Articles | Volume 14, issue 9
https://doi.org/10.5194/gmd-14-5373-2021
© Author(s) 2021. 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-14-5373-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model experiment description paper
| 
01 Sep 2021
Model experiment description paper |
| 01 Sep 2021
| 01 Sep 2021
Calibrating a global atmospheric chemistry transport model using Gaussian process emulation and ground-level concentrations of ozone and carbon monoxide
Edmund Ryan
Lancaster Environment Centre, Lancaster University, Lancaster, UK
now at: Corndel, London, UK
Lancaster Environment Centre, Lancaster University, Lancaster, UK
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Gunnar Myhre, Øivind Hodnebrog, Srinath Krishnan, Maria Sand, Marit Sandstad, Ragnhild B. Skeie, Lieven Clarisse, Bruno Franco, Dylan B. Millet, Kelley C. Wells, Alexander Archibald, Hannah N. Bryant, Alex T. Chaudhri, David S. Stevenson, Didier Hauglustaine, Michael Prather, J. Christopher Kaiser, Dirk J. L. Olivie, Michael Schulz, Oliver Wild, Ye Wang, Thérèse Salameh, Jason E. Williams, Philippe Le Sager, Fabien Paulot, Kostas Tsigaridis, and Haley E. Plaas
Geosci. Model Dev., 19, 2577–2591, https://doi.org/10.5194/gmd-19-2577-2026, https://doi.org/10.5194/gmd-19-2577-2026, 2026
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Volatile organic compounds (VOCs) affect air quality and climate, but their behavior in the atmosphere is still uncertain. We launched a global research effort to compare how different models represent these compounds and to improve their accuracy. By analyzing model results alongside observations and satellite data, we aim to better understand the atmospheric composition of these compounds.
Tim Butler, Tabish Ansari, Claudio A. Belis, Elisa Bergas-Masso, Willem van Caspel, Hilde Fagerli, Johannes Flemming, Marta Garcia Vivanco, Paul Griffiths, Douglas S. Hamilton, Coralina Hernandez Trujillo, Lena Höglund-Isaksson, Vincent Huijnen, Matthew Kasoar, Johannes W. Kaiser, Gerbrand Koren, Zbigniew Klimont, Florian Lindl, Aura Lupascu, Mariano Mertens, Martijn Schaap, Steven T. Turnock, Oliver Wild, Philipp Weiss, Jacek Kaminski, Rosa Wu, and Terry Keating
EGUsphere, https://doi.org/10.5194/egusphere-2026-1367, https://doi.org/10.5194/egusphere-2026-1367, 2026
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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Air pollution travels across continents, meaning emissions in one region can affect air quality far away. To better understand this, scientists from many groups are planning to run coordinated computer simulations of the atmosphere. By comparing results across models and emission scenarios, the planned study will show how pollution moves between regions and which sources matter most, helping governments design more effective air quality policies.
Oliver Wild and Edmund M. Ryan
Atmos. Chem. Phys., 26, 2255–2273, https://doi.org/10.5194/acp-26-2255-2026, https://doi.org/10.5194/acp-26-2255-2026, 2026
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This study provides a self-consistent quantitative analysis of how a wide range of physical, chemical and meteorological processes influence tropospheric ozone and oxidation as represented in global chemistry transport models. It identifies the largest sources of uncertainty in our current understanding and demonstrates the use of observations for formally constraining models and providing information on uncertainty at a process level.
Ruth M. Doherty, Zhenze Liu, Massimo Vieno, Oliver Wild, Fiona M. O'Connor, Steven T. Turnock, Christina M. Hood, Jenny R. Stocker, Mathew R. Heal, Dwayne E. Heard, Emma G. Sands, David J. Carruthers, and Lisa K. Whalley
EGUsphere, https://doi.org/10.5194/egusphere-2025-6407, https://doi.org/10.5194/egusphere-2025-6407, 2026
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This study developed a coupled model approach to investigate key processes determining how climate change impacts 21st-century air quality. Elevated isoprene emissions drive summer ozone and fine particulate matter increases over continental Europe; but their response to climate change is uncertain. Unabated climate change, without emission reductions, poses a challenge for achieving ozone, fine particulate matter and nitrogen dioxide long-term air quality guidelines over much of Europe by 2100.
Laura A. Mansfield, Peer J. Nowack, Edmund M. Ryan, Oliver Wild, and Apostolos Voulgarakis
EGUsphere, https://doi.org/10.5194/egusphere-2025-6046, https://doi.org/10.5194/egusphere-2025-6046, 2025
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We present a fast machine learning emulator that predicts how Earth’s surface temperature reacts within the first five years to changes in greenhouse gases and aerosol pollutants. It is trained on carefully designed simulations from a complex climate model, but can be run much faster. Our emulator can be used to show where the climate is most sensitive to different emissions and can help explore many possible future paths, making it easier to assess the climate effects of policy choices.
Zhenze Liu, Ke Li, Oliver Wild, Ruth M. Doherty, Fiona M. O’Connor, and Steven T. Turnock
Atmos. Chem. Phys., 25, 16969–16981, https://doi.org/10.5194/acp-25-16969-2025, https://doi.org/10.5194/acp-25-16969-2025, 2025
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Chemistry-climate models have advanced substantially over the decades, yet they still exhibit substantial systematic biases in simulating atmospheric composition due to gaps in our understanding of underlying processes. We improve the predictions of an Earth system model using deep learning, and evaluate the performance of difference types of statistical models. We find that simulations of future surface ozone are likely to become less accurate under a warmer climate.
Ken S. Carslaw, Leighton A. Regayre, Ulrike Proske, Andrew Gettelman, David M. H. Sexton, Yun Qian, Lauren Marshall, Oliver Wild, Marcus van Lier-Walqui, Annika Oertel, Saloua Peatier, Ben Yang, Jill S. Johnson, Sihan Li, Daniel T. McCoy, Benjamin M. Sanderson, Christina J. Williamson, Gregory S. Elsaesser, Kuniko Yamazaki, and Ben B. B. Booth
EGUsphere, https://doi.org/10.5194/egusphere-2025-4341, https://doi.org/10.5194/egusphere-2025-4341, 2025
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A major challenge in climate science is reducing projection uncertainty despite advances in models and observational constraints. Perturbed parameter ensembles (PPEs) offer a powerful tool to explore and reduce uncertainty by revealing model weaknesses and guiding development. PPEs are now widely applied across climate systems and scales. We argue they should be prioritized alongside complexity and resolution in model resource planning.
Cynthia H. Whaley, Tim Butler, Jose A. Adame, Rupal Ambulkar, Steve R. Arnold, Rebecca R. Buchholz, Benjamin Gaubert, Douglas S. Hamilton, Min Huang, Hayley Hung, Johannes W. Kaiser, Jacek W. Kaminski, Christoph Knote, Gerbrand Koren, Jean-Luc Kouassi, Meiyun Lin, Tianjia Liu, Jianmin Ma, Kasemsan Manomaiphiboon, Elisa Bergas Masso, Jessica L. McCarty, Mariano Mertens, Mark Parrington, Helene Peiro, Pallavi Saxena, Saurabh Sonwani, Vanisa Surapipith, Damaris Y. T. Tan, Wenfu Tang, Veerachai Tanpipat, Kostas Tsigaridis, Christine Wiedinmyer, Oliver Wild, Yuanyu Xie, and Paquita Zuidema
Geosci. Model Dev., 18, 3265–3309, https://doi.org/10.5194/gmd-18-3265-2025, https://doi.org/10.5194/gmd-18-3265-2025, 2025
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The multi-model experiment design of the HTAP3 Fires project takes a multi-pollutant approach to improving our understanding of transboundary transport of wildland fire and agricultural burning emissions and their impacts. The experiments are designed with the goal of answering science policy questions related to fires. The options for the multi-model approach, including inputs, outputs, and model setup, are discussed, and the official recommendations for the project are presented.
Pierluigi Renan Guaita, Riccardo Marzuoli, Leiming Zhang, Steven Turnock, Gerbrand Koren, Oliver Wild, Paola Crippa, and Giacomo Alessandro Gerosa
EGUsphere, https://doi.org/10.5194/egusphere-2024-2573, https://doi.org/10.5194/egusphere-2024-2573, 2024
Preprint archived
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This study assesses the global impact of tropospheric ozone on wheat crops in the 21st century under various climate scenarios. The research highlights that ozone damage to wheat varies by region and depends on both ozone levels and climate. Vulnerable regions include East Asia, Northern Europe, and the Southern and Eastern edges of the Tibetan Plateau. Our results emphasize the need of policies to reduce ozone levels and mitigate climate change to protect global food security.
Ailish M. Graham, Richard J. Pope, Martyn P. Chipperfield, Sandip S. Dhomse, Matilda Pimlott, Wuhu Feng, Vikas Singh, Ying Chen, Oliver Wild, Ranjeet Sokhi, and Gufran Beig
Atmos. Chem. Phys., 24, 789–806, https://doi.org/10.5194/acp-24-789-2024, https://doi.org/10.5194/acp-24-789-2024, 2024
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Our paper uses novel satellite datasets and high-resolution emissions datasets alongside a back-trajectory model to investigate the balance of local and external sources influencing NOx air pollution changes in Delhi. We find in the post-monsoon season that NOx from local and non-local transport emissions contributes most to poor air quality in Delhi. Therefore, air quality mitigation strategies in Delhi and surrounding regions are used to control this issue.
Xuewei Hou, Oliver Wild, Bin Zhu, and James Lee
Atmos. Chem. Phys., 23, 15395–15411, https://doi.org/10.5194/acp-23-15395-2023, https://doi.org/10.5194/acp-23-15395-2023, 2023
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In response to the climate crisis, many countries have committed to net zero in a certain future year. The impacts of net-zero scenarios on tropospheric O3 are less well studied and remain unclear. In this study, we quantified the changes of tropospheric O3 budgets, spatiotemporal distributions of future surface O3 in east Asia and regional O3 source contributions for 2060 under a net-zero scenario using the NCAR Community Earth System Model (CESM) and online O3-tagging methods.
Zhenze Liu, Oliver Wild, Ruth M. Doherty, Fiona M. O'Connor, and Steven T. Turnock
Atmos. Chem. Phys., 23, 13755–13768, https://doi.org/10.5194/acp-23-13755-2023, https://doi.org/10.5194/acp-23-13755-2023, 2023
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We investigate the impact of net-zero policies on surface ozone pollution in China. A chemistry–climate model is used to simulate ozone changes driven by local and external emissions, methane, and warmer climates. A deep learning model is applied to generate more robust ozone projection, and we find that the benefits of net-zero policies may be overestimated with the chemistry–climate model. Nevertheless, it is clear that the policies can still substantially reduce ozone pollution in future.
Ernesto Reyes-Villegas, Douglas Lowe, Jill S. Johnson, Kenneth S. Carslaw, Eoghan Darbyshire, Michael Flynn, James D. Allan, Hugh Coe, Ying Chen, Oliver Wild, Scott Archer-Nicholls, Alex Archibald, Siddhartha Singh, Manish Shrivastava, Rahul A. Zaveri, Vikas Singh, Gufran Beig, Ranjeet Sokhi, and Gordon McFiggans
Atmos. Chem. Phys., 23, 5763–5782, https://doi.org/10.5194/acp-23-5763-2023, https://doi.org/10.5194/acp-23-5763-2023, 2023
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Organic aerosols (OAs), their sources and their processes remain poorly understood. The volatility basis set (VBS) approach, implemented in air quality models such as WRF-Chem, can be a useful tool to describe primary OA (POA) production and aging. However, the main disadvantage is its complexity. We used a Gaussian process simulator to reproduce model results and to estimate the sources of model uncertainty. We do this by comparing the outputs with OA observations made at Delhi, India, in 2018.
Zixuan Jia, Carlos Ordóñez, Ruth M. Doherty, Oliver Wild, Steven T. Turnock, and Fiona M. O'Connor
Atmos. Chem. Phys., 23, 2829–2842, https://doi.org/10.5194/acp-23-2829-2023, https://doi.org/10.5194/acp-23-2829-2023, 2023
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This study investigates the influence of the winter large-scale circulation on daily concentrations of PM2.5 and their sensitivity to emissions. The new proposed circulation index can effectively distinguish different levels of air pollution and explain changes in PM2.5 sensitivity to emissions from local and surrounding regions. We then project future changes in PM2.5 concentrations using this index and find an increase in PM2.5 concentrations over the region due to climate change.
David S. Stevenson, Richard G. Derwent, Oliver Wild, and William J. Collins
Atmos. Chem. Phys., 22, 14243–14252, https://doi.org/10.5194/acp-22-14243-2022, https://doi.org/10.5194/acp-22-14243-2022, 2022
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Atmospheric methane’s growth rate rose by 50 % in 2020 relative to 2019. Lower nitrogen oxide (NOx) emissions tend to increase methane’s atmospheric residence time; lower carbon monoxide (CO) and non-methane volatile organic compound (NMVOC) emissions decrease its lifetime. Combining model sensitivities with emission changes, we find that COVID-19 lockdown emission reductions can explain over half the observed increases in methane in 2020.
Zhenze Liu, Ruth M. Doherty, Oliver Wild, Fiona M. O'Connor, and Steven T. Turnock
Atmos. Chem. Phys., 22, 12543–12557, https://doi.org/10.5194/acp-22-12543-2022, https://doi.org/10.5194/acp-22-12543-2022, 2022
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Weaknesses in process representation in chemistry–climate models lead to biases in simulating surface ozone and to uncertainty in projections of future ozone change. We develop a deep learning model to demonstrate the feasibility of ozone bias correction and show its capability in providing improved assessments of the impacts of climate and emission changes on future air quality, along with valuable information to guide future model development.
Zixuan Jia, Ruth M. Doherty, Carlos Ordóñez, Chaofan Li, Oliver Wild, Shipra Jain, and Xiao Tang
Atmos. Chem. Phys., 22, 6471–6487, https://doi.org/10.5194/acp-22-6471-2022, https://doi.org/10.5194/acp-22-6471-2022, 2022
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This study investigates the modulation of daily PM2.5 over three major populated regions in China by regional meteorology and large-scale circulation during winter. These results demonstrate the benefits of considering the large-scale circulation for air quality studies. The novel circulation indices proposed here can explain a considerable fraction of the day-to-day variability of PM2.5 and can be combined with regional meteorology to improve our capability to predict the variability of PM2.5.
Zhenze Liu, Ruth M. Doherty, Oliver Wild, Fiona M. O'Connor, and Steven T. Turnock
Atmos. Chem. Phys., 22, 1209–1227, https://doi.org/10.5194/acp-22-1209-2022, https://doi.org/10.5194/acp-22-1209-2022, 2022
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Tropospheric ozone is important to future air quality and climate, and changing emissions and climate influence ozone. We investigate the evolution of ozone and ozone sensitivity from the present day (2004–2014) to the future (2045–2055) and explore the main drivers of ozone changes from global and regional perspectives. This helps guide suitable emission control strategies to mitigate ozone pollution.
Michael Biggart, Jenny Stocker, Ruth M. Doherty, Oliver Wild, David Carruthers, Sue Grimmond, Yiqun Han, Pingqing Fu, and Simone Kotthaus
Atmos. Chem. Phys., 21, 13687–13711, https://doi.org/10.5194/acp-21-13687-2021, https://doi.org/10.5194/acp-21-13687-2021, 2021
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Heat-related illnesses are of increasing concern in China given its rapid urbanisation and our ever-warming climate. We examine the relative impacts that land surface properties and anthropogenic heat have on the urban heat island (UHI) in Beijing using ADMS-Urban. Air temperature measurements and satellite-derived land surface temperatures provide valuable means of evaluating modelled spatiotemporal variations. This work provides critical information for urban planners and UHI mitigation.
Zhenze Liu, Ruth M. Doherty, Oliver Wild, Michael Hollaway, and Fiona M. O’Connor
Atmos. Chem. Phys., 21, 10689–10706, https://doi.org/10.5194/acp-21-10689-2021, https://doi.org/10.5194/acp-21-10689-2021, 2021
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Surface ozone (O3) has become the main cause of atmospheric pollution in the summertime in China since 2013. We find that 70 % reductions in NOx emissions are required to reduce O3 pollution in most of industrial regions of China, and controls in VOC emissions are very important. The new chemical scheme developed for a global chemistry–climate model not only captures the regional air pollution but also benefits the future studies of regional air-quality–climate interactions.
Baozhu Ge, Danhui Xu, Oliver Wild, Xuefeng Yao, Junhua Wang, Xueshun Chen, Qixin Tan, Xiaole Pan, and Zifa Wang
Atmos. Chem. Phys., 21, 9441–9454, https://doi.org/10.5194/acp-21-9441-2021, https://doi.org/10.5194/acp-21-9441-2021, 2021
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In this study, an improved sequential sampling method is developed and implemented to estimate the contribution of below-cloud and in-cloud wet deposition over four years of measurements in Beijing. We find that the contribution of below-cloud scavenging for Ca2+, SO4 2–, and NH4+ decreases from above 50 % in 2014 to below 40 % in 2017. This suggests that the Action Plan has mitigated particulate matter pollution in the surface layer and hence decreased scavenging due to the washout process.
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Short summary
Atmospheric chemistry transport models are important tools to investigate the local, regional and global controls on atmospheric composition and air quality. In this study, we estimate some of the model parameters using machine learning and statistics. Our findings identify the level of error and spatial coverage in the O2 and CO data that are needed to achieve good parameter estimates. We also highlight the benefits of using multiple constraints to calibrate atmospheric chemistry models.
Atmospheric chemistry transport models are important tools to investigate the local, regional...
