Articles | Volume 18, issue 1
https://doi.org/10.5194/gmd-18-181-2025
© Author(s) 2025. 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-18-181-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Methods for assessment of models
| 
16 Jan 2025
Methods for assessment of models |
| 16 Jan 2025
| 16 Jan 2025
Virtual Integration of Satellite and In-situ Observation Networks (VISION) v1.0: In-Situ Observations Simulator (ISO_simulator)
National Centre for Atmospheric Science, Cambridge, UK
Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, UK
Sadie L. Bartholomew
National Centre for Atmospheric Science, Reading, UK
Department of Meteorology, University of Reading, Reading, UK
David Hassell
National Centre for Atmospheric Science, Reading, UK
Department of Meteorology, University of Reading, Reading, UK
Alex M. Mason
Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, UK
Erica Neininger
Met Office, Exeter, UK
A. James Perman
Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, UK
David A. J. Sproson
FAAM Airborne Laboratory, National Centre for Atmospheric Science, University of Leeds, Leeds, UK
Duncan Watson-Parris
Scripps Institution of Oceanography, University of California San Diego, San Diego, USA
Halıcıoğlu Data Science Institute, University of California San Diego, San Diego, USA
Nathan Luke Abraham
National Centre for Atmospheric Science, Cambridge, UK
Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, UK
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Aerosols affect clouds and climate. However, current climate models still struggle to simulate them accurately. We used aircraft data from a global mission to evaluate how well the UK Earth System Model represents aerosols and their precursors. Our results show that the model misses key formation processes in clean ocean regions, suggesting that future improvements should focus on better representing how aerosols form naturally in the atmosphere.
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Here, we present an overview of the data generated as part of the North Atlantic Climate System Integrated Study (ACSIS) programme that are available through dedicated repositories at the Centre for Environmental Data Analysis (CEDA; www.ceda.ac.uk) and the British Oceanographic Data Centre (BODC; bodc.ac.uk). The datasets described here cover the North Atlantic Ocean, the atmosphere above (it including its composition), and Arctic sea ice.
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Tropospheric ozone is an important component of the Earth system as it can affect both climate and air quality. In this work we use observed tropospheric ozone derived from satellite observations and compare it to tropospheric ozone from model simulations. Our aim is to investigate recent changes (2005–2018) in tropospheric ozone in the North Atlantic region and to understand what factors are driving such changes.
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Geosci. Model Dev., 19, 1537–1557, https://doi.org/10.5194/gmd-19-1537-2026, https://doi.org/10.5194/gmd-19-1537-2026, 2026
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EGUsphere, https://doi.org/10.5194/egusphere-2026-128, https://doi.org/10.5194/egusphere-2026-128, 2026
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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The UK Earth System Model is updated with an improved polar stratospheric cloud scheme. The performance of the scheme is evaluated against satellite data. While the observed wave ice still fails to form in the model, the scheme improves its ability to represent different polar stratospheric cloud types and their variations. This brings the model closer to satellite observations and highlights the need for further development to capture the polar stratospheric cloud formation in mountain waves.
Ellen H. Davenport, J. Varan Madan, Rebecca Gjini, Jared Brzenski, Nick Ho, Tien-Yiao Hsu, Yueshan Liang, Zhixing Liu, Veeramakali Manivannan, Eric Pham, Rohith Vutukuru, Andrew I. L. Williams, Zhiqi Yang, Rose Yu, Nicholas J. Lutsko, Stephan Hoyer, and Duncan Watson-Parris
EGUsphere, https://doi.org/10.5194/egusphere-2025-6266, https://doi.org/10.5194/egusphere-2025-6266, 2026
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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We introduce version 1.0 of the JAX Circulation Model (JCM), an open-source atmosphere model. JCM is written in JAX, a framework for high-performance Python code that supports automatic differentiation (automated calculation of how sensitive any program output is to any input). JCM's differentiability and modular design make it easier to train, test, and combine physical-theory-based and data-driven model components, thus providing a flexible and modern platform to facilitate climate research.
Marta Abalos, Thomas Birner, Andreas Chrysanthou, Sean Davis, Alvaro de la Cámara, Sandip Dhomse, Hella Garny, Michaela I. Hegglin, Daan Hubert, Oksana Ivaniha, James Keeble, Marianna Linz, Daniele Minganti, Jessica Neu, David Plummer, Laura Saunders, Kasturi Shah, Gabriele Stiller, Kleareti Tourpali, Darryn Waugh, Nathan Luke Abraham, Hideharu Akiyoshi, Martyn P. Chipperfield, Patrick Jöckel, Béatrice Josse, Olaf Morgenstern, Timofei Sukhodolov, Shingo Watanabe, and Yousuke Yamashita
EGUsphere, https://doi.org/10.5194/egusphere-2025-6549, https://doi.org/10.5194/egusphere-2025-6549, 2026
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Chemistry-climate models are widely used to understand stratospheric ozone and its interactions with climate. We evaluate the most recent generations of models against modern observations. We find that important long-standing errors remain, and some have increased in recent models. Transported too fast in the stratosphere, and the strong winter circulation around the polar region lasts too long. These results highlight where models must improve to better assess past and future changes.
Yusuf A. Bhatti, Duncan Watson-Parris, Leighton A. Regayre, Hailing Jia, David Neubauer, Ulas Im, Carl Svenhag, Nick Schutgens, Athanasios Tsikerdekis, Athanasios Nenes, Muhammed Irfan, Bastiaan van Diedenhoven, Ardit Arifi, Guangliang Fu, and Otto P. Hasekamp
Atmos. Chem. Phys., 26, 269–293, https://doi.org/10.5194/acp-26-269-2026, https://doi.org/10.5194/acp-26-269-2026, 2026
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Aerosols (small airborne particles) impact Earth's climate, but their extent is unknown. By running climate model simulations and using machine learning to emulate millions of additional variants with different settings, we found that natural emissions like sea spray and sulfur are key sources of uncertainty in climate predictions. Our work shows that understanding these natural processes better can help improve climate models and make future climate projections more accurate.
Alex M. Mason, Matthew Henry, Haruki Hirasawa, Fiona M. O'Connor, and James Haywood
EGUsphere, https://doi.org/10.5194/egusphere-2025-5591, https://doi.org/10.5194/egusphere-2025-5591, 2025
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Marine Cloud Brightening (MCB) proposes the spraying of sea salt particles into marine clouds to cool the planet. MCB in midlatitude regions in models gave a relatively even climate response. We use 42 simulations of MCB to target several climate responses. Two optimised combinations are compared to a midlatitude MCB simulation, which improved sea ice restoration and the temperature response pattern, highlighting the importance of high latitude MCB for MCB optimisation in this model.
Stephanie Fiedler, Fiona M. O'Connor, Duncan Watson-Parris, Robert J. Allen, William J. Collins, Paul T. Griffiths, Matthew Kasoar, Jarmo Kikstra, Jasper F. Kok, Lee T. Murray, Fabien Paulot, Maria Sand, Steven Turnock, James Weber, Laura J. Wilcox, and Vaishali Naik
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The Aerosol and Chemistry Model Intercomparison Project phase two (AerChemMIP2) allows the community to compare results from contemporary Earth system models. AerChemMIP2 is asking modelling centres to perform experiments following the same protocol. It includes experiments for enabling new science and for tracking progress. Model output will be used for addressing research and policy questions about anthropogenic and natural drivers of climate change, and the impacts on air quality.
Sini Talvinen, Paul Kim, Emanuele Tovazzi, Eemeli Holopainen, Roxana Cremer, Thomas Kühn, Harri Kokkola, Zak Kipling, David Neubauer, João C. Teixeira, Alistair Sellar, Duncan Watson-Parris, Yang Yang, Jialei Zhu, Srinath Krishnan, Annele Virtanen, and Daniel G. Partridge
Atmos. Chem. Phys., 25, 14449–14478, https://doi.org/10.5194/acp-25-14449-2025, https://doi.org/10.5194/acp-25-14449-2025, 2025
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Climate models struggle to predict how clouds and aerosols interact, affecting Earth’s energy balance. This study compares models to observations to see how they describe effects of clouds and rain on aerosols. While both models show similar overall trends, seasonal differences emerged. These, however, align with differences in key variables participating in cloud formation. The study provides insights on how to improve the representation of aerosol-cloud interactions in climate models.
George Jordan, Florent Malavelle, Jim Haywood, Ying Chen, Ben Johnson, Daniel Partridge, Amy Peace, Eliza Duncan, Duncan Watson-Parris, David Neubauer, Anton Laakso, Martine Michou, and Pierre Nabat
Atmos. Chem. Phys., 25, 13393–13428, https://doi.org/10.5194/acp-25-13393-2025, https://doi.org/10.5194/acp-25-13393-2025, 2025
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The 2014–15 Holuhraun eruption created a vast aerosol plume that acted as a natural experiment to assess how well climate models capture changes in cloud properties due to increased aerosol. We find that climate models represent the observed shift to smaller, more numerous cloud droplets well. However, climate models diverge in their aerosol-induced changes to large-scale cloud properties, particularly cloud liquid water content. Our study shows that Holuhraun had a cooling effect on the Earth.
Man Mei Chim, Nathan Luke Abraham, Thomas J. Aubry, Ben Johnson, Hella Garny, Susan Solomon, and Anja Schmidt
EGUsphere, https://doi.org/10.5194/egusphere-2025-4860, https://doi.org/10.5194/egusphere-2025-4860, 2025
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Sulfate aerosols from explosive eruptions can provide surfaces for chemical reactions destroying ozone. Assessing the effects of volcanic sulfate aerosols is crucial for understanding future ozone recovery. We find sporadic eruptions can induce a small delay in stratospheric ozone recovery by a few years over Antarctica and Southern Hemisphere mid-latitudes. Our results highlight the importance to continuously monitor atmospheric composition and processes to understand changes in ozone recovery.
Xu-Cheng He, Nathan Luke Abraham, Han Ding, Maria R. Russo, Daniel P. Grosvenor, Yao Ge, Xuemei Wang, Anthony C. Jones, Pedro Campuzano-Jost, Benjamin Nault, Agnieszka Kupc, Donald Blake, Jose L. Jimenez, Christina J. Williamson, Kenneth S. Carslaw, James Weber, Alexander T. Archibald, and Hamish Gordon
EGUsphere, https://doi.org/10.5194/egusphere-2025-3700, https://doi.org/10.5194/egusphere-2025-3700, 2025
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Aerosols affect clouds and climate. However, current climate models still struggle to simulate them accurately. We used aircraft data from a global mission to evaluate how well the UK Earth System Model represents aerosols and their precursors. Our results show that the model misses key formation processes in clean ocean regions, suggesting that future improvements should focus on better representing how aerosols form naturally in the atmosphere.
William J. Collins, Fiona M. O'Connor, Rachael E. Byrom, Øivind Hodnebrog, Patrick Jöckel, Mariano Mertens, Gunnar Myhre, Matthias Nützel, Dirk Olivié, Ragnhild Bieltvedt Skeie, Laura Stecher, Larry W. Horowitz, Vaishali Naik, Gregory Faluvegi, Ulas Im, Lee T. Murray, Drew Shindell, Kostas Tsigaridis, Nathan Luke Abraham, and James Keeble
Atmos. Chem. Phys., 25, 9031–9060, https://doi.org/10.5194/acp-25-9031-2025, https://doi.org/10.5194/acp-25-9031-2025, 2025
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We used 7 climate models that include atmospheric chemistry and find that in a scenario with weak controls on air quality, the warming effects (over 2015 to 2050) of decreases in ozone-depleting substances and increases in air quality pollutants are approximately equal and would make ozone the second highest contributor to warming over this period. We find that for stratospheric ozone recovery, the standard measure of climate effects underestimates a more comprehensive measure.
Paul T. Griffiths, Laura J. Wilcox, Robert J. Allen, Vaishali Naik, Fiona M. O'Connor, Michael Prather, Alex Archibald, Florence Brown, Makoto Deushi, William Collins, Stephanie Fiedler, Naga Oshima, Lee T. Murray, Bjørn H. Samset, Chris Smith, Steven Turnock, Duncan Watson-Parris, and Paul J. Young
Atmos. Chem. Phys., 25, 8289–8328, https://doi.org/10.5194/acp-25-8289-2025, https://doi.org/10.5194/acp-25-8289-2025, 2025
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The Aerosol Chemistry Model Intercomparison Project (AerChemMIP) aimed to quantify the climate and air quality impacts of aerosols and chemically reactive gases. We review its contribution to AR6 (Sixth Assessment Report of the Intergovernmental Panel on Climate Change) and the wider understanding of the role of these species in climate and climate change. We identify challenges and provide recommendations to improve the utility and uptake of climate model data, detailed summary tables of CMIP6 models, experiments, and emergent diagnostics.
Ross J. Herbert, Andrew I. L. Williams, Philipp Weiss, Duncan Watson-Parris, Elisabeth Dingley, Daniel Klocke, and Philip Stier
Atmos. Chem. Phys., 25, 7789–7814, https://doi.org/10.5194/acp-25-7789-2025, https://doi.org/10.5194/acp-25-7789-2025, 2025
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Clouds exist at scales that climate models struggle to represent, limiting our knowledge of how climate change may impact clouds. Here we use a new kilometer-scale global model representing an important step towards the necessary scale. We focus on how aerosol particles modify clouds, radiation, and precipitation. We find the magnitude and manner of responses tend to vary from region to region, highlighting the potential of global kilometer-scale simulations and a need to represent aerosols in climate models.
Duncan Watson-Parris, Laura J. Wilcox, Camilla W. Stjern, Robert J. Allen, Geeta Persad, Massimo A. Bollasina, Annica M. L. Ekman, Carley E. Iles, Manoj Joshi, Marianne T. Lund, Daniel McCoy, Daniel M. Westervelt, Andrew I. L. Williams, and Bjørn H. Samset
Atmos. Chem. Phys., 25, 4443–4454, https://doi.org/10.5194/acp-25-4443-2025, https://doi.org/10.5194/acp-25-4443-2025, 2025
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In 2020, regulations by the International Maritime Organization aimed to reduce aerosol emissions from ships. These aerosols previously had a cooling effect, which the regulations might reduce, revealing more greenhouse gas warming. Here we find that, while there is regional warming, the global 2020–2040 temperature rise is only +0.03 °C. This small change is difficult to distinguish from natural climate variability, indicating the regulations have had a limited effect on observed warming to date.
Peer Nowack and Duncan Watson-Parris
Atmos. Chem. Phys., 25, 2365–2384, https://doi.org/10.5194/acp-25-2365-2025, https://doi.org/10.5194/acp-25-2365-2025, 2025
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In our article, we review uncertainties in global climate change projections and current methods using Earth observations as constraints, which is crucial for climate risk assessments and for informing society. We then discuss how machine learning can advance the field, discussing recent work that provides potentially stronger and more robust links between observed data and future climate projections. We further discuss the challenges of applying machine learning to climate science.
Mariya Petrenko, Ralph Kahn, Mian Chin, Susanne E. Bauer, Tommi Bergman, Huisheng Bian, Gabriele Curci, Ben Johnson, Johannes W. Kaiser, Zak Kipling, Harri Kokkola, Xiaohong Liu, Keren Mezuman, Tero Mielonen, Gunnar Myhre, Xiaohua Pan, Anna Protonotariou, Samuel Remy, Ragnhild Bieltvedt Skeie, Philip Stier, Toshihiko Takemura, Kostas Tsigaridis, Hailong Wang, Duncan Watson-Parris, and Kai Zhang
Atmos. Chem. Phys., 25, 1545–1567, https://doi.org/10.5194/acp-25-1545-2025, https://doi.org/10.5194/acp-25-1545-2025, 2025
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We compared smoke plume simulations from 11 global models to each other and to satellite smoke amount observations aimed at constraining smoke source strength. In regions where plumes are thick and background aerosol is low, models and satellites compare well. However, the input emission inventory tends to underestimate in many places, and particle property and loss rate assumptions vary enormously among models, causing uncertainties that require systematic in situ measurements to resolve.
Lauren R. Marshall, Anja Schmidt, Andrew P. Schurer, Nathan Luke Abraham, Lucie J. Lücke, Rob Wilson, Kevin J. Anchukaitis, Gabriele C. Hegerl, Ben Johnson, Bette L. Otto-Bliesner, Esther C. Brady, Myriam Khodri, and Kohei Yoshida
Clim. Past, 21, 161–184, https://doi.org/10.5194/cp-21-161-2025, https://doi.org/10.5194/cp-21-161-2025, 2025
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Large volcanic eruptions have caused temperature deviations over the past 1000 years; however, climate model results and reconstructions of surface cooling using tree rings do not match. We explore this mismatch using the latest models and find a better match to tree-ring reconstructions for some eruptions. Our results show that the way in which eruptions are simulated in models matters for the comparison to tree-rings, particularly regarding the spatial spread of volcanic aerosol.
Alex T. Archibald, Bablu Sinha, Maria R. Russo, Emily Matthews, Freya A. Squires, N. Luke Abraham, Stephane J.-B. Bauguitte, Thomas J. Bannan, Thomas G. Bell, David Berry, Lucy J. Carpenter, Hugh Coe, Andrew Coward, Peter Edwards, Daniel Feltham, Dwayne Heard, Jim Hopkins, James Keeble, Elizabeth C. Kent, Brian A. King, Isobel R. Lawrence, James Lee, Claire R. Macintosh, Alex Megann, Bengamin I. Moat, Katie Read, Chris Reed, Malcolm J. Roberts, Reinhard Schiemann, David Schroeder, Timothy J. Smyth, Loren Temple, Navaneeth Thamban, Lisa Whalley, Simon Williams, Huihui Wu, and Mingxi Yang
Earth Syst. Sci. Data, 17, 135–164, https://doi.org/10.5194/essd-17-135-2025, https://doi.org/10.5194/essd-17-135-2025, 2025
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Here, we present an overview of the data generated as part of the North Atlantic Climate System Integrated Study (ACSIS) programme that are available through dedicated repositories at the Centre for Environmental Data Analysis (CEDA; www.ceda.ac.uk) and the British Oceanographic Data Centre (BODC; bodc.ac.uk). The datasets described here cover the North Atlantic Ocean, the atmosphere above (it including its composition), and Arctic sea ice.
Trude Eidhammer, Andrew Gettelman, Katherine Thayer-Calder, Duncan Watson-Parris, Gregory Elsaesser, Hugh Morrison, Marcus van Lier-Walqui, Ci Song, and Daniel McCoy
Geosci. Model Dev., 17, 7835–7853, https://doi.org/10.5194/gmd-17-7835-2024, https://doi.org/10.5194/gmd-17-7835-2024, 2024
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We describe a dataset where 45 parameters related to cloud processes in the Community Earth System Model version 2 (CESM2) Community Atmosphere Model version 6 (CAM6) are perturbed. Three sets of perturbed parameter ensembles (263 members) were created: current climate, preindustrial aerosol loading and future climate with sea surface temperature increased by 4 K.
Stephanie Fiedler, Vaishali Naik, Fiona M. O'Connor, Christopher J. Smith, Paul Griffiths, Ryan J. Kramer, Toshihiko Takemura, Robert J. Allen, Ulas Im, Matthew Kasoar, Angshuman Modak, Steven Turnock, Apostolos Voulgarakis, Duncan Watson-Parris, Daniel M. Westervelt, Laura J. Wilcox, Alcide Zhao, William J. Collins, Michael Schulz, Gunnar Myhre, and Piers M. Forster
Geosci. Model Dev., 17, 2387–2417, https://doi.org/10.5194/gmd-17-2387-2024, https://doi.org/10.5194/gmd-17-2387-2024, 2024
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Climate scientists want to better understand modern climate change. Thus, climate model experiments are performed and compared. The results of climate model experiments differ, as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. This article gives insights into the challenges and outlines opportunities for further improving the understanding of climate change. It is based on views of a group of experts in atmospheric composition–climate interactions.
George Jordan, Florent Malavelle, Ying Chen, Amy Peace, Eliza Duncan, Daniel G. Partridge, Paul Kim, Duncan Watson-Parris, Toshihiko Takemura, David Neubauer, Gunnar Myhre, Ragnhild Skeie, Anton Laakso, and James Haywood
Atmos. Chem. Phys., 24, 1939–1960, https://doi.org/10.5194/acp-24-1939-2024, https://doi.org/10.5194/acp-24-1939-2024, 2024
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The 2014–15 Holuhraun eruption caused a huge aerosol plume in an otherwise unpolluted region, providing a chance to study how aerosol alters cloud properties. This two-part study uses observations and models to quantify this relationship’s impact on the Earth’s energy budget. Part 1 suggests the models capture the observed spatial and chemical evolution of the plume, yet no model plume is exact. Understanding these differences is key for Part 2, where changes to cloud properties are explored.
Ben A. Cala, Scott Archer-Nicholls, James Weber, N. Luke Abraham, Paul T. Griffiths, Lorrie Jacob, Y. Matthew Shin, Laura E. Revell, Matthew Woodhouse, and Alexander T. Archibald
Atmos. Chem. Phys., 23, 14735–14760, https://doi.org/10.5194/acp-23-14735-2023, https://doi.org/10.5194/acp-23-14735-2023, 2023
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Dimethyl sulfide (DMS) is an important trace gas emitted from the ocean recognised as setting the sulfate aerosol background, but its oxidation is complex. As a result representation in chemistry-climate models is greatly simplified. We develop and compare a new mechanism to existing mechanisms via a series of global and box model experiments. Our studies show our updated DMS scheme is a significant improvement but significant variance exists between mechanisms.
Ewa M. Bednarz, Ryan Hossaini, N. Luke Abraham, and Martyn P. Chipperfield
Geosci. Model Dev., 16, 6187–6209, https://doi.org/10.5194/gmd-16-6187-2023, https://doi.org/10.5194/gmd-16-6187-2023, 2023
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Development and performance of the new DEST chemistry scheme of UM–UKCA is described. The scheme extends the standard StratTrop scheme by including important updates to the halogen chemistry, thus allowing process-oriented studies of stratospheric ozone depletion and recovery, including impacts from both controlled long-lived ozone-depleting substances and emerging issues around uncontrolled, very short-lived substances. It will thus aid studies in support of future ozone assessment reports.
Peter Manshausen, Duncan Watson-Parris, Matthew W. Christensen, Jukka-Pekka Jalkanen, and Philip Stier
Atmos. Chem. Phys., 23, 12545–12555, https://doi.org/10.5194/acp-23-12545-2023, https://doi.org/10.5194/acp-23-12545-2023, 2023
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Aerosol from burning fuel changes cloud properties, e.g., the number of droplets and the content of water. Here, we study how clouds respond to different amounts of shipping aerosol. Droplet numbers increase linearly with increasing aerosol over a broad range until they stop increasing, while the amount of liquid water always increases, independently of emission amount. These changes in cloud properties can make them reflect more or less sunlight, which is important for the earth's climate.
Leighton A. Regayre, Lucia Deaconu, Daniel P. Grosvenor, David M. H. Sexton, Christopher Symonds, Tom Langton, Duncan Watson-Paris, Jane P. Mulcahy, Kirsty J. Pringle, Mark Richardson, Jill S. Johnson, John W. Rostron, Hamish Gordon, Grenville Lister, Philip Stier, and Ken S. Carslaw
Atmos. Chem. Phys., 23, 8749–8768, https://doi.org/10.5194/acp-23-8749-2023, https://doi.org/10.5194/acp-23-8749-2023, 2023
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Aerosol forcing of Earth’s energy balance has persisted as a major cause of uncertainty in climate simulations over generations of climate model development. We show that structural deficiencies in a climate model are exposed by comprehensively exploring parametric uncertainty and that these deficiencies limit how much the model uncertainty can be reduced through observational constraint. This provides a future pathway towards building models with greater physical realism and lower uncertainty.
Maria Rosa Russo, Brian John Kerridge, Nathan Luke Abraham, James Keeble, Barry Graham Latter, Richard Siddans, James Weber, Paul Thomas Griffiths, John Adrian Pyle, and Alexander Thomas Archibald
Atmos. Chem. Phys., 23, 6169–6196, https://doi.org/10.5194/acp-23-6169-2023, https://doi.org/10.5194/acp-23-6169-2023, 2023
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Tropospheric ozone is an important component of the Earth system as it can affect both climate and air quality. In this work we use observed tropospheric ozone derived from satellite observations and compare it to tropospheric ozone from model simulations. Our aim is to investigate recent changes (2005–2018) in tropospheric ozone in the North Atlantic region and to understand what factors are driving such changes.
Scott Archer-Nicholls, Rachel Allen, Nathan L. Abraham, Paul T. Griffiths, and Alex T. Archibald
Atmos. Chem. Phys., 23, 5801–5813, https://doi.org/10.5194/acp-23-5801-2023, https://doi.org/10.5194/acp-23-5801-2023, 2023
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The nitrate radical is a major oxidant at nighttime, but much less is known about it than about the other oxidants ozone and OH. We use Earth system model calculations to show how the nitrate radical has changed in abundance from 1850–2014 and to 2100 under a range of different climate and emission scenarios. Depending on the emissions and climate scenario, significant increases are projected with implications for the oxidation of volatile organic compounds and the formation of fine aerosol.
Leighton A. Regayre, Lucia Deaconu, Daniel P. Grosvenor, David Sexton, Christopher C. Symonds, Tom Langton, Duncan Watson-Paris, Jane P. Mulcahy, Kirsty J. Pringle, Mark Richardson, Jill S. Johnson, John Rostron, Hamish Gordon, Grenville Lister, Philip Stier, and Ken S. Carslaw
EGUsphere, https://doi.org/10.5194/egusphere-2022-1330, https://doi.org/10.5194/egusphere-2022-1330, 2022
Preprint archived
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We show that potential structural deficiencies in a climate model can be exposed by comprehensively exploring its parametric uncertainty, and that these deficiencies limit how much the model uncertainty can be reduced through observational constraint. Combined consideration of parametric and structural uncertainties provides a future pathway towards building models that have greater physical realism and lower uncertainty.
Haochi Che, Philip Stier, Duncan Watson-Parris, Hamish Gordon, and Lucia Deaconu
Atmos. Chem. Phys., 22, 10789–10807, https://doi.org/10.5194/acp-22-10789-2022, https://doi.org/10.5194/acp-22-10789-2022, 2022
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Extensive stratocumulus clouds over the south-eastern Atlantic (SEA) can lead to a cooling effect on the climate. A key pathway by which aerosols affect cloud properties is by acting as cloud condensation nuclei (CCN). Here, we investigated the source attribution of CCN in the SEA as well as the cloud responses. Our results show that aerosol nucleation contributes most to CCN in the marine boundary layer. In terms of emissions, anthropogenic sources contribute most to the CCN and cloud droplets.
Ewa M. Bednarz, Ryan Hossaini, Martyn P. Chipperfield, N. Luke Abraham, and Peter Braesicke
Atmos. Chem. Phys., 22, 10657–10676, https://doi.org/10.5194/acp-22-10657-2022, https://doi.org/10.5194/acp-22-10657-2022, 2022
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Atmospheric impacts of chlorinated very short-lived substances (Cl-VSLS) over the first two decades of the 21st century are assessed using the UM-UKCA chemistry–climate model. Stratospheric input of Cl from Cl-VSLS is estimated at ~130 ppt in 2019. The use of model set-up with constrained meteorology significantly increases the abundance of Cl-VSLS in the lower stratosphere relative to the free-running set-up. The growth in Cl-VSLS emissions significantly impacted recent HCl and COCl2 trends.
Cynthia H. Whaley, Rashed Mahmood, Knut von Salzen, Barbara Winter, Sabine Eckhardt, Stephen Arnold, Stephen Beagley, Silvia Becagli, Rong-You Chien, Jesper Christensen, Sujay Manish Damani, Xinyi Dong, Konstantinos Eleftheriadis, Nikolaos Evangeliou, Gregory Faluvegi, Mark Flanner, Joshua S. Fu, Michael Gauss, Fabio Giardi, Wanmin Gong, Jens Liengaard Hjorth, Lin Huang, Ulas Im, Yugo Kanaya, Srinath Krishnan, Zbigniew Klimont, Thomas Kühn, Joakim Langner, Kathy S. Law, Louis Marelle, Andreas Massling, Dirk Olivié, Tatsuo Onishi, Naga Oshima, Yiran Peng, David A. Plummer, Olga Popovicheva, Luca Pozzoli, Jean-Christophe Raut, Maria Sand, Laura N. Saunders, Julia Schmale, Sangeeta Sharma, Ragnhild Bieltvedt Skeie, Henrik Skov, Fumikazu Taketani, Manu A. Thomas, Rita Traversi, Kostas Tsigaridis, Svetlana Tsyro, Steven Turnock, Vito Vitale, Kaley A. Walker, Minqi Wang, Duncan Watson-Parris, and Tahya Weiss-Gibbons
Atmos. Chem. Phys., 22, 5775–5828, https://doi.org/10.5194/acp-22-5775-2022, https://doi.org/10.5194/acp-22-5775-2022, 2022
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Air pollutants, like ozone and soot, play a role in both global warming and air quality. Atmospheric models are often used to provide information to policy makers about current and future conditions under different emissions scenarios. In order to have confidence in those simulations, in this study we compare simulated air pollution from 18 state-of-the-art atmospheric models to measured air pollution in order to assess how well the models perform.
Matthew W. Christensen, Andrew Gettelman, Jan Cermak, Guy Dagan, Michael Diamond, Alyson Douglas, Graham Feingold, Franziska Glassmeier, Tom Goren, Daniel P. Grosvenor, Edward Gryspeerdt, Ralph Kahn, Zhanqing Li, Po-Lun Ma, Florent Malavelle, Isabel L. McCoy, Daniel T. McCoy, Greg McFarquhar, Johannes Mülmenstädt, Sandip Pal, Anna Possner, Adam Povey, Johannes Quaas, Daniel Rosenfeld, Anja Schmidt, Roland Schrödner, Armin Sorooshian, Philip Stier, Velle Toll, Duncan Watson-Parris, Robert Wood, Mingxi Yang, and Tianle Yuan
Atmos. Chem. Phys., 22, 641–674, https://doi.org/10.5194/acp-22-641-2022, https://doi.org/10.5194/acp-22-641-2022, 2022
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Trace gases and aerosols (tiny airborne particles) are released from a variety of point sources around the globe. Examples include volcanoes, industrial chimneys, forest fires, and ship stacks. These sources provide opportunistic experiments with which to quantify the role of aerosols in modifying cloud properties. We review the current state of understanding on the influence of aerosol on climate built from the wide range of natural and anthropogenic laboratories investigated in recent decades.
Duncan Watson-Parris, Andrew Williams, Lucia Deaconu, and Philip Stier
Geosci. Model Dev., 14, 7659–7672, https://doi.org/10.5194/gmd-14-7659-2021, https://doi.org/10.5194/gmd-14-7659-2021, 2021
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The Earth System Emulator (ESEm) provides a fast and flexible framework for emulating a wide variety of Earth science datasets and tools for constraining (or tuning) models of any complexity. Three distinct use cases are presented that demonstrate the utility of ESEm and provide some insight into the use of machine learning for emulation in these different settings. The open-source Python package is freely available so that it might become a valuable tool for the community.
Maria Sand, Bjørn H. Samset, Gunnar Myhre, Jonas Gliß, Susanne E. Bauer, Huisheng Bian, Mian Chin, Ramiro Checa-Garcia, Paul Ginoux, Zak Kipling, Alf Kirkevåg, Harri Kokkola, Philippe Le Sager, Marianne T. Lund, Hitoshi Matsui, Twan van Noije, Dirk J. L. Olivié, Samuel Remy, Michael Schulz, Philip Stier, Camilla W. Stjern, Toshihiko Takemura, Kostas Tsigaridis, Svetlana G. Tsyro, and Duncan Watson-Parris
Atmos. Chem. Phys., 21, 15929–15947, https://doi.org/10.5194/acp-21-15929-2021, https://doi.org/10.5194/acp-21-15929-2021, 2021
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Absorption of shortwave radiation by aerosols can modify precipitation and clouds but is poorly constrained in models. A total of 15 different aerosol models from AeroCom phase III have reported total aerosol absorption, and for the first time, 11 of these models have reported in a consistent experiment the contributions to absorption from black carbon, dust, and organic aerosol. Here, we document the model diversity in aerosol absorption.
Anthony C. Jones, Adrian Hill, Samuel Remy, N. Luke Abraham, Mohit Dalvi, Catherine Hardacre, Alan J. Hewitt, Ben Johnson, Jane P. Mulcahy, and Steven T. Turnock
Atmos. Chem. Phys., 21, 15901–15927, https://doi.org/10.5194/acp-21-15901-2021, https://doi.org/10.5194/acp-21-15901-2021, 2021
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Ammonium nitrate is hard to model because it forms and evaporates rapidly. One approach is to relate its equilibrium concentration to temperature, humidity, and the amount of nitric acid and ammonia gases. Using this approach, we limit the rate at which equilibrium is reached using various condensation rates in a climate model. We show that ammonium nitrate concentrations are highly sensitive to the condensation rate. Our results will help improve the representation of nitrate in climate models.
James Weber, Scott Archer-Nicholls, Nathan Luke Abraham, Youngsub M. Shin, Thomas J. Bannan, Carl J. Percival, Asan Bacak, Paulo Artaxo, Michael Jenkin, M. Anwar H. Khan, Dudley E. Shallcross, Rebecca H. Schwantes, Jonathan Williams, and Alex T. Archibald
Geosci. Model Dev., 14, 5239–5268, https://doi.org/10.5194/gmd-14-5239-2021, https://doi.org/10.5194/gmd-14-5239-2021, 2021
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The new mechanism CRI-Strat 2 features state-of-the-art isoprene chemistry not previously available in UKCA and improves UKCA's ability to reproduce observed concentrations of isoprene, monoterpenes, and OH in tropical regions. The enhanced ability to model isoprene, the most widely emitted non-methane volatile organic compound (VOC), will allow understanding of how isoprene and other biogenic VOCs affect atmospheric composition and, through biosphere–atmosphere feedbacks, climate change.
Shipeng Zhang, Philip Stier, and Duncan Watson-Parris
Atmos. Chem. Phys., 21, 10179–10197, https://doi.org/10.5194/acp-21-10179-2021, https://doi.org/10.5194/acp-21-10179-2021, 2021
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The relationship between aerosol-induced changes in atmospheric energetics and precipitation responses across different scales is studied in terms of fast (radiatively or microphysically mediated) and slow (temperature-mediated) responses. We introduced a method to decompose rainfall changes into contributions from clouds, aerosols, and clear–clean sky from an energetic perspective. It provides a way to better interpret and quantify the precipitation changes caused by aerosol perturbations.
John Staunton-Sykes, Thomas J. Aubry, Youngsub M. Shin, James Weber, Lauren R. Marshall, Nathan Luke Abraham, Alex Archibald, and Anja Schmidt
Atmos. Chem. Phys., 21, 9009–9029, https://doi.org/10.5194/acp-21-9009-2021, https://doi.org/10.5194/acp-21-9009-2021, 2021
Ashok K. Luhar, Ian E. Galbally, Matthew T. Woodhouse, and Nathan Luke Abraham
Atmos. Chem. Phys., 21, 7053–7082, https://doi.org/10.5194/acp-21-7053-2021, https://doi.org/10.5194/acp-21-7053-2021, 2021
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Lightning-generated nitrogen oxides (LNOx) greatly influence tropospheric photochemistry. The most common parameterisation of lightning flash rate used to calculate LNOx in global composition models underestimates measurements over the ocean by a factor of 20–25. We formulate and validate an alternative parameterisation to remedy this problem. The new scheme causes an increase in the ozone burden by 8.5 % and the hydroxyl radical by 13 %, and these have implications for climate and air quality.
Ananth Ranjithkumar, Hamish Gordon, Christina Williamson, Andrew Rollins, Kirsty Pringle, Agnieszka Kupc, Nathan Luke Abraham, Charles Brock, and Ken Carslaw
Atmos. Chem. Phys., 21, 4979–5014, https://doi.org/10.5194/acp-21-4979-2021, https://doi.org/10.5194/acp-21-4979-2021, 2021
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The effect aerosols have on climate can be better understood by studying their vertical and spatial distribution throughout the atmosphere. We use observation data from the ATom campaign and evaluate the vertical profile of aerosol number concentration, sulfur dioxide and condensation sink using the UKESM (UK Earth System Model). We identify uncertainties in key atmospheric processes that help improve their theoretical representation in global climate models.
Paul T. Griffiths, Lee T. Murray, Guang Zeng, Youngsub Matthew Shin, N. Luke Abraham, Alexander T. Archibald, Makoto Deushi, Louisa K. Emmons, Ian E. Galbally, Birgit Hassler, Larry W. Horowitz, James Keeble, Jane Liu, Omid Moeini, Vaishali Naik, Fiona M. O'Connor, Naga Oshima, David Tarasick, Simone Tilmes, Steven T. Turnock, Oliver Wild, Paul J. Young, and Prodromos Zanis
Atmos. Chem. Phys., 21, 4187–4218, https://doi.org/10.5194/acp-21-4187-2021, https://doi.org/10.5194/acp-21-4187-2021, 2021
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We analyse the CMIP6 Historical and future simulations for tropospheric ozone, a species which is important for many aspects of atmospheric chemistry. We show that the current generation of models agrees well with observations, being particularly successful in capturing trends in surface ozone and its vertical distribution in the troposphere. We analyse the factors that control ozone and show that they evolve over the period of the CMIP6 experiments.
Cited articles
Abraham, N. L. and Russo, M. R.: UKESM1 hourly modelled ozone for comparison to observations. NERC EDS Centre for Environmental Data Analysis [data set], https://catalogue.ceda.ac.uk/uuid/300046500aeb4af080337ff86ae8e776, last access: April 2024.
Anderson, D. C., Duncan, B. N., Fiore, A. M., Baublitz, C. B., Follette-Cook, M. B., Nicely, J. M., and Wolfe, G. M.: Spatial and temporal variability in the hydroxyl (OH) radical: understanding the role of large-scale climate features and their influence on OH through its dynamical and photochemical drivers, Atmos. Chem. Phys., 21, 6481–6508, https://doi.org/10.5194/acp-21-6481-2021, 2021.
Archibald, A. T., Sinha, B., Russo, M., Matthews, E., Squires, F., Abraham, N. L., Bauguitte, S., Bannan, T., Bell, T., Berry, D., Carpenter, L., Coe, H., Coward, A., Edwards, P., Feltham, D., Heard, D., Hopkins, J., Keeble, J., Kent, E. C., King, B., Lawrence, I. R., Lee, J., Macintosh, C. R., Megann, A., Moat, B. I., Read, K., Reed, C., Roberts, M., Schiemann, R., Schroeder, D., Smyth, T., Temple, L., Thamban, N., Whalley, L., Williams, S., Wu, H., and Yang, M.-X.: Data supporting the North Atlantic Climate System: Integrated Studies (ACSIS) programme, including atmospheric composition, oceanographic and sea ice observations (2016–2022) and output from ocean, atmosphere, land and sea-ice models (1950–2050), Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2023-405, in review, 2024.
Carpenter, L. J., Hopkins, J. R., Lewis, A. C., Neves, L. M., Moller, S., Pilling, M. J., Read, K. A., Young, T. D., and Lee, J. D.: Continuous Cape Verde Atmospheric Observatory Observations [data set], https://catalogue.ceda.ac.uk/uuid/81693aad69409100b1b9a247b9ae75d5, last access: April 2024.
Facility for Airborne Atmospheric Measurements, National Centre for Atmospheric Science, UK, Russo, M., and Abraham, N. L.: VISION: Collated subset of FAAM ozone data 2010 to 2020, NERC EDS Centre for Environmental Data Analysis [data set], https://catalogue.ceda.ac.uk/uuid/8df2e81dbfc2499983aa87781fb3fd5a/ (last access: April 2024), 2024.
Griffiths, P. T., Murray, L. T., Zeng, G., Shin, Y. M., Abraham, N. L., Archibald, A. T., Deushi, M., Emmons, L. K., Galbally, I. E., Hassler, B., Horowitz, L. W., Keeble, J., Liu, J., Moeini, O., Naik, V., O'Connor, F. M., Oshima, N., Tarasick, D., Tilmes, S., Turnock, S. T., Wild, O., Young, P. J., and Zanis, P.: Tropospheric ozone in CMIP6 simulations, Atmos. Chem. Phys., 21, 4187–4218, https://doi.org/10.5194/acp-21-4187-2021, 2021.
Hassell, D. and Bartholomew, S.: cfdm: A Python reference implementation of the CF data model, JOSS, 5, 2717, https://doi.org/10.21105/joss.02717, 2020.
Hattersley, R., Little, B., Peglar, P., Elson, P., Campbell, E., Killick, P., Blay, B., De Andrade, E. S., Lbdreyer, Dawson, A., Yeo, M., Comer, R., Bosley, C., Kirkham, D., Tkknight, Stephenworsley, Benfold, W., Kwilliams-Mo, Tv3141, Filipe, Elias, Gm-S, Leuprecht, A., Hoyer, S., Robinson, N., and Penn, J.: SciTools/iris: v3.7.0, Zenodo [code], https://doi.org/10.5281/ZENODO.595182, 2023.
Kanaya, Y., Miyazaki, K., Taketani, F., Miyakawa, T., Takashima, H., Komazaki, Y., Pan, X., Kato, S., Sudo, K., Sekiya, T., Inoue, J., Sato, K., and Oshima, K.: Ozone and carbon monoxide observations over open oceans on R/V Mirai from 67° S to 75° N during 2012 to 2017: testing global chemical reanalysis in terms of Arctic processes, low ozone levels at low latitudes, and pollution transport, Atmos. Chem. Phys., 19, 7233–7254, https://doi.org/10.5194/acp-19-7233-2019, 2019.
Kim, P. S., Jacob, D. J., Fisher, J. A., Travis, K., Yu, K., Zhu, L., Yantosca, R. M., Sulprizio, M. P., Jimenez, J. L., Campuzano-Jost, P., Froyd, K. D., Liao, J., Hair, J. W., Fenn, M. A., Butler, C. F., Wagner, N. L., Gordon, T. D., Welti, A., Wennberg, P. O., Crounse, J. D., St. Clair, J. M., Teng, A. P., Millet, D. B., Schwarz, J. P., Markovic, M. Z., and Perring, A. E.: Sources, seasonality, and trends of southeast US aerosol: an integrated analysis of surface, aircraft, and satellite observations with the GEOS-Chem chemical transport model, Atmos. Chem. Phys., 15, 10411–10433, https://doi.org/10.5194/acp-15-10411-2015, 2015.
Lawrence, B. N., Bennett, V., Churchill, J., Juckes, M., Kershaw, P., Oliver, P., Pritchard, M., and Stephens, A.: The JASMIN super-data-cluster, ARXIV [preprint], https://doi.org/10.48550/ARXIV.1204.3553, 2012.
Lelieveld, J., Van Aardenne, J., Fischer, H., De Reus, M., Williams, J., and Winkler, P.: Increasing Ozone over the Atlantic Ocean, Science, 304, 1483–1487, https://doi.org/10.1126/science.1096777, 2004.
Oliver, H. J., Shin, M., Fitzpatrick, B., Clark, A., Sanders, O., Valters, D., Smout-Day, K., Bartholomew, S., Prasanna Challuri, Matthews, D., Wales, S., Tomek Trzeciak, Kinoshita, B. P., Hatcher, R., Osprey, A., Reinecke, A., Williams, J., Jontyq, Coleman, T., Dix, M., and Pulo, K.: Cylc – a workflow engine, Zenodo [software], https://doi.org/10.5281/ZENODO.1208732, 2018.
Rew, R., Davis, G., Emmerson, S., Cormack, C., Caron, J., Pincus, R., Hartnett, E., Heimbigner, D., Appel, L., and Fisher, W.: Unidata NetCDF, UniData [data set], https://doi.org/10.5065/D6H70CW6, 1989.
Russo, M. R. and Bartholomew, S. L.: NCAS-VISION/VISION-toolkit: 1.0 (v1.0), Zenodo [code], https://doi.org/10.5281/zenodo.10927302, 2024.
Russo, M. R., Kerridge, B. J., Abraham, N. L., Keeble, J., Latter, B. G., Siddans, R., Weber, J., Griffiths, P. T., Pyle, J. A., and Archibald, A. T.: Seasonal, interannual and decadal variability of tropospheric ozone in the North Atlantic: comparison of UM-UKCA and remote sensing observations for 2005–2018, Atmos. Chem. Phys., 23, 6169–6196, https://doi.org/10.5194/acp-23-6169-2023, 2023.
Russo, M. R., Abraham, N. L., and FAAM Airborne Laboratory: FAAM ozone dataset 2010 to 2020. NERC EDS Centre for Environmental Data Analysis [data set], https://catalogue.ceda.ac.uk/uuid/8df2e81dbfc2499983aa87781fb3fd5a (last access: 8 January 2025), 2024.
Shin, M., Fitzpatrick, B., Clark, A., Sanders, O., Smout-Day, K., Whitehouse, S., Wardle, S., Matthews, D., Oxley, S., Valters, D., Mancell, J., Harry-Shepherd, Bartholomew, S., Oliver, H. J., Wales, S., Seddon, J., Osprey, A., Dix, M., and Sharp, R.: metomi/rose: Rose 2018.02.0, Zenodo [code], https://doi.org/10.5281/ZENODO.1168021, 2018.
Smith, M., Met Office, and Natural Environment Research Council: Facility for Airborne Atmospheric Measurements [data set], http://catalogue.ceda.ac.uk/uuid/affe775e8d8890a4556aec5bc4e0b45c (last access: 8 January 2025), 2024.
Stevenson, D. S., Zhao, A., Naik, V., O'Connor, F. M., Tilmes, S., Zeng, G., Murray, L. T., Collins, W. J., Griffiths, P. T., Shim, S., Horowitz, L. W., Sentman, L. T., and Emmons, L.: Trends in global tropospheric hydroxyl radical and methane lifetime since 1850 from AerChemMIP, Atmos. Chem. Phys., 20, 12905–12920, https://doi.org/10.5194/acp-20-12905-2020, 2020.
Telford, P. J., Braesicke, P., Morgenstern, O., and Pyle, J. A.: Technical Note: Description and assessment of a nudged version of the new dynamics Unified Model, Atmos. Chem. Phys., 8, 1701–1712, https://doi.org/10.5194/acp-8-1701-2008, 2008.
Telford, P. J., Abraham, N. L., Archibald, A. T., Braesicke, P., Dalvi, M., Morgenstern, O., O'Connor, F. M., Richards, N. A. D., and Pyle, J. A.: Implementation of the Fast-JX Photolysis scheme (v6.4) into the UKCA component of the MetUM chemistry-climate model (v7.3), Geosci. Model Dev., 6, 161–177, https://doi.org/10.5194/gmd-6-161-2013, 2013.
Thompson, C. R., Wofsy, S. C., Prather, M. J., Newman, P. A., Hanisco, T. F., Ryerson, T. B., Fahey, D. W., Apel, E. C., Brock, C. A., Brune, W. H., Froyd, K., Katich, J. M., Nicely, J. M., Peischl, J., Ray, E., Veres, P. R., Wang, S., Allen, H. M., Asher, E., Bian, H., Blake, D., Bourgeois, I., Budney, J., Bui, T. P., Butler, A., Campuzano-Jost, P., Chang, C., Chin, M., Commane, R., Correa, G., Crounse, J. D., Daube, B., Dibb, J. E., DiGangi, J. P., Diskin, G. S., Dollner, M., Elkins, J. W., Fiore, A. M., Flynn, C. M., Guo, H., Hall, S. R., Hannun, R. A., Hills, A., Hintsa, E. J., Hodzic, A., Hornbrook, R. S., Huey, L. G., Jimenez, J. L., Keeling, R. F., Kim, M. J., Kupc, A., Lacey, F., Lait, L. R., Lamarque, J.-F., Liu, J., McKain, K., Meinardi, S., Miller, D. O., Montzka, S. A., Moore, F. L., Morgan, E. J., Murphy, D. M., Murray, L. T., Nault, B. A., Neuman, J. A., Nguyen, L., Gonzalez, Y., Rollins, A., Rosenlof, K., Sargent, M., Schill, G., Schwarz, J. P., Clair, J. M. St., Steenrod, S. D., Stephens, B. B., Strahan, S. E., Strode, S. A., Sweeney, C., Thames, A. B., Ullmann, K., Wagner, N., Weber, R., Weinzierl, B., Wennberg, P. O., Williamson, C. J., Wolfe, G. M., and Zeng, L.: The NASA Atmospheric Tomography (ATom) Mission: Imaging the Chemistry of the Global Atmosphere, B. Am. Meteorol. Soc., 103, E761–E790, https://doi.org/10.1175/BAMS-D-20-0315.1, 2022.
Thornhill, G., Collins, W., Olivié, D., Skeie, R. B., Archibald, A., Bauer, S., Checa-Garcia, R., Fiedler, S., Folberth, G., Gjermundsen, A., Horowitz, L., Lamarque, J.-F., Michou, M., Mulcahy, J., Nabat, P., Naik, V., O'Connor, F. M., Paulot, F., Schulz, M., Scott, C. E., Séférian, R., Smith, C., Takemura, T., Tilmes, S., Tsigaridis, K., and Weber, J.: Climate-driven chemistry and aerosol feedbacks in CMIP6 Earth system models, Atmos. Chem. Phys., 21, 1105–1126, https://doi.org/10.5194/acp-21-1105-2021, 2021.
Wang, Y., Ma, Y.-F., Eskes, H., Inness, A., Flemming, J., and Brasseur, G. P.: Evaluation of the CAMS global atmospheric trace gas reanalysis 2003–2016 using aircraft campaign observations, Atmos. Chem. Phys., 20, 4493–4521, https://doi.org/10.5194/acp-20-4493-2020, 2020.
Watson-Parris, D., Schutgens, N., Cook, N., Kipling, Z., Kershaw, P., Gryspeerdt, E., Lawrence, B., and Stier, P.: Community Intercomparison Suite (CIS) v1.4.0: a tool for intercomparing models and observations, Geosci. Model Dev., 9, 3093–3110, https://doi.org/10.5194/gmd-9-3093-2016, 2016.
Wofsy, S. C., Afshar, S., Allen, H. M., Apel, E. C., Asher, E. C., Barletta, B., Bent, J., Bian, H., Biggs, B. C., Blake, D. R., Blake, N., Bourgeois, I., Brock, C. A., Brune, W. H., Budney, J. W., Bui, T. P., Butler, A., Campuzano-Jost, P., Chang, C. S., Chin, M., Commane, R., Correa, G., Crounse, J. D., Cullis, P. D., Daube, B. C., Day, D. A., Dean-Day, J. M., Dibb, J. E., DiGangi, J. P., Diskin, G. S., Dollner, M., Elkins, J. W., Erdesz, F., Fiore, A. M., Flynn, C. M., Froyd, K. D., Gesler, D. W., Hall, S. R., Hanisco, T. F., Hannun, R. A., Hills, A. J., Hintsa, E. J., Hoffman, A., Hornbrook, R. S., Huey, L. G., Hughes, S., Jimenez, J. L., Johnson, B. J., Katich, J. M., Keeling, R. F., Kim, M. J., Kupc, A., Lait, L. R., McKain, K., Mclaughlin, R. J., Meinardi, S., Miller, D. O., Montzka, S. A., Moore, F. L., Morgan, E. J., Murphy, D. M., Murray, L. T., Nault, B. A., Neuman, J. A., Newman, P. A., Nicely, J. M., Pan, X., Paplawsky, W., Peischl, J., Prather, M. J., Price, D. J., Ray, E. A., Reeves, J. M., Richardson, M., Rollins, A. W., Rosenlof, K. H., Ryerson, T. B., Scheuer, E., Schill, G. P., Schroder, J. C., Schwarz, J. P., St.Clair, J. M., Steenrod, S. D., Stephens, B. B., Strode, S. A., Sweeney, C., Tanner, D., Teng, A. P., Thames, A. B., Thompson, C. R., Ullmann, K., Veres, P. R., Wagner, N. L., Watt, A., Weber, R., Weinzierl, B. B., Wennberg, P. O., Williamson, C. J., Wilson, J. C., Wolfe, G. M., Woods, C. T., Zeng, L. H., and Vieznor, N.: ATom: Merged Atmospheric Chemistry, Trace Gases, and Aerosols, Version 2, ORNL DAAC, Oak Ridge, Tennessee, USA [data set], https://doi.org/10.3334/ORNLDAAC/1925, 2021.
Zeng, X., Atlas, R., Birk, R. J., Carr, F. H., Carrier, M. J., Cucurull, L., Hooke, W. H., Kalnay, E., Murtugudde, R., Posselt, D. J., Russell, J. L., Tyndall, D. P., Weller, R. A., and Zhang, F.: Use of Observing System Simulation Experiments in the United States, B. Am. Meteorol. Soc., 101, E1427–E1438, https://doi.org/10.1175/BAMS-D-19-0155.1, 2020.
Short summary
Observational data and modelling capabilities have expanded in recent years, but there are still barriers preventing these two data sources from being used in synergy. Proper comparison requires generating, storing, and handling a large amount of data. This work describes the first step in the development of a new set of software tools, the VISION toolkit, which can enable the easy and efficient integration of observational and model data required for model evaluation.
Observational data and modelling capabilities have expanded in recent years, but there are still...
