Articles | Volume 15, issue 1
https://doi.org/10.5194/gmd-15-45-2022
© Author(s) 2022. 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-15-45-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
06 Jan 2022
Development and technical paper |
| 06 Jan 2022
| 06 Jan 2022
WOMBAT v1.0: a fully Bayesian global flux-inversion framework
School of Mathematics and Applied Statistics, University of Wollongong, Wollongong, Australia
Michael Bertolacci
School of Mathematics and Applied Statistics, University of Wollongong, Wollongong, Australia
Jenny Fisher
School of Earth and Life Sciences, University of Wollongong, Wollongong, Australia
Ann Stavert
Climate Science Centre, CSIRO Oceans and Atmosphere, Aspendale, Australia
Matthew Rigby
School of Chemistry, University of Bristol, Bristol, UK
Yi Cao
School of Mathematics and Applied Statistics, University of Wollongong, Wollongong, Australia
Noel Cressie
School of Mathematics and Applied Statistics, University of Wollongong, Wollongong, Australia
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Jan C. Minx, William F. Lamb, Robbie M. Andrew, Josep G. Canadell, Monica Crippa, Niklas Döbbeling, Piers M. Forster, Diego Guizzardi, Jos Olivier, Glen P. Peters, Julia Pongratz, Andy Reisinger, Matthew Rigby, Marielle Saunois, Steven J. Smith, Efisio Solazzo, and Hanqin Tian
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Daniel Say, Alistair J. Manning, Luke M. Western, Dickon Young, Adam Wisher, Matthew Rigby, Stefan Reimann, Martin K. Vollmer, Michela Maione, Jgor Arduini, Paul B. Krummel, Jens Mühle, Christina M. Harth, Brendan Evans, Ray F. Weiss, Ronald G. Prinn, and Simon O'Doherty
Atmos. Chem. Phys., 21, 2149–2164, https://doi.org/10.5194/acp-21-2149-2021, https://doi.org/10.5194/acp-21-2149-2021, 2021
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Angharad C. Stell, Luke M. Western, Tomás Sherwen, and Matthew Rigby
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Atmos. Chem. Phys., 20, 12813–12851, https://doi.org/10.5194/acp-20-12813-2020, https://doi.org/10.5194/acp-20-12813-2020, 2020
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Guillaume Monteil, Grégoire Broquet, Marko Scholze, Matthew Lang, Ute Karstens, Christoph Gerbig, Frank-Thomas Koch, Naomi E. Smith, Rona L. Thompson, Ingrid T. Luijkx, Emily White, Antoon Meesters, Philippe Ciais, Anita L. Ganesan, Alistair Manning, Michael Mischurow, Wouter Peters, Philippe Peylin, Jerôme Tarniewicz, Matt Rigby, Christian Rödenbeck, Alex Vermeulen, and Evie M. Walton
Atmos. Chem. Phys., 20, 12063–12091, https://doi.org/10.5194/acp-20-12063-2020, https://doi.org/10.5194/acp-20-12063-2020, 2020
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Marielle Saunois, Ann R. Stavert, Ben Poulter, Philippe Bousquet, Josep G. Canadell, Robert B. Jackson, Peter A. Raymond, Edward J. Dlugokencky, Sander Houweling, Prabir K. Patra, Philippe Ciais, Vivek K. Arora, David Bastviken, Peter Bergamaschi, Donald R. Blake, Gordon Brailsford, Lori Bruhwiler, Kimberly M. Carlson, Mark Carrol, Simona Castaldi, Naveen Chandra, Cyril Crevoisier, Patrick M. Crill, Kristofer Covey, Charles L. Curry, Giuseppe Etiope, Christian Frankenberg, Nicola Gedney, Michaela I. Hegglin, Lena Höglund-Isaksson, Gustaf Hugelius, Misa Ishizawa, Akihiko Ito, Greet Janssens-Maenhout, Katherine M. Jensen, Fortunat Joos, Thomas Kleinen, Paul B. Krummel, Ray L. Langenfelds, Goulven G. Laruelle, Licheng Liu, Toshinobu Machida, Shamil Maksyutov, Kyle C. McDonald, Joe McNorton, Paul A. Miller, Joe R. Melton, Isamu Morino, Jurek Müller, Fabiola Murguia-Flores, Vaishali Naik, Yosuke Niwa, Sergio Noce, Simon O'Doherty, Robert J. Parker, Changhui Peng, Shushi Peng, Glen P. Peters, Catherine Prigent, Ronald Prinn, Michel Ramonet, Pierre Regnier, William J. Riley, Judith A. Rosentreter, Arjo Segers, Isobel J. Simpson, Hao Shi, Steven J. Smith, L. Paul Steele, Brett F. Thornton, Hanqin Tian, Yasunori Tohjima, Francesco N. Tubiello, Aki Tsuruta, Nicolas Viovy, Apostolos Voulgarakis, Thomas S. Weber, Michiel van Weele, Guido R. van der Werf, Ray F. Weiss, Doug Worthy, Debra Wunch, Yi Yin, Yukio Yoshida, Wenxin Zhang, Zhen Zhang, Yuanhong Zhao, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data, 12, 1561–1623, https://doi.org/10.5194/essd-12-1561-2020, https://doi.org/10.5194/essd-12-1561-2020, 2020
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Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. We have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. This is the second version of the review dedicated to the decadal methane budget, integrating results of top-down and bottom-up estimates.
Peter G. Simmonds, Matthew Rigby, Alistair J. Manning, Sunyoung Park, Kieran M. Stanley, Archie McCulloch, Stephan Henne, Francesco Graziosi, Michela Maione, Jgor Arduini, Stefan Reimann, Martin K. Vollmer, Jens Mühle, Simon O'Doherty, Dickon Young, Paul B. Krummel, Paul J. Fraser, Ray F. Weiss, Peter K. Salameh, Christina M. Harth, Mi-Kyung Park, Hyeri Park, Tim Arnold, Chris Rennick, L. Paul Steele, Blagoj Mitrevski, Ray H. J. Wang, and Ronald G. Prinn
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Geosci. Model Dev., 13, 2095–2107, https://doi.org/10.5194/gmd-13-2095-2020, https://doi.org/10.5194/gmd-13-2095-2020, 2020
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Assessments of greenhouse gas emissions using atmospheric measurements and meteorological models, or
top-downmethods, are important to verify national inventories or produce a stand-alone estimate where no inventory exists. We present a novel top-down method to estimate emissions. This approach uses a fast method called an integrated nested Laplacian approximation to estimate how these emissions are correlated with other emissions in different locations and at different times.
Becky Alexander, Tomás Sherwen, Christopher D. Holmes, Jenny A. Fisher, Qianjie Chen, Mat J. Evans, and Prasad Kasibhatla
Atmos. Chem. Phys., 20, 3859–3877, https://doi.org/10.5194/acp-20-3859-2020, https://doi.org/10.5194/acp-20-3859-2020, 2020
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Nitrogen oxides are important for the formation of tropospheric oxidants and are removed from the atmosphere mainly through the formation of nitrate. We compare observations of the oxygen isotopes of nitrate with a global model to test our understanding of the chemistry nitrate formation. We use the model to quantify nitrate formation pathways in the atmosphere and identify key uncertainties and their relevance for the oxidation capacity of the atmosphere.
Angelina Wenger, Katherine Pugsley, Simon O'Doherty, Matt Rigby, Alistair J. Manning, Mark F. Lunt, and Emily D. White
Atmos. Chem. Phys., 19, 14057–14070, https://doi.org/10.5194/acp-19-14057-2019, https://doi.org/10.5194/acp-19-14057-2019, 2019
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We present 14CO2 observations at a background site in Ireland and a tall tower site in the UK. These data have been used to calculate the contribution of fossil fuel sources to atmospheric CO2 mole fractions from the UK and Ireland. 14CO2 emissions from nuclear industry sites in the UK cause a higher uncertainty in the results compared to observations in other locations. The observed ffCO2 at the site was not significantly different from simulated values based on the bottom-up inventory.
Yuanhong Zhao, Marielle Saunois, Philippe Bousquet, Xin Lin, Antoine Berchet, Michaela I. Hegglin, Josep G. Canadell, Robert B. Jackson, Didier A. Hauglustaine, Sophie Szopa, Ann R. Stavert, Nathan Luke Abraham, Alex T. Archibald, Slimane Bekki, Makoto Deushi, Patrick Jöckel, Béatrice Josse, Douglas Kinnison, Ole Kirner, Virginie Marécal, Fiona M. O'Connor, David A. Plummer, Laura E. Revell, Eugene Rozanov, Andrea Stenke, Sarah Strode, Simone Tilmes, Edward J. Dlugokencky, and Bo Zheng
Atmos. Chem. Phys., 19, 13701–13723, https://doi.org/10.5194/acp-19-13701-2019, https://doi.org/10.5194/acp-19-13701-2019, 2019
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The role of hydroxyl radical changes in methane trends is debated, hindering our understanding of the methane cycle. This study quantifies how uncertainties in the hydroxyl radical may influence methane abundance in the atmosphere based on the inter-model comparison of hydroxyl radical fields and model simulations of CH4 abundance with different hydroxyl radical scenarios during 2000–2016. We show that hydroxyl radical changes could contribute up to 54 % of model-simulated methane biases.
Laura Cartwright, Andrew Zammit-Mangion, Sangeeta Bhatia, Ivan Schroder, Frances Phillips, Trevor Coates, Karita Negandhi, Travis Naylor, Martin Kennedy, Steve Zegelin, Nick Wokker, Nicholas M. Deutscher, and Andrew Feitz
Atmos. Meas. Tech., 12, 4659–4676, https://doi.org/10.5194/amt-12-4659-2019, https://doi.org/10.5194/amt-12-4659-2019, 2019
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Despite extensive research, emission detection and quantification of greenhouse gases (GHGs) remain an open problem. This article presents a novel statistical framework for detecting and quantifying methane emissions and showcases its efficacy on data collected from different instruments in the 2015 Ginninderra controlled-release experiment. The developed techniques can be used to aid GHG emission reduction schemes by, for example, detecting and quantifying leaks from carbon storage facilities.
Ann R. Stavert, Simon O'Doherty, Kieran Stanley, Dickon Young, Alistair J. Manning, Mark F. Lunt, Christopher Rennick, and Tim Arnold
Atmos. Meas. Tech., 12, 4495–4518, https://doi.org/10.5194/amt-12-4495-2019, https://doi.org/10.5194/amt-12-4495-2019, 2019
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Under the UK GAUGE project, two new greenhouse gas observation sites were established in the 2013/2014 winter at two telecommunications towers. A combination of spectroscopic and chromatographic instrumentation was used to measure CO2, CH4, CO, N2O and SF6. The advantages and disadvantages of two CRDS sample drying strategies, Nafion(R) and empirical water correction, were also examined.
Jens Mühle, Cathy M. Trudinger, Luke M. Western, Matthew Rigby, Martin K. Vollmer, Sunyoung Park, Alistair J. Manning, Daniel Say, Anita Ganesan, L. Paul Steele, Diane J. Ivy, Tim Arnold, Shanlan Li, Andreas Stohl, Christina M. Harth, Peter K. Salameh, Archie McCulloch, Simon O'Doherty, Mi-Kyung Park, Chun Ok Jo, Dickon Young, Kieran M. Stanley, Paul B. Krummel, Blagoj Mitrevski, Ove Hermansen, Chris Lunder, Nikolaos Evangeliou, Bo Yao, Jooil Kim, Benjamin Hmiel, Christo Buizert, Vasilii V. Petrenko, Jgor Arduini, Michela Maione, David M. Etheridge, Eleni Michalopoulou, Mike Czerniak, Jeffrey P. Severinghaus, Stefan Reimann, Peter G. Simmonds, Paul J. Fraser, Ronald G. Prinn, and Ray F. Weiss
Atmos. Chem. Phys., 19, 10335–10359, https://doi.org/10.5194/acp-19-10335-2019, https://doi.org/10.5194/acp-19-10335-2019, 2019
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We discuss atmospheric concentrations and emissions of the strong greenhouse gas perfluorocyclobutane. A large fraction of recent emissions stem from China, India, and Russia, probably as a by-product from the production of fluoropolymers and fluorochemicals. Most historic emissions likely stem from developed countries. Total emissions are higher than what is being reported. Clearly, more measurements and better reporting are needed to understand emissions of this and other greenhouse gases.
Daniel Say, Anita L. Ganesan, Mark F. Lunt, Matthew Rigby, Simon O'Doherty, Christina Harth, Alistair J. Manning, Paul B. Krummel, and Stephane Bauguitte
Atmos. Chem. Phys., 19, 9865–9885, https://doi.org/10.5194/acp-19-9865-2019, https://doi.org/10.5194/acp-19-9865-2019, 2019
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Despite its emergence as a global economic power, very little information exists regarding India's halocarbon (CFC, HCFC, HFC and chlorocarbon) emissions. We report atmospheric measurements of these gases from above India, and use them to estimate India's emissions. Our results are consistent with the emissions profile of a developing country, with large emissions of HCFCs, HFCs and chlorocarbons not regulated under the Montreal Protocol, but little evidence for ongoing CFC consumption.
Beata Bukosa, Nicholas M. Deutscher, Jenny A. Fisher, Dagmar Kubistin, Clare Paton-Walsh, and David W. T. Griffith
Atmos. Chem. Phys., 19, 7055–7072, https://doi.org/10.5194/acp-19-7055-2019, https://doi.org/10.5194/acp-19-7055-2019, 2019
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The carbon greenhouse gases (CO2, CH4 and CO) were proven to have a large impact on the global carbon cycle and our climate. To understand the variability of the carbon cycle and predict future climate change scenarios, we need to study the processes that drive the changes of these gases in the atmosphere. We study the sources and sinks of CO2, CH4 and CO with a combination of measurements and chemical transport modelling to identify missing, underestimated or overestimated sources in Australia.
Emily D. White, Matthew Rigby, Mark F. Lunt, T. Luke Smallman, Edward Comyn-Platt, Alistair J. Manning, Anita L. Ganesan, Simon O'Doherty, Ann R. Stavert, Kieran Stanley, Mathew Williams, Peter Levy, Michel Ramonet, Grant L. Forster, Andrew C. Manning, and Paul I. Palmer
Atmos. Chem. Phys., 19, 4345–4365, https://doi.org/10.5194/acp-19-4345-2019, https://doi.org/10.5194/acp-19-4345-2019, 2019
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Understanding carbon dioxide (CO2) fluxes from the terrestrial biosphere on a national scale is important for evaluating land use strategies to mitigate climate change. We estimate emissions of CO2 from the UK biosphere using atmospheric data in a top-down approach. Our findings show that bottom-up estimates from models of biospheric fluxes overestimate the amount of CO2 uptake in summer. This suggests these models wrongly estimate or omit key processes, e.g. land disturbance due to harvest.
Debra Wunch, Dylan B. A. Jones, Geoffrey C. Toon, Nicholas M. Deutscher, Frank Hase, Justus Notholt, Ralf Sussmann, Thorsten Warneke, Jeroen Kuenen, Hugo Denier van der Gon, Jenny A. Fisher, and Joannes D. Maasakkers
Atmos. Chem. Phys., 19, 3963–3980, https://doi.org/10.5194/acp-19-3963-2019, https://doi.org/10.5194/acp-19-3963-2019, 2019
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We used five atmospheric observatories in Europe measuring total column dry-air mole fractions of methane and carbon monoxide to infer methane emissions in the area between the observatories. We find that the methane emissions are overestimated by the state-of-the-art inventories, and that this is likely due, at least in part, to the inventory disaggregation. We find that there is significant uncertainty in the carbon monoxide inventories that requires further investigation.
Kieran Brophy, Heather Graven, Alistair J. Manning, Emily White, Tim Arnold, Marc L. Fischer, Seongeun Jeong, Xinguang Cui, and Matthew Rigby
Atmos. Chem. Phys., 19, 2991–3006, https://doi.org/10.5194/acp-19-2991-2019, https://doi.org/10.5194/acp-19-2991-2019, 2019
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We investigate potential errors and uncertainties related to the spatial and temporal prior representation of emissions and modelled atmospheric transport for the inversion of California's fossil fuel CO2 emissions. Our results indicate that uncertainties in posterior total state fossil fuel CO2 estimates arising from the choice of prior emissions or atmospheric transport model are on the order of 15 % or less for the ground-based network in California we consider.
Daniel Say, Anita L. Ganesan, Mark F. Lunt, Matthew Rigby, Simon O'Doherty, Chris Harth, Alistair J. Manning, Paul B. Krummel, and Stephane Bauguitte
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2018-1287, https://doi.org/10.5194/acp-2018-1287, 2019
Publication in ACP not foreseen
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India is a potentially significant source of chlorocarbons, gases typically used as solvents and feedstocks. Given the potential for these species to deplete stratospheric ozone, understanding their sources is important. We use flask measurements collected from an aircraft to infer India's chlorocarbon emissions. We link emissions of carbon tetrachloride to the industrial production of other chloromethanes, and provide evidence for rapid growth in India's emissions of dichloromethane.
Ann R. Stavert, Rachel M. Law, Marcel van der Schoot, Ray L. Langenfelds, Darren A. Spencer, Paul B. Krummel, Scott D. Chambers, Alistair G. Williams, Sylvester Werczynski, Roger J. Francey, and Russell T. Howden
Atmos. Meas. Tech., 12, 1103–1121, https://doi.org/10.5194/amt-12-1103-2019, https://doi.org/10.5194/amt-12-1103-2019, 2019
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The Southern Ocean is a key sink of carbon dioxide (CO2), but efforts to study trends in and the variability of the sink have been hindered by the limited number of CO2 measurements in this region. Here we describe a set of new in situ continuous (minutely) atmospheric CO2 observations. We show that this new record better captures long-term changes and seasonality than traditional 2-weekly flask records. As such, this data set will provide key insights into the changing Southern Ocean sink.
Sarah Connors, Alistair J. Manning, Andrew D. Robinson, Stuart N. Riddick, Grant L. Forster, Anita Ganesan, Aoife Grant, Stephen Humphrey, Simon O'Doherty, Dave E. Oram, Paul I. Palmer, Robert L. Skelton, Kieran Stanley, Ann Stavert, Dickon Young, and Neil R. P. Harris
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2018-1187, https://doi.org/10.5194/acp-2018-1187, 2018
Preprint withdrawn
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Methane is an important greenhouse gas & reducing its emissions is a vital part of climate change mitigation to limit global temperature increase to 1.5 °C or 2.0 °C. This paper explains a way to estimate emitted methane over a sub-national area by combining measurements & computer dispersion modelling in a so-called
inversiontechnique. Compared with the current national inventory, our results show lower emissions for Cambridgeshire, possibly due to waste sector emission differences.
Paul I. Palmer, Simon O'Doherty, Grant Allen, Keith Bower, Hartmut Bösch, Martyn P. Chipperfield, Sarah Connors, Sandip Dhomse, Liang Feng, Douglas P. Finch, Martin W. Gallagher, Emanuel Gloor, Siegfried Gonzi, Neil R. P. Harris, Carole Helfter, Neil Humpage, Brian Kerridge, Diane Knappett, Roderic L. Jones, Michael Le Breton, Mark F. Lunt, Alistair J. Manning, Stephan Matthiesen, Jennifer B. A. Muller, Neil Mullinger, Eiko Nemitz, Sebastian O'Shea, Robert J. Parker, Carl J. Percival, Joseph Pitt, Stuart N. Riddick, Matthew Rigby, Harjinder Sembhi, Richard Siddans, Robert L. Skelton, Paul Smith, Hannah Sonderfeld, Kieran Stanley, Ann R. Stavert, Angelina Wenger, Emily White, Christopher Wilson, and Dickon Young
Atmos. Chem. Phys., 18, 11753–11777, https://doi.org/10.5194/acp-18-11753-2018, https://doi.org/10.5194/acp-18-11753-2018, 2018
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This paper provides an overview of the Greenhouse gAs Uk and Global Emissions (GAUGE) experiment. GAUGE was designed to quantify nationwide GHG emissions of the UK, bringing together measurements and atmospheric transport models. This novel experiment is the first of its kind. We anticipate it will inform the blueprint for countries that are building a measurement infrastructure in preparation for global stocktakes, which are a key part of the Paris Agreement.
Ronald G. Prinn, Ray F. Weiss, Jgor Arduini, Tim Arnold, H. Langley DeWitt, Paul J. Fraser, Anita L. Ganesan, Jimmy Gasore, Christina M. Harth, Ove Hermansen, Jooil Kim, Paul B. Krummel, Shanlan Li, Zoë M. Loh, Chris R. Lunder, Michela Maione, Alistair J. Manning, Ben R. Miller, Blagoj Mitrevski, Jens Mühle, Simon O'Doherty, Sunyoung Park, Stefan Reimann, Matt Rigby, Takuya Saito, Peter K. Salameh, Roland Schmidt, Peter G. Simmonds, L. Paul Steele, Martin K. Vollmer, Ray H. Wang, Bo Yao, Yoko Yokouchi, Dickon Young, and Lingxi Zhou
Earth Syst. Sci. Data, 10, 985–1018, https://doi.org/10.5194/essd-10-985-2018, https://doi.org/10.5194/essd-10-985-2018, 2018
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We present the data and accomplishments of the multinational global atmospheric measurement program AGAGE (Advanced Global Atmospheric Gases Experiment). At high frequency and at multiple sites, AGAGE measures all the important chemicals in the Montreal Protocol for the protection of the ozone layer and the non-carbon-dioxide gases assessed by the Intergovernmental Panel on Climate Change. AGAGE uses these data to estimate sources and sinks of all these gases and has operated since 1978.
Jennifer Kaiser, Daniel J. Jacob, Lei Zhu, Katherine R. Travis, Jenny A. Fisher, Gonzalo González Abad, Lin Zhang, Xuesong Zhang, Alan Fried, John D. Crounse, Jason M. St. Clair, and Armin Wisthaler
Atmos. Chem. Phys., 18, 5483–5497, https://doi.org/10.5194/acp-18-5483-2018, https://doi.org/10.5194/acp-18-5483-2018, 2018
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Isoprene emissions from vegetation have a large effect on atmospheric chemistry and air quality. Here we use the adjoint of GEOS-Chem in an inversion of OMI formaldehyde observations to produce top-down estimates of isoprene emissions in the southeast US during the summer of 2013. We find that MEGAN v2.1 is biased high on average by 40 %. Our downward correction of isoprene emissions leads to a small reduction in modeled surface O3 and decreases the contribution of isoprene to organic aerosol.
Peter G. Simmonds, Matthew Rigby, Archie McCulloch, Martin K. Vollmer, Stephan Henne, Jens Mühle, Simon O'Doherty, Alistair J. Manning, Paul B. Krummel, Paul J. Fraser, Dickon Young, Ray F. Weiss, Peter K. Salameh, Christina M. Harth, Stefan Reimann, Cathy M. Trudinger, L. Paul Steele, Ray H. J. Wang, Diane J. Ivy, Ronald G. Prinn, Blagoj Mitrevski, and David M. Etheridge
Atmos. Chem. Phys., 18, 4153–4169, https://doi.org/10.5194/acp-18-4153-2018, https://doi.org/10.5194/acp-18-4153-2018, 2018
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Recent measurements of the potent greenhouse gas HFC-23, a by-product of HCFC-22 production, show a 28 % increase in the atmospheric mole fraction from 2009 to 2016. A minimum in the atmospheric abundance of HFC-23 in 2009 was attributed to abatement of HFC-23 emissions by incineration under the Clean Development Mechanism (CDM). Our results indicate that the recent increase in HFC-23 emissions is driven by failure of mitigation under the CDM to keep pace with increased HCFC-22 production.
Kieran M. Stanley, Aoife Grant, Simon O'Doherty, Dickon Young, Alistair J. Manning, Ann R. Stavert, T. Gerard Spain, Peter K. Salameh, Christina M. Harth, Peter G. Simmonds, William T. Sturges, David E. Oram, and Richard G. Derwent
Atmos. Meas. Tech., 11, 1437–1458, https://doi.org/10.5194/amt-11-1437-2018, https://doi.org/10.5194/amt-11-1437-2018, 2018
Martin K. Vollmer, Dickon Young, Cathy M. Trudinger, Jens Mühle, Stephan Henne, Matthew Rigby, Sunyoung Park, Shanlan Li, Myriam Guillevic, Blagoj Mitrevski, Christina M. Harth, Benjamin R. Miller, Stefan Reimann, Bo Yao, L. Paul Steele, Simon A. Wyss, Chris R. Lunder, Jgor Arduini, Archie McCulloch, Songhao Wu, Tae Siek Rhee, Ray H. J. Wang, Peter K. Salameh, Ove Hermansen, Matthias Hill, Ray L. Langenfelds, Diane Ivy, Simon O'Doherty, Paul B. Krummel, Michela Maione, David M. Etheridge, Lingxi Zhou, Paul J. Fraser, Ronald G. Prinn, Ray F. Weiss, and Peter G. Simmonds
Atmos. Chem. Phys., 18, 979–1002, https://doi.org/10.5194/acp-18-979-2018, https://doi.org/10.5194/acp-18-979-2018, 2018
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We measured the three chlorofluorocarbons (CFCs) CFC-13, CFC-114, and CFC-115 in the atmosphere because they are important in stratospheric ozone depletion. These compounds should have decreased in the atmosphere because they are banned by the Montreal Protocol but we find the opposite. Emissions over the last decade have not declined on a global scale. We use inverse modeling and our observations to find that a large part of the emissions originate in the Asian region.
Jenny A. Fisher, Lee T. Murray, Dylan B. A. Jones, and Nicholas M. Deutscher
Geosci. Model Dev., 10, 4129–4144, https://doi.org/10.5194/gmd-10-4129-2017, https://doi.org/10.5194/gmd-10-4129-2017, 2017
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Carbon monoxide (CO) simulation in atmospheric chemistry models is used for source–receptor analysis, emission inversion, and interpretation of observations. We introduce a major update to CO simulation in the GEOS-Chem chemical transport model that removes fundamental inconsistencies relative to the standard model, resolving biases of more than 100 ppb and errors in vertical structure. We also add source tagging of secondary CO and demonstrate it provides added value in low-emission regions.
Amy Braverman, Snigdhansu Chatterjee, Megan Heyman, and Noel Cressie
Adv. Stat. Clim. Meteorol. Oceanogr., 3, 93–105, https://doi.org/10.5194/ascmo-3-93-2017, https://doi.org/10.5194/ascmo-3-93-2017, 2017
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In this paper, we introduce a method for expressing the agreement between climate model output time series and time series of observational data as a probability value. Our metric is an estimate of the probability that one would obtain two time series as similar as the ones under consideration, if the climate model and the observed series actually shared the same underlying climate signal.
Dean Howard, Peter F. Nelson, Grant C. Edwards, Anthony L. Morrison, Jenny A. Fisher, Jason Ward, James Harnwell, Marcel van der Schoot, Brad Atkinson, Scott D. Chambers, Alan D. Griffiths, Sylvester Werczynski, and Alastair G. Williams
Atmos. Chem. Phys., 17, 11623–11636, https://doi.org/10.5194/acp-17-11623-2017, https://doi.org/10.5194/acp-17-11623-2017, 2017
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Mercury, a toxic metal, can be transported globally through the atmosphere, with deposition to ecosystems an important pathway to human exposure. 2 years of atmospheric mercury monitoring in tropical Australia supports recent evidence that Southern Hemisphere concentrations are lower than previously thought. Exchange between the atmosphere and ecosystems can take place on daily scales, with night deposition offset by morning re-emission. This could be an important transport pathway for mercury.
Jesse W. Greenslade, Simon P. Alexander, Robyn Schofield, Jenny A. Fisher, and Andrew K. Klekociuk
Atmos. Chem. Phys., 17, 10269–10290, https://doi.org/10.5194/acp-17-10269-2017, https://doi.org/10.5194/acp-17-10269-2017, 2017
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An analysis of data from ozonesondes released at three southern oceanic sites shows the impact of stratospheric ozone in this region. Using a novel method of transport classification, this work estimates the seasonality and quantity of stratospherically sourced ozone. We find that ozone is transported most frequently in summer due to regional-scale low-pressure weather systems. We also estimate a stratospheric ozone source of 2.0–3.3 Tg/year over three Southern Ocean regions.
Christopher Chan Miller, Daniel J. Jacob, Eloise A. Marais, Karen Yu, Katherine R. Travis, Patrick S. Kim, Jenny A. Fisher, Lei Zhu, Glenn M. Wolfe, Thomas F. Hanisco, Frank N. Keutsch, Jennifer Kaiser, Kyung-Eun Min, Steven S. Brown, Rebecca A. Washenfelder, Gonzalo González Abad, and Kelly Chance
Atmos. Chem. Phys., 17, 8725–8738, https://doi.org/10.5194/acp-17-8725-2017, https://doi.org/10.5194/acp-17-8725-2017, 2017
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The use of satellite glyoxal observations for estimating isoprene emissions has been limited by knowledge of the glyoxal yield from isoprene. We use SENEX aircraft observations over the southeast US to evaluate glyoxal yields from isoprene in a 3-D atmospheric model. The SENEX observations support a pathway for glyoxal formation in pristine regions that we propose here, which may have implications for improving isoprene emissions estimates from upcoming high-resolution geostationary satellites.
Peter G. Simmonds, Matthew Rigby, Archie McCulloch, Simon O'Doherty, Dickon Young, Jens Mühle, Paul B. Krummel, Paul Steele, Paul J. Fraser, Alistair J. Manning, Ray F. Weiss, Peter K. Salameh, Chris M. Harth, Ray H. J. Wang, and Ronald G. Prinn
Atmos. Chem. Phys., 17, 4641–4655, https://doi.org/10.5194/acp-17-4641-2017, https://doi.org/10.5194/acp-17-4641-2017, 2017
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This paper reports how long-term atmospheric measurements demonstrate that the Montreal Protocol has been effective in controlling production and consumption of the hydrochlorofluorocarbons, a group of industrial chemicals that have detrimental effects on the ozone layer and also contribute to global warming as greenhouse gases and their hydrofluorocarbon substitutes which are also potent greenhouse gases but do not materially affect the ozone layer.
Martyn P. Chipperfield, Qing Liang, Matthew Rigby, Ryan Hossaini, Stephen A. Montzka, Sandip Dhomse, Wuhu Feng, Ronald G. Prinn, Ray F. Weiss, Christina M. Harth, Peter K. Salameh, Jens Mühle, Simon O'Doherty, Dickon Young, Peter G. Simmonds, Paul B. Krummel, Paul J. Fraser, L. Paul Steele, James D. Happell, Robert C. Rhew, James Butler, Shari A. Yvon-Lewis, Bradley Hall, David Nance, Fred Moore, Ben R. Miller, James W. Elkins, Jeremy J. Harrison, Chris D. Boone, Elliot L. Atlas, and Emmanuel Mahieu
Atmos. Chem. Phys., 16, 15741–15754, https://doi.org/10.5194/acp-16-15741-2016, https://doi.org/10.5194/acp-16-15741-2016, 2016
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Carbon tetrachloride (CCl4) is a compound which, when released into the atmosphere, can cause depletion of the stratospheric ozone layer. Its emissions are controlled under the Montreal Protocol, and its atmospheric abundance is slowly decreasing. However, this decrease is not as fast as expected based on estimates of its emissions and its atmospheric lifetime. We have used an atmospheric model to look at the uncertainties in the CCl4 lifetime and to examine the impact on its atmospheric decay.
Georgina Davies and Noel Cressie
Adv. Stat. Clim. Meteorol. Oceanogr., 2, 155–169, https://doi.org/10.5194/ascmo-2-155-2016, https://doi.org/10.5194/ascmo-2-155-2016, 2016
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Sea surface temperature (SST) is a key component of global climate models, particularly in the tropical Pacific Ocean where El Niño and La Nina events have worldwide implications. In our paper, we analyse monthly SSTs in the Niño 3.4 region and find a transformation that removes a spatial mean-variance dependence for each month. For 10 out of 12 months in the year, the transformed monthly time series gave more accurate or as accurate forecasts than those from the untransformed time series.
Katherine R. Travis, Daniel J. Jacob, Jenny A. Fisher, Patrick S. Kim, Eloise A. Marais, Lei Zhu, Karen Yu, Christopher C. Miller, Robert M. Yantosca, Melissa P. Sulprizio, Anne M. Thompson, Paul O. Wennberg, John D. Crounse, Jason M. St. Clair, Ronald C. Cohen, Joshua L. Laughner, Jack E. Dibb, Samuel R. Hall, Kirk Ullmann, Glenn M. Wolfe, Illana B. Pollack, Jeff Peischl, Jonathan A. Neuman, and Xianliang Zhou
Atmos. Chem. Phys., 16, 13561–13577, https://doi.org/10.5194/acp-16-13561-2016, https://doi.org/10.5194/acp-16-13561-2016, 2016
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Ground-level ozone pollution in the Southeast US involves complex chemistry driven by anthropogenic emissions of nitrogen oxides (NOx) and biogenic emissions of isoprene. We find that US NOx emissions are overestimated nationally by as much as 50 % and that reducing model emissions by this amount results in good agreement with SEAC4RS aircraft measurements in August and September 2013. Observations of nitrate wet deposition fluxes and satellite NO2 columns further support this result.
Lei Zhu, Daniel J. Jacob, Patrick S. Kim, Jenny A. Fisher, Karen Yu, Katherine R. Travis, Loretta J. Mickley, Robert M. Yantosca, Melissa P. Sulprizio, Isabelle De Smedt, Gonzalo González Abad, Kelly Chance, Can Li, Richard Ferrare, Alan Fried, Johnathan W. Hair, Thomas F. Hanisco, Dirk Richter, Amy Jo Scarino, James Walega, Petter Weibring, and Glenn M. Wolfe
Atmos. Chem. Phys., 16, 13477–13490, https://doi.org/10.5194/acp-16-13477-2016, https://doi.org/10.5194/acp-16-13477-2016, 2016
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HCHO column data are widely used as a proxy for VOCs emissions, but validation of the data has been extremely limited. We use accurate aircraft observations to validate and intercompare 6 HCHO retrievals with GEOS-Chem as the intercomparison platform. Retrievals are interconsistent in spatial variability over the SE US and in daily variability, but are biased low by 20–51 %. Our work supports the use of HCHO column as a quantitative proxy for isoprene emission after correction of the low bias.
Cathy M. Trudinger, Paul J. Fraser, David M. Etheridge, William T. Sturges, Martin K. Vollmer, Matt Rigby, Patricia Martinerie, Jens Mühle, David R. Worton, Paul B. Krummel, L. Paul Steele, Benjamin R. Miller, Johannes Laube, Francis S. Mani, Peter J. Rayner, Christina M. Harth, Emmanuel Witrant, Thomas Blunier, Jakob Schwander, Simon O'Doherty, and Mark Battle
Atmos. Chem. Phys., 16, 11733–11754, https://doi.org/10.5194/acp-16-11733-2016, https://doi.org/10.5194/acp-16-11733-2016, 2016
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Perfluorocarbons (PFCs) are potent, long-lived and mostly man-made greenhouse gases released to the atmosphere mainly during aluminium production and semiconductor manufacture. Here we present the first continuous histories of three PFCs from 1800 to 2014, derived from measurements of these PFCs in the atmosphere and in air bubbles in polar ice. The records show how human actions have affected these important greenhouse gases over the past century.
Mark F. Lunt, Matt Rigby, Anita L. Ganesan, and Alistair J. Manning
Geosci. Model Dev., 9, 3213–3229, https://doi.org/10.5194/gmd-9-3213-2016, https://doi.org/10.5194/gmd-9-3213-2016, 2016
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Bayesian inversions can be used to estimate emissions of gases from atmospheric data. We present an inversion framework that objectively defines the basis functions, which describe regions of emissions. The framework allows for the uncertainty in the choice of basis functions to be propagated through to the posterior emissions distribution in a single-step process, and provides an alternative to using a single set of basis functions.
Joe McNorton, Martyn P. Chipperfield, Manuel Gloor, Chris Wilson, Wuhu Feng, Garry D. Hayman, Matt Rigby, Paul B. Krummel, Simon O'Doherty, Ronald G. Prinn, Ray F. Weiss, Dickon Young, Ed Dlugokencky, and Steve A. Montzka
Atmos. Chem. Phys., 16, 7943–7956, https://doi.org/10.5194/acp-16-7943-2016, https://doi.org/10.5194/acp-16-7943-2016, 2016
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Methane (CH4) is an important greenhouse gas. The growth of atmospheric CH4 stalled from 1999 to 2006, with current explanations focussed mainly on changing surface fluxes. We combine models with observations and meteorological data to assess the atmospheric contribution to CH4 changes. We find that variations in mean atmospheric hydroxyl concentration can explain part of the stall in growth. Our study highlights the role of multi-annual variability in atmospheric chemistry in global CH4 trends.
Jenny A. Fisher, Daniel J. Jacob, Katherine R. Travis, Patrick S. Kim, Eloise A. Marais, Christopher Chan Miller, Karen Yu, Lei Zhu, Robert M. Yantosca, Melissa P. Sulprizio, Jingqiu Mao, Paul O. Wennberg, John D. Crounse, Alex P. Teng, Tran B. Nguyen, Jason M. St. Clair, Ronald C. Cohen, Paul Romer, Benjamin A. Nault, Paul J. Wooldridge, Jose L. Jimenez, Pedro Campuzano-Jost, Douglas A. Day, Weiwei Hu, Paul B. Shepson, Fulizi Xiong, Donald R. Blake, Allen H. Goldstein, Pawel K. Misztal, Thomas F. Hanisco, Glenn M. Wolfe, Thomas B. Ryerson, Armin Wisthaler, and Tomas Mikoviny
Atmos. Chem. Phys., 16, 5969–5991, https://doi.org/10.5194/acp-16-5969-2016, https://doi.org/10.5194/acp-16-5969-2016, 2016
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We use new airborne and ground-based observations from two summer 2013 campaigns in the southeastern US, interpreted with a chemical transport model, to understand the impact of isoprene and monoterpene chemistry on the atmospheric NOx budget via production of organic nitrates (RONO2). We find that a diversity of species contribute to observed RONO2. Our work implies that the NOx sink to RONO2 production is only sensitive to NOx emissions in regions where they are already low.
Karen Yu, Daniel J. Jacob, Jenny A. Fisher, Patrick S. Kim, Eloise A. Marais, Christopher C. Miller, Katherine R. Travis, Lei Zhu, Robert M. Yantosca, Melissa P. Sulprizio, Ron C. Cohen, Jack E. Dibb, Alan Fried, Tomas Mikoviny, Thomas B. Ryerson, Paul O. Wennberg, and Armin Wisthaler
Atmos. Chem. Phys., 16, 4369–4378, https://doi.org/10.5194/acp-16-4369-2016, https://doi.org/10.5194/acp-16-4369-2016, 2016
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Increasing the spatial resolution of a chemical transport model may improve simulations but can be computationally expensive. Using observations from the SEAC4RS aircraft campaign, we find that at higher spatial resolutions, models are better able to simulate the chemical pathways of ozone precursors, but the overall effect on regional mean concentrations is small. This implies that for continental boundary layer applications, coarse resolution models are adequate.
E. A. Marais, D. J. Jacob, J. L. Jimenez, P. Campuzano-Jost, D. A. Day, W. Hu, J. Krechmer, L. Zhu, P. S. Kim, C. C. Miller, J. A. Fisher, K. Travis, K. Yu, T. F. Hanisco, G. M. Wolfe, H. L. Arkinson, H. O. T. Pye, K. D. Froyd, J. Liao, and V. F. McNeill
Atmos. Chem. Phys., 16, 1603–1618, https://doi.org/10.5194/acp-16-1603-2016, https://doi.org/10.5194/acp-16-1603-2016, 2016
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Isoprene secondary organic aerosol (SOA) is a dominant aerosol component in the southeast US, but models routinely underestimate isoprene SOA with traditional schemes based on chamber studies operated under conditions not representative of isoprene-emitting forests. We develop a new irreversible uptake mechanism to reproduce isoprene SOA yields (3.3 %) and composition, and find a factor of 2 co-benefit of SO2 emission controls on reducing sulfate and organic aerosol in the southeast US.
P. G. Simmonds, M. Rigby, A. J. Manning, M. F. Lunt, S. O'Doherty, A. McCulloch, P. J. Fraser, S. Henne, M. K. Vollmer, J. Mühle, R. F. Weiss, P. K. Salameh, D. Young, S. Reimann, A. Wenger, T. Arnold, C. M. Harth, P. B. Krummel, L. P. Steele, B. L. Dunse, B. R. Miller, C. R. Lunder, O. Hermansen, N. Schmidbauer, T. Saito, Y. Yokouchi, S. Park, S. Li, B. Yao, L. X. Zhou, J. Arduini, M. Maione, R. H. J. Wang, D. Ivy, and R. G. Prinn
Atmos. Chem. Phys., 16, 365–382, https://doi.org/10.5194/acp-16-365-2016, https://doi.org/10.5194/acp-16-365-2016, 2016
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We report regional and global emissions estimates of HFC-152a using high frequency measurements from 11 observing sites and archived air samples dating back to 1978 together with atmospheric transport models. The "bottom-up" emissions of HFC-152a reported to the UNFCCC appear to significantly underestimate those reported here from observations. This discrepancy we suggest arises from largely underestimated USA and undeclared Asian emissions.
P. S. Kim, D. J. Jacob, J. A. Fisher, K. Travis, K. Yu, L. Zhu, R. M. Yantosca, M. P. Sulprizio, J. L. Jimenez, P. Campuzano-Jost, K. D. Froyd, J. Liao, J. W. Hair, M. A. Fenn, C. F. Butler, N. L. Wagner, T. D. Gordon, A. Welti, P. O. Wennberg, J. D. Crounse, J. M. St. Clair, A. P. Teng, D. B. Millet, J. P. Schwarz, M. Z. Markovic, and A. E. Perring
Atmos. Chem. Phys., 15, 10411–10433, https://doi.org/10.5194/acp-15-10411-2015, https://doi.org/10.5194/acp-15-10411-2015, 2015
G. Zeng, J. E. Williams, J. A. Fisher, L. K. Emmons, N. B. Jones, O. Morgenstern, J. Robinson, D. Smale, C. Paton-Walsh, and D. W. T. Griffith
Atmos. Chem. Phys., 15, 7217–7245, https://doi.org/10.5194/acp-15-7217-2015, https://doi.org/10.5194/acp-15-7217-2015, 2015
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We assess the impact of biogenic emissions on CO and HCHO in the Southern Hemisphere (SH), with simulations using different emission inventories. Differences in biogenic emissions result in large differences on modelled CO in the source and the remote regions. Substantial inter-model differences exist. Models significantly underestimate observed HCHO columns in the SH, suggesting missing sources in the models. Differences in the CO/OH/CH4 chemistry lead to differences in HCHO in remote regions.
J. A. Fisher, S. R. Wilson, G. Zeng, J. E. Williams, L. K. Emmons, R. L. Langenfelds, P. B. Krummel, and L. P. Steele
Atmos. Chem. Phys., 15, 3217–3239, https://doi.org/10.5194/acp-15-3217-2015, https://doi.org/10.5194/acp-15-3217-2015, 2015
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The Southern Hemisphere (SH) serves as an important test bed for evaluating our understanding of the processes that drive the composition of the clean background atmosphere. Using data from two aircraft campaigns, combined with four atmospheric chemistry models, we find a large sensitivity in the remote SH to biogenic emissions and their subsequent chemistry and transport. Future model evaluation and measurement campaigns should prioritize reducing uncertainties in these processes.
P. J. Rayner, A. Stavert, M. Scholze, A. Ahlström, C. E. Allison, and R. M. Law
Biogeosciences, 12, 835–844, https://doi.org/10.5194/bg-12-835-2015, https://doi.org/10.5194/bg-12-835-2015, 2015
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Recent papers suggest a slow-down in the natural uptake of
anthropogenic CO2. We analyse recent trends in atmospheric concentration and
known inputs to test for such a slow-down. We see, rather, an increase
in uptake compared to a simple response to changing CO2 concentration. Using atmospheric models and statistical techniques we isolate this increased uptake to the northern temperate and boreal continents during summer, suggesting a stronger growing season.
S. O'Doherty, M. Rigby, J. Mühle, D. J. Ivy, B. R. Miller, D. Young, P. G. Simmonds, S. Reimann, M. K. Vollmer, P. B. Krummel, P. J. Fraser, L. P. Steele, B. Dunse, P. K. Salameh, C. M. Harth, T. Arnold, R. F. Weiss, J. Kim, S. Park, S. Li, C. Lunder, O. Hermansen, N. Schmidbauer, L. X. Zhou, B. Yao, R. H. J. Wang, A. J. Manning, and R. G. Prinn
Atmos. Chem. Phys., 14, 9249–9258, https://doi.org/10.5194/acp-14-9249-2014, https://doi.org/10.5194/acp-14-9249-2014, 2014
E. Saikawa, R. G. Prinn, E. Dlugokencky, K. Ishijima, G. S. Dutton, B. D. Hall, R. Langenfelds, Y. Tohjima, T. Machida, M. Manizza, M. Rigby, S. O'Doherty, P. K. Patra, C. M. Harth, R. F. Weiss, P. B. Krummel, M. van der Schoot, P. J. Fraser, L. P. Steele, S. Aoki, T. Nakazawa, and J. W. Elkins
Atmos. Chem. Phys., 14, 4617–4641, https://doi.org/10.5194/acp-14-4617-2014, https://doi.org/10.5194/acp-14-4617-2014, 2014
A. L. Ganesan, M. Rigby, A. Zammit-Mangion, A. J. Manning, R. G. Prinn, P. J. Fraser, C. M. Harth, K.-R. Kim, P. B. Krummel, S. Li, J. Mühle, S. J. O'Doherty, S. Park, P. K. Salameh, L. P. Steele, and R. F. Weiss
Atmos. Chem. Phys., 14, 3855–3864, https://doi.org/10.5194/acp-14-3855-2014, https://doi.org/10.5194/acp-14-3855-2014, 2014
D. A. Belikov, S. Maksyutov, M. Krol, A. Fraser, M. Rigby, H. Bian, A. Agusti-Panareda, D. Bergmann, P. Bousquet, P. Cameron-Smith, M. P. Chipperfield, A. Fortems-Cheiney, E. Gloor, K. Haynes, P. Hess, S. Houweling, S. R. Kawa, R. M. Law, Z. Loh, L. Meng, P. I. Palmer, P. K. Patra, R. G. Prinn, R. Saito, and C. Wilson
Atmos. Chem. Phys., 13, 1093–1114, https://doi.org/10.5194/acp-13-1093-2013, https://doi.org/10.5194/acp-13-1093-2013, 2013
Related subject area
Atmospheric sciences
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
SLUCM+BEM (v1.0): a simple parameterisation for dynamic anthropogenic heat and electricity consumption in WRF-Urban (v4.3.2)
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
An updated parameterization of the unstable atmospheric surface layer in the Weather Research and Forecasting (WRF) modeling system
The impact of cloud microphysics and ice nucleation on Southern Ocean clouds assessed with single-column modeling and instrument simulators
An updated aerosol simulation in the Community Earth System Model (v2.1.3): dust and marine aerosol emissions and secondary organic aerosol formation
Exploring ship track spreading rates with a physics-informed Langevin particle parameterization
Do data-driven models beat numerical models in forecasting weather extremes? A comparison of IFS HRES, Pangu-Weather, and GraphCast
Development of the MPAS-CMAQ coupled system (V1.0) for multiscale global air quality modeling
Assessment of object-based indices to identify convective organization
The Global Forest Fire Emissions Prediction System version 1.0
NEIVAv1.0: Next-generation Emissions InVentory expansion of Akagi et al. (2011) version 1.0
FLEXPART version 11: improved accuracy, efficiency, and flexibility
Challenges of high-fidelity air quality modeling in urban environments – PALM sensitivity study during stable conditions
Air quality modeling intercomparison and multiscale ensemble chain for Latin America
Recommended coupling to global meteorological fields for long-term tracer simulations with WRF-GHG
Selecting CMIP6 global climate models (GCMs) for Coordinated Regional Climate Downscaling Experiment (CORDEX) dynamical downscaling over Southeast Asia using a standardised benchmarking framework
Improved definition of prior uncertainties in CO2 and CO fossil fuel fluxes and its impact on multi-species inversion with GEOS-Chem (v12.5)
RASCAL v1.0: an open-source tool for climatological time series reconstruction and extension
Introducing graupel density prediction in Weather Research and Forecasting (WRF) double-moment 6-class (WDM6) microphysics and evaluation of the modified scheme during the ICE-POP field campaign
Enabling high-performance cloud computing for the Community Multiscale Air Quality Model (CMAQ) version 5.3.3: performance evaluation and benefits for the user community
Atmospheric-river-induced precipitation in California as simulated by the regionally refined Simple Convective Resolving E3SM Atmosphere Model (SCREAM) Version 0
Recent improvements and maximum covariance analysis of aerosol and cloud properties in the EC-Earth3-AerChem model
GPU-HADVPPM4HIP V1.0: using the heterogeneous-compute interface for portability (HIP) to speed up the piecewise parabolic method in the CAMx (v6.10) air quality model on China's domestic GPU-like accelerator
Preliminary evaluation of the effect of electro-coalescence with conducting sphere approximation on the formation of warm cumulus clouds using SCALE-SDM version 0.2.5–2.3.0
Similarity-Based Analysis of Atmospheric Organic Compounds for Machine Learning Applications
Exploring the footprint representation of microwave radiance observations in an Arctic limited-area data assimilation system
Orbital-Radar v1.0.0: A tool to transform suborbital radar observations to synthetic EarthCARE cloud radar data
Analysis of model error in forecast errors of extended atmospheric Lorenz 05 systems and the ECMWF system
Description and validation of Vehicular Emissions from Road Traffic (VERT) 1.0, an R-based framework for estimating road transport emissions from traffic flows
AeroMix v1.0.1: a Python package for modeling aerosol optical properties and mixing states
Impact of ITCZ width on global climate: ITCZ-MIP
Deep-learning-driven simulations of boundary layer clouds over the Southern Great Plains
Mixed-precision computing in the GRIST dynamical core for weather and climate modelling
A conservative immersed boundary method for the multi-physics urban large-eddy simulation model uDALES v2.0
Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes
RCEMIP-II: mock-Walker simulations as phase II of the radiative–convective equilibrium model intercomparison project
The MESSy DWARF (based on MESSy v2.55.2)
Objective identification of meteorological fronts and climatologies from ERA-Interim and ERA5
TAMS: a tracking, classifying, and variable-assigning algorithm for mesoscale convective systems in simulated and satellite-derived datasets
Development of the adjoint of the unified tropospheric–stratospheric chemistry extension (UCX) in GEOS-Chem adjoint v36
New explicit formulae for the settling speed of prolate spheroids in the atmosphere: theoretical background and implementation in AerSett v2.0.2
ZJU-AERO V0.5: an Accurate and Efficient Radar Operator designed for CMA-GFS/MESO with the capability to simulate non-spherical hydrometeors
The Year of Polar Prediction site Model Intercomparison Project (YOPPsiteMIP) phase 1: project overview and Arctic winter forecast evaluation
Evaluating CHASER V4.0 global formaldehyde (HCHO) simulations using satellite, aircraft, and ground-based remote-sensing observations
Global variable-resolution simulations of extreme precipitation over Henan, China, in 2021 with MPAS-Atmosphere v7.3
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
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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
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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.
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
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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.
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
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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
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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
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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
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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.
Prabhakar Namdev, Maithili Sharan, Piyush Srivastava, and Saroj Kanta Mishra
Geosci. Model Dev., 17, 8093–8114, https://doi.org/10.5194/gmd-17-8093-2024, https://doi.org/10.5194/gmd-17-8093-2024, 2024
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Inadequate representation of surface–atmosphere interaction processes is a major source of uncertainty in numerical weather prediction models. Here, an effort has been made to improve the Weather Research and Forecasting (WRF) model version 4.2.2 by introducing a unique theoretical framework under convective conditions. In addition, to enhance the potential applicability of the WRF modeling system, various commonly used similarity functions under convective conditions have also been installed.
Andrew Gettelman, Richard Forbes, Roger Marchand, Chih-Chieh Chen, and Mark Fielding
Geosci. Model Dev., 17, 8069–8092, https://doi.org/10.5194/gmd-17-8069-2024, https://doi.org/10.5194/gmd-17-8069-2024, 2024
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Supercooled liquid clouds (liquid clouds colder than 0°C) are common at higher latitudes (especially over the Southern Ocean) and are critical for constraining climate projections. We compare a single-column version of a weather model to observations with two different cloud schemes and find that both the dynamical environment and atmospheric aerosols are important for reproducing observations.
Yujuan Wang, Peng Zhang, Jie Li, Yaman Liu, Yanxu Zhang, Jiawei Li, and Zhiwei Han
Geosci. Model Dev., 17, 7995–8021, https://doi.org/10.5194/gmd-17-7995-2024, https://doi.org/10.5194/gmd-17-7995-2024, 2024
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This study updates the CESM's aerosol schemes, focusing on dust, marine aerosol emissions, and secondary organic aerosol (SOA) . Dust emission modifications make deflation areas more continuous, improving results in North America and the sub-Arctic. Humidity correction to sea-salt emissions has a minor effect. Introducing marine organic aerosol emissions, coupled with ocean biogeochemical processes, and adding aqueous reactions for SOA formation advance the CESM's aerosol modelling results.
Lucas A. McMichael, Michael J. Schmidt, Robert Wood, Peter N. Blossey, and Lekha Patel
Geosci. Model Dev., 17, 7867–7888, https://doi.org/10.5194/gmd-17-7867-2024, https://doi.org/10.5194/gmd-17-7867-2024, 2024
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Marine cloud brightening (MCB) is a climate intervention technique to potentially cool the climate. Climate models used to gauge regional climate impacts associated with MCB often assume large areas of the ocean are uniformly perturbed. However, a more realistic representation of MCB application would require information about how an injected particle plume spreads. This work aims to develop such a plume-spreading model.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 7915–7962, https://doi.org/10.5194/gmd-17-7915-2024, https://doi.org/10.5194/gmd-17-7915-2024, 2024
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Data-driven models are becoming a viable alternative to physics-based models for weather forecasting up to 15 d into the future. However, it is unclear whether they are as reliable as physics-based models when forecasting weather extremes. We evaluate their performance in forecasting near-surface cold, hot, and windy extremes globally. We find that data-driven models can compete with physics-based models and that the choice of the best model mainly depends on the region and type of extreme.
David C. Wong, Jeff Willison, Jonathan E. Pleim, Golam Sarwar, James Beidler, Russ Bullock, Jerold A. Herwehe, Rob Gilliam, Daiwen Kang, Christian Hogrefe, George Pouliot, and Hosein Foroutan
Geosci. Model Dev., 17, 7855–7866, https://doi.org/10.5194/gmd-17-7855-2024, https://doi.org/10.5194/gmd-17-7855-2024, 2024
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This work describe how we linked the meteorological Model for Prediction Across Scales – Atmosphere (MPAS-A) with the Community Multiscale Air Quality (CMAQ) air quality model to form a coupled modelling system. This could be used to study air quality or climate and air quality interaction at a global scale. This new model scales well in high-performance computing environments and performs well with respect to ground surface networks in terms of ozone and PM2.5.
Giulio Mandorli and Claudia J. Stubenrauch
Geosci. Model Dev., 17, 7795–7813, https://doi.org/10.5194/gmd-17-7795-2024, https://doi.org/10.5194/gmd-17-7795-2024, 2024
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In recent years, several studies focused their attention on the disposition of convection. Lots of methods, called indices, have been developed to quantify the amount of convection clustering. These indices are evaluated in this study by defining criteria that must be satisfied and then evaluating the indices against these standards. None of the indices meet all criteria, with some only partially meeting them.
Kerry Anderson, Jack Chen, Peter Englefield, Debora Griffin, Paul A. Makar, and Dan Thompson
Geosci. Model Dev., 17, 7713–7749, https://doi.org/10.5194/gmd-17-7713-2024, https://doi.org/10.5194/gmd-17-7713-2024, 2024
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The Global Forest Fire Emissions Prediction System (GFFEPS) is a model that predicts smoke and carbon emissions from wildland fires. The model calculates emissions from the ground up based on satellite-detected fires, modelled weather and fire characteristics. Unlike other global models, GFFEPS uses daily weather conditions to capture changing burning conditions on a day-to-day basis. GFFEPS produced lower carbon emissions due to the changing weather not captured by the other models.
Samiha Binte Shahid, Forrest G. Lacey, Christine Wiedinmyer, Robert J. Yokelson, and Kelley C. Barsanti
Geosci. Model Dev., 17, 7679–7711, https://doi.org/10.5194/gmd-17-7679-2024, https://doi.org/10.5194/gmd-17-7679-2024, 2024
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The Next-generation Emissions InVentory expansion of Akagi (NEIVA) v.1.0 is a comprehensive biomass burning emissions database that allows integration of new data and flexible querying. Data are stored in connected datasets, including recommended averages of ~1500 constituents for 14 globally relevant fire types. Individual compounds were mapped to common model species to allow better attribution of emissions in modeling studies that predict the effects of fires on air quality and climate.
Lucie Bakels, Daria Tatsii, Anne Tipka, Rona Thompson, Marina Dütsch, Michael Blaschek, Petra Seibert, Katharina Baier, Silvia Bucci, Massimo Cassiani, Sabine Eckhardt, Christine Groot Zwaaftink, Stephan Henne, Pirmin Kaufmann, Vincent Lechner, Christian Maurer, Marie D. Mulder, Ignacio Pisso, Andreas Plach, Rakesh Subramanian, Martin Vojta, and Andreas Stohl
Geosci. Model Dev., 17, 7595–7627, https://doi.org/10.5194/gmd-17-7595-2024, https://doi.org/10.5194/gmd-17-7595-2024, 2024
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Computer models are essential for improving our understanding of how gases and particles move in the atmosphere. We present an update of the atmospheric transport model FLEXPART. FLEXPART 11 is more accurate due to a reduced number of interpolations and a new scheme for wet deposition. It can simulate non-spherical aerosols and includes linear chemical reactions. It is parallelised using OpenMP and includes new user options. A new user manual details how to use FLEXPART 11.
Jaroslav Resler, Petra Bauerová, Michal Belda, Martin Bureš, Kryštof Eben, Vladimír Fuka, Jan Geletič, Radek Jareš, Jan Karel, Josef Keder, Pavel Krč, William Patiño, Jelena Radović, Hynek Řezníček, Matthias Sühring, Adriana Šindelářová, and Ondřej Vlček
Geosci. Model Dev., 17, 7513–7537, https://doi.org/10.5194/gmd-17-7513-2024, https://doi.org/10.5194/gmd-17-7513-2024, 2024
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Detailed modeling of urban air quality in stable conditions is a challenge. We show the unprecedented sensitivity of a large eddy simulation (LES) model to meteorological boundary conditions and model parameters in an urban environment under stable conditions. We demonstrate the crucial role of boundary conditions for the comparability of results with observations. The study reveals a strong sensitivity of the results to model parameters and model numerical instabilities during such conditions.
Jorge E. Pachón, Mariel A. Opazo, Pablo Lichtig, Nicolas Huneeus, Idir Bouarar, Guy Brasseur, Cathy W. Y. Li, Johannes Flemming, Laurent Menut, Camilo Menares, Laura Gallardo, Michael Gauss, Mikhail Sofiev, Rostislav Kouznetsov, Julia Palamarchuk, Andreas Uppstu, Laura Dawidowski, Nestor Y. Rojas, María de Fátima Andrade, Mario E. Gavidia-Calderón, Alejandro H. Delgado Peralta, and Daniel Schuch
Geosci. Model Dev., 17, 7467–7512, https://doi.org/10.5194/gmd-17-7467-2024, https://doi.org/10.5194/gmd-17-7467-2024, 2024
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Latin America (LAC) has some of the most populated urban areas in the world, with high levels of air pollution. Air quality management in LAC has been traditionally focused on surveillance and building emission inventories. This study performed the first intercomparison and model evaluation in LAC, with interesting and insightful findings for the region. A multiscale modeling ensemble chain was assembled as a first step towards an air quality forecasting system.
David Ho, Michał Gałkowski, Friedemann Reum, Santiago Botía, Julia Marshall, Kai Uwe Totsche, and Christoph Gerbig
Geosci. Model Dev., 17, 7401–7422, https://doi.org/10.5194/gmd-17-7401-2024, https://doi.org/10.5194/gmd-17-7401-2024, 2024
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Atmospheric model users often overlook the impact of the land–atmosphere interaction. This study accessed various setups of WRF-GHG simulations that ensure consistency between the model and driving reanalysis fields. We found that a combination of nudging and frequent re-initialization allows certain improvement by constraining the soil moisture fields and, through its impact on atmospheric mixing, improves atmospheric transport.
Phuong Loan Nguyen, Lisa V. Alexander, Marcus J. Thatcher, Son C. H. Truong, Rachael N. Isphording, and John L. McGregor
Geosci. Model Dev., 17, 7285–7315, https://doi.org/10.5194/gmd-17-7285-2024, https://doi.org/10.5194/gmd-17-7285-2024, 2024
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We use a comprehensive approach to select a subset of CMIP6 models for dynamical downscaling over Southeast Asia, taking into account model performance, model independence, data availability and the range of future climate projections. The standardised benchmarking framework is applied to assess model performance through both statistical and process-based metrics. Ultimately, we identify two independent model groups that are suitable for dynamical downscaling in the Southeast Asian region.
Ingrid Super, Tia Scarpelli, Arjan Droste, and Paul I. Palmer
Geosci. Model Dev., 17, 7263–7284, https://doi.org/10.5194/gmd-17-7263-2024, https://doi.org/10.5194/gmd-17-7263-2024, 2024
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Monitoring greenhouse gas emission reductions requires a combination of models and observations, as well as an initial emission estimate. Each component provides information with a certain level of certainty and is weighted to yield the most reliable estimate of actual emissions. We describe efforts for estimating the uncertainty in the initial emission estimate, which significantly impacts the outcome. Hence, a good uncertainty estimate is key for obtaining reliable information on emissions.
Álvaro González-Cervera and Luis Durán
Geosci. Model Dev., 17, 7245–7261, https://doi.org/10.5194/gmd-17-7245-2024, https://doi.org/10.5194/gmd-17-7245-2024, 2024
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RASCAL is an open-source Python tool designed for reconstructing daily climate observations, especially in regions with complex local phenomena. It merges large-scale weather patterns with local weather using the analog method. Evaluations in central Spain show that RASCAL outperforms ERA20C reanalysis in reconstructing precipitation and temperature. RASCAL offers opportunities for broad scientific applications, from short-term forecasts to local-scale climate change scenarios.
Sun-Young Park, Kyo-Sun Sunny Lim, Kwonil Kim, Gyuwon Lee, and Jason A. Milbrandt
Geosci. Model Dev., 17, 7199–7218, https://doi.org/10.5194/gmd-17-7199-2024, https://doi.org/10.5194/gmd-17-7199-2024, 2024
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We enhance the WDM6 scheme by incorporating predicted graupel density. The modification affects graupel characteristics, including fall velocity–diameter and mass–diameter relationships. Simulations highlight changes in graupel distribution and precipitation patterns, potentially influencing surface snow amounts. The study underscores the significance of integrating predicted graupel density for a more realistic portrayal of microphysical properties in weather models.
Christos I. Efstathiou, Elizabeth Adams, Carlie J. Coats, Robert Zelt, Mark Reed, John McGee, Kristen M. Foley, Fahim I. Sidi, David C. Wong, Steven Fine, and Saravanan Arunachalam
Geosci. Model Dev., 17, 7001–7027, https://doi.org/10.5194/gmd-17-7001-2024, https://doi.org/10.5194/gmd-17-7001-2024, 2024
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We present a summary of enabling high-performance computing of the Community Multiscale Air Quality Model (CMAQ) – a state-of-the-science community multiscale air quality model – on two cloud computing platforms through documenting the technologies, model performance, scaling and relative merits. This may be a new paradigm for computationally intense future model applications. We initiated this work due to a need to leverage cloud computing advances and to ease the learning curve for new users.
Peter A. Bogenschutz, Jishi Zhang, Qi Tang, and Philip Cameron-Smith
Geosci. Model Dev., 17, 7029–7050, https://doi.org/10.5194/gmd-17-7029-2024, https://doi.org/10.5194/gmd-17-7029-2024, 2024
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Using high-resolution and state-of-the-art modeling techniques we simulate five atmospheric river events for California to test the capability to represent precipitation for these events. We find that our model is able to capture the distribution of precipitation very well but suffers from overestimating the precipitation amounts over high elevation. Increasing the resolution further has no impact on reducing this bias, while increasing the domain size does have modest impacts.
Manu Anna Thomas, Klaus Wyser, Shiyu Wang, Marios Chatziparaschos, Paraskevi Georgakaki, Montserrat Costa-Surós, Maria Gonçalves Ageitos, Maria Kanakidou, Carlos Pérez García-Pando, Athanasios Nenes, Twan van Noije, Philippe Le Sager, and Abhay Devasthale
Geosci. Model Dev., 17, 6903–6927, https://doi.org/10.5194/gmd-17-6903-2024, https://doi.org/10.5194/gmd-17-6903-2024, 2024
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Aerosol–cloud interactions occur at a range of spatio-temporal scales. While evaluating recent developments in EC-Earth3-AerChem, this study aims to understand the extent to which the Twomey effect manifests itself at larger scales. We find a reduction in the warm bias over the Southern Ocean due to model improvements. While we see footprints of the Twomey effect at larger scales, the negative relationship between cloud droplet number and liquid water drives the shortwave radiative effect.
Kai Cao, Qizhong Wu, Lingling Wang, Hengliang Guo, Nan Wang, Huaqiong Cheng, Xiao Tang, Dongxing Li, Lina Liu, Dongqing Li, Hao Wu, and Lanning Wang
Geosci. Model Dev., 17, 6887–6901, https://doi.org/10.5194/gmd-17-6887-2024, https://doi.org/10.5194/gmd-17-6887-2024, 2024
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AMD’s heterogeneous-compute interface for portability was implemented to port the piecewise parabolic method solver from NVIDIA GPUs to China's GPU-like accelerators. The results show that the larger the model scale, the more acceleration effect on the GPU-like accelerator, up to 28.9 times. The multi-level parallelism achieves a speedup of 32.7 times on the heterogeneous cluster. By comparing the results, the GPU-like accelerators have more accuracy for the geoscience numerical models.
Ruyi Zhang, Limin Zhou, Shin-ichiro Shima, and Huawei Yang
Geosci. Model Dev., 17, 6761–6774, https://doi.org/10.5194/gmd-17-6761-2024, https://doi.org/10.5194/gmd-17-6761-2024, 2024
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Solar activity weakly ionises Earth's atmosphere, charging cloud droplets. Electro-coalescence is when oppositely charged droplets stick together. We introduce an analytical expression of electro-coalescence probability and use it in a warm-cumulus-cloud simulation. Results show that charge cases increase rain and droplet size, with the new method outperforming older ones. The new method requires longer computation time, but its impact on rain justifies inclusion in meteorology models.
Hilda Sandström and Patrick Rinke
EGUsphere, https://doi.org/10.48550/arXiv.2406.18171, https://doi.org/10.48550/arXiv.2406.18171, 2024
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Machine learning has the potential to aid the identification 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 model in atmospheric sciences.
Máté Mile, Stephanie Guedj, and Roger Randriamampianina
Geosci. Model Dev., 17, 6571–6587, https://doi.org/10.5194/gmd-17-6571-2024, https://doi.org/10.5194/gmd-17-6571-2024, 2024
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Satellite observations provide crucial information about atmospheric constituents in a global distribution that helps to better predict the weather over sparsely observed regions like the Arctic. However, the use of satellite data is usually conservative and imperfect. In this study, a better spatial representation of satellite observations is discussed and explored by a so-called footprint function or operator, highlighting its added value through a case study and diagnostics.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-129, https://doi.org/10.5194/gmd-2024-129, 2024
Revised manuscript accepted for GMD
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Orbital-radar is a Python tool transferring sub-orbital radar data (ground-based, airborne, and forward-simulated NWP) into synthetical space-borne cloud profiling radar data mimicking the platform characteristics, e.g. EarthCARE or CloudSat CPR. The novelty of orbital-radar is the simulation platform characteristic noise floors and errors. By this long time data sets can be transformed into synthetic observations for Cal/Valor sensitivity studies for new or future satellite missions.
Hynek Bednář and Holger Kantz
Geosci. Model Dev., 17, 6489–6511, https://doi.org/10.5194/gmd-17-6489-2024, https://doi.org/10.5194/gmd-17-6489-2024, 2024
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The forecast error growth of atmospheric phenomena is caused by initial and model errors. When studying the initial error growth, it may turn out that small-scale phenomena, which contribute little to the forecast product, significantly affect the ability to predict this product. With a negative result, we investigate in the extended Lorenz (2005) system whether omitting these phenomena will improve predictability. A theory explaining and describing this behavior is developed.
Giorgio Veratti, Alessandro Bigi, Sergio Teggi, and Grazia Ghermandi
Geosci. Model Dev., 17, 6465–6487, https://doi.org/10.5194/gmd-17-6465-2024, https://doi.org/10.5194/gmd-17-6465-2024, 2024
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In this study, we present VERT (Vehicular Emissions from Road Traffic), an R package designed to estimate transport emissions using traffic estimates and vehicle fleet composition data. Compared to other tools available in the literature, VERT stands out for its user-friendly configuration and flexibility of user input. Case studies demonstrate its accuracy in both urban and regional contexts, making it a valuable tool for air quality management and transport scenario planning.
Sam P. Raj, Puna Ram Sinha, Rohit Srivastava, Srinivas Bikkina, and Damu Bala Subrahamanyam
Geosci. Model Dev., 17, 6379–6399, https://doi.org/10.5194/gmd-17-6379-2024, https://doi.org/10.5194/gmd-17-6379-2024, 2024
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A Python successor to the aerosol module of the OPAC model, named AeroMix, has been developed, with enhanced capabilities to better represent real atmospheric aerosol mixing scenarios. AeroMix’s performance in modeling aerosol mixing states has been evaluated against field measurements, substantiating its potential as a versatile aerosol optical model framework for next-generation algorithms to infer aerosol mixing states and chemical composition.
Angeline G. Pendergrass, Michael P. Byrne, Oliver Watt-Meyer, Penelope Maher, and Mark J. Webb
Geosci. Model Dev., 17, 6365–6378, https://doi.org/10.5194/gmd-17-6365-2024, https://doi.org/10.5194/gmd-17-6365-2024, 2024
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The width of the tropical rain belt affects many aspects of our climate, yet we do not understand what controls it. To better understand it, we present a method to change it in numerical model experiments. We show that the method works well in four different models. The behavior of the width is unexpectedly simple in some ways, such as how strong the winds are as it changes, but in other ways, it is more complicated, especially how temperature increases with carbon dioxide.
Tianning Su and Yunyan Zhang
Geosci. Model Dev., 17, 6319–6336, https://doi.org/10.5194/gmd-17-6319-2024, https://doi.org/10.5194/gmd-17-6319-2024, 2024
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Using 2 decades of field observations over the Southern Great Plains, this study developed a deep-learning model to simulate the complex dynamics of boundary layer clouds. The deep-learning model can serve as the cloud parameterization within reanalysis frameworks, offering insights into improving the simulation of low clouds. By quantifying biases due to various meteorological factors and parameterizations, this deep-learning-driven approach helps bridge the observation–modeling divide.
Siyuan Chen, Yi Zhang, Yiming Wang, Zhuang Liu, Xiaohan Li, and Wei Xue
Geosci. Model Dev., 17, 6301–6318, https://doi.org/10.5194/gmd-17-6301-2024, https://doi.org/10.5194/gmd-17-6301-2024, 2024
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This study explores strategies and techniques for implementing mixed-precision code optimization within an atmosphere model dynamical core. The coded equation terms in the governing equations that are sensitive (or insensitive) to the precision level have been identified. The performance of mixed-precision computing in weather and climate simulations was analyzed.
Sam O. Owens, Dipanjan Majumdar, Chris E. Wilson, Paul Bartholomew, and Maarten van Reeuwijk
Geosci. Model Dev., 17, 6277–6300, https://doi.org/10.5194/gmd-17-6277-2024, https://doi.org/10.5194/gmd-17-6277-2024, 2024
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Designing cities that are resilient, sustainable, and beneficial to health requires an understanding of urban climate and air quality. This article presents an upgrade to the multi-physics numerical model uDALES, which can simulate microscale airflow, heat transfer, and pollutant dispersion in urban environments. This upgrade enables it to resolve realistic urban geometries more accurately and to take advantage of the resources available on current and future high-performance computing systems.
Felipe Cifuentes, Henk Eskes, Folkert Boersma, Enrico Dammers, and Charlotte Bryan
EGUsphere, https://doi.org/10.5194/egusphere-2024-2225, https://doi.org/10.5194/egusphere-2024-2225, 2024
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We tested the capability of the flux divergence approach (FDA) to reproduce known NOX emissions using synthetic NO2 satellite column retrievals derived 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 NO2 lifetime, NOX:NO2 ratio, and NO2 profile shapes were correctly modeled. This introduces a strong model dependency, reducing the simplicity of the original FDA formulation.
Allison A. Wing, Levi G. Silvers, and Kevin A. Reed
Geosci. Model Dev., 17, 6195–6225, https://doi.org/10.5194/gmd-17-6195-2024, https://doi.org/10.5194/gmd-17-6195-2024, 2024
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This paper presents the experimental design for a model intercomparison project to study tropical clouds and climate. It is a follow-up from a prior project that used a simplified framework for tropical climate. The new project adds one new component – a specified pattern of sea surface temperatures as the lower boundary condition. We provide example results from one cloud-resolving model and one global climate model and test the sensitivity to the experimental parameters.
Astrid Kerkweg, Timo Kirfel, Doung H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-117, https://doi.org/10.5194/gmd-2024-117, 2024
Revised manuscript accepted for GMD
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This article introduces the MESSy DWARF. Usually, the Modular Earth Submodel System (MESSy) is linked to full dynamical models to build chemistry climate models. However, due to the modular concept of MESSy, and the newly developed DWARF component, it is now possible to create simplified models containing just one or some process descriptions. This renders very useful for technical optimisation (e.g., GPU porting) and can be used to create less complex models, e.g., a chemical box model.
Philip G. Sansom and Jennifer L. Catto
Geosci. Model Dev., 17, 6137–6151, https://doi.org/10.5194/gmd-17-6137-2024, https://doi.org/10.5194/gmd-17-6137-2024, 2024
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Weather fronts bring a lot of rain and strong winds to many regions of the mid-latitudes. We have developed an updated method of identifying these fronts in gridded data that can be used on new datasets with small grid spacing. The method can be easily applied to different datasets due to the use of open-source software for its development and shows improvements over similar previous methods. We present an updated estimate of the average frequency of fronts over the past 40 years.
Kelly M. Núñez Ocasio and Zachary L. Moon
Geosci. Model Dev., 17, 6035–6049, https://doi.org/10.5194/gmd-17-6035-2024, https://doi.org/10.5194/gmd-17-6035-2024, 2024
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TAMS is an open-source Python-based package for tracking and classifying mesoscale convective systems that can be used to study observed and simulated systems. Each step of the algorithm is described in this paper with examples showing how to make use of visualization and post-processing tools within the package. A unique and valuable feature of this tracker is its support for unstructured grids in the identification stage and grid-independent tracking.
Irene C. Dedoussi, Daven K. Henze, Sebastian D. Eastham, Raymond L. Speth, and Steven R. H. Barrett
Geosci. Model Dev., 17, 5689–5703, https://doi.org/10.5194/gmd-17-5689-2024, https://doi.org/10.5194/gmd-17-5689-2024, 2024
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Atmospheric model gradients provide a meaningful tool for better understanding the underlying atmospheric processes. Adjoint modeling enables computationally efficient gradient calculations. We present the adjoint of the GEOS-Chem unified chemistry extension (UCX). With this development, the GEOS-Chem adjoint model can capture stratospheric ozone and other processes jointly with tropospheric processes. We apply it to characterize the Antarctic ozone depletion potential of active halogen species.
Sylvain Mailler, Sotirios Mallios, Arineh Cholakian, Vassilis Amiridis, Laurent Menut, and Romain Pennel
Geosci. Model Dev., 17, 5641–5655, https://doi.org/10.5194/gmd-17-5641-2024, https://doi.org/10.5194/gmd-17-5641-2024, 2024
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We propose two explicit expressions to calculate the settling speed of solid atmospheric particles with prolate spheroidal shapes. The first formulation is based on theoretical arguments only, while the second one is based on computational fluid dynamics calculations. We show that the first method is suitable for virtually all atmospheric aerosols, provided their shape can be adequately described as a prolate spheroid, and we provide an implementation of the first method in AerSett v2.0.2.
Hejun Xie, Lei Bi, and Wei Han
Geosci. Model Dev., 17, 5657–5688, https://doi.org/10.5194/gmd-17-5657-2024, https://doi.org/10.5194/gmd-17-5657-2024, 2024
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A radar operator plays a crucial role in utilizing radar observations to enhance numerical weather forecasts. However, developing an advanced radar operator is challenging due to various complexities associated with the wave scattering by non-spherical hydrometeors, radar beam propagation, and multiple platforms. In this study, we introduce a novel radar operator named the Accurate and Efficient Radar Operator developed by ZheJiang University (ZJU-AERO) which boasts several unique features.
Jonathan J. Day, Gunilla Svensson, Barbara Casati, Taneil Uttal, Siri-Jodha Khalsa, Eric Bazile, Elena Akish, Niramson Azouz, Lara Ferrighi, Helmut Frank, Michael Gallagher, Øystein Godøy, Leslie M. Hartten, Laura X. Huang, Jareth Holt, Massimo Di Stefano, Irene Suomi, Zen Mariani, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Teresa Remes, Rostislav Fadeev, Amy Solomon, Johanna Tjernström, and Mikhail Tolstykh
Geosci. Model Dev., 17, 5511–5543, https://doi.org/10.5194/gmd-17-5511-2024, https://doi.org/10.5194/gmd-17-5511-2024, 2024
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The YOPP site Model Intercomparison Project (YOPPsiteMIP), which was designed to facilitate enhanced weather forecast evaluation in polar regions, is discussed here, focussing on describing the archive of forecast data and presenting a multi-model evaluation at Arctic supersites during February and March 2018. The study highlights an underestimation in boundary layer temperature variance that is common across models and a related inability to forecast cold extremes at several of the sites.
Hossain Mohammed Syedul Hoque, Kengo Sudo, Hitoshi Irie, Yanfeng He, and Md Firoz Khan
Geosci. Model Dev., 17, 5545–5571, https://doi.org/10.5194/gmd-17-5545-2024, https://doi.org/10.5194/gmd-17-5545-2024, 2024
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Using multi-platform observations, we validated global formaldehyde (HCHO) simulations from a chemistry transport model. HCHO is a crucial intermediate in the chemical catalytic cycle that governs the ozone formation in the troposphere. The model was capable of replicating the observed spatiotemporal variability in HCHO. In a few cases, the model's capability was limited. This is attributed to the uncertainties in the observations and the model parameters.
Zijun Liu, Li Dong, Zongxu Qiu, Xingrong Li, Huiling Yuan, Dongmei Meng, Xiaobin Qiu, Dingyuan Liang, and Yafei Wang
Geosci. Model Dev., 17, 5477–5496, https://doi.org/10.5194/gmd-17-5477-2024, https://doi.org/10.5194/gmd-17-5477-2024, 2024
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In this study, we completed a series of simulations with MPAS-Atmosphere (version 7.3) to study the extreme precipitation event of Henan, China, during 20–22 July 2021. We found the different performance of two built-in parameterization scheme suites (mesoscale and convection-permitting suites) with global quasi-uniform and variable-resolution meshes. This study holds significant implications for advancing the understanding of the scale-aware capability of MPAS-Atmosphere.
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Short summary
We present a framework for estimating the sources and sinks (flux) of carbon dioxide from satellite data. The framework is statistical and yields measures of uncertainty alongside all estimates of flux and other parameters in the underlying model. It also allows us to generate other insights, such as the size of errors and biases in the data. The primary aim of this research was to develop a fully statistical flux inversion framework for use by atmospheric scientists.
We present a framework for estimating the sources and sinks (flux) of carbon dioxide from...
