merbold, Mirco Migliavacca, Leonardo Montagnani, Walter Oechel, Marian Pavelka, Matthias Peichl, Serge Rambal, Antonio Raschi, Russell L. Scott, Francesco P. Vaccari, Eva van Gorsel, Andrej Varlagin, Georg Wohlfahrt, and Miguel D. Mahecha
Biogeosciences, 15, 1293–1318, https://doi.org/10.5194/bg-15-1293-2018, https://doi.org/10.5194/bg-15-1293-2018, 2018
Short summary
Short summary
Our work systematically quantifies extreme heat and drought event impacts on gross primary productivity (GPP) and ecosystem respiration globally across a wide range of ecosystems. We show that heat extremes typically increased mainly respiration whereas drought decreased both fluxes. Combined heat and drought extremes had opposing effects offsetting each other for respiration, but there were also strong reductions in GPP and hence the strongest reductions in the ecosystems carbon sink capacity.
Manfred Brath, Stuart Fox, Patrick Eriksson, R. Chawn Harlow, Martin Burgdorf, and Stefan A. Buehler
Atmos. Meas. Tech., 11, 611–632, https://doi.org/10.5194/amt-11-611-2018, https://doi.org/10.5194/amt-11-611-2018, 2018
Short summary
Short summary
A method to estimate the amounts of ice, liquid water, and water vapor from aircraft radiation measurements at wavelengths just over and under 1 mm is presented and its performance is estimated. The method uses an ensemble of artificial neural networks. It strongly benefits from the submillimeter frequencies reducing the error for the estimated amount of ice by a factor of 2 compared to a traditional microwave method. The method was applied to measurement of a precipitating frontal system.
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
Short summary
Short summary
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.
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
Short summary
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: 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.
Stuart Fox, Clare Lee, Brian Moyna, Martin Philipp, Ian Rule, Stuart Rogers, Robert King, Matthew Oldfield, Simon Rea, Manju Henry, Hui Wang, and R. Chawn Harlow
Atmos. Meas. Tech., 10, 477–490, https://doi.org/10.5194/amt-10-477-2017, https://doi.org/10.5194/amt-10-477-2017, 2017
Short summary
Short summary
In this paper we present the ISMAR instrument, a new airborne submillimetre radiometer designed for cloud ice remote sensing. We discuss the instrument calibration and evaluate the main sources of bias and the radiometric sensitivity in different measurement scenarios. We also compare clear-sky zenith measurements from high altitude with radiative transfer simulations to demonstrate the performance of ISMAR in flight.
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
Short summary
Short summary
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.
Congsheng Fu, Guiling Wang, Michael L. Goulden, Russell L. Scott, Kenneth Bible, and Zoe G. Cardon
Hydrol. Earth Syst. Sci., 20, 2001–2018, https://doi.org/10.5194/hess-20-2001-2016, https://doi.org/10.5194/hess-20-2001-2016, 2016
Short summary
Short summary
Hydraulic redistribution (HR) of plant root has important hydrological impact (on evapotranspiration, Bowen ratio, and soil moisture) in ecosystems that have a pronounced dry season but are not overall so dry that sparse vegetation and very low soil moisture limit HR.
Alex E. West, Alison J. McLaren, Helene T. Hewitt, and Martin J. Best
Geosci. Model Dev., 9, 1125–1141, https://doi.org/10.5194/gmd-9-1125-2016, https://doi.org/10.5194/gmd-9-1125-2016, 2016
Short summary
Short summary
This study compares two methods of coupling a sea ice model to an atmospheric model in a series of idealized one-dimensional experiments. The JULES method calculates surface variables in the atmosphere; the CICE method calculates surface variables in the sea ice. It is found that simulations of all variables are more accurate in the JULES method, likely because of the shorter time step of the atmosphere.
W. Shen, G. D. Jenerette, D. Hui, and R. L. Scott
Biogeosciences, 13, 425–439, https://doi.org/10.5194/bg-13-425-2016, https://doi.org/10.5194/bg-13-425-2016, 2016
Short summary
Short summary
This simulation study found that dry legacy imposed positive impacts on net ecosystem production (NEP) whereas wet legacy had negative impacts on NEP, indicating that dry legacy can foster more C sequestration and wet legacy more C release. The carryover of soil nitrogen was mainly responsible for the gross ecosystem production (GEP) responses, while the carryovers of plant biomass, litter and soil organic matter were mainly responsible for the ecosystem respiration (Re) responses.
C. L. Ryder, J. B. McQuaid, C. Flamant, P. D. Rosenberg, R. Washington, H. E. Brindley, E. J. Highwood, J. H. Marsham, D. J. Parker, M. C. Todd, J. R. Banks, J. K. Brooke, S. Engelstaedter, V. Estelles, P. Formenti, L. Garcia-Carreras, C. Kocha, F. Marenco, H. Sodemann, C. J. T. Allen, A. Bourdon, M. Bart, C. Cavazos-Guerra, S. Chevaillier, J. Crosier, E. Darbyshire, A. R. Dean, J. R. Dorsey, J. Kent, D. O'Sullivan, K. Schepanski, K. Szpek, J. Trembath, and A. Woolley
Atmos. Chem. Phys., 15, 8479–8520, https://doi.org/10.5194/acp-15-8479-2015, https://doi.org/10.5194/acp-15-8479-2015, 2015
Short summary
Short summary
Measurements of the Saharan atmosphere and of atmospheric mineral dust are lacking but are vital to our understanding of the climate of this region and their impacts further afield. Novel observations were made by the Fennec climate programme during June 2011 and 2012 using ground-based, remote sensing and airborne platforms. Here we describe the airborne observations and the contributions they have made to furthering our understanding of the Saharan climate system.
S.-H. Hong, J. M. H. Hendrickx, J. Kleissl, R. G. Allen, W. G. M. Bastiaanssen, R. L. Scott, and A. L. Steinwand
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-11-13479-2014, https://doi.org/10.5194/hessd-11-13479-2014, 2014
Manuscript not accepted for further review
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
Related subject area
Atmospheric sciences
ClimKern v1.2: a new Python package and kernel repository for calculating radiative feedbacks
Accounting for effects of coagulation and model uncertainties in particle number concentration estimates based on measurements from sampling lines – a Bayesian inversion approach with SLIC v1.0
Top-down CO emission estimates using TROPOMI CO data in the TM5-4DVAR (r1258) inverse modeling suit
The Multi-Compartment Hg Modeling and Analysis Project (MCHgMAP): mercury modeling to support international environmental policy
Similarity-based analysis of atmospheric organic compounds for machine learning applications
Porting the Meso-NH atmospheric model on different GPU architectures for the next generation of supercomputers (version MESONH-v55-OpenACC)
Estimation of aerosol and cloud radiative heating rate in the tropical stratosphere using a radiative kernel method
Evaluation of dust emission and land surface schemes in predicting a mega Asian dust storm over South Korea using WRF-Chem
Sensitivity studies of a four-dimensional local ensemble transform Kalman filter coupled with WRF-Chem version 3.9.1 for improving particulate matter simulation accuracy
A Bayesian method for predicting background radiation at environmental monitoring stations in local-scale networks
Inclusion of the ECMWF ecRad radiation scheme (v1.5.0) in the MAR (v3.14), regional evaluation for Belgium, and assessment of surface shortwave spectral fluxes at Uccle
Development of a fast radiative transfer model for ground-based microwave radiometers (ARMS-gb v1.0): validation and comparison to RTTOV-gb
Indian Institute of Tropical Meteorology (IITM) High-Resolution Global Forecast Model version 1: an attempt to resolve monsoon prediction deadlock
Cell-tracking-based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall
NeuralMie (v1.0): an aerosol optics emulator
Simulation performance of planetary boundary layer schemes in WRF v4.3.1 for near-surface wind over the western Sichuan Basin: a single-site assessment
FootNet v1.0: development of a machine learning emulator of atmospheric transport
Updates and evaluation of NOAA's online-coupled air quality model version 7 (AQMv7) within the Unified Forecast System
Quantifying the analysis uncertainty for nowcasting application
Improving the ensemble square root filter (EnSRF) in the Community Inversion Framework: a case study with ICON-ART 2024.01
The MESSy DWARF (based on MESSy v2.55.2)
An enhanced emission module for the PALM model system 23.10 with application for PM10 emission from urban domestic heating
Identifying lightning processes in ERA5 soundings with deep learning
Sensitivity of predicted ultrafine particle size distributions in Europe to different nucleation rate parameterizations using PMCAMx-UF v2.2
Explaining neural networks for detection of tropical cyclones and atmospheric rivers in gridded atmospheric simulation data
PALACE v1.0: Paranal Airglow Line And Continuum Emission model
Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes
Exploring a high-level programming model for the NWP domain using ECMWF microphysics schemes
Quantifying uncertainties in satellite NO2 superobservations for data assimilation and model evaluation
ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool
Coupling the urban canopy model TEB (SURFEXv9.0) with the radiation model SPARTACUS-Urbanv0.6.1 for more realistic urban radiative exchange calculation
Forecasting contrail climate forcing for flight planning and air traffic management applications: the CocipGrid model in pycontrails 0.51.0
Simulation of the heat mitigation potential of unsealing measures in cities by parameterizing grass grid pavers for urban microclimate modelling with ENVI-met (V5)
AI-NAOS: an AI-based nonspherical aerosol optical scheme for the chemical weather model GRAPES_Meso5.1/CUACE
Orbital-Radar v1.0.0: a tool to transform suborbital radar observations to synthetic EarthCARE cloud radar data
Modelling extensive green roof CO2 exchanges in the TEB urban canopy model
The Modular and Integrated Data Assimilation System at Environment and Climate Change Canada (MIDAS v3.9.1)
A new set of indicators for model evaluation complementing to FAIRMODE’s MQO
Modeling of polycyclic aromatic hydrocarbons (PAHs) from global to regional scales: model development (IAP-AACM_PAH v1.0) and investigation of health risks in 2013 and 2018 in China
LIMA (v2.0): A full two-moment cloud microphysical scheme for the mesoscale non-hydrostatic model Meso-NH v5-6
A dynamical process-based model for quantifying global agricultural ammonia emissions – AMmonia–CLIMate v1.0 (AMCLIM v1.0) – Part 2: livestock farming
Least travel time ray tracer, version Two (LTT v2) adapted to the grid geometry of the OpenIFS atmospheric model
SLUCM+BEM (v1.0): a simple parameterisation for dynamic anthropogenic heat and electricity consumption in WRF-Urban (v4.3.2)
Carbon dioxide plume dispersion simulated at hectometer scale using DALES: model formulation and observational evaluation
NAQPMS-PDAF v2.0: a novel hybrid nonlinear data assimilation system for improved simulation of PM2.5 chemical components
Source-specific bias correction of US background and anthropogenic ozone modeled in CMAQ
Observational operator for fair model evaluation with ground NO2 measurements
Valid time shifting ensemble Kalman filter (VTS-EnKF) for dust storm forecasting
Development of the CMA-GFS-AERO 4D-Var assimilation system v1.0 – Part 1: System description
The third Met Office Unified Model-JULES Regional Atmosphere and Land Configuration, RAL3
Tyler P. Janoski, Ivan Mitevski, Ryan J. Kramer, Michael Previdi, and Lorenzo M. Polvani
Geosci. Model Dev., 18, 3065–3079, https://doi.org/10.5194/gmd-18-3065-2025, https://doi.org/10.5194/gmd-18-3065-2025, 2025
Short summary
Short summary
We developed ClimKern, a Python package and radiative kernel repository, to simplify calculating radiative feedbacks and make climate sensitivity studies more reproducible. Testing of ClimKern with sample climate model data reveals that radiative kernel choice may be more important than previously thought, especially in polar regions. Our work highlights the need for kernel sensitivity analyses to be included in future studies.
Matti Niskanen, Aku Seppänen, Henri Oikarinen, Miska Olin, Panu Karjalainen, Santtu Mikkonen, and Kari Lehtinen
Geosci. Model Dev., 18, 2983–3001, https://doi.org/10.5194/gmd-18-2983-2025, https://doi.org/10.5194/gmd-18-2983-2025, 2025
Short summary
Short summary
Particle size is a key factor determining the properties of aerosol particles which have a major influence on the climate and on human health. When measuring the particle sizes, however, sometimes the sampling lines that transfer the aerosol to the measurement device distort the size distribution, making the measurement unreliable. We propose a method to correct for the distortions and estimate the true particle sizes, improving measurement accuracy.
Johann Rasmus Nüß, Nikos Daskalakis, Fabian Günther Piwowarczyk, Angelos Gkouvousis, Oliver Schneising, Michael Buchwitz, Maria Kanakidou, Maarten C. Krol, and Mihalis Vrekoussis
Geosci. Model Dev., 18, 2861–2890, https://doi.org/10.5194/gmd-18-2861-2025, https://doi.org/10.5194/gmd-18-2861-2025, 2025
Short summary
Short summary
We estimate carbon monoxide emissions through inverse modeling, an approach where measurements of tracers in the atmosphere are fed to a model to calculate backwards in time (inverse) where the tracers came from. We introduce measurements from a new satellite instrument and show that, in most places globally, these on their own sufficiently constrain the emissions. This alleviates the need for additional datasets, which could shorten the delay for future carbon monoxide source estimates.
Ashu Dastoor, Hélène Angot, Johannes Bieser, Flora Brocza, Brock Edwards, Aryeh Feinberg, Xinbin Feng, Benjamin Geyman, Charikleia Gournia, Yipeng He, Ian M. Hedgecock, Ilia Ilyin, Jane Kirk, Che-Jen Lin, Igor Lehnherr, Robert Mason, David McLagan, Marilena Muntean, Peter Rafaj, Eric M. Roy, Andrei Ryjkov, Noelle E. Selin, Francesco De Simone, Anne L. Soerensen, Frits Steenhuisen, Oleg Travnikov, Shuxiao Wang, Xun Wang, Simon Wilson, Rosa Wu, Qingru Wu, Yanxu Zhang, Jun Zhou, Wei Zhu, and Scott Zolkos
Geosci. Model Dev., 18, 2747–2860, https://doi.org/10.5194/gmd-18-2747-2025, https://doi.org/10.5194/gmd-18-2747-2025, 2025
Short summary
Short summary
This paper introduces the Multi-Compartment Mercury (Hg) Modeling and Analysis Project (MCHgMAP) aimed at informing the effectiveness evaluations of two multilateral environmental agreements: the Minamata Convention on Mercury and the Convention on Long-Range Transboundary Air Pollution. The experimental design exploits a variety of models (atmospheric, land, oceanic ,and multimedia mass balance models) to assess the short- and long-term influences of anthropogenic Hg releases into the environment.
Hilda Sandström and Patrick Rinke
Geosci. Model Dev., 18, 2701–2724, https://doi.org/10.5194/gmd-18-2701-2025, https://doi.org/10.5194/gmd-18-2701-2025, 2025
Short summary
Short summary
Machine learning has the potential to aid the identification of organic molecules involved in aerosol formation. Yet, progress is stalled by a lack of curated atmospheric molecular datasets. Here, we compared atmospheric compounds with large molecular datasets used in machine learning and found minimal overlap with similarity algorithms. Our result underlines the need for collaborative efforts to curate atmospheric molecular data to facilitate machine learning models in atmospheric sciences.
Juan Escobar, Philippe Wautelet, Joris Pianezze, Florian Pantillon, Thibaut Dauhut, Christelle Barthe, and Jean-Pierre Chaboureau
Geosci. Model Dev., 18, 2679–2700, https://doi.org/10.5194/gmd-18-2679-2025, https://doi.org/10.5194/gmd-18-2679-2025, 2025
Short summary
Short summary
The Meso-NH weather research code is adapted for GPUs using OpenACC, leading to significant performance and energy efficiency improvements. Called MESONH-v55-OpenACC, it includes enhanced memory management, communication optimizations and a new solver. On the AMD MI250X Adastra platform, it achieved up to 6× speedup and 2.3× energy efficiency gain compared to CPUs. Storm simulations at 100 m resolution show positive results, positioning the code for future use on exascale supercomputers.
Jie Gao, Yi Huang, Jonathon S. Wright, Ke Li, Tao Geng, and Qiurun Yu
Geosci. Model Dev., 18, 2569–2586, https://doi.org/10.5194/gmd-18-2569-2025, https://doi.org/10.5194/gmd-18-2569-2025, 2025
Short summary
Short summary
The aerosol in the upper troposphere and stratosphere is highly variable, and its radiative effect is poorly understood. To estimate this effect, the radiative kernel is constructed and applied. The results show that the kernels can reproduce aerosol radiative effects and are expected to simulate stratospheric aerosol radiative effects. This approach reduces computational expense, is consistent with radiative model calculations, and can be applied to atmospheric models with speed requirements.
Ji Won Yoon, Seungyeon Lee, Ebony Lee, and Seon Ki Park
Geosci. Model Dev., 18, 2303–2328, https://doi.org/10.5194/gmd-18-2303-2025, https://doi.org/10.5194/gmd-18-2303-2025, 2025
Short summary
Short summary
This study evaluates the Weather Research and Forecasting Model (WRF) coupled with Chemistry (WRF-Chem) to predict a mega Asian dust storm (ADS) over South Korea on 28–29 March 2021. We assessed combinations of five dust emission and four land surface schemes by analyzing meteorological and air quality variables. The best scheme combination reduced the root mean square error (RMSE) for particulate matter 10 (PM10) by up to 29.6 %, demonstrating the highest performance.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
Geosci. Model Dev., 18, 2231–2248, https://doi.org/10.5194/gmd-18-2231-2025, https://doi.org/10.5194/gmd-18-2231-2025, 2025
Short summary
Short summary
The effectiveness of this assimilation system and its sensitivity to the ensemble member size and length of the assimilation window are investigated. This study advances our understanding of the selection of basic parameters in the four-dimensional local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate-matter-polluted environment.
Jens Peter Karolus Wenceslaus Frankemölle, Johan Camps, Pieter De Meutter, and Johan Meyers
Geosci. Model Dev., 18, 1989–2003, https://doi.org/10.5194/gmd-18-1989-2025, https://doi.org/10.5194/gmd-18-1989-2025, 2025
Short summary
Short summary
To detect anomalous radioactivity in the environment, it is paramount that we understand the natural background level. In this work, we propose a statistical model to describe the most likely background level and the associated uncertainty in a network of dose rate detectors. We train, verify, and validate the model using real environmental data. Using the model, we show that we can correctly predict the background level in a subset of the detector network during a known
anomalous event.
Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, David Bolsée, Xavier Fettweis, and Marilaure Grégoire
Geosci. Model Dev., 18, 1965–1988, https://doi.org/10.5194/gmd-18-1965-2025, https://doi.org/10.5194/gmd-18-1965-2025, 2025
Short summary
Short summary
The MAR (Modèle Régional Atmosphérique) is a regional climate model used for weather forecasting and studying the climate over various regions. This paper presents an update of MAR thanks to which it can precisely decompose solar radiation, in particular in the UV (ultraviolet) and photosynthesis ranges, both being critical to human health and ecosystems. As a first application of this new capability, this paper presents a method for predicting UV indices with MAR.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
Geosci. Model Dev., 18, 1947–1964, https://doi.org/10.5194/gmd-18-1947-2025, https://doi.org/10.5194/gmd-18-1947-2025, 2025
Short summary
Short summary
Direct assimilation of observations from ground-based microwave radiometers (GMRs) holds significant potential for improving forecast accuracy. Radiative transfer models (RTMs) play a crucial role in direct data assimilation. In this study, we introduce a new RTM, the Advanced Radiative Transfer Modeling System – Ground-Based (ARMS-gb), designed to simulate brightness temperatures observed by GMRs along with their Jacobians. Several enhancements have been incorporated to achieve higher accuracy.
R. Phani Murali Krishna, Siddharth Kumar, A. Gopinathan Prajeesh, Peter Bechtold, Nils Wedi, Kumar Roy, Malay Ganai, B. Revanth Reddy, Snehlata Tirkey, Tanmoy Goswami, Radhika Kanase, Sahadat Sarkar, Medha Deshpande, and Parthasarathi Mukhopadhyay
Geosci. Model Dev., 18, 1879–1894, https://doi.org/10.5194/gmd-18-1879-2025, https://doi.org/10.5194/gmd-18-1879-2025, 2025
Short summary
Short summary
The High-Resolution Global Forecast Model (HGFM) is an advanced iteration of the operational Global Forecast System (GFS) model. HGFM can produce forecasts at a spatial scale of ~6 km in tropics. It demonstrates improved accuracy in short- to medium-range weather prediction over the Indian region, with notable success in predicting extreme events. Further, the model will be entrusted to operational forecasting agencies after validation and testing.
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev., 18, 1851–1878, https://doi.org/10.5194/gmd-18-1851-2025, https://doi.org/10.5194/gmd-18-1851-2025, 2025
Short summary
Short summary
Nowcasting models struggle with the rapid evolution of heavy rain, and common verification methods are unable to describe how accurately the models predict the growth and decay of heavy rain. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and the model skill is then evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with four open-source models.
Andrew Geiss and Po-Lun Ma
Geosci. Model Dev., 18, 1809–1827, https://doi.org/10.5194/gmd-18-1809-2025, https://doi.org/10.5194/gmd-18-1809-2025, 2025
Short summary
Short summary
Particles in the Earth's atmosphere strongly impact the planet's energy budget, and atmosphere simulations require accurate representation of their interaction with light. This work introduces two approaches to represent light scattering by small particles. The first is a scattering simulator based on Mie theory implemented in Python. The second is a neural network emulator that is more accurate than existing methods and is fast enough to be used in climate and weather simulations.
Qin Wang, Bo Zeng, Gong Chen, and Yaoting Li
Geosci. Model Dev., 18, 1769–1784, https://doi.org/10.5194/gmd-18-1769-2025, https://doi.org/10.5194/gmd-18-1769-2025, 2025
Short summary
Short summary
This study evaluates the performance of four planetary boundary layer (PBL) schemes in near-surface wind fields over the Sichuan Basin, China. Using 112 sensitivity experiments with the Weather Research and Forecasting (WRF) model and focusing on 28 wind events, it is found that wind direction was less sensitive to the PBL schemes. The quasi-normal scale elimination (QNSE) scheme captured temporal variations best, while the Mellor–Yamada–Janjić (MYJ) scheme had the least error in wind speed.
Tai-Long He, Nikhil Dadheech, Tammy M. Thompson, and Alexander J. Turner
Geosci. Model Dev., 18, 1661–1671, https://doi.org/10.5194/gmd-18-1661-2025, https://doi.org/10.5194/gmd-18-1661-2025, 2025
Short summary
Short summary
It is computationally expensive to infer greenhouse gas (GHG) emissions using atmospheric observations. This is partly due to the detailed model used to represent atmospheric transport. We demonstrate how a machine learning (ML) model can be used to simulate high-resolution atmospheric transport. This type of ML model will help estimate GHG emissions using dense observations, which are becoming increasingly common with the proliferation of urban monitoring networks and geostationary satellites.
Wei Li, Beiming Tang, Patrick C. Campbell, Youhua Tang, Barry Baker, Zachary Moon, Daniel Tong, Jianping Huang, Kai Wang, Ivanka Stajner, and Raffaele Montuoro
Geosci. Model Dev., 18, 1635–1660, https://doi.org/10.5194/gmd-18-1635-2025, https://doi.org/10.5194/gmd-18-1635-2025, 2025
Short summary
Short summary
The study describes the updates of NOAA's current UFS-AQMv7 air quality forecast model by incorporating the latest scientific and structural changes in CMAQv5.4. An evaluation during the summer of 2023 shows that the updated model overall improves the simulation of MDA8 O3 by reducing the bias by 8%–12% in the contiguous US. PM2.5 predictions have mixed results due to wildfire, highlighting the need for future refinements.
Yanwei Zhu, Aitor Atencia, Markus Dabernig, and Yong Wang
Geosci. Model Dev., 18, 1545–1559, https://doi.org/10.5194/gmd-18-1545-2025, https://doi.org/10.5194/gmd-18-1545-2025, 2025
Short summary
Short summary
Most works have delved into convective weather nowcasting, and only a few works have discussed the nowcasting uncertainty for variables at the surface level. Hence, we proposed a method to estimate uncertainty. Generating appropriate noises associated with the characteristic of the error in analysis can simulate the uncertainty of nowcasting. This method can contribute to the estimation of near–surface analysis uncertainty in both nowcasting applications and ensemble nowcasting development.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
Geosci. Model Dev., 18, 1505–1544, https://doi.org/10.5194/gmd-18-1505-2025, https://doi.org/10.5194/gmd-18-1505-2025, 2025
Short summary
Short summary
The Community Inversion Framework (CIF) brings together methods for estimating greenhouse gas fluxes from atmospheric observations. The initial ensemble method implemented in CIF was found to be incomplete and could hardly be compared to other ensemble methods employed in the inversion community. In this paper, we present and evaluate a new implementation of the ensemble mode, building upon the initial developments.
Astrid Kerkweg, Timo Kirfel, Duong H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev., 18, 1265–1286, https://doi.org/10.5194/gmd-18-1265-2025, https://doi.org/10.5194/gmd-18-1265-2025, 2025
Short summary
Short summary
Normally, the Modular Earth Submodel System (MESSy) is linked to complete dynamic models to create chemical climate models. However, the modular concept of MESSy and the newly developed DWARF component presented here make it possible to create simplified models that contain only one or a few process descriptions. This is very useful for technical optimisation, such as porting to GPUs, and can be used to create less complex models, such as a chemical box model.
Edward C. Chan, Ilona J. Jäkel, Basit Khan, Martijn Schaap, Timothy M. Butler, Renate Forkel, and Sabine Banzhaf
Geosci. Model Dev., 18, 1119–1139, https://doi.org/10.5194/gmd-18-1119-2025, https://doi.org/10.5194/gmd-18-1119-2025, 2025
Short summary
Short summary
An enhanced emission module has been developed for the PALM model system, improving flexibility and scalability of emission source representation across different sectors. A model for parametrized domestic emissions has also been included, for which an idealized model run is conducted for particulate matter (PM10). The results show that, in addition to individual sources and diurnal variations in energy consumption, vertical transport and urban topology play a role in concentration distribution.
Gregor Ehrensperger, Thorsten Simon, Georg J. Mayr, and Tobias Hell
Geosci. Model Dev., 18, 1141–1153, https://doi.org/10.5194/gmd-18-1141-2025, https://doi.org/10.5194/gmd-18-1141-2025, 2025
Short summary
Short summary
As lightning is a brief and localized event, it is not explicitly resolved in atmospheric models. Instead, expert-based auxiliary descriptions are used to assess it. This study explores how AI can improve our understanding of lightning without relying on traditional expert knowledge. We reveal that AI independently identified the key factors known to experts as essential for lightning in the Alps region. This shows how knowledge discovery could be sped up in areas with limited expert knowledge.
David Patoulias, Kalliopi Florou, and Spyros N. Pandis
Geosci. Model Dev., 18, 1103–1118, https://doi.org/10.5194/gmd-18-1103-2025, https://doi.org/10.5194/gmd-18-1103-2025, 2025
Short summary
Short summary
The effect of the assumed atmospheric nucleation mechanism on particle number concentrations and size distribution was investigated. Two quite different mechanisms involving sulfuric acid and ammonia or a biogenic organic vapor gave quite similar results which were consistent with measurements at 26 measurement stations across Europe. The number of larger particles that serve as cloud condensation nuclei showed little sensitivity to the assumed nucleation mechanism.
Tim Radke, Susanne Fuchs, Christian Wilms, Iuliia Polkova, and Marc Rautenhaus
Geosci. Model Dev., 18, 1017–1039, https://doi.org/10.5194/gmd-18-1017-2025, https://doi.org/10.5194/gmd-18-1017-2025, 2025
Short summary
Short summary
In our study, we built upon previous work to investigate the patterns artificial intelligence (AI) learns to detect atmospheric features like tropical cyclones (TCs) and atmospheric rivers (ARs). As primary objective, we adopt a method to explain the AI used and investigate the plausibility of learned patterns. We find that plausible patterns are learned for both TCs and ARs. Hence, the chosen method is very useful for gaining confidence in the AI-based detection of atmospheric features.
Stefan Noll, Carsten Schmidt, Patrick Hannawald, Wolfgang Kausch, and Stefan Kimeswenger
EGUsphere, https://doi.org/10.5194/egusphere-2024-3512, https://doi.org/10.5194/egusphere-2024-3512, 2025
Short summary
Short summary
Non-thermal emission from chemical reactions in the Earth's middle und upper atmosphere strongly contributes to the brightness of the night sky below about 2.3 µm. The new Paranal Airglow Line and Continuum Emission model calculates the emission spectrum and its variability with an unprecedented accuracy. Relying on a large spectroscopic data set from astronomical spectrographs and theoretical molecular/atomic data, it is valuable for airglow research and astronomical observatories.
Felipe Cifuentes, Henk Eskes, Enrico Dammers, Charlotte Bryan, and Folkert Boersma
Geosci. Model Dev., 18, 621–649, https://doi.org/10.5194/gmd-18-621-2025, https://doi.org/10.5194/gmd-18-621-2025, 2025
Short summary
Short summary
We tested the capability of the flux divergence approach (FDA) to reproduce known NOx emissions using synthetic NO2 satellite column retrievals from high-resolution model simulations. The FDA accurately reproduced NOx emissions when column observations were limited to the boundary layer and when the variability of the NO2 lifetime, the NOx : NO2 ratio, and NO2 profile shapes were correctly modeled. This introduces strong model dependency, reducing the simplicity of the original FDA formulation.
Stefano Ubbiali, Christian Kühnlein, Christoph Schär, Linda Schlemmer, Thomas C. Schulthess, Michael Staneker, and Heini Wernli
Geosci. Model Dev., 18, 529–546, https://doi.org/10.5194/gmd-18-529-2025, https://doi.org/10.5194/gmd-18-529-2025, 2025
Short summary
Short summary
We explore a high-level programming model for porting numerical weather prediction (NWP) model codes to graphics processing units (GPUs). We present a Python rewrite with the domain-specific library GT4Py (GridTools for Python) of two renowned cloud microphysics schemes and the associated tangent-linear and adjoint algorithms. We find excellent portability, competitive GPU performance, robust execution on diverse computing architectures, and enhanced code maintainability and user productivity.
Pieter Rijsdijk, Henk Eskes, Arlene Dingemans, K. Folkert Boersma, Takashi Sekiya, Kazuyuki Miyazaki, and Sander Houweling
Geosci. Model Dev., 18, 483–509, https://doi.org/10.5194/gmd-18-483-2025, https://doi.org/10.5194/gmd-18-483-2025, 2025
Short summary
Short summary
Clustering high-resolution satellite observations into superobservations improves model validation and data assimilation applications. In our paper, we derive quantitative uncertainties for satellite NO2 column observations based on knowledge of the retrievals, including a detailed analysis of spatial error correlations and representativity errors. The superobservations and uncertainty estimates are tested in a global chemical data assimilation system and are found to improve the forecasts.
Dario Di Santo, Cenlin He, Fei Chen, and Lorenzo Giovannini
Geosci. Model Dev., 18, 433–459, https://doi.org/10.5194/gmd-18-433-2025, https://doi.org/10.5194/gmd-18-433-2025, 2025
Short summary
Short summary
This paper presents the Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool (ML-AMPSIT), a computationally efficient tool that uses machine learning algorithms for sensitivity analysis in atmospheric models. It is tested with the Weather Research and Forecasting (WRF) model coupled with the Noah-Multiparameterization (Noah-MP) land surface model to investigate sea breeze circulation sensitivity to vegetation-related parameters.
Robert Schoetter, Robin James Hogan, Cyril Caliot, and Valéry Masson
Geosci. Model Dev., 18, 405–431, https://doi.org/10.5194/gmd-18-405-2025, https://doi.org/10.5194/gmd-18-405-2025, 2025
Short summary
Short summary
Radiation is relevant to the atmospheric impact on people and infrastructure in cities as it can influence the urban heat island, building energy consumption, and human thermal comfort. A new urban radiation model, assuming a more realistic form of urban morphology, is coupled to the urban climate model Town Energy Balance (TEB). The new TEB is evaluated with a reference radiation model for a variety of urban morphologies, and an improvement in the simulated radiative observables is found.
Zebediah Engberg, Roger Teoh, Tristan Abbott, Thomas Dean, Marc E. J. Stettler, and Marc L. Shapiro
Geosci. Model Dev., 18, 253–286, https://doi.org/10.5194/gmd-18-253-2025, https://doi.org/10.5194/gmd-18-253-2025, 2025
Short summary
Short summary
Contrails forming in some atmospheric conditions may persist and become strongly warming cirrus, while in other conditions may be neutral or cooling. We develop a contrail forecast model to predict contrail climate forcing for any arbitrary point in space and time and explore integration into flight planning and air traffic management. This approach enables contrail interventions to target high-probability high-climate-impact regions and reduce unintended consequences of contrail management.
Nils Eingrüber, Alina Domm, Wolfgang Korres, and Karl Schneider
Geosci. Model Dev., 18, 141–160, https://doi.org/10.5194/gmd-18-141-2025, https://doi.org/10.5194/gmd-18-141-2025, 2025
Short summary
Short summary
Climate change adaptation measures like unsealings can reduce urban heat stress. As grass grid pavers have never been parameterized for microclimate model simulations with ENVI-met, a new parameterization was developed based on field measurements. To analyse the cooling potential, scenario analyses were performed for a densely developed area in Cologne. Statistically significant average cooling effects of up to −11.1 K were found for surface temperature and up to −2.9 K for 1 m air temperature.
Xuan Wang, Lei Bi, Hong Wang, Yaqiang Wang, Wei Han, Xueshun Shen, and Xiaoye Zhang
Geosci. Model Dev., 18, 117–139, https://doi.org/10.5194/gmd-18-117-2025, https://doi.org/10.5194/gmd-18-117-2025, 2025
Short summary
Short summary
The Artificial-Intelligence-based Nonspherical Aerosol Optical Scheme (AI-NAOS) was developed to improve the estimation of the aerosol direct radiation effect and was coupled online with a chemical weather model. The AI-NAOS scheme considers black carbon as fractal aggregates and soil dust as super-spheroids, encapsulated with hygroscopic aerosols. Real-case simulations emphasize the necessity of accurately representing nonspherical and inhomogeneous aerosols in chemical weather models.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev., 18, 101–115, https://doi.org/10.5194/gmd-18-101-2025, https://doi.org/10.5194/gmd-18-101-2025, 2025
Short summary
Short summary
The Python tool Orbital-Radar transfers suborbital radar data (ground-based, airborne, and forward-simulated numerical weather prediction model) into synthetic spaceborne cloud profiling radar data, mimicking platform-specific instrument characteristics, e.g. EarthCARE or CloudSat. The tool's novelty lies in simulating characteristic errors and instrument noise. Thus, existing data sets are transferred into synthetic observations and can be used for satellite calibration–validation studies.
Aurélien Mirebeau, Cécile de Munck, Bertrand Bonan, Christine Delire, Aude Lemonsu, Valéry Masson, and Stephan Weber
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-233, https://doi.org/10.5194/gmd-2024-233, 2025
Revised manuscript accepted for GMD
Short summary
Short summary
The greening of cities is recommended to limit the effects of climate change. In particular, green roofs can provide numerous environmental benefits, such as urban cooling, water retention and carbon sequestration. The aim of this research is to develop a new module for calculating green roof CO2 fluxes within a model that can already simulate hydrological and thermal processes of such roofs. The calibration and evaluation of this module take advantage of long term experimental data.
Mark Buehner, Jean-Francois Caron, Ervig Lapalme, Alain Caya, Ping Du, Yves Rochon, Sergey Skachko, Maziar Bani Shahabadi, Sylvain Heilliette, Martin Deshaies-Jacques, Weiguang Chang, and Michael Sitwell
Geosci. Model Dev., 18, 1–18, https://doi.org/10.5194/gmd-18-1-2025, https://doi.org/10.5194/gmd-18-1-2025, 2025
Short summary
Short summary
The Modular and Integrated Data Assimilation System (MIDAS) software is described. The flexible design of MIDAS enables both deterministic and ensemble prediction applications for the atmosphere and several other Earth system components. It is currently used for all main operational weather prediction systems in Canada and also for sea ice and sea surface temperature analysis. The use of MIDAS for multiple Earth system components will facilitate future research on coupled data assimilation.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, and Enrico Pisoni
EGUsphere, https://doi.org/10.5194/egusphere-2024-3690, https://doi.org/10.5194/egusphere-2024-3690, 2025
Short summary
Short summary
We assess the relevance and utility indicators developed within FAIRMODE by evaluating 9 CAMS models in calculated air pollutant values. For NO2, the results highlight difficulties at traffic stations. For PM2.5 and PM10 the bias and Winter-Summer gradients reveal issues. O3 evaluation shows that e.g. seasonal gradients are useful. Overall, the indicators provide valuable insights into model limitations, yet there is a need to reconsider the strictness of some indicators for certain pollutants.
Zichen Wu, Xueshun Chen, Zifa Wang, Huansheng Chen, Zhe Wang, Qing Mu, Lin Wu, Wending Wang, Xiao Tang, Jie Li, Ying Li, Qizhong Wu, Yang Wang, Zhiyin Zou, and Zijian Jiang
Geosci. Model Dev., 17, 8885–8907, https://doi.org/10.5194/gmd-17-8885-2024, https://doi.org/10.5194/gmd-17-8885-2024, 2024
Short summary
Short summary
We developed a model to simulate polycyclic aromatic hydrocarbons (PAHs) from global to regional scales. The model can reproduce PAH distribution well. The concentration of BaP (indicator species for PAHs) could exceed the target values of 1 ng m-3 over some areas (e.g., in central Europe, India, and eastern China). The change in BaP is lower than that in PM2.5 from 2013 to 2018. China still faces significant potential health risks posed by BaP although the Action Plan has been implemented.
Marie Taufour, Jean-Pierre Pinty, Christelle Barthe, Benoît Vié, and Chien Wang
Geosci. Model Dev., 17, 8773–8798, https://doi.org/10.5194/gmd-17-8773-2024, https://doi.org/10.5194/gmd-17-8773-2024, 2024
Short summary
Short summary
We have developed a complete two-moment version of the LIMA (Liquid Ice Multiple Aerosols) microphysics scheme. We have focused on collection processes, where the hydrometeor number transfer is often estimated in proportion to the mass transfer. The impact of these parameterizations on a convective system and the prospects for more realistic estimates of secondary parameters (reflectivity, hydrometeor size) are shown in a first test on an idealized case.
Jize Jiang, David S. Stevenson, Aimable Uwizeye, Giuseppe Tempio, Alessandra Falcucci, Flavia Casu, and Mark A. Sutton
EGUsphere, https://doi.org/10.5194/egusphere-2024-3803, https://doi.org/10.5194/egusphere-2024-3803, 2024
Short summary
Short summary
A special model called AMmonia–CLIMate (AMCLIM) has been developed to understand and calculate NH3 emissions from livestock farming. It is estimated that about 30 % of excreted N from livestock was lost due to NH3 emissions from housing, manure management and land application of manure. High NH3 volatilization often occurred in hot regions, while poor management practices also result in significant N losses through NH3 emissions.
Maksym Vasiuta, Angel Navarro Trastoy, Sanam Motlaghzadeh, Lauri Tuppi, Torsten Mayer-Gürr, and Heikki Järvinen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-136, https://doi.org/10.5194/gmd-2024-136, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Propagation of electromagnetic signals in the Earth's neutral atmosphere inflicts errors in space geodetic observations. To model these errors as accurately as possible, it is necessary to use a signal ray tracing algorithm which is informed of the state of the atmosphere. We developed such algorithm and tested it by modelling errors in GNSS network observations. Our algorithm's main advantage is loss-less utilization of atmospheric information provided by numerical weather prediction models.
Yuya Takane, Yukihiro Kikegawa, Ko Nakajima, and Hiroyuki Kusaka
Geosci. Model Dev., 17, 8639–8664, https://doi.org/10.5194/gmd-17-8639-2024, https://doi.org/10.5194/gmd-17-8639-2024, 2024
Short summary
Short summary
A new parameterisation for dynamic anthropogenic heat and electricity consumption is described. The model reproduced the temporal variation in and spatial distributions of electricity consumption and temperature well in summer and winter. The partial air conditioning was the most critical factor, significantly affecting the value of anthropogenic heat emission.
Arseniy Karagodin-Doyennel, Fredrik Jansson, Bart van Stratum, Hugo Denier van der Gon, Jordi Vilà-Guerau de Arellano, and Sander Houweling
EGUsphere, https://doi.org/10.5194/egusphere-2024-3721, https://doi.org/10.5194/egusphere-2024-3721, 2024
Short summary
Short summary
We introduce a new simulation platform based on the Dutch Large-Eddy Simulation (DALES) to simulate carbon dioxide (CO2) emissions and their dispersion in the turbulent environments with hectometer resolution. This model incorporates both anthropogenic emission inventory and ecosystem exchanges. Simulation results for the main urban area in the Netherlands demonstrate a strong potential of DALES to enhance CO2 emission modeling, which is important for refining their reduction strategies.
Hongyi Li, Ting Yang, Lars Nerger, Dawei Zhang, Di Zhang, Guigang Tang, Haibo Wang, Yele Sun, Pingqing Fu, Hang Su, and Zifa Wang
Geosci. Model Dev., 17, 8495–8519, https://doi.org/10.5194/gmd-17-8495-2024, https://doi.org/10.5194/gmd-17-8495-2024, 2024
Short summary
Short summary
To accurately characterize the spatiotemporal distribution of particulate matter <2.5 µm chemical components, we developed the Nested Air Quality Prediction Model System with the Parallel Data Assimilation Framework (NAQPMS-PDAF) v2.0 for chemical components with non-Gaussian and nonlinear properties. NAQPMS-PDAF v2.0 has better computing efficiency, excels when used with a small ensemble size, and can significantly improve the simulation performance of chemical components.
T. Nash Skipper, Christian Hogrefe, Barron H. Henderson, Rohit Mathur, Kristen M. Foley, and Armistead G. Russell
Geosci. Model Dev., 17, 8373–8397, https://doi.org/10.5194/gmd-17-8373-2024, https://doi.org/10.5194/gmd-17-8373-2024, 2024
Short summary
Short summary
Chemical transport model simulations are combined with ozone observations to estimate the bias in ozone attributable to US anthropogenic sources and individual sources of US background ozone: natural sources, non-US anthropogenic sources, and stratospheric ozone. Results indicate a positive bias correlated with US anthropogenic emissions during summer in the eastern US and a negative bias correlated with stratospheric ozone during spring.
Li Fang, Jianbing Jin, Arjo Segers, Ke Li, Ji Xia, Wei Han, Baojie Li, Hai Xiang Lin, Lei Zhu, Song Liu, and Hong Liao
Geosci. Model Dev., 17, 8267–8282, https://doi.org/10.5194/gmd-17-8267-2024, https://doi.org/10.5194/gmd-17-8267-2024, 2024
Short summary
Short summary
Model evaluations against ground observations are usually unfair. The former simulates mean status over coarse grids and the latter the surrounding atmosphere. To solve this, we proposed the new land-use-based representative (LUBR) operator that considers intra-grid variance. The LUBR operator is validated to provide insights that align with satellite measurements. The results highlight the importance of considering fine-scale urban–rural differences when comparing models and observation.
Mijie Pang, Jianbing Jin, Arjo Segers, Huiya Jiang, Wei Han, Batjargal Buyantogtokh, Ji Xia, Li Fang, Jiandong Li, Hai Xiang Lin, and Hong Liao
Geosci. Model Dev., 17, 8223–8242, https://doi.org/10.5194/gmd-17-8223-2024, https://doi.org/10.5194/gmd-17-8223-2024, 2024
Short summary
Short summary
The ensemble Kalman filter (EnKF) improves dust storm forecasts but faces challenges with position errors. The valid time shifting EnKF (VTS-EnKF) addresses this by adjusting for position errors, enhancing accuracy in forecasting dust storms, as proven in tests on 2021 events, even with smaller ensembles and time intervals.
Yongzhu Liu, Xiaoye Zhang, Wei Han, Chao Wang, Wenxing Jia, Deying Wang, Zhaorong Zhuang, and Xueshun Shen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-148, https://doi.org/10.5194/gmd-2024-148, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
In order to investigate the feedbacks of chemical data assimilation on meteorological forecasts, we developed a strongly coupled chemistry meteorology four-dimensional variational (4D-Var) assimilation system, CMA-GFS-AERO 4D-Var, based on the framework of the incremental analysis scheme of the CMA-GFS operational global numerical weather model. The results show that assimilating BC observations can generate analysis increments not only for BC but also for atmospheric variables.
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
Short summary
Short summary
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.
Cited articles
AmeriFlux data repository: AmeriFlux data at half-hourly resolution,
available at: http://ameriflux.lbl.gov/, last access:
17 July 2018.
Best, M. J., Pryor, M., Clark, D. B., Rooney, G. G., Essery, R. L. H.,
Ménard, C. B., Edwards, J. M., Hendry, M. A., Porson, 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.
Bugbee, B., Droter, M., Monje, O., and Tanner, B.: Evaluation and
modification of commercial infrared transducers for leaf temperature
measurement, Adv. Space Res., 22, 1425–1434, 1998.
Cameron, J. and Bell, W.: The testing and implementation of variational bias
correction (VarBC) in the global model at the Met Office, Weather Science
Technical Report No: 63,
available at: https://www.metoffice.gov.uk/research/library-and-archive/publications/science/weather-science-technical-reports/
(last access: 18 April 2019), 2018.
Candy, B., Saunders, R. W., Ghent, D., and Bulgin, C. E.: The impact of
satellite-derived land surface temperatures on numerical weather prediction
analyses and forecasts, J. Geophys. Res.-Atmos., 122, https://doi.org/10.1002/2016JD026417, 2017.
Cardinali, C.: Monitoring the observation impact on the short-range
forecast, Q. J. Roy. Meteor. Soc., 135, 239–250, 2009.
Castelli, F., Entekhabi, D., and Caporali, E.: Estimation of surface heat
flux and an index of soil moisture using adjoint-state surface energy
balance, Water Resour. Res., 35, 3115–3125, 1999.
Chen, F. and Zhang, Y.: On the coupling strength between the land surface
and the atmosphere: From viewpoint of surface exchange coefficients, Geophys. Res. Lett., 36, L10404, https://doi.org/10.1029/2009GL037980, 2009.
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.,
Harding, R. J., Huntingford, C., and Cox, P. M.: The Joint UK Land
Environment Simulator (JULES), model description – Part 2: Carbon fluxes and
vegetation dynamics, Geosci. Model Dev., 4, 701–722,
https://doi.org/10.5194/gmd-4-701-2011, 2011.
Coll, C., Caselles, V., Galve, J. M., Valor, E., Niclos, R., Sanchez, J. M.,
and Rivas, R.: Ground measurements for the validation of land surface
temperatures derived from AATSR and MODIS data, Remote Sens. Environ.,
97, 288–300, 2005.
Coops, N. C., Duro, D. C., Wulder, M. A., and Han, T.: Estimating afternoon
MODIS land surface temperatures (LST) based on morning MODIS overpass,
location and elevation information, Int. J. Remote Sens.,
28, 2391–2396, 2007.
Davies, T.: Lateral boundary conditions for limited area models, Q. J. Roy.
Meteor. Soc., 140, 185–196, 2014.
Davies, T., Cullen, M. J. P., Malcolm, A. J., Mawson, M. H., Staniforth, A.,
White, A. A., and Wood, N.: A new dynamical core for the Met Office's global
and regional modelling of the atmosphere, Q. J. Roy. Meteor. Soc., 131,
1759–1782, 2005.
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P.,
Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P.,
Bechtold, P., Beljaars, A. C., van de Berg, L., Bidlot, J., Bormann, N.,
Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S.
B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P.,
Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M.,
Morcrette, J., Park, B., Peubey, C., de Rosnay, P., Tavolato, C.,
Thépaut, J., and Vitart, F.: The ERA-Interim reanalysis: configuration
and performance of the data assimilation system, Q. J. Roy. Meteor. Soc.,
137, 553–597, https://doi.org/10.1002/qj.828, 2011.
Dharssi, I., Bovis, K. J., Macpherson, B., and Jones, C. P.: Operational
assimilation of ASCAT surface soil wetness at the Met Office, Hydrol. Earth
Syst. Sci., 15, 2729–2746, https://doi.org/10.5194/hess-15-2729-2011, 2011.
Dickinson, R. E., Hendersin-Sellers, A., Rosenzweig, C., and Sellers, P. J.:
Evapotranspiration models with canopy resistance for use in climate models: A
review, Agr. Forest Meteorol., 54, 373–388, 1991.
Duffour, C., Lagouarde, J. P., Olioso, A., Demarty, J., and Roujean, J. L.:
Driving factors of the directional variability of thermal infrared signal in
temperate regions, Remote Sens. Environ., 177, https://doi.org/10.1016/j.rse.2016.02.024, 2016.
Edwards, J. M.: Assessment of Met Office forecasting models with SEVIRI LSTs,
Proceedings of the 4th LSA SAF User Training Workshop, 15–17 November 2010,
Météo-France, Toulouse, France, 2010.
Emmerich, W. E. and Verdugo, C. L.: Long-term carbon dioxide and water flux
database Walnut Gulch Experimental Watershed, Arizona, United States, Water Resour. Res., 44, W05S09, https://doi.org/10.1029/2006WR005693, 2008.
English, S. J., Renshaw, R. J., Dibben, P. C., Smith, A. J., Rayer, P. J.,
Poulsen, C., Saunders, F. W., and Eyre, J. R.: A comparison of the impact of
TOVS and ATOVS satellite sounding data on the accuracy of numerical weather
forecasts, Q. J. Roy. Meteor. Soc., 126, 2911–2931, 2000.
Ermida, S. L., Trigo, I. F., Dacamara, C. C., Göttsche, F. M., Olesen,
F. S., and Hulley, G.: Validation of remotely sensed surface temperature over an
oak woodland landscape – The problem of viewing and illumination
geometries, Remote Sens. Environ., 148, 16–27, 2014.
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. Hydrometeorol., 4, 530–543, 2003.
Fan, Y. and van den Dool, H.: Climate Prediction Center global monthly soil
moisture data set at 0.5∘ resolution for 1948 to present, J.
Geophys. Res., 109, D10102, https://doi.org/10.1029/2003JD004345, 2004.
Fiebrich, C. A., Martinez, J. E., Brotzge, J. A., and Basara, J. B.: The
Oklahoma Mesonet's skin temperature network, J. Atmos. Ocean. Tech., 20,
1496–1504, 2003.
Foken, T.: The energy balance closure problem: an overview, Ecol. Appl., 18, 1351–1367, 2008.
Fry, J., Xian, G., Jin, S., Dewitz, J., Homer, C., Yang, L., Barnes, C.,
Herold, N., and Wickham, J.: Completion of the 2006 National Land Cover
Database for the Conterminous United States, Photogramm. Eng. Rem. S., 77, 858–864, 2011.
Gentine, P., Entekhabi, D., and Heusinkveld, B.: Systematic errors in ground
heat flux estimation and their correction, Water Resour. Res., 48, W09541,
https://doi.org/10.1029/2010WR010203, 2012.
Ghent, D., Dodd, E., Trigo, I., Pires, A., Sardou, O., Bruniquel, J.,
Gottsche, F., Martin, M., Prigent, C., Jimenez, C., and Remedios, J.: ESA DUE
GlobTemperature product user guide V2, available at:
http://www.globtemperature.info (last access: 11 September 2018), 2016.
Guedj, S., Karbou, F., and Rabier, F.: Land surface temperature estimation
to improve the assimilation of SEVIRI radiances over land, J. Geophys. Res.,
116, D14107, https://doi.org/10.1029/2011JD015776, 2011.
Hanley, K. E., Barrett, A. I., and Lean, H. W.: Simulating the 20 May 2013
Moore, Oklahoma tornado with a 10-metre grid-length NWP model, Atmos. Sci.
Lett., 17, 453–461, 2016.
Harper, A. B., Cox, P. M., Friedlingstein, P., Wiltshire, A. J., Jones, C.
D., Sitch, S., Mercado, L. M., Groenendijk, M., Robertson, E., Kattge, J.,
Bönisch, G., Atkin, O. K., Bahn, M., Cornelissen, J., Niinemets, Ü.,
Onipchenko, V., Peñuelas, J., Poorter, L., Reich, P. B., Soudzilovskaia, N.
A., and Bodegom, P. V.: Improved representation of plant functional types and
physiology in the Joint UK Land Environment Simulator (JULES v4.2) using
plant trait information, Geosci. Model Dev., 9, 2415–2440,
https://doi.org/10.5194/gmd-9-2415-2016, 2016.
Harris, B. A. and Kelly, G.: A satellite radiance-bias correction scheme
for data assimilation, Q. J. Roy. Meteor. Soc., 127, 1453–1468, 2001.
Havemann, S.: The development of a fast radiative transfer model based on an
empirical orthogonal functions (EOF) technique, Proc. SPIE, 6405, 64050M,
https://doi.org/10.1117/12.693995, 2006.
Henderson-Sellers, A., Yang, Z., and Dickinson, R. E.: The Project for
Intercomparison of Landsurface Parameterization Schemes, B. Am. Meteorol.
Soc., 74, 1335–1350, https://doi.org/10.1175/1520-0477(1993)074<1335:TPFIOL>2.0.CO;2,
1993.
Hilton, F.: Hyperspectral Earth observation from IASI: Five years of
accomplishments, B. Am. Meteorol. Soc., 93, 347–370,
https://doi.org/10.1175/BAMS-D-11-00027.1, 2012.
Hu, L., Brunsell, N. A., Monaghan, A. J., Barlage, M., and Wilhelmi, O. V.:
How can we use MODIS land surface temperature to validate long-term urban
model simulations?, J. Geophys. Res.-Atmos., 119, 3185–3201, 2014.
Kasahara, A., Mizzi, A. P., and Donner, L. J.: Impact of Cumulus
Initialization on the Spinup of Precipitation Forecasts in the Tropics, Mon. Weather Rev., 120, 1360–1380, 1992.
Kerr, Y. H., Lagouarde, J. P., Nerry, F., and Ottlé, C.: Land surface
temperature retrieval techniques and applications, Thermal remote sensing in
land surface processes, CRC Press, Boca Raton, Florida, 33–109, 2000.
Li, Z., Tang, B., Wu, H., Ren, H., Yan, G., Wan, Z., Trigo, I. F., and
Sobrino, J.: Satellite-derived land surface temperature: Current status and
perspectives, Remote Sens. Environ., 131, 14–37, 2013.
Manners, J., Vosper, S. B., and Roberts, N.: Radiative transfer over
resolved topographic features for high-resolution weather prediction, Q. J.
Roy. Meteor. Soc., 138, 720–733, https://doi.org/10.1002/qj.956, 2012.
Monin, A. S. and Obukhov, A. M.: Basic laws of turbulent mixing in the
surface layer of the atmosphere, Contrib. Geophys. Inst. Acad. Sci. USSR,
151, 163–187, 1954.
Myneni, R., Knyazikhin, Y., and Park, T.: MOD15A2H MODIS/Terra Leaf Area
Index/FPAR 8-Day L4 Global 500 m SIN Grid V006 [Data set], NASA EOSDIS Land
Processes DAAC, https://doi.org/10.5067/MODIS/MOD15A2H.006, 2015.
Newman, S. M., Smith, J. A., Glew, M. D., Rogers, S. M., and Taylor, J. P.:
Temperature and salinity dependence of sea surface emissivity in the thermal
infrared, Q. J. Roy. Meteor. Soc., 131, 2539–2557, https://doi.org/10.1256/qj.04.150,
2005.
Ogawa, K., Schmugge, T., and Jacob, F., Estimation of land surface window
(8–12 µm) emissivity from multispectral thermal infrared remote
sensing: A case study in a part of Sahara Desert, Geophys. Res. Lett., 30,
1067, https://doi.org/10.1029/2003GL016354, 2003.
Oke, T. R.: Boundary layer climates, Routledge, London, New York, p. 435,
1987.
Pavelin, E. G. and Candy, B.: Assimilation of surface-sensitive infrared
radiances over land: Estimation of land surface temperature and emissivity, Q. J. Roy. Meteor. Soc., 140, 1198–1208, https://doi.org/10.1002/qj.2218, 2014.
Poulter, B., MacBean, N., Hartley, A., Khlystova, I., Arino, O., Betts, R.,
Bontemps, S., Boettcher, M., Brockmann, C., Defourny, P., Hagemann, S.,
Herold, M., Kirches, G., Lamarche, C., Lederer, D., Ottlé, C., Peters, M.,
and Peylin, P.: Plant functional type classification for earth system models:
results from the European Space Agency's Land Cover Climate Change
Initiative, Geosci. Model Dev., 8, 2315–2328, https://doi.org/10.5194/gmd-8-2315-2015,
2015.
Prince, S. D., Goetz, S. J., Dubayah, R. O., Czajkowski, K. P., and Thawley,
M.: Inference of surface and air temperature, atmospheric precipitable water
and vapor pressure deficit using advanced very high-resolution radiometer
satellite observations: Comparison with field observations, J. Hydrol., 213,
230–29, 1998.
Rabier, F.: Overview of global data assimilation developments in numerical
weather-prediction centres, Q. J. Roy. Meteor. Soc., 131, 3215–3233,
https://doi.org/10.1256/qj.05.129, 2005.
Rasmussen, M. O., Pinheiro, A. C., Proud, S. R., and Sandholt, I.: Modeling
Angular Dependences in Land Surface Temperatures From the SEVIRI Instrument
Onboard the Geostationary Meteosat Second Generation Satellites, IEEE T.
Geosci. Remote, 48, 3123–3133, 2010.
Ritchie, J. C., Nearing, M. A., Nichols, M. H., and Ritchie, C. A.: Patterns
of soil erosion and redeposition on Lucky Hills Watershed, Walnut Gulch
Experimental Watershed, Arizona, Catena, 61, 122–130, 2005.
Rowntree, P. R.: Atmospheric parameterization schemes for evaporation over
land: Basic concepts and climate modelling aspects, in: Land Surface
Evaporation: Measurement and Parameterization, edited by: Schmugge, T. J. and Andre, J. C., 5–29, Springer Verlag, New York, 1991.
Scott, R. L., Jenerette, G. D., Potts, D. L., and Huxman, T. E.: Effects of
seasonal drought on net carbon dioxide exchange from a
woody-plant-encroached semiarid grassland, J. Geophys. Res.-Biogeo, 114, G04004, https://doi.org/10.1029/2008JG000900, 2009.
Scott, R. L., Hamerlynck, E. P., Jenerette, G. D., Moran, M. S., and
Barron-Gafford, G. A.: Carbon dioxide exchange in a semidesert grassland
through drought-induced vegetation change, J. Geophys. Res., 115, G03026, https://doi.org/10.1029/2010JG001348, 2010.
Scott, R. L., Biederman, J. A., Hamerlynck, E. P., and Barron-Gafford, G.
A.: The carbon balance pivot point of southwestern U.S. semiarid ecosystems:
Insights from the 21st century drought, J. Geophys. Res.-Biogeo., 120,
2612–2624, 2015.
Trigo, I. F., Boussetta, S., Viterbo, P., Balsamo, G., Beljaars, A., and
Sandu, I.: Comparison of model land skin temperature with remotely sensed
estimates and assessment of surface-atmosphere coupling, J. Geophys.
Res.-Atmos., 120, 12096–12111, https://doi.org/10.1002/2015JD023812, 2015.
Twine, T. E., Kustas, W. P., Norman, J. M., Cook, D. R., Houser, P. R., Meyers,
T. P., Prueger, J. H., Starks, P. J., and Wesely, M. L.: Correcting
eddy-covariance flux underestimates over a grassland, Agr. Forest Meteorol., 103, 279–300, 2000.
Ukkola, A. M., De Kauwe, M. G., Pitman, A. J., Best, M. J., Abramowitz, G.,
Haverd, V., Decker, M., and Haughton, N.: Land surface models systematically
overestimate the intensity, duration and magnitude of seasonal-scale
evaporative droughts, Environ. Res. Lett., 11, 104012,
https://doi.org/10.1088/1748-9326/11/10/104012, 2016.
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., Webster, S., Wilkinson, J. M., 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.
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., Hardiman, S. C., 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. L.: 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.
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.
Wan, Z.: MODIS land-surface temperature algorithm theoretical basis document
(LST ATBD), Version 3.3, University of California, Santa Barbara, 1999.
Wan, Z.: New refinements and validation of the collection-6 MODIS
land-surface temperature/emissivity product, Remote Sens. Environ., 140, 36–45, 2014.
Wan, Z. and Dozier, J.: A generalized split-window algorithm for retrieving
land-surface temperature from space, IEEE T. Geosci. Remote, 34, 892–905, 1996.
Wan, Z.: MODIS land-surface temperature algorithm theoretical basis document
(LST ATBD), Version 3.3, University of California, Santa Barbara, 1999.
Wan, Z., Zhanga, Y., Zhanga Q., and Lib, Z. L.: Quality assessment and
validation of the MODIS global land surface temperature, Int. J. Remote Sens., 25, 261–274, 2004.
Wang, K., Wan, Z.,Wang, P., Sparrow, M., Liu, J., and Haginoya, S.:
Evaluation and improvement of the MODIS land surface temperature/emissivity
products using ground-based measurements at a semi-desert site on the
western Tibetan Plateau, Int. J. Remote Sens., 28,
2549–2565, 2007.
Weltz, M. A., Ritchie, J. C., and Fox, H. D.: Comparison of laser and field
measurements of vegetation heights and canopy cover, Water Resour. Res., 30, 1311–1319, 1994.
Wilson, K., Goldstein, A., Falge, E., Aubinet, M., Baldocchi, D., Berbigier,
P., Bernhofer, C., Ceulemans, R., Dolman, H., Field, C., Grelle, A., Ibrom,
A., Law, B. E., Kowalski, A., Meyers, T., Moncrieff, J., Monson, R., Oechel,
W., Tenhunen, J., Valentini, R., and Verma, S.: Energy balance closure at
FLUXNET sites, Agr. Forest Meteorol., 113, 223–243, 2002.
Zheng, W., Wei, H., Wang, Z., Zeng, X., Meng, J., Ek, M., Mitchell, K., and
Derber, J.: Improvement of daytime land surface skin temperature over arid
regions in the NCEP GFS model and its impact on satellite data assimilation,
J. Geophys. Res., 117, DO6117, https://doi.org/10.1029/2011JD015901, 2012.
Zhu, Y., Derber, J., Collard, A., Dee, D., Treadon, R., Gayno, G., and Jung,
J. A.: Enhanced radiance bias correction in the National Centers for
Environmental Prediction's Gridpoint Statistical Interpolation data
assimilation system, Q. J. Roy. Meteor. Soc., 140, 1479–1492, https://doi.org/10.1002/qj.2233, 2014.
Short summary
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.
This paper evaluates a significant cold land surface temperature bias in semi-arid regions in...
