Articles | Volume 14, issue 11
https://doi.org/10.5194/gmd-14-7021-2021
© 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-14-7021-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
18 Nov 2021
Model evaluation paper |
| 18 Nov 2021
| 18 Nov 2021
Evaluation of global EMEP MSC-W (rv4.34) WRF (v3.9.1.1) model surface concentrations and wet deposition of reactive N and S with measurements
School of Chemistry, University of Edinburgh, Joseph Black Building, David Brewster Road, Edinburgh, EH9 3FJ, UK
UK Centre for Ecology & Hydrology, Bush Estate, Penicuik, Midlothian, EH26 0QB, UK
School of Chemistry, University of Edinburgh, Joseph Black Building, David Brewster Road, Edinburgh, EH9 3FJ, UK
David S. Stevenson
School of GeoSciences, University of Edinburgh, Crew Building, Alexander Crum Brown Road, Edinburgh, EH9 3FF, UK
Peter Wind
The Norwegian Meteorological Institute, Henrik Mohns Plass 1, 0313, Oslo, Norway
Massimo Vieno
UK Centre for Ecology & Hydrology, Bush Estate, Penicuik, Midlothian, EH26 0QB, UK
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Gemma Purser, Julia Drewer, Mathew R. Heal, Robert A. S. Sircus, Lara K. Dunn, and James I. L. Morison
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Y. Sim Tang, Chris R. Flechard, Ulrich Dämmgen, Sonja Vidic, Vesna Djuricic, Marta Mitosinkova, Hilde T. Uggerud, Maria J. Sanz, Ivan Simmons, Ulrike Dragosits, Eiko Nemitz, Marsailidh Twigg, Netty van Dijk, Yannick Fauvel, Francisco Sanz, Martin Ferm, Cinzia Perrino, Maria Catrambone, David Leaver, Christine F. Braban, J. Neil Cape, Mathew R. Heal, and Mark A. Sutton
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Bruce Rolstad Denby, Michael Gauss, Peter Wind, Qing Mu, Eivind Grøtting Wærsted, Hilde Fagerli, Alvaro Valdebenito, and Heiko Klein
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David S. Stevenson, Alcide Zhao, Vaishali Naik, Fiona M. O'Connor, Simone Tilmes, Guang Zeng, Lee T. Murray, William J. Collins, Paul T. Griffiths, Sungbo Shim, Larry W. Horowitz, Lori T. Sentman, and Louisa Emmons
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Hannah L. Walker, Mathew R. Heal, Christine F. Braban, Mhairi Coyle, Sarah R. Leeson, Ivan Simmons, Matthew R. Jones, Richard Kift, and Marsailidh M. Twigg
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Revised manuscript not accepted
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Peter Wind, Bruce Rolstad Denby, and Michael Gauss
Geosci. Model Dev., 13, 1623–1634, https://doi.org/10.5194/gmd-13-1623-2020, https://doi.org/10.5194/gmd-13-1623-2020, 2020
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We present a new method for individually quantifying the contributions from different sources to local air pollution. The method can be used to distinguish the sources of local air pollution for any position in one single model simulation and thus to provide detailed maps of the origin of the pollutants. Hence, it can be used for time-critical operational services by providing scientific information as input for local policy decisions on air pollution abatement.
Giancarlo Ciarelli, Mark R. Theobald, Marta G. Vivanco, Matthias Beekmann, Wenche Aas, Camilla Andersson, Robert Bergström, Astrid Manders-Groot, Florian Couvidat, Mihaela Mircea, Svetlana Tsyro, Hilde Fagerli, Kathleen Mar, Valentin Raffort, Yelva Roustan, Maria-Teresa Pay, Martijn Schaap, Richard Kranenburg, Mario Adani, Gino Briganti, Andrea Cappelletti, Massimo D'Isidoro, Cornelis Cuvelier, Arineh Cholakian, Bertrand Bessagnet, Peter Wind, and Augustin Colette
Geosci. Model Dev., 12, 4923–4954, https://doi.org/10.5194/gmd-12-4923-2019, https://doi.org/10.5194/gmd-12-4923-2019, 2019
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The novel multi-model EURODELTA-Trends exercise provided 21 years of continuous PM components and their gas-phase precursor concentrations over Europe from the year 1990. The models’ capabilities to reproduce PM components and gas-phase PM precursor trends over the 1990–2010 period is the key focus of this study. The models were able to reproduce the observed trends relatively well, indicating a possible shift in the thermodynamic equilibrium between gas and particle phases.
Alcide Zhao, Massimo A. Bollasina, Monica Crippa, and David S. Stevenson
Atmos. Chem. Phys., 19, 14517–14533, https://doi.org/10.5194/acp-19-14517-2019, https://doi.org/10.5194/acp-19-14517-2019, 2019
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Emissions of aerosols over the recent past have been regulated largely by two policy-relevant drivers: energy-use growth and technology advances. These generate large and competing impacts on global radiation balance and climate, particularly over Asia, Europe, and the Arctic. This may help better assess and interpret future climate projections, and hence inform future climate change impact reduction strategies. Yet, it is pressing to better constrain various uncertainties related to aerosols.
Zongbo Shi, Tuan Vu, Simone Kotthaus, Roy M. Harrison, Sue Grimmond, Siyao Yue, Tong Zhu, James Lee, Yiqun Han, Matthias Demuzere, Rachel E. Dunmore, Lujie Ren, Di Liu, Yuanlin Wang, Oliver Wild, James Allan, W. Joe Acton, Janet Barlow, Benjamin Barratt, David Beddows, William J. Bloss, Giulia Calzolai, David Carruthers, David C. Carslaw, Queenie Chan, Lia Chatzidiakou, Yang Chen, Leigh Crilley, Hugh Coe, Tie Dai, Ruth Doherty, Fengkui Duan, Pingqing Fu, Baozhu Ge, Maofa Ge, Daobo Guan, Jacqueline F. Hamilton, Kebin He, Mathew Heal, Dwayne Heard, C. Nicholas Hewitt, Michael Hollaway, Min Hu, Dongsheng Ji, Xujiang Jiang, Rod Jones, Markus Kalberer, Frank J. Kelly, Louisa Kramer, Ben Langford, Chun Lin, Alastair C. Lewis, Jie Li, Weijun Li, Huan Liu, Junfeng Liu, Miranda Loh, Keding Lu, Franco Lucarelli, Graham Mann, Gordon McFiggans, Mark R. Miller, Graham Mills, Paul Monk, Eiko Nemitz, Fionna O'Connor, Bin Ouyang, Paul I. Palmer, Carl Percival, Olalekan Popoola, Claire Reeves, Andrew R. Rickard, Longyi Shao, Guangyu Shi, Dominick Spracklen, David Stevenson, Yele Sun, Zhiwei Sun, Shu Tao, Shengrui Tong, Qingqing Wang, Wenhua Wang, Xinming Wang, Xuejun Wang, Zifang Wang, Lianfang Wei, Lisa Whalley, Xuefang Wu, Zhijun Wu, Pinhua Xie, Fumo Yang, Qiang Zhang, Yanli Zhang, Yuanhang Zhang, and Mei Zheng
Atmos. Chem. Phys., 19, 7519–7546, https://doi.org/10.5194/acp-19-7519-2019, https://doi.org/10.5194/acp-19-7519-2019, 2019
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APHH-Beijing is a collaborative international research programme to study the sources, processes and health effects of air pollution in Beijing. This introduction to the special issue provides an overview of (i) the APHH-Beijing programme, (ii) the measurement and modelling activities performed as part of it and (iii) the air quality and meteorological conditions during joint intensive field campaigns as a core activity within APHH-Beijing.
Carole Helfter, Neil Mullinger, Massimo Vieno, Simon O'Doherty, Michel Ramonet, Paul I. Palmer, and Eiko Nemitz
Atmos. Chem. Phys., 19, 3043–3063, https://doi.org/10.5194/acp-19-3043-2019, https://doi.org/10.5194/acp-19-3043-2019, 2019
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We present a novel approach to estimate the annual budgets of carbon dioxide (881.0 ± 128.5 Tg) and methane (2.55 ± 0.48 Tg) of the British Isles from shipborne measurements taken over a 3-year period (2015–2017). This study brings independent verification of the emission budgets estimated using alternative products and investigates the seasonality of these emissions, which is usually not possible.
Ksenia Aleksankina, Stefan Reis, Massimo Vieno, and Mathew R. Heal
Atmos. Chem. Phys., 19, 2881–2898, https://doi.org/10.5194/acp-19-2881-2019, https://doi.org/10.5194/acp-19-2881-2019, 2019
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Atmospheric chemistry transport models are widely used to underpin policies to mitigate the detrimental effects of air pollution on human health and ecosystems. Understanding the level of confidence in model predictions is thus vital. We present a comprehensive approach for uncertainty assessment and global variance-based sensitivity analysis to propagate uncertainty from model input data and identify the extent to which uncertainty in different emissions drives the model output uncertainty.
Mark R. Theobald, Marta G. Vivanco, Wenche Aas, Camilla Andersson, Giancarlo Ciarelli, Florian Couvidat, Kees Cuvelier, Astrid Manders, Mihaela Mircea, Maria-Teresa Pay, Svetlana Tsyro, Mario Adani, Robert Bergström, Bertrand Bessagnet, Gino Briganti, Andrea Cappelletti, Massimo D'Isidoro, Hilde Fagerli, Kathleen Mar, Noelia Otero, Valentin Raffort, Yelva Roustan, Martijn Schaap, Peter Wind, and Augustin Colette
Atmos. Chem. Phys., 19, 379–405, https://doi.org/10.5194/acp-19-379-2019, https://doi.org/10.5194/acp-19-379-2019, 2019
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Model estimates of the mean European wet deposition of nitrogen and sulfur for 1990 to 2010 were within 40 % of the observed values. As a result of systematic biases, the models were better at estimating relative trends for the periods 1990–2000 and 2000–2010 than the absolute trends. Although the predominantly decreasing trends were mostly due to emission reductions, they were partially offset by other factors (e.g. changes in precipitation) during the first period, but not the second.
Robbie Ramsay, Chiara F. Di Marco, Mathew R. Heal, Marsailidh M. Twigg, Nicholas Cowan, Matthew R. Jones, Sarah R. Leeson, William J. Bloss, Louisa J. Kramer, Leigh Crilley, Matthias Sörgel, Meinrat Andreae, and Eiko Nemitz
Atmos. Chem. Phys., 18, 16953–16978, https://doi.org/10.5194/acp-18-16953-2018, https://doi.org/10.5194/acp-18-16953-2018, 2018
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Understanding the impact of agricultural activities on the atmosphere requires more measurements of inorganic trace gases and associated aerosol counterparts. This research presents 1 month of measurements above agricultural grassland during a period of fertiliser application. It was found that emissions of the important trace gases ammonia and nitrous acid peaked after fertiliser use and that the velocity at which the measured aerosols were deposited was dependent upon their size.
Y. Sim Tang, Christine F. Braban, Ulrike Dragosits, Ivan Simmons, David Leaver, Netty van Dijk, Janet Poskitt, Sarah Thacker, Manisha Patel, Heather Carter, M. Glória Pereira, Patrick O. Keenan, Alan Lawlor, Christopher Conolly, Keith Vincent, Mathew R. Heal, and Mark A. Sutton
Atmos. Chem. Phys., 18, 16293–16324, https://doi.org/10.5194/acp-18-16293-2018, https://doi.org/10.5194/acp-18-16293-2018, 2018
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A unique long-term dataset (1999–2015) of atmospheric gases (HNO3, SO2, HCl, NH3) and aerosol (NO3-, SO42-, Cl-, NH4+, Na+, Ca2+, Mg2+) from two integrated UK networks (>12 sites) was analysed to assess spatial, temporal, and long-term trends. A change in particulate phase from (NH4)2SO4 to NH4NO3 is seen, with indications that a larger fraction of the reduced and oxidized N is remaining in the gas phase. Key pollutant events captured highlight influence of trans-boundary transport into the UK.
Arlene M. Fiore, Emily V. Fischer, George P. Milly, Shubha Pandey Deolal, Oliver Wild, Daniel A. Jaffe, Johannes Staehelin, Olivia E. Clifton, Dan Bergmann, William Collins, Frank Dentener, Ruth M. Doherty, Bryan N. Duncan, Bernd Fischer, Stefan Gilge, Peter G. Hess, Larry W. Horowitz, Alexandru Lupu, Ian A. MacKenzie, Rokjin Park, Ludwig Ries, Michael G. Sanderson, Martin G. Schultz, Drew T. Shindell, Martin Steinbacher, David S. Stevenson, Sophie Szopa, Christoph Zellweger, and Guang Zeng
Atmos. Chem. Phys., 18, 15345–15361, https://doi.org/10.5194/acp-18-15345-2018, https://doi.org/10.5194/acp-18-15345-2018, 2018
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We demonstrate a proof-of-concept approach for applying northern midlatitude mountaintop peroxy acetyl nitrate (PAN) measurements and a multi-model ensemble during April to constrain the influence of continental-scale anthropogenic precursor emissions on PAN. Our findings imply a role for carefully coordinated multi-model ensembles in helping identify observations for discriminating among widely varying (and poorly constrained) model responses of atmospheric constituents to changes in emissions.
Noelia Otero, Jana Sillmann, Kathleen A. Mar, Henning W. Rust, Sverre Solberg, Camilla Andersson, Magnuz Engardt, Robert Bergström, Bertrand Bessagnet, Augustin Colette, Florian Couvidat, Cournelius Cuvelier, Svetlana Tsyro, Hilde Fagerli, Martijn Schaap, Astrid Manders, Mihaela Mircea, Gino Briganti, Andrea Cappelletti, Mario Adani, Massimo D'Isidoro, María-Teresa Pay, Mark Theobald, Marta G. Vivanco, Peter Wind, Narendra Ojha, Valentin Raffort, and Tim Butler
Atmos. Chem. Phys., 18, 12269–12288, https://doi.org/10.5194/acp-18-12269-2018, https://doi.org/10.5194/acp-18-12269-2018, 2018
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This paper evaluates the capability of air-quality models to capture the observed relationship between surface ozone concentrations and meteorology over Europe. The air-quality models tended to overestimate the influence of maximum temperature and surface solar radiation. None of the air-quality models captured the strength of the observed relationship between ozone and relative humidity appropriately, underestimating the effect of relative humidity, a key factor in the ozone removal processes.
Christina Hood, Ian MacKenzie, Jenny Stocker, Kate Johnson, David Carruthers, Massimo Vieno, and Ruth Doherty
Atmos. Chem. Phys., 18, 11221–11245, https://doi.org/10.5194/acp-18-11221-2018, https://doi.org/10.5194/acp-18-11221-2018, 2018
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A coupled atmospheric dispersion modelling system has been developed, comprising a regional chemical transport model and a street-scale urban dispersion model. It was applied in London for 2012 and for all common regulated air quality pollutants, with evaluation against measurements. The modelling demonstrates the interaction between local and regional scales, which differs between pollutants. Real-world estimates of emissions have been used to adjust standard factors and improve model results.
Marta G. Vivanco, Mark R. Theobald, Héctor García-Gómez, Juan Luis Garrido, Marje Prank, Wenche Aas, Mario Adani, Ummugulsum Alyuz, Camilla Andersson, Roberto Bellasio, Bertrand Bessagnet, Roberto Bianconi, Johannes Bieser, Jørgen Brandt, Gino Briganti, Andrea Cappelletti, Gabriele Curci, Jesper H. Christensen, Augustin Colette, Florian Couvidat, Cornelis Cuvelier, Massimo D'Isidoro, Johannes Flemming, Andrea Fraser, Camilla Geels, Kaj M. Hansen, Christian Hogrefe, Ulas Im, Oriol Jorba, Nutthida Kitwiroon, Astrid Manders, Mihaela Mircea, Noelia Otero, Maria-Teresa Pay, Luca Pozzoli, Efisio Solazzo, Svetlana Tsyro, Alper Unal, Peter Wind, and Stefano Galmarini
Atmos. Chem. Phys., 18, 10199–10218, https://doi.org/10.5194/acp-18-10199-2018, https://doi.org/10.5194/acp-18-10199-2018, 2018
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European wet and dry atmospheric deposition of N and S estimated by 14 air quality models was found to vary substantially. An ensemble of models meeting acceptability criteria was used to estimate the exceedances of the critical loads for N in habitats within the Natura 2000 network, as well as their lower and upper limits. Scenarios with 20 % emission reductions in different regions of the world showed that European emissions are responsible for most of the N and S deposition in Europe.
Ksenia Aleksankina, Mathew R. Heal, Anthony J. Dore, Marcel Van Oijen, and Stefan Reis
Geosci. Model Dev., 11, 1653–1664, https://doi.org/10.5194/gmd-11-1653-2018, https://doi.org/10.5194/gmd-11-1653-2018, 2018
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Atmospheric chemistry transport models are widely used to underpin policy decisions. We present a global sensitivity and uncertainty analysis approach to understand how uncertainty in input emissions of SO2, NOx, and NH3 drives uncertainties in model outputs, using the FRAME model as an example. We interpret results for input emissions uncertainty ranges reported by the national emissions inventory. Variance-based measures of sensitivity were used to apportion model output uncertainty.
Riinu Ots, Mathew R. Heal, Dominique E. Young, Leah R. Williams, James D. Allan, Eiko Nemitz, Chiara Di Marco, Anais Detournay, Lu Xu, Nga L. Ng, Hugh Coe, Scott C. Herndon, Ian A. Mackenzie, David C. Green, Jeroen J. P. Kuenen, Stefan Reis, and Massimo Vieno
Atmos. Chem. Phys., 18, 4497–4518, https://doi.org/10.5194/acp-18-4497-2018, https://doi.org/10.5194/acp-18-4497-2018, 2018
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The main hypothesis of this paper is that people who live in large cities in the UK disobey the
smoke control lawas it has not been actively enforced for decades now. However, the use of wood in residential heating has increased, partly due to renewable energy targets, but also for discretionary (i.e. pleasant fireplaces) reasons. Our study is based mainly in London, but similar struggles with urban air quality due to residential wood and coal burning are seen in other major European cities.
Christopher S. Malley, Erika von Schneidemesser, Sarah Moller, Christine F. Braban, W. Kevin Hicks, and Mathew R. Heal
Atmos. Chem. Phys., 18, 3563–3587, https://doi.org/10.5194/acp-18-3563-2018, https://doi.org/10.5194/acp-18-3563-2018, 2018
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This study quantifies the contribution of hourly nitrogen dioxide (NO2) variation to annual NO2 concentrations at > 2500 sites across Europe. Sites with distinct monthly, hour of day, and hourly NO2 contributions to annual NO2 were not grouped into specific European regions. Within relatively small areas there were sites with similar annual NO2 but with differences in these contributions. Therefore, measures implemented to reduce annual NO2 in one location may not be as effective in others.
Yuk S. Tang, Christine F. Braban, Ulrike Dragosits, Anthony J. Dore, Ivan Simmons, Netty van Dijk, Janet Poskitt, Gloria Dos Santos Pereira, Patrick O. Keenan, Christopher Conolly, Keith Vincent, Rognvald I. Smith, Mathew R. Heal, and Mark A. Sutton
Atmos. Chem. Phys., 18, 705–733, https://doi.org/10.5194/acp-18-705-2018, https://doi.org/10.5194/acp-18-705-2018, 2018
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A unique long-term dataset of NH3 and NH4+ data from the NAMN is used to assess spatial, seasonal and long-term variability across the UK. NH3 is spatially variable, with distinct temporal profiles according to source types. NH4+ is spatially smoother, with peak concentrations in spring from long-range transport. Decrease in NH3 is smaller than emissions, but NH4+ decreased faster than NH3, due to a shift from stable (NH4)2SO4 to semi-volatile NH4NO3, increasing the atmospheric lifetime of NH3.
Matthieu Pommier, Hilde Fagerli, Michael Gauss, David Simpson, Sumit Sharma, Vinay Sinha, Sachin D. Ghude, Oskar Landgren, Agnes Nyiri, and Peter Wind
Atmos. Chem. Phys., 18, 103–127, https://doi.org/10.5194/acp-18-103-2018, https://doi.org/10.5194/acp-18-103-2018, 2018
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India has to cope with a poor air quality, and this work shows a predicted increase in pollution (O3 & PM2.5) if no further policy efforts are made in the future. Climate change will modify the soil moisture leading to changes in O3. Changes in PM2.5 are related to changes in precipitation, biogenic emissions and wind speed. It is also shown that in the 2050s, the secondary inorganic aerosols will become the main component of PM2.5 over India related to the increase in anthropogenic emissions.
Andrea Móring, Massimo Vieno, Ruth M. Doherty, Celia Milford, Eiko Nemitz, Marsailidh M. Twigg, László Horváth, and Mark A. Sutton
Biogeosciences, 14, 4161–4193, https://doi.org/10.5194/bg-14-4161-2017, https://doi.org/10.5194/bg-14-4161-2017, 2017
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This study describes and evaluates a new ammonia (NH3) exchange model for grazed fields (GAG_field). GAG_field is able to simulate the main features of the observed NH3 fluxes. A sensitivity analysis for the non-meteorological model parameters showed that the sensitivity of the NH3 fluxes to a parameter varies among urine patches. Moreover, the fluxes modelled with a dynamic soil pH are similar if a constant pH 7.5 is used, suggesting a useful simplification for regional-scale model application.
Augustin Colette, Camilla Andersson, Astrid Manders, Kathleen Mar, Mihaela Mircea, Maria-Teresa Pay, Valentin Raffort, Svetlana Tsyro, Cornelius Cuvelier, Mario Adani, Bertrand Bessagnet, Robert Bergström, Gino Briganti, Tim Butler, Andrea Cappelletti, Florian Couvidat, Massimo D'Isidoro, Thierno Doumbia, Hilde Fagerli, Claire Granier, Chris Heyes, Zig Klimont, Narendra Ojha, Noelia Otero, Martijn Schaap, Katarina Sindelarova, Annemiek I. Stegehuis, Yelva Roustan, Robert Vautard, Erik van Meijgaard, Marta Garcia Vivanco, and Peter Wind
Geosci. Model Dev., 10, 3255–3276, https://doi.org/10.5194/gmd-10-3255-2017, https://doi.org/10.5194/gmd-10-3255-2017, 2017
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The EURODELTA-Trends numerical experiment has been designed to assess the capability of chemistry-transport models to capture the evolution of surface air quality over the 1990–2010 period in Europe. It also includes sensitivity experiments in order to analyse the relative contribution of (i) emission changes, (ii) meteorological variability, and (iii) boundary conditions to air quality trends. The article is a detailed presentation of the experiment design and participating models.
Birthe M. Steensen, Michael Schulz, Peter Wind, Álvaro M. Valdebenito, and Hilde Fagerli
Geosci. Model Dev., 10, 1927–1943, https://doi.org/10.5194/gmd-10-1927-2017, https://doi.org/10.5194/gmd-10-1927-2017, 2017
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The operational emergency version of the EMEP MSC-W model for dispersion calculations of volcanic SO2 and ash is described. Additions and changes to the standard EMEP MSC-W are presented. Grid resolution dependencies for meteorological data and numerical diffusion are studied by investigating model results driven by ensemble meteorological data for volcanic SO2 emissions. The vertical ash layer sensitivity on gravitational settling is evaluated by comparing model results to lidar observations.
Chun Lin, Mathew R. Heal, Massimo Vieno, Ian A. MacKenzie, Ben G. Armstrong, Barbara K. Butland, Ai Milojevic, Zaid Chalabi, Richard W. Atkinson, David S. Stevenson, Ruth M. Doherty, and Paul Wilkinson
Geosci. Model Dev., 10, 1767–1787, https://doi.org/10.5194/gmd-10-1767-2017, https://doi.org/10.5194/gmd-10-1767-2017, 2017
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We evaluated EMEP4UK-WRF v4.3 atmospheric chemistry transport simulations at 5 km horizontal resolution over the UK for use in air pollution epidemiology and health burden assessment. Model-measurement comparison focused on daily and annual means for NO2, O3, PM10, and PM2.5. Important statistics for evaluation of air-quality model output against policy (and hence health)-relevant standards – correlation, bias, and root mean square error – were evaluated by site type, year, month and day-of-week.
Mark R. Theobald, David Simpson, and Massimo Vieno
Geosci. Model Dev., 9, 4475–4489, https://doi.org/10.5194/gmd-9-4475-2016, https://doi.org/10.5194/gmd-9-4475-2016, 2016
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Impacts of air pollution at a continental scale, estimated using air quality models, can potentially be greatly under- or overestimated due to the low spatial resolution used (grid cells of 10–50 km). We present a method to estimate the spatial variations in air quality within a model grid cell by combining high-resolution emission data with estimates of short range dispersion. This simple but robust technique has the potential to improve estimates of air quality impacts at a continental scale.
Riinu Ots, Massimo Vieno, James D. Allan, Stefan Reis, Eiko Nemitz, Dominique E. Young, Hugh Coe, Chiara Di Marco, Anais Detournay, Ian A. Mackenzie, David C. Green, and Mathew R. Heal
Atmos. Chem. Phys., 16, 13773–13789, https://doi.org/10.5194/acp-16-13773-2016, https://doi.org/10.5194/acp-16-13773-2016, 2016
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Emissions of cooking organic aerosol (COA; from charbroiling, frying, etc.) are currently absent in European emissions inventories yet measurements have pointed to significant COA concentrations. In this study, emissions of COA were developed for the UK by model iteration against year-long measurements at two sites in London. Modelled COA dropped rapidly outside of major urban areas, suggesting that although a notable component in UK urban air, COA does not have a significant effect on rural PM.
Marsailidh M. Twigg, Evgenia Ilyinskaya, Sonya Beccaceci, David C. Green, Matthew R. Jones, Ben Langford, Sarah R. Leeson, Justin J. N. Lingard, Gloria M. Pereira, Heather Carter, Jan Poskitt, Andreas Richter, Stuart Ritchie, Ivan Simmons, Ron I. Smith, Y. Sim Tang, Netty Van Dijk, Keith Vincent, Eiko Nemitz, Massimo Vieno, and Christine F. Braban
Atmos. Chem. Phys., 16, 11415–11431, https://doi.org/10.5194/acp-16-11415-2016, https://doi.org/10.5194/acp-16-11415-2016, 2016
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This study integrates high and low resolution temporal measurements to assess the impact of the Holuhraun effusive eruption in 2014 across the UK. Measurements, modelling and satellite analysis provides details on the transport and chemistry of both gases and particulates during this unique event. The results of the study can be used verify existing atmospheric chemistry models of volcano plumes in order to carry improved risk assessments for future volcanic eruptions.
Raquel A. Silva, J. Jason West, Jean-François Lamarque, Drew T. Shindell, William J. Collins, Stig Dalsoren, Greg Faluvegi, Gerd Folberth, Larry W. Horowitz, Tatsuya Nagashima, Vaishali Naik, Steven T. Rumbold, Kengo Sudo, Toshihiko Takemura, Daniel Bergmann, Philip Cameron-Smith, Irene Cionni, Ruth M. Doherty, Veronika Eyring, Beatrice Josse, Ian A. MacKenzie, David Plummer, Mattia Righi, David S. Stevenson, Sarah Strode, Sophie Szopa, and Guang Zengast
Atmos. Chem. Phys., 16, 9847–9862, https://doi.org/10.5194/acp-16-9847-2016, https://doi.org/10.5194/acp-16-9847-2016, 2016
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Using ozone and PM2.5 concentrations from the ACCMIP ensemble of chemistry-climate models for the four Representative Concentration Pathway scenarios (RCPs), together with projections of future population and baseline mortality rates, we quantify the human premature mortality impacts of future ambient air pollution in 2030, 2050 and 2100, relative to 2000 concentrations. We also estimate the global mortality burden of ozone and PM2.5 in 2000 and each future period.
Riinu Ots, Dominique E. Young, Massimo Vieno, Lu Xu, Rachel E. Dunmore, James D. Allan, Hugh Coe, Leah R. Williams, Scott C. Herndon, Nga L. Ng, Jacqueline F. Hamilton, Robert Bergström, Chiara Di Marco, Eiko Nemitz, Ian A. Mackenzie, Jeroen J. P. Kuenen, David C. Green, Stefan Reis, and Mathew R. Heal
Atmos. Chem. Phys., 16, 6453–6473, https://doi.org/10.5194/acp-16-6453-2016, https://doi.org/10.5194/acp-16-6453-2016, 2016
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This study investigates the contribution of diesel vehicle emissions to organic aerosol formation and particulate matter concentrations in London. Comparisons of simulated pollutant concentrations with observations show good agreement and give confidence in the skill of the model applied. The contribution of diesel vehicle emissions, which are currently not included in official emissions inventories, is demonstrated to be substantial, indicating that more research on this topic is required.
Andrea Móring, Massimo Vieno, Ruth M. Doherty, Johannes Laubach, Arezoo Taghizadeh-Toosi, and Mark A. Sutton
Biogeosciences, 13, 1837–1861, https://doi.org/10.5194/bg-13-1837-2016, https://doi.org/10.5194/bg-13-1837-2016, 2016
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A process-based, weather-driven model for ammonia emission from a urine patch has been developed and its sensitivity to various factors assessed. The model can simulate the ammoniacal nitrogen content, pH and the water content of the soil under a urine patch.
The simulated variables were in a good agreement with the measurements. The sensitivity analysis highlighted the vital role of temperature in ammonia exchange. The model is potentially suitable for larger scale application.
M. Vieno, M. R. Heal, M. L. Williams, E. J. Carnell, E. Nemitz, J. R. Stedman, and S. Reis
Atmos. Chem. Phys., 16, 265–276, https://doi.org/10.5194/acp-16-265-2016, https://doi.org/10.5194/acp-16-265-2016, 2016
D. Fowler, C. E. Steadman, D. Stevenson, M. Coyle, R. M. Rees, U. M. Skiba, M. A. Sutton, J. N. Cape, A. J. Dore, M. Vieno, D. Simpson, S. Zaehle, B. D. Stocker, M. Rinaldi, M. C. Facchini, C. R. Flechard, E. Nemitz, M. Twigg, J. W. Erisman, K. Butterbach-Bahl, and J. N. Galloway
Atmos. Chem. Phys., 15, 13849–13893, https://doi.org/10.5194/acp-15-13849-2015, https://doi.org/10.5194/acp-15-13849-2015, 2015
P. S. Monks, A. T. Archibald, A. Colette, O. Cooper, M. Coyle, R. Derwent, D. Fowler, C. Granier, K. S. Law, G. E. Mills, D. S. Stevenson, O. Tarasova, V. Thouret, E. von Schneidemesser, R. Sommariva, O. Wild, and M. L. Williams
Atmos. Chem. Phys., 15, 8889–8973, https://doi.org/10.5194/acp-15-8889-2015, https://doi.org/10.5194/acp-15-8889-2015, 2015
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Ozone holds a certain fascination in atmospheric science. It is ubiquitous in the atmosphere, central to tropospheric oxidation chemistry, and yet harmful to human and ecosystem health as well as being an important greenhouse gas. It is not emitted into the atmosphere but is a byproduct of the very oxidation chemistry it largely initiates. This review examines current understanding of the processes regulating tropospheric ozone at global to local scales from both measurements and models.
C. S. Malley, C. F. Braban, P. Dumitrean, J. N. Cape, and M. R. Heal
Atmos. Chem. Phys., 15, 8361–8380, https://doi.org/10.5194/acp-15-8361-2015, https://doi.org/10.5194/acp-15-8361-2015, 2015
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In this study the regional component of ground level ozone is linked to the chemical loss of 27 measured VOCs at two UK monitoring sites and integrated with gridded European VOC emissions. The relative VOC chemical loss indicates that emission controls of a large number of VOCs and targeting VOCs with highest chemical loss are both required to reduce regional ozone. The benefit resulting from the disaggregation of VOC source sectors to the identification of high VOC-emitting sources is shown.
C. S. Malley, M. R. Heal, G. Mills, and C. F. Braban
Atmos. Chem. Phys., 15, 4025–4042, https://doi.org/10.5194/acp-15-4025-2015, https://doi.org/10.5194/acp-15-4025-2015, 2015
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Health- and vegetation-relevant ozone exposure metrics (SOMO10/SOMO35 and PODY/AOT40 respectively) are analysed between 1990 and 2013 using data from the UK EMEP supersites: Auchencorth Moss, southern Scotland and Harwell, south-east England. Analysis shows that for health-relevant ozone exposure, improvement has been achieved for SOMO35 but not for SOMO10 despite European mitigation strategies reducing precursor emissions. Vegetation impacts based on PODY have also not decreased.
L. R. Crilley, W. J. Bloss, J. Yin, D. C. S. Beddows, R. M. Harrison, J. D. Allan, D. E. Young, M. Flynn, P. Williams, P. Zotter, A. S. H. Prevot, M. R. Heal, J. F. Barlow, C. H. Halios, J. D. Lee, S. Szidat, and C. Mohr
Atmos. Chem. Phys., 15, 3149–3171, https://doi.org/10.5194/acp-15-3149-2015, https://doi.org/10.5194/acp-15-3149-2015, 2015
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Wood is a renewable fuel but its combustion for residential heating releases a number of locally acting air pollutants, most notably particulate matter known to have adverse effects on human health. This paper used chemical tracers for wood smoke to estimate the contribution that burning wood makes to concentrations of airborne particles in the atmosphere of southern England and most particularly in London.
D. Simpson, C. Andersson, J.H. Christensen, M. Engardt, C. Geels, A. Nyiri, M. Posch, J. Soares, M. Sofiev, P. Wind, and J. Langner
Atmos. Chem. Phys., 14, 6995–7017, https://doi.org/10.5194/acp-14-6995-2014, https://doi.org/10.5194/acp-14-6995-2014, 2014
E. von Schneidemesser, M. Vieno, and P. S. Monks
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-14-1287-2014, https://doi.org/10.5194/acpd-14-1287-2014, 2014
Revised manuscript not accepted
K. W. Bowman, D. T. Shindell, H. M. Worden, J.F. Lamarque, P. J. Young, D. S. Stevenson, Z. Qu, M. de la Torre, D. Bergmann, P. J. Cameron-Smith, W. J. Collins, R. Doherty, S. B. Dalsøren, G. Faluvegi, G. Folberth, L. W. Horowitz, B. M. Josse, Y. H. Lee, I. A. MacKenzie, G. Myhre, T. Nagashima, V. Naik, D. A. Plummer, S. T. Rumbold, R. B. Skeie, S. A. Strode, K. Sudo, S. Szopa, A. Voulgarakis, G. Zeng, S. S. Kulawik, A. M. Aghedo, and J. R. Worden
Atmos. Chem. Phys., 13, 4057–4072, https://doi.org/10.5194/acp-13-4057-2013, https://doi.org/10.5194/acp-13-4057-2013, 2013
Related subject area
Atmospheric sciences
Optimized dynamic mode decomposition for reconstruction and forecasting of atmospheric chemistry data
Interpolating turbulent heat fluxes missing from a prairie observation on the Tibetan Plateau using artificial intelligence models
Carbon dioxide plume dispersion simulated at the hectometer scale using DALES: model formulation and observational evaluation
Low-level jets in the North and Baltic seas: mesoscale model sensitivity and climatology using WRF V4.2.1
SynRad v1.0: a radar forward operator to simulate synthetic weather radar observations from volcanic ash clouds
Chempath 1.0: an open-source pathway analysis program for photochemical models
PALACE v1.0: Paranal Airglow Line And Continuum Emission model
Atmospheric moisture tracking with WAM2layers v3
A new set of indicators for model evaluation complementing FAIRMODE's modelling quality objective (MQO)
Impact of multiple radar wind profiler data assimilation on convective-scale short-term rainfall forecasts: OSSE studies over the Beijing–Tianjin–Hebei region
New submodel for emissions from Explosive Volcanic ERuptions (EVER v1.1) within the Modular Earth Submodel System (MESSy, version 2.55.1)
Quantifying the oscillatory evolution of simulated boundary-layer cloud fields using Gaussian process regression
Numerical investigations on the modelling of ultrafine particles in SSH-aerosol-v1.3a: size resolution and redistribution
The third Met Office Unified Model–JULES Regional Atmosphere and Land Configuration, RAL3
The sensitivity of aerosol data assimilation to vertical profiles: case study of dust storm assimilation with LOTOS-EUROS v2.2
Knowledge-inspired fusion strategies for the inference of PM2.5 values with a neural network
Tuning the ICON-A 2.6.4 climate model with machine-learning-based emulators and history matching
A novel method for quantifying the contribution of regional transport to PM2.5 in Beijing (2013–2020): combining machine learning with concentration-weighted trajectory analysis
Quantification of CO2 hotspot emissions from OCO-3 SAM CO2 satellite images using deep learning methods
Diagnosis of winter precipitation types using the spectral bin model (version 1DSBM-19M): comparison of five methods using ICE-POP 2018 field experiment data
Improving winter condition simulations in SURFEX-TEB v9.0 with a multi-layer snow model and ice
UA-ICON with the NWP physics package (version ua-icon-2.1): mean state and variability of the middle atmosphere
Integrated Methane Inversion (IMI) 2.0: an improved research and stakeholder tool for monitoring total methane emissions with high resolution worldwide using TROPOMI satellite observations
HTAP3 Fires: towards a multi-model, multi-pollutant study of fire impacts
Using a data-driven statistical model to better evaluate surface turbulent heat fluxes in weather and climate numerical models: a demonstration study
Pochva: a new hydro-thermal process model in soil, snow, and vegetation for application in atmosphere numerical models
ClimKern v1.2: a new Python package and kernel repository for calculating radiative feedbacks
Accounting for effects of coagulation and model uncertainties in particle number concentration estimates based on measurements from sampling lines – a Bayesian inversion approach with SLIC v1.0
Top-down CO emission estimates using TROPOMI CO data in the TM5-4DVAR (r1258) inverse modeling suit
The Multi-Compartment Hg Modeling and Analysis Project (MCHgMAP): mercury modeling to support international environmental policy
Similarity-based analysis of atmospheric organic compounds for machine learning applications
The Atmospheric Potential Oxygen forward Model Intercomparison Project (APO-MIP1): Evaluating simulated atmospheric transport of air-sea gas exchange tracers and APO flux products
Porting the Meso-NH atmospheric model on different GPU architectures for the next generation of supercomputers (version MESONH-v55-OpenACC)
Estimation of aerosol and cloud radiative heating rate in the tropical stratosphere using a radiative kernel method
Development of a High-Resolution Coupled SHiELD-MOM6 Model. Part I – Model Overview, Coupling Technique, and Validation in a Regional Setup
Evaluation of dust emission and land surface schemes in predicting a mega Asian dust storm over South Korea using WRF-Chem
Sensitivity studies of a four-dimensional local ensemble transform Kalman filter coupled with WRF-Chem version 3.9.1 for improving particulate matter simulation accuracy
A Bayesian method for predicting background radiation at environmental monitoring stations in local-scale networks
Inclusion of the ECMWF ecRad radiation scheme (v1.5.0) in the MAR (v3.14), regional evaluation for Belgium, and assessment of surface shortwave spectral fluxes at Uccle
Development of a fast radiative transfer model for ground-based microwave radiometers (ARMS-gb v1.0): validation and comparison to RTTOV-gb
Indian Institute of Tropical Meteorology (IITM) High-Resolution Global Forecast Model version 1: an attempt to resolve monsoon prediction deadlock
Cell-tracking-based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall
NeuralMie (v1.0): an aerosol optics emulator
A REtrieval Method for optical and physical Aerosol Properties in the stratosphere (REMAPv1)
Simulation performance of planetary boundary layer schemes in WRF v4.3.1 for near-surface wind over the western Sichuan Basin: a single-site assessment
FootNet v1.0: development of a machine learning emulator of atmospheric transport
Updates and evaluation of NOAA's online-coupled air quality model version 7 (AQMv7) within the Unified Forecast System
Quantifying the analysis uncertainty for nowcasting application
Improving the ensemble square root filter (EnSRF) in the Community Inversion Framework: a case study with ICON-ART 2024.01
The MESSy DWARF (based on MESSy v2.55.2)
Meghana Velagar, Christoph Keller, and J. Nathan Kutz
Geosci. Model Dev., 18, 4667–4684, https://doi.org/10.5194/gmd-18-4667-2025, https://doi.org/10.5194/gmd-18-4667-2025, 2025
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We develop the data-driven method of dynamic mode decomposition for producing a robust and stable surrogate reduced-order model of atmospheric chemistry dynamics. The model is computationally efficient, provides interpretable patterns of activity, and produces uncertainty quantification metrics. It is ideal for the forecasting of atmospheric chemistry in a computationally tractable manner.
Quanzhe Hou, Zhiqiu Gao, Zexia Duan, and Minghui Yu
Geosci. Model Dev., 18, 4625–4641, https://doi.org/10.5194/gmd-18-4625-2025, https://doi.org/10.5194/gmd-18-4625-2025, 2025
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This study evaluates various machine learning and statistical methods for interpolating turbulent heat flux data over the Tibetan Plateau. The Transformer model showed the best performance, leading to the development of the Transformer_CNN model, which combines global and local attention mechanisms. Results show that Transformer_CNN outperforms the other models and was successfully applied to interpolate heat flux data from 2007 to 2016.
Arseniy Karagodin-Doyennel, Fredrik Jansson, Bart J. H. van Stratum, Hugo Denier van der Gon, Jordi Vilà-Guerau de Arellano, and Sander Houweling
Geosci. Model Dev., 18, 4571–4599, https://doi.org/10.5194/gmd-18-4571-2025, https://doi.org/10.5194/gmd-18-4571-2025, 2025
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We introduce a new simulation platform based on the Dutch Atmospheric Large-Eddy Simulation (DALES) to simulate carbon dioxide (CO2) emissions and their dispersion in turbulent environments at a hectometer resolution. This model incorporates both anthropogenic emission inventories and online ecosystem fluxes. Simulation results for the main urban area in the Netherlands demonstrate the strong potential of DALES to improve CO2 emission modeling and to support mitigation strategies.
Bjarke T. E. Olsen, Andrea N. Hahmann, Nicolas G. Alonso-de-Linaje, Mark Žagar, and Martin Dörenkämper
Geosci. Model Dev., 18, 4499–4533, https://doi.org/10.5194/gmd-18-4499-2025, https://doi.org/10.5194/gmd-18-4499-2025, 2025
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Low-level jets (LLJs) are strong winds in the lower atmosphere that are important for wind energy as turbines get taller. This study compares a weather model (WRF) with real data across five North and Baltic Sea sites. Adjusting the model improved accuracy over the widely used ERA5. In key offshore regions, LLJs occur 10–15 % of the time and significantly boost wind power, especially in spring and summer, contributing up to 30 % of total capacity in some areas.
Vishnu Nair, Anujah Mohanathan, Michael Herzog, David G. Macfarlane, and Duncan A. Robertson
Geosci. Model Dev., 18, 4417–4432, https://doi.org/10.5194/gmd-18-4417-2025, https://doi.org/10.5194/gmd-18-4417-2025, 2025
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A numerical model that simulates the measurement processes behind the ground-based radars used to detect volcanic ash clouds is introduced. Using weather radars to detect volcanic clouds is not ideal, as fine ash particles are smaller than raindrops and remain undetected. We evaluate the performance of weather radars to study ash clouds and to identify optimal frequencies that balance the trade-off between a higher return signal and the higher path attenuation that comes at these higher frequencies.
Daniel Garduno Ruiz, Colin Goldblatt, and Anne-Sofie Ahm
Geosci. Model Dev., 18, 4433–4454, https://doi.org/10.5194/gmd-18-4433-2025, https://doi.org/10.5194/gmd-18-4433-2025, 2025
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Photochemical models describe how the composition of the atmosphere changes due to chemical reactions, transport, and other processes. These models are useful for studying the composition of the Earth's and other planets' atmospheres. Understanding the results of these models can be difficult. Here, we build on previous work to develop open-source code that can identify the reaction chains (pathways) that produce the results of these models, facilitating the understanding of these results.
Stefan Noll, Carsten Schmidt, Patrick Hannawald, Wolfgang Kausch, and Stefan Kimeswenger
Geosci. Model Dev., 18, 4353–4398, https://doi.org/10.5194/gmd-18-4353-2025, https://doi.org/10.5194/gmd-18-4353-2025, 2025
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Non-thermal emission from chemical reactions in the Earth's middle und upper atmosphere strongly contributes to the brightness of the night sky below about 2.3 µm. The new Paranal Airglow Line And Continuum Emission model calculates the emission spectrum and its variability with an unprecedented accuracy. Relying on a large spectroscopic data set from astronomical spectrographs and theoretical molecular/atomic data, this model is valuable for airglow research and astronomical observatories.
Peter Kalverla, Imme Benedict, Chris Weijenborg, and Ruud J. van der Ent
Geosci. Model Dev., 18, 4335–4352, https://doi.org/10.5194/gmd-18-4335-2025, https://doi.org/10.5194/gmd-18-4335-2025, 2025
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We introduce a new version of WAM2layers (Water Accounting Model – 2 layers), a computer program that tracks how the weather brings water from one place to another. It uses data from weather and climate models, whose resolution is steadily increasing. Processing the latest data had become a challenge, and the updates presented here ensure that WAM2layers runs smoothly again. We also made it easier to use the program and to understand its source code. This makes it more transparent, reliable, and easier to maintain.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, and Enrico Pisoni
Geosci. Model Dev., 18, 4231–4245, https://doi.org/10.5194/gmd-18-4231-2025, https://doi.org/10.5194/gmd-18-4231-2025, 2025
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We assess relevance and utility indicators by evaluating nine Copernicus Atmospheric Monitoring Service models in calculated air pollutant values. For NO2, the results highlight difficulties at traffic stations. For PM2.5 and PM10 the bias and winter–summer gradients reveal issues. O3 evaluation shows that seasonal gradients are useful. Overall, the indicators reveal model limitations, yet there is a need to reconsider the strictness of some indicators for certain pollutants.
Juan Zhao, Jianping Guo, and Xiaohui Zheng
Geosci. Model Dev., 18, 4075–4101, https://doi.org/10.5194/gmd-18-4075-2025, https://doi.org/10.5194/gmd-18-4075-2025, 2025
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A series of observing system simulation experiments are conducted to assess the impact of multiple radar wind profiler (RWP) networks on convective-scale numerical weather prediction. Results from three southwest-type heavy rainfall cases in the Beijing–Tianjin–Hebei region suggest the added forecast skill of ridge and foothill networks associated with the Taihang Mountains over the existing RWP network. This research provides valuable guidance for designing optimal RWP networks in the region.
Matthias Kohl, Christoph Brühl, Jennifer Schallock, Holger Tost, Patrick Jöckel, Adrian Jost, Steffen Beirle, Michael Höpfner, and Andrea Pozzer
Geosci. Model Dev., 18, 3985–4007, https://doi.org/10.5194/gmd-18-3985-2025, https://doi.org/10.5194/gmd-18-3985-2025, 2025
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SO2 from explosive volcanic eruptions reaching the stratosphere can oxidize and form sulfur aerosols, potentially persisting for several years. We developed a new submodel, Explosive Volcanic ERuptions (EVER), that seamlessly includes stratospheric volcanic SO2 emissions in global numerical simulations based on a novel standard historical model setup, successfully evaluated with satellite observations. Sensitivity studies on the Nabro eruption in 2011 evaluate different emission methods.
Gunho Loren Oh and Philip H. Austin
Geosci. Model Dev., 18, 3921–3940, https://doi.org/10.5194/gmd-18-3921-2025, https://doi.org/10.5194/gmd-18-3921-2025, 2025
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It is difficult to study the behaviour of a cloud field due to internal fluctuations and observational noise. We perform a high-resolution simulation of the boundary-layer cloud field and introduce statistical and numerical techniques, including machine-learning models, to study the evolution of the cloud field, which shows a periodic behaviour. We aim to use the numerical techniques to identify the underlying behaviour within noisy observations.
Oscar Jacquot and Karine Sartelet
Geosci. Model Dev., 18, 3965–3984, https://doi.org/10.5194/gmd-18-3965-2025, https://doi.org/10.5194/gmd-18-3965-2025, 2025
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Modelling the size distribution and the number concentration is important to represent ultrafine particles. A new analytic formulation is presented to compute coagulation partition coefficients, allowing us to lower the numerical diffusion associated with the resolution of aerosol dynamics. The significance of this effect is assessed in a 0D box model and over greater Paris with a chemistry transport model, using different size resolutions of the particle distribution.
Mike Bush, David L. A. Flack, Huw W. Lewis, Sylvia I. Bohnenstengel, Chris J. Short, Charmaine Franklin, Adrian P. Lock, Martin Best, Paul Field, Anne McCabe, Kwinten Van Weverberg, Segolene Berthou, Ian Boutle, Jennifer K. Brooke, Seb Cole, Shaun Cooper, Gareth Dow, John Edwards, Anke Finnenkoetter, Kalli Furtado, Kate Halladay, Kirsty Hanley, Margaret A. Hendry, Adrian Hill, Aravindakshan Jayakumar, Richard W. Jones, Humphrey Lean, Joshua C. K. Lee, Andy Malcolm, Marion Mittermaier, Saji Mohandas, Stuart Moore, Cyril Morcrette, Rachel North, Aurore Porson, Susan Rennie, Nigel Roberts, Belinda Roux, Claudio Sanchez, Chun-Hsu Su, Simon Tucker, Simon Vosper, David Walters, James Warner, Stuart Webster, Mark Weeks, Jonathan Wilkinson, Michael Whitall, Keith D. Williams, and Hugh Zhang
Geosci. Model Dev., 18, 3819–3855, https://doi.org/10.5194/gmd-18-3819-2025, https://doi.org/10.5194/gmd-18-3819-2025, 2025
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RAL configurations define settings for the Unified Model atmosphere and Joint UK Land Environment Simulator. The third version of the Regional Atmosphere and Land (RAL3) science configuration for kilometre- and sub-kilometre-scale modelling represents a major advance compared to previous versions (RAL2) by delivering a common science definition for applications in tropical and mid-latitude regions. RAL3 has more realistic precipitation distributions and an improved representation of clouds and visibility.
Mijie Pang, Jianbing Jin, Ting Yang, Xi Chen, Arjo Segers, Batjargal Buyantogtokh, Yixuan Gu, Jiandong Li, Hai Xiang Lin, Hong Liao, and Wei Han
Geosci. Model Dev., 18, 3781–3798, https://doi.org/10.5194/gmd-18-3781-2025, https://doi.org/10.5194/gmd-18-3781-2025, 2025
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Aerosol data assimilation has gained popularity as it combines the advantages of modelling and observation. However, few studies have addressed the challenges in the prior vertical structure. Different observations are assimilated to examine the sensitivity of assimilation to vertical structure. Results show that assimilation can optimize the dust field in general. However, if the prior introduces an incorrect structure, the assimilation can significantly deteriorate the integrity of the aerosol profile.
Matthieu Dabrowski, José Mennesson, Jérôme Riedi, Chaabane Djeraba, and Pierre Nabat
Geosci. Model Dev., 18, 3707–3733, https://doi.org/10.5194/gmd-18-3707-2025, https://doi.org/10.5194/gmd-18-3707-2025, 2025
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This work focuses on the prediction of aerosol concentration values at the ground level, which are a strong indicator of air quality, using artificial neural networks. A study of different variables and their efficiency as inputs for these models is also proposed and reveals that the best results are obtained when using all of them. Comparison between network architectures and information fusion methods allows for the extraction of knowledge on the most efficient methods in the context of this study.
Pauline Bonnet, Lorenzo Pastori, Mierk Schwabe, Marco Giorgetta, Fernando Iglesias-Suarez, and Veronika Eyring
Geosci. Model Dev., 18, 3681–3706, https://doi.org/10.5194/gmd-18-3681-2025, https://doi.org/10.5194/gmd-18-3681-2025, 2025
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Tuning a climate model means adjusting uncertain parameters in the model to best match observations like the global radiation balance and cloud cover. This is usually done by running many simulations of the model with different settings, which can be time-consuming and relies heavily on expert knowledge. To make this process faster and more objective, we developed a machine learning emulator to create a large ensemble and apply a method called history matching to find the best settings.
Kang Hu, Hong Liao, Dantong Liu, Jianbing Jin, Lei Chen, Siyuan Li, Yangzhou Wu, Changhao Wu, Shitong Zhao, Xiaotong Jiang, Ping Tian, Kai Bi, Ye Wang, and Delong Zhao
Geosci. Model Dev., 18, 3623–3634, https://doi.org/10.5194/gmd-18-3623-2025, https://doi.org/10.5194/gmd-18-3623-2025, 2025
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This study combines machine learning with concentration-weighted trajectory analysis to quantify regional transport PM2.5. From 2013–2020, local emissions dominated Beijing's pollution events. The Air Pollution Prevention and Control Action Plan reduced regional transport pollution, but the eastern region showed the smallest decrease. Beijing should prioritize local emission reduction while considering the east region's contributions in future strategies.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 18, 3607–3622, https://doi.org/10.5194/gmd-18-3607-2025, https://doi.org/10.5194/gmd-18-3607-2025, 2025
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We developed a deep learning method to estimate CO2 emissions from power plants using satellite images. Trained and validated on simulated data, our model accurately predicts emissions despite challenges like cloud cover. When applied to real OCO3 satellite images, the results closely match reported emissions. This study shows that neural networks trained on simulations can effectively analyse real satellite data, offering a new way to monitor CO2 emissions from space.
Wonbae Bang, Jacob T. Carlin, Kwonil Kim, Alexander V. Ryzhkov, Guosheng Liu, and GyuWon Lee
Geosci. Model Dev., 18, 3559–3581, https://doi.org/10.5194/gmd-18-3559-2025, https://doi.org/10.5194/gmd-18-3559-2025, 2025
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Microphysics model-based diagnosis, such as the spectral bin model (SBM), has recently been attempted to diagnose winter precipitation types. In this study, the accuracy of SBM-based precipitation type diagnosis is compared with other traditional methods. SBM has a relatively higher accuracy for dry-snow and wet-snow events, whereas it has lower accuracy for rain events. When the microphysics scheme in the SBM was optimized for the corresponding region, the accuracy for rain events improved.
Gabriel Colas, Valéry Masson, François Bouttier, Ludovic Bouilloud, Laura Pavan, and Virve Karsisto
Geosci. Model Dev., 18, 3453–3472, https://doi.org/10.5194/gmd-18-3453-2025, https://doi.org/10.5194/gmd-18-3453-2025, 2025
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In winter, snow- and ice-covered artificial surfaces are important aspects of the urban climate. They may influence the magnitude of the urban heat island effect, but this is still unclear. In this study, we improved the representation of the snow and ice cover in the Town Energy Balance (TEB) urban climate model. Evaluations have shown that the results are promising for using TEB to study the climate of cold cities.
Markus Kunze, Christoph Zülicke, Tarique A. Siddiqui, Claudia C. Stephan, Yosuke Yamazaki, Claudia Stolle, Sebastian Borchert, and Hauke Schmidt
Geosci. Model Dev., 18, 3359–3385, https://doi.org/10.5194/gmd-18-3359-2025, https://doi.org/10.5194/gmd-18-3359-2025, 2025
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We present the Icosahedral Nonhydrostatic (ICON) general circulation model with an upper-atmospheric extension with the physics package for numerical weather prediction (UA-ICON(NWP)). We optimized the parameters for the gravity wave parameterizations and achieved realistic modeling of the thermal and dynamic states of the mesopause regions. UA-ICON(NWP) now shows a realistic frequency of major sudden stratospheric warmings and well-represented solar tides in temperature.
Lucas A. Estrada, Daniel J. Varon, Melissa Sulprizio, Hannah Nesser, Zichong Chen, Nicholas Balasus, Sarah E. Hancock, Megan He, James D. East, Todd A. Mooring, Alexander Oort Alonso, Joannes D. Maasakkers, Ilse Aben, Sabour Baray, Kevin W. Bowman, John R. Worden, Felipe J. Cardoso-Saldaña, Emily Reidy, and Daniel J. Jacob
Geosci. Model Dev., 18, 3311–3330, https://doi.org/10.5194/gmd-18-3311-2025, https://doi.org/10.5194/gmd-18-3311-2025, 2025
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Reducing emissions of methane, a powerful greenhouse gas, is a top policy concern for mitigating anthropogenic climate change. The Integrated Methane Inversion (IMI) is an advanced, cloud-based software that translates satellite observations into actionable emissions data. Here we present IMI version 2.0 with vastly expanded capabilities. These updates enable a wider range of scientific and stakeholder applications from individual basin to global scales with continuous emissions monitoring.
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.
Maurin Zouzoua, Sophie Bastin, Fabienne Lohou, Marie Lothon, Marjolaine Chiriaco, Mathilde Jome, Cécile Mallet, Laurent Barthes, and Guylaine Canut
Geosci. Model Dev., 18, 3211–3239, https://doi.org/10.5194/gmd-18-3211-2025, https://doi.org/10.5194/gmd-18-3211-2025, 2025
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This study proposes using a statistical model to freeze errors due to differences in environmental forcing when evaluating the surface turbulent heat fluxes from numerical simulations with observations. The statistical model is first built with observations and then applied to the simulated environment to generate possibly observed fluxes. This novel method provides insight into differently evaluating the numerical formulation of turbulent heat fluxes with a long period of observational data.
Oxana Drofa
Geosci. Model Dev., 18, 3175–3209, https://doi.org/10.5194/gmd-18-3175-2025, https://doi.org/10.5194/gmd-18-3175-2025, 2025
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This paper presents the result of many years of effort of the author, who developed an original mathematical numerical model of heat and moisture exchange processes in soil, vegetation, and snow. The author relied on her 30 years of research experience in atmospheric numerical modelling. The presented model is the fruit of the author's research on physical processes at the surface–atmosphere interface and their numerical approximation and aims at improving numerical weather forecasting and climate simulations.
Tyler P. Janoski, Ivan Mitevski, Ryan J. Kramer, Michael Previdi, and Lorenzo M. Polvani
Geosci. Model Dev., 18, 3065–3079, https://doi.org/10.5194/gmd-18-3065-2025, https://doi.org/10.5194/gmd-18-3065-2025, 2025
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We developed ClimKern, a Python package and radiative kernel repository, to simplify calculating radiative feedbacks and make climate sensitivity studies more reproducible. Testing of ClimKern with sample climate model data reveals that radiative kernel choice may be more important than previously thought, especially in polar regions. Our work highlights the need for kernel sensitivity analyses to be included in future studies.
Matti Niskanen, Aku Seppänen, Henri Oikarinen, Miska Olin, Panu Karjalainen, Santtu Mikkonen, and Kari Lehtinen
Geosci. Model Dev., 18, 2983–3001, https://doi.org/10.5194/gmd-18-2983-2025, https://doi.org/10.5194/gmd-18-2983-2025, 2025
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Particle size is a key factor determining the properties of aerosol particles which have a major influence on the climate and on human health. When measuring the particle sizes, however, sometimes the sampling lines that transfer the aerosol to the measurement device distort the size distribution, making the measurement unreliable. We propose a method to correct for the distortions and estimate the true particle sizes, improving measurement accuracy.
Johann Rasmus Nüß, Nikos Daskalakis, Fabian Günther Piwowarczyk, Angelos Gkouvousis, Oliver Schneising, Michael Buchwitz, Maria Kanakidou, Maarten C. Krol, and Mihalis Vrekoussis
Geosci. Model Dev., 18, 2861–2890, https://doi.org/10.5194/gmd-18-2861-2025, https://doi.org/10.5194/gmd-18-2861-2025, 2025
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We estimate carbon monoxide emissions through inverse modeling, an approach where measurements of tracers in the atmosphere are fed to a model to calculate backwards in time (inverse) where the tracers came from. We introduce measurements from a new satellite instrument and show that, in most places globally, these on their own sufficiently constrain the emissions. This alleviates the need for additional datasets, which could shorten the delay for future carbon monoxide source estimates.
Ashu Dastoor, Hélène Angot, Johannes Bieser, Flora Brocza, Brock Edwards, Aryeh Feinberg, Xinbin Feng, Benjamin Geyman, Charikleia Gournia, Yipeng He, Ian M. Hedgecock, Ilia Ilyin, Jane Kirk, Che-Jen Lin, Igor Lehnherr, Robert Mason, David McLagan, Marilena Muntean, Peter Rafaj, Eric M. Roy, Andrei Ryjkov, Noelle E. Selin, Francesco De Simone, Anne L. Soerensen, Frits Steenhuisen, Oleg Travnikov, Shuxiao Wang, Xun Wang, Simon Wilson, Rosa Wu, Qingru Wu, Yanxu Zhang, Jun Zhou, Wei Zhu, and Scott Zolkos
Geosci. Model Dev., 18, 2747–2860, https://doi.org/10.5194/gmd-18-2747-2025, https://doi.org/10.5194/gmd-18-2747-2025, 2025
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This paper introduces the Multi-Compartment Mercury (Hg) Modeling and Analysis Project (MCHgMAP) aimed at informing the effectiveness evaluations of two multilateral environmental agreements: the Minamata Convention on Mercury and the Convention on Long-Range Transboundary Air Pollution. The experimental design exploits a variety of models (atmospheric, land, oceanic ,and multimedia mass balance models) to assess the short- and long-term influences of anthropogenic Hg releases into the environment.
Hilda Sandström and Patrick Rinke
Geosci. Model Dev., 18, 2701–2724, https://doi.org/10.5194/gmd-18-2701-2025, https://doi.org/10.5194/gmd-18-2701-2025, 2025
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Machine learning has the potential to aid the identification of organic molecules involved in aerosol formation. Yet, progress is stalled by a lack of curated atmospheric molecular datasets. Here, we compared atmospheric compounds with large molecular datasets used in machine learning and found minimal overlap with similarity algorithms. Our result underlines the need for collaborative efforts to curate atmospheric molecular data to facilitate machine learning models in atmospheric sciences.
Yuming Jin, Britton B. Stephens, Matthew C. Long, Naveen Chandra, Frédéric Chevallier, Joram J. D. Hooghiem, Ingrid T. Luijkx, Shamil Maksyutov, Eric J. Morgan, Yosuke Niwa, Prabir K. Patra, Christian Rödenbeck, and Jesse Vance
EGUsphere, https://doi.org/10.5194/egusphere-2025-1736, https://doi.org/10.5194/egusphere-2025-1736, 2025
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We carry out a comprehensive atmospheric transport model (ATM) intercomparison project. This project aims to evaluate errors in ATMs and three air-sea O2 exchange products by comparing model simulations with observations collected from surface stations, ships, and aircraft. We also present a model evaluation framework to independently quantify transport-related and flux-related biases that contribute to model-observation discrepancies in atmospheric tracer distributions.
Juan Escobar, Philippe Wautelet, Joris Pianezze, Florian Pantillon, Thibaut Dauhut, Christelle Barthe, and Jean-Pierre Chaboureau
Geosci. Model Dev., 18, 2679–2700, https://doi.org/10.5194/gmd-18-2679-2025, https://doi.org/10.5194/gmd-18-2679-2025, 2025
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The Meso-NH weather research code is adapted for GPUs using OpenACC, leading to significant performance and energy efficiency improvements. Called MESONH-v55-OpenACC, it includes enhanced memory management, communication optimizations and a new solver. On the AMD MI250X Adastra platform, it achieved up to 6× speedup and 2.3× energy efficiency gain compared to CPUs. Storm simulations at 100 m resolution show positive results, positioning the code for future use on exascale supercomputers.
Jie Gao, Yi Huang, Jonathon S. Wright, Ke Li, Tao Geng, and Qiurun Yu
Geosci. Model Dev., 18, 2569–2586, https://doi.org/10.5194/gmd-18-2569-2025, https://doi.org/10.5194/gmd-18-2569-2025, 2025
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The aerosol in the upper troposphere and stratosphere is highly variable, and its radiative effect is poorly understood. To estimate this effect, the radiative kernel is constructed and applied. The results show that the kernels can reproduce aerosol radiative effects and are expected to simulate stratospheric aerosol radiative effects. This approach reduces computational expense, is consistent with radiative model calculations, and can be applied to atmospheric models with speed requirements.
Joseph Mouallem, Kun Gao, Brandon G. Reichl, Lauren Chilutti, Lucas Harris, Rusty Benson, Niki Zadeh, Jing Chen, Jan-Huey Chen, and Cheng Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2025-1690, https://doi.org/10.5194/egusphere-2025-1690, 2025
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We introduce a new high-resolution model that couple the atmosphere and ocean to better simulate extreme weather events. It combines GFDL’s advanced atmospheric and ocean models with a powerful coupling system that allows robust and efficient two-way interactions. Simulations show the model accurately captures hurricane behavior and its impact on the ocean. It also runs efficiently on supercomputers. This model is a key step toward improving extreme weather forecast.
Ji Won Yoon, Seungyeon Lee, Ebony Lee, and Seon Ki Park
Geosci. Model Dev., 18, 2303–2328, https://doi.org/10.5194/gmd-18-2303-2025, https://doi.org/10.5194/gmd-18-2303-2025, 2025
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This study evaluates the Weather Research and Forecasting Model (WRF) coupled with Chemistry (WRF-Chem) to predict a mega Asian dust storm (ADS) over South Korea on 28–29 March 2021. We assessed combinations of five dust emission and four land surface schemes by analyzing meteorological and air quality variables. The best scheme combination reduced the root mean square error (RMSE) for particulate matter 10 (PM10) by up to 29.6 %, demonstrating the highest performance.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
Geosci. Model Dev., 18, 2231–2248, https://doi.org/10.5194/gmd-18-2231-2025, https://doi.org/10.5194/gmd-18-2231-2025, 2025
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The effectiveness of this assimilation system and its sensitivity to the ensemble member size and length of the assimilation window are investigated. This study advances our understanding of the selection of basic parameters in the four-dimensional local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate-matter-polluted environment.
Jens Peter Karolus Wenceslaus Frankemölle, Johan Camps, Pieter De Meutter, and Johan Meyers
Geosci. Model Dev., 18, 1989–2003, https://doi.org/10.5194/gmd-18-1989-2025, https://doi.org/10.5194/gmd-18-1989-2025, 2025
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To detect anomalous radioactivity in the environment, it is paramount that we understand the natural background level. In this work, we propose a statistical model to describe the most likely background level and the associated uncertainty in a network of dose rate detectors. We train, verify, and validate the model using real environmental data. Using the model, we show that we can correctly predict the background level in a subset of the detector network during a known
anomalous event.
Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, David Bolsée, Xavier Fettweis, and Marilaure Grégoire
Geosci. Model Dev., 18, 1965–1988, https://doi.org/10.5194/gmd-18-1965-2025, https://doi.org/10.5194/gmd-18-1965-2025, 2025
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The MAR (Modèle Régional Atmosphérique) is a regional climate model used for weather forecasting and studying the climate over various regions. This paper presents an update of MAR thanks to which it can precisely decompose solar radiation, in particular in the UV (ultraviolet) and photosynthesis ranges, both being critical to human health and ecosystems. As a first application of this new capability, this paper presents a method for predicting UV indices with MAR.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
Geosci. Model Dev., 18, 1947–1964, https://doi.org/10.5194/gmd-18-1947-2025, https://doi.org/10.5194/gmd-18-1947-2025, 2025
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Direct assimilation of observations from ground-based microwave radiometers (GMRs) holds significant potential for improving forecast accuracy. Radiative transfer models (RTMs) play a crucial role in direct data assimilation. In this study, we introduce a new RTM, the Advanced Radiative Transfer Modeling System – Ground-Based (ARMS-gb), designed to simulate brightness temperatures observed by GMRs along with their Jacobians. Several enhancements have been incorporated to achieve higher accuracy.
R. Phani Murali Krishna, Siddharth Kumar, A. Gopinathan Prajeesh, Peter Bechtold, Nils Wedi, Kumar Roy, Malay Ganai, B. Revanth Reddy, Snehlata Tirkey, Tanmoy Goswami, Radhika Kanase, Sahadat Sarkar, Medha Deshpande, and Parthasarathi Mukhopadhyay
Geosci. Model Dev., 18, 1879–1894, https://doi.org/10.5194/gmd-18-1879-2025, https://doi.org/10.5194/gmd-18-1879-2025, 2025
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The High-Resolution Global Forecast Model (HGFM) is an advanced iteration of the operational Global Forecast System (GFS) model. HGFM can produce forecasts at a spatial scale of ~6 km in tropics. It demonstrates improved accuracy in short- to medium-range weather prediction over the Indian region, with notable success in predicting extreme events. Further, the model will be entrusted to operational forecasting agencies after validation and testing.
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev., 18, 1851–1878, https://doi.org/10.5194/gmd-18-1851-2025, https://doi.org/10.5194/gmd-18-1851-2025, 2025
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Nowcasting models struggle with the rapid evolution of heavy rain, and common verification methods are unable to describe how accurately the models predict the growth and decay of heavy rain. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and the model skill is then evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with four open-source models.
Andrew Geiss and Po-Lun Ma
Geosci. Model Dev., 18, 1809–1827, https://doi.org/10.5194/gmd-18-1809-2025, https://doi.org/10.5194/gmd-18-1809-2025, 2025
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Particles in the Earth's atmosphere strongly impact the planet's energy budget, and atmosphere simulations require accurate representation of their interaction with light. This work introduces two approaches to represent light scattering by small particles. The first is a scattering simulator based on Mie theory implemented in Python. The second is a neural network emulator that is more accurate than existing methods and is fast enough to be used in climate and weather simulations.
Andrin Jörimann, Timofei Sukhodolov, Beiping Luo, Gabriel Chiodo, Graham Mann, and Thomas Peter
EGUsphere, https://doi.org/10.5194/egusphere-2025-145, https://doi.org/10.5194/egusphere-2025-145, 2025
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Aerosol particles in the stratosphere affect our climate. Climate models therefore need an accurate description of their properties and evolution. Satellites measure how strongly aerosol particles extinguish light passing through the stratosphere. We describe a method to use such aerosol extinction data to retrieve the number and sizes of the aerosol particles and calculate their optical effects. The resulting data sets for models are validated against ground-based and balloon observations.
Qin Wang, Bo Zeng, Gong Chen, and Yaoting Li
Geosci. Model Dev., 18, 1769–1784, https://doi.org/10.5194/gmd-18-1769-2025, https://doi.org/10.5194/gmd-18-1769-2025, 2025
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This study evaluates the performance of four planetary boundary layer (PBL) schemes in near-surface wind fields over the Sichuan Basin, China. Using 112 sensitivity experiments with the Weather Research and Forecasting (WRF) model and focusing on 28 wind events, it is found that wind direction was less sensitive to the PBL schemes. The quasi-normal scale elimination (QNSE) scheme captured temporal variations best, while the Mellor–Yamada–Janjić (MYJ) scheme had the least error in wind speed.
Tai-Long He, Nikhil Dadheech, Tammy M. Thompson, and Alexander J. Turner
Geosci. Model Dev., 18, 1661–1671, https://doi.org/10.5194/gmd-18-1661-2025, https://doi.org/10.5194/gmd-18-1661-2025, 2025
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It is computationally expensive to infer greenhouse gas (GHG) emissions using atmospheric observations. This is partly due to the detailed model used to represent atmospheric transport. We demonstrate how a machine learning (ML) model can be used to simulate high-resolution atmospheric transport. This type of ML model will help estimate GHG emissions using dense observations, which are becoming increasingly common with the proliferation of urban monitoring networks and geostationary satellites.
Wei Li, Beiming Tang, Patrick C. Campbell, Youhua Tang, Barry Baker, Zachary Moon, Daniel Tong, Jianping Huang, Kai Wang, Ivanka Stajner, and Raffaele Montuoro
Geosci. Model Dev., 18, 1635–1660, https://doi.org/10.5194/gmd-18-1635-2025, https://doi.org/10.5194/gmd-18-1635-2025, 2025
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The study describes the updates of NOAA's current UFS-AQMv7 air quality forecast model by incorporating the latest scientific and structural changes in CMAQv5.4. An evaluation during the summer of 2023 shows that the updated model overall improves the simulation of MDA8 O3 by reducing the bias by 8%–12% in the contiguous US. PM2.5 predictions have mixed results due to wildfire, highlighting the need for future refinements.
Yanwei Zhu, Aitor Atencia, Markus Dabernig, and Yong Wang
Geosci. Model Dev., 18, 1545–1559, https://doi.org/10.5194/gmd-18-1545-2025, https://doi.org/10.5194/gmd-18-1545-2025, 2025
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Most works have delved into convective weather nowcasting, and only a few works have discussed the nowcasting uncertainty for variables at the surface level. Hence, we proposed a method to estimate uncertainty. Generating appropriate noises associated with the characteristic of the error in analysis can simulate the uncertainty of nowcasting. This method can contribute to the estimation of near–surface analysis uncertainty in both nowcasting applications and ensemble nowcasting development.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
Geosci. Model Dev., 18, 1505–1544, https://doi.org/10.5194/gmd-18-1505-2025, https://doi.org/10.5194/gmd-18-1505-2025, 2025
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The Community Inversion Framework (CIF) brings together methods for estimating greenhouse gas fluxes from atmospheric observations. The initial ensemble method implemented in CIF was found to be incomplete and could hardly be compared to other ensemble methods employed in the inversion community. In this paper, we present and evaluate a new implementation of the ensemble mode, building upon the initial developments.
Astrid Kerkweg, Timo Kirfel, Duong H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev., 18, 1265–1286, https://doi.org/10.5194/gmd-18-1265-2025, https://doi.org/10.5194/gmd-18-1265-2025, 2025
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Normally, the Modular Earth Submodel System (MESSy) is linked to complete dynamic models to create chemical climate models. However, the modular concept of MESSy and the newly developed DWARF component presented here make it possible to create simplified models that contain only one or a few process descriptions. This is very useful for technical optimisation, such as porting to GPUs, and can be used to create less complex models, such as a chemical box model.
Cited articles
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Aleksankina, K., Reis, S., Vieno, M., and Heal, M. R.: Advanced methods for uncertainty assessment and global sensitivity analysis of an Eulerian atmospheric chemistry transport model, Atmos. Chem. Phys., 19, 2881–2898, https://doi.org/10.5194/acp-19-2881-2019, 2019.
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Bian, H., Chin, M., Hauglustaine, D. A., Schulz, M., Myhre, G., Bauer, S. E., Lund, M. T., Karydis, V. A., Kucsera, T. L., Pan, X., Pozzer, A., Skeie, R. B., Steenrod, S. D., Sudo, K., Tsigaridis, K., Tsimpidi, A. P., and Tsyro, S. G.: Investigation of global particulate nitrate from the AeroCom phase III experiment, Atmos. Chem. Phys., 17, 12911–12940, https://doi.org/10.5194/acp-17-12911-2017, 2017.
Burnett, R., Chen, H., Szyszkowicz, M., Fann, N., Hubbell, B., Pope, C. A., Apte, J. S., Brauer, M., Cohen, A., Weichenthal, S., Coggins, J., Di, Q., Brunekreef, B., Frostad, J., Lim, S. S., Kan, H., Walker, K. D., Thurston, G. D., Hayes, R. B., Lim, C. C., Turner, M. C., Jerrett, M., Krewski, D., Gapstur, S. M., Diver, W. R., Ostro, B., Goldberg, D., Crouse, D. L., Martin, R. V., Peters, P., Pinault, L., Tjepkema, M., van Donkelaar, A., Villeneuve, P. J., Miller, A. B., Yin, P., Zhou, M., Wang, L., Janssen, N. A. H., Marra, M., Atkinson, R. W., Tsang, H., Quoc Thach, T., Cannon, J. B., Allen, R. T., Hart, J. E., Laden, F., Cesaroni, G., Forastiere, F., Weinmayr, G., Jaensch, A., Nagel, G., Concin, H., and Spadaro, J. V.: Global estimates of mortality associated with long-term exposure to outdoor fine particulate matter, P. Natl. Acad. Sci. USA, 115, 9592, https://doi.org/10.1073/pnas.1803222115, 2018.
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Cheng, Y., Duan, F.-k., He, K.-b., Du, Z.-y., Zheng, M., and Ma, Y.-l.: Sampling artifacts of organic and inorganic aerosol: Implications for the speciation measurement of particulate matter, Atmos. Environ., 55, 229–233, https://doi.org/10.1016/j.atmosenv.2012.03.032, 2012.
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Crippa, M., Solazzo, E., Huang, G., Guizzardi, D., Koffi, E., Muntean, M., Schieberle, C., Friedrich, R., and Janssens-Maenhout, G.: High resolution temporal profiles in the Emissions Database for Global Atmospheric Research, Sci. Data, 7, 121, https://doi.org/10.1038/s41597-020-0462-2, 2020.
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Hjellbrekke, A.-G.: Data Report 2015 Particulate matter, carbonaceous and inorganic compounds, EMEP Co-operative Programme for Monitoring and Evaluation of the Long-range Transmission of Air Pollutants in Europe, Chemical Co-ordinating Centre of EMEP (CCC), EMEP/CCC Reports, 143 pp., 2017.
Hood, C., MacKenzie, I., Stocker, J., Johnson, K., Carruthers, D., Vieno, M., and Doherty, R.: Air quality simulations for London using a coupled regional-to-local modelling system, Atmos. Chem. Phys., 18, 11221–11245, https://doi.org/10.5194/acp-18-11221-2018, 2018.
Janssens-Maenhout, G., Crippa, M., Guizzardi, D., Dentener, F., Muntean, M., Pouliot, G., Keating, T., Zhang, Q., Kurokawa, J., Wankmüller, R., Denier van der Gon, H., Kuenen, J. J. P., Klimont, Z., Frost, G., Darras, S., Koffi, B., and Li, M.: HTAP_v2.2: a mosaic of regional and global emission grid maps for 2008 and 2010 to study hemispheric transport of air pollution, Atmos. Chem. Phys., 15, 11411–11432, https://doi.org/10.5194/acp-15-11411-2015, 2015.
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Khan, M. A. H., Lowe, D., Derwent, R. G., Foulds, A., Chhantyal-Pun, R., McFiggans, G., Orr-Ewing, A. J., Percival, C. J., and Shallcross, D. E.: Global and regional model simulations of atmospheric ammonia, Atmos. Res., 234, 104702, https://doi.org/10.1016/j.atmosres.2019.104702, 2020.
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Kong, L., Tang, X., Zhu, J., Wang, Z., Fu, J. S., Wang, X., Itahashi, S., Yamaji, K., Nagashima, T., Lee, H.-J., Kim, C.-H., Lin, C.-Y., Chen, L., Zhang, M., Tao, Z., Li, J., Kajino, M., Liao, H., Wang, Z., Sudo, K., Wang, Y., Pan, Y., Tang, G., Li, M., Wu, Q., Ge, B., and Carmichael, G. R.: Evaluation and uncertainty investigation of the NO2, CO and NH3 modeling over China under the framework of MICS-Asia III, Atmos. Chem. Phys., 20, 181–202, https://doi.org/10.5194/acp-20-181-2020, 2020.
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Short summary
This study reports the first evaluation of the global EMEP MSC-W ACTM driven by WRF meteorology, with a focus on surface concentrations and wet deposition of reactive N and S species. The model–measurement comparison is conducted both spatially and temporally, covering 10 monitoring networks worldwide. The statistics from the comprehensive evaluations presented in this study support the application of this model framework for global analysis of the budgets and fluxes of reactive N and SIA.
This study reports the first evaluation of the global EMEP MSC-W ACTM driven by WRF meteorology,...
