Articles | Volume 6, issue 5
https://doi.org/10.5194/gmd-6-1389-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/gmd-6-1389-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model description paper
| 
09 Sep 2013
Model description paper |
| 09 Sep 2013
The Chemistry CATT-BRAMS model (CCATT-BRAMS 4.5): a regional atmospheric model system for integrated air quality and weather forecasting and research
K. M. Longo
Centro de Previsão de Tempo e Estudos Climáticos, INPE, Cachoeira Paulista, Brazil
S. R. Freitas
Centro de Previsão de Tempo e Estudos Climáticos, INPE, Cachoeira Paulista, Brazil
M. Pirre
Laboratoire de Physique et Chimie de l'Environnement et de l'Espace, CNRS-Université d'Orléans, Orléans, UMR7328, France
V. Marécal
Centre National de Recherches Météorologique/Groupe d'étude de l'Atmosphère Météorologique, Météo-France and CNRS, UMR3589, Toulouse, France
L. F. Rodrigues
Centro de Previsão de Tempo e Estudos Climáticos, INPE, Cachoeira Paulista, Brazil
J. Panetta
Divisão de Ciências da Computação, Instituto Tecnológico da Aeronáutica (ITA), São José dos Campos, Brazil
M. F. Alonso
Faculdade de Meteorologia, Universidade Federal de Pelotas (UFPEL), Pelotas, Rio Grande do Sul, Brazil
N. E. Rosário
Departamento de Ciências Biológicas, Universidade Federal de São Paulo (UNIFESP), Diadema, São Paulo, Brazil
D. S. Moreira
Centro de Previsão de Tempo e Estudos Climáticos, INPE, Cachoeira Paulista, Brazil
M. S. Gácita
Centro de Previsão de Tempo e Estudos Climáticos, INPE, Cachoeira Paulista, Brazil
J. Arteta
Centre National de Recherches Météorologique/Groupe d'étude de l'Atmosphère Météorologique, Météo-France and CNRS, UMR3589, Toulouse, France
R. Fonseca
Centro de Previsão de Tempo e Estudos Climáticos, INPE, Cachoeira Paulista, Brazil
R. Stockler
Centro de Previsão de Tempo e Estudos Climáticos, INPE, Cachoeira Paulista, Brazil
D. M. Katsurayama
Centro de Previsão de Tempo e Estudos Climáticos, INPE, Cachoeira Paulista, Brazil
A. Fazenda
Instituto de Ciência e Tecnologia, Universidade Federal de São Paulo (UNIFESP), São José dos Campos, São Paulo, Brazil
M. Bela
Laboratory for Atmospheric and Space Physics, University of Colorado, Boulder, USA
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Jason E. Williams, Vincent Huijnen, Idir Bouarar, Mehdi Meziane, Timo Schreurs, Sophie Pelletier, Virginie Marécal, Beatrice Josse, and Johannes Flemming
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Saulo R. Freitas, Georg A. Grell, and Haiqin Li
Geosci. Model Dev., 14, 5393–5411, https://doi.org/10.5194/gmd-14-5393-2021, https://doi.org/10.5194/gmd-14-5393-2021, 2021
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Claire Lamotte, Jonathan Guth, Virginie Marécal, Martin Cussac, Paul David Hamer, Nicolas Theys, and Philipp Schneider
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Yann Cohen, Virginie Marécal, Béatrice Josse, and Valérie Thouret
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Atmos. Meas. Tech., 13, 4645–4667, https://doi.org/10.5194/amt-13-4645-2020, https://doi.org/10.5194/amt-13-4645-2020, 2020
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Martin Cussac, Virginie Marécal, Valérie Thouret, Béatrice Josse, and Bastien Sauvage
Atmos. Chem. Phys., 20, 9393–9417, https://doi.org/10.5194/acp-20-9393-2020, https://doi.org/10.5194/acp-20-9393-2020, 2020
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Biomass burning emissions are a major source of carbon monoxide in the atmosphere. Here, the vertical transport that these emissions can undergo until the upper troposphere is investigated, as well as their contribution to carbon monoxide concentrations. It was found that boreal forest emissions were specific to the occurrence of pyroconvection directly above the fires, whereas biomass burning emissions from other regions of the globe relied more on the occurrence of deep convection.
Olivier Coopmann, Vincent Guidard, Nadia Fourrié, Béatrice Josse, and Virginie Marécal
Atmos. Meas. Tech., 13, 2659–2680, https://doi.org/10.5194/amt-13-2659-2020, https://doi.org/10.5194/amt-13-2659-2020, 2020
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Clara Orbe, David A. Plummer, Darryn W. Waugh, Huang Yang, Patrick Jöckel, Douglas E. Kinnison, Beatrice Josse, Virginie Marecal, Makoto Deushi, Nathan Luke Abraham, Alexander T. Archibald, Martyn P. Chipperfield, Sandip Dhomse, Wuhu Feng, and Slimane Bekki
Atmos. Chem. Phys., 20, 3809–3840, https://doi.org/10.5194/acp-20-3809-2020, https://doi.org/10.5194/acp-20-3809-2020, 2020
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Anne-Marlene Blechschmidt, Joaquim Arteta, Adriana Coman, Lyana Curier, Henk Eskes, Gilles Foret, Clio Gielen, Francois Hendrick, Virginie Marécal, Frédérik Meleux, Jonathan Parmentier, Enno Peters, Gaia Pinardi, Ankie J. M. Piters, Matthieu Plu, Andreas Richter, Arjo Segers, Mikhail Sofiev, Álvaro M. Valdebenito, Michel Van Roozendael, Julius Vira, Tim Vlemmix, and John P. Burrows
Atmos. Chem. Phys., 20, 2795–2823, https://doi.org/10.5194/acp-20-2795-2020, https://doi.org/10.5194/acp-20-2795-2020, 2020
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MAX-DOAS tropospheric NO2 vertical column retrievals from a set of European measurement stations are compared to regional air quality models which contribute to the operational Copernicus Atmosphere Monitoring Service (CAMS). Correlations are on the order of 35 %–75 %; large differences occur for individual pollution plumes. The results demonstrate that future model development needs to concentrate on improving representation of diurnal cycles and associated temporal scalings.
Julie M. Nicely, Bryan N. Duncan, Thomas F. Hanisco, Glenn M. Wolfe, Ross J. Salawitch, Makoto Deushi, Amund S. Haslerud, Patrick Jöckel, Béatrice Josse, Douglas E. Kinnison, Andrew Klekociuk, Michael E. Manyin, Virginie Marécal, Olaf Morgenstern, Lee T. Murray, Gunnar Myhre, Luke D. Oman, Giovanni Pitari, Andrea Pozzer, Ilaria Quaglia, Laura E. Revell, Eugene Rozanov, Andrea Stenke, Kane Stone, Susan Strahan, Simone Tilmes, Holger Tost, Daniel M. Westervelt, and Guang Zeng
Atmos. Chem. Phys., 20, 1341–1361, https://doi.org/10.5194/acp-20-1341-2020, https://doi.org/10.5194/acp-20-1341-2020, 2020
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Differences in methane lifetime among global models are large and poorly understood. We use a neural network method and simulations from the Chemistry Climate Model Initiative to quantify the factors influencing methane lifetime spread among models and variations over time. UV photolysis, tropospheric ozone, and nitrogen oxides drive large model differences, while the same factors plus specific humidity contribute to a decreasing trend in methane lifetime between 1980 and 2015.
Yuanhong Zhao, Marielle Saunois, Philippe Bousquet, Xin Lin, Antoine Berchet, Michaela I. Hegglin, Josep G. Canadell, Robert B. Jackson, Didier A. Hauglustaine, Sophie Szopa, Ann R. Stavert, Nathan Luke Abraham, Alex T. Archibald, Slimane Bekki, Makoto Deushi, Patrick Jöckel, Béatrice Josse, Douglas Kinnison, Ole Kirner, Virginie Marécal, Fiona M. O'Connor, David A. Plummer, Laura E. Revell, Eugene Rozanov, Andrea Stenke, Sarah Strode, Simone Tilmes, Edward J. Dlugokencky, and Bo Zheng
Atmos. Chem. Phys., 19, 13701–13723, https://doi.org/10.5194/acp-19-13701-2019, https://doi.org/10.5194/acp-19-13701-2019, 2019
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The role of hydroxyl radical changes in methane trends is debated, hindering our understanding of the methane cycle. This study quantifies how uncertainties in the hydroxyl radical may influence methane abundance in the atmosphere based on the inter-model comparison of hydroxyl radical fields and model simulations of CH4 abundance with different hydroxyl radical scenarios during 2000–2016. We show that hydroxyl radical changes could contribute up to 54 % of model-simulated methane biases.
Kévin Lamy, Thierry Portafaix, Béatrice Josse, Colette Brogniez, Sophie Godin-Beekmann, Hassan Bencherif, Laura Revell, Hideharu Akiyoshi, Slimane Bekki, Michaela I. Hegglin, Patrick Jöckel, Oliver Kirner, Ben Liley, Virginie Marecal, Olaf Morgenstern, Andrea Stenke, Guang Zeng, N. Luke Abraham, Alexander T. Archibald, Neil Butchart, Martyn P. Chipperfield, Glauco Di Genova, Makoto Deushi, Sandip S. Dhomse, Rong-Ming Hu, Douglas Kinnison, Michael Kotkamp, Richard McKenzie, Martine Michou, Fiona M. O'Connor, Luke D. Oman, Giovanni Pitari, David A. Plummer, John A. Pyle, Eugene Rozanov, David Saint-Martin, Kengo Sudo, Taichu Y. Tanaka, Daniele Visioni, and Kohei Yoshida
Atmos. Chem. Phys., 19, 10087–10110, https://doi.org/10.5194/acp-19-10087-2019, https://doi.org/10.5194/acp-19-10087-2019, 2019
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In this study, we simulate the ultraviolet radiation evolution during the 21st century on Earth's surface using the output from several numerical models which participated in the Chemistry-Climate Model Initiative. We present four possible futures which depend on greenhouse gases emissions. The role of ozone-depleting substances, greenhouse gases and aerosols are investigated. Our results emphasize the important role of aerosols for future ultraviolet radiation in the Northern Hemisphere.
Lianet Hernández Pardo, Luiz Augusto Toledo Machado, Micael Amore Cecchini, and Madeleine Sánchez Gácita
Atmos. Chem. Phys., 19, 7839–7857, https://doi.org/10.5194/acp-19-7839-2019, https://doi.org/10.5194/acp-19-7839-2019, 2019
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This work analyzes the effects of changes in the environmental aerosol population on Amazonian clouds. The results confirm that the clouds can be very sensitive to changes in the aerosol properties, but the relative importance of each property is variable and depends on the values of the other aerosol characteristics, especially aerosol size. This is controlled by the degree to which the cloud mixes with the surrounding air and by the efficiency with which aerosols are consumed by droplets.
Vincent Huijnen, Andrea Pozzer, Joaquim Arteta, Guy Brasseur, Idir Bouarar, Simon Chabrillat, Yves Christophe, Thierno Doumbia, Johannes Flemming, Jonathan Guth, Béatrice Josse, Vlassis A. Karydis, Virginie Marécal, and Sophie Pelletier
Geosci. Model Dev., 12, 1725–1752, https://doi.org/10.5194/gmd-12-1725-2019, https://doi.org/10.5194/gmd-12-1725-2019, 2019
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We report on an evaluation of tropospheric ozone and its precursor gases in three atmospheric chemistry versions as implemented in ECMWF’s Integrated Forecasting System (IFS), referred to as IFS(CB05BASCOE), IFS(MOZART) and IFS(MOCAGE). This configuration of having various chemistry versions within IFS provides a quantification of uncertainties in CAMS trace gas products that are induced by chemistry modelling.
Kai-Lan Chang, Owen R. Cooper, J. Jason West, Marc L. Serre, Martin G. Schultz, Meiyun Lin, Virginie Marécal, Béatrice Josse, Makoto Deushi, Kengo Sudo, Junhua Liu, and Christoph A. Keller
Geosci. Model Dev., 12, 955–978, https://doi.org/10.5194/gmd-12-955-2019, https://doi.org/10.5194/gmd-12-955-2019, 2019
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We developed a new method for combining surface ozone observations from thousands of monitoring sites worldwide with the output from multiple atmospheric chemistry models. The result is a global surface ozone distribution with greater accuracy than any single model can achieve. We focused on an ozone metric relevant to human mortality caused by long-term ozone exposure. Our method can be applied to studies that quantify the impacts of ozone on human health and mortality.
Maxence Descheemaecker, Matthieu Plu, Virginie Marécal, Marine Claeyman, Francis Olivier, Youva Aoun, Philippe Blanc, Lucien Wald, Jonathan Guth, Bojan Sič, Jérôme Vidot, Andrea Piacentini, and Béatrice Josse
Atmos. Meas. Tech., 12, 1251–1275, https://doi.org/10.5194/amt-12-1251-2019, https://doi.org/10.5194/amt-12-1251-2019, 2019
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The future Flexible Combined Imager (FCI) on board MeteoSat Third Generation is expected to improve the detection and the quantification of aerosols. The study assesses the potential of FCI/VIS04 channel for monitoring air pollution in Europe. An observing system simulation experiment in MOCAGE is developed, and they show a large positive impact of the assimilation over a 4-month period and particularly during a severe pollution episode. The added value of geostationary data is also assessed.
Fernando Santos, Karla Longo, Alex Guenther, Saewung Kim, Dasa Gu, Dave Oram, Grant Forster, James Lee, James Hopkins, Joel Brito, and Saulo Freitas
Atmos. Chem. Phys., 18, 12715–12734, https://doi.org/10.5194/acp-18-12715-2018, https://doi.org/10.5194/acp-18-12715-2018, 2018
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We investigated the impact of biomass burning on the chemical composition of trace gases in the Amazon. The findings corroborate the influence of biomass burning activity not only on direct emissions of particulate matter but also on the oxidative capacity to produce secondary organic aerosol. The scientists plan to use this information to improve the numerical model simulation with a better representativeness of the chemical processes, which can impact on global climate prediction.
Lindsay D. Yee, Gabriel Isaacman-VanWertz, Rebecca A. Wernis, Meng Meng, Ventura Rivera, Nathan M. Kreisberg, Susanne V. Hering, Mads S. Bering, Marianne Glasius, Mary Alice Upshur, Ariana Gray Bé, Regan J. Thomson, Franz M. Geiger, John H. Offenberg, Michael Lewandowski, Ivan Kourtchev, Markus Kalberer, Suzane de Sá, Scot T. Martin, M. Lizabeth Alexander, Brett B. Palm, Weiwei Hu, Pedro Campuzano-Jost, Douglas A. Day, Jose L. Jimenez, Yingjun Liu, Karena A. McKinney, Paulo Artaxo, Juarez Viegas, Antonio Manzi, Maria B. Oliveira, Rodrigo de Souza, Luiz A. T. Machado, Karla Longo, and Allen H. Goldstein
Atmos. Chem. Phys., 18, 10433–10457, https://doi.org/10.5194/acp-18-10433-2018, https://doi.org/10.5194/acp-18-10433-2018, 2018
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Biogenic volatile organic compounds react in the atmosphere to form secondary organic aerosol, yet the chemical pathways remain unclear. We collected filter samples and deployed a semi-volatile thermal desorption aerosol gas chromatograph in the central Amazon. We measured 30 sesquiterpenes and 4 diterpenes and find them to be important for reactive ozone loss. We estimate that sesquiterpene oxidation contributes at least 0.4–5 % (median 1 %) of observed submicron organic aerosol mass.
Sandip S. Dhomse, Douglas Kinnison, Martyn P. Chipperfield, Ross J. Salawitch, Irene Cionni, Michaela I. Hegglin, N. Luke Abraham, Hideharu Akiyoshi, Alex T. Archibald, Ewa M. Bednarz, Slimane Bekki, Peter Braesicke, Neal Butchart, Martin Dameris, Makoto Deushi, Stacey Frith, Steven C. Hardiman, Birgit Hassler, Larry W. Horowitz, Rong-Ming Hu, Patrick Jöckel, Beatrice Josse, Oliver Kirner, Stefanie Kremser, Ulrike Langematz, Jared Lewis, Marion Marchand, Meiyun Lin, Eva Mancini, Virginie Marécal, Martine Michou, Olaf Morgenstern, Fiona M. O'Connor, Luke Oman, Giovanni Pitari, David A. Plummer, John A. Pyle, Laura E. Revell, Eugene Rozanov, Robyn Schofield, Andrea Stenke, Kane Stone, Kengo Sudo, Simone Tilmes, Daniele Visioni, Yousuke Yamashita, and Guang Zeng
Atmos. Chem. Phys., 18, 8409–8438, https://doi.org/10.5194/acp-18-8409-2018, https://doi.org/10.5194/acp-18-8409-2018, 2018
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We analyse simulations from the Chemistry-Climate Model Initiative (CCMI) to estimate the return dates of the stratospheric ozone layer from depletion by anthropogenic chlorine and bromine. The simulations from 20 models project that global column ozone will return to 1980 values in 2047 (uncertainty range 2042–2052). Return dates in other regions vary depending on factors related to climate change and importance of chlorine and bromine. Column ozone in the tropics may continue to decline.
Paulo R. Teixeira, Saulo R. de Freitas, Francis W. Correia, and Antonio O. Manzi
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2018-81, https://doi.org/10.5194/gmd-2018-81, 2018
Publication in GMD not foreseen
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Emissions of gases and particulates in urban areas are associated with a mixture of various sources, both natural and anthropogenic. Understanding and quantifying these emissions is necessary in studies of climate change, local air pollution issues, and weather modification. This work will also contribute to improved air quality numerical simulations, provide more accurate scenarios for policymakers and regulatory agencies to develop strategies for controlling the vehicular emissions.
Clara Orbe, Huang Yang, Darryn W. Waugh, Guang Zeng, Olaf Morgenstern, Douglas E. Kinnison, Jean-Francois Lamarque, Simone Tilmes, David A. Plummer, John F. Scinocca, Beatrice Josse, Virginie Marecal, Patrick Jöckel, Luke D. Oman, Susan E. Strahan, Makoto Deushi, Taichu Y. Tanaka, Kohei Yoshida, Hideharu Akiyoshi, Yousuke Yamashita, Andreas Stenke, Laura Revell, Timofei Sukhodolov, Eugene Rozanov, Giovanni Pitari, Daniele Visioni, Kane A. Stone, Robyn Schofield, and Antara Banerjee
Atmos. Chem. Phys., 18, 7217–7235, https://doi.org/10.5194/acp-18-7217-2018, https://doi.org/10.5194/acp-18-7217-2018, 2018
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In this study we compare a few atmospheric transport properties among several numerical models that are used to study the influence of atmospheric chemistry on climate. We show that there are large differences among models in terms of the timescales that connect the Northern Hemisphere midlatitudes, where greenhouse gases and ozone-depleting substances are emitted, to the Southern Hemisphere. Our results may have important implications for how models represent atmospheric composition.
Vanessa Brocchi, Gisèle Krysztofiak, Valéry Catoire, Jonathan Guth, Virginie Marécal, Régina Zbinden, Laaziz El Amraoui, François Dulac, and Philippe Ricaud
Atmos. Chem. Phys., 18, 6887–6906, https://doi.org/10.5194/acp-18-6887-2018, https://doi.org/10.5194/acp-18-6887-2018, 2018
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The Mediterranean Basin still suffers from a limited amount of in situ measurements for a good characterization of its environmental state. This study shows that intercontinental transport of very high CO concentrations can affect the upper Mediterranean Basin troposphere. By using modeling, 5- to 12-day eastward transport of biomass burning starting from North America and Siberia impacts the mid-troposphere of the Mediterranean Basin.
Yann Cohen, Hervé Petetin, Valérie Thouret, Virginie Marécal, Béatrice Josse, Hannah Clark, Bastien Sauvage, Alain Fontaine, Gilles Athier, Romain Blot, Damien Boulanger, Jean-Marc Cousin, and Philippe Nédélec
Atmos. Chem. Phys., 18, 5415–5453, https://doi.org/10.5194/acp-18-5415-2018, https://doi.org/10.5194/acp-18-5415-2018, 2018
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Measurements of ozone and carbon monoxide were performed during 1994–2013 around the tropopause on board commercial aircraft. Seasonal cycles and trends were calculated above eight well-sampled regions in Northern Hemisphere midlatitudes. CO shows decreasing concentrations over the last 10 years, thus reflecting the impact of the legislation on anthropogenic emissions. Ozone amounts increased over the 20 years in the upper troposphere during different seasons, depending on the longitudes.
Jonathan Guth, Virginie Marécal, Béatrice Josse, Joaquim Arteta, and Paul Hamer
Atmos. Chem. Phys., 18, 4911–4934, https://doi.org/10.5194/acp-18-4911-2018, https://doi.org/10.5194/acp-18-4911-2018, 2018
Demerval S. Moreira, Karla M. Longo, Saulo R. Freitas, Marcia A. Yamasoe, Lina M. Mercado, Nilton E. Rosário, Emauel Gloor, Rosane S. M. Viana, John B. Miller, Luciana V. Gatti, Kenia T. Wiedemann, Lucas K. G. Domingues, and Caio C. S. Correia
Atmos. Chem. Phys., 17, 14785–14810, https://doi.org/10.5194/acp-17-14785-2017, https://doi.org/10.5194/acp-17-14785-2017, 2017
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Fire in the Amazon forest produces a large amount of smoke that is released into the atmosphere and covers a large portion of South America for about 3 months each year. The smoke affects the energy and CO2 budgets. Using a numerical atmospheric model, we demonstrated that the smoke changes the forest from a source to a sink of CO2 to the atmosphere. The smoke ultimately acts to at least partially compensate for the forest carbon lost due to fire emissions.
Mikhail Sofiev, Olga Ritenberga, Roberto Albertini, Joaquim Arteta, Jordina Belmonte, Carmi Geller Bernstein, Maira Bonini, Sevcan Celenk, Athanasios Damialis, John Douros, Hendrik Elbern, Elmar Friese, Carmen Galan, Gilles Oliver, Ivana Hrga, Rostislav Kouznetsov, Kai Krajsek, Donat Magyar, Jonathan Parmentier, Matthieu Plu, Marje Prank, Lennart Robertson, Birthe Marie Steensen, Michel Thibaudon, Arjo Segers, Barbara Stepanovich, Alvaro M. Valdebenito, Julius Vira, and Despoina Vokou
Atmos. Chem. Phys., 17, 12341–12360, https://doi.org/10.5194/acp-17-12341-2017, https://doi.org/10.5194/acp-17-12341-2017, 2017
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This work presents the features and evaluates the quality of the Copernicus Atmospheric Monitoring Service forecasts of olive pollen distribution in Europe. It is shown that the models can predict the main features of the observed pollen distribution but have more difficulties in capturing the season start and end, which appeared shifted by a few days. We also demonstrated that the combined use of model predictions with up-to-date measurements (data fusion) can strongly improve the results.
Madeleine Sánchez Gácita, Karla M. Longo, Julliana L. M. Freire, Saulo R. Freitas, and Scot T. Martin
Atmos. Chem. Phys., 17, 2373–2392, https://doi.org/10.5194/acp-17-2373-2017, https://doi.org/10.5194/acp-17-2373-2017, 2017
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This study uses an adiabatic cloud model to simulate the activation of smoke aerosol particles in the Amazon region as cloud condensation nuclei (CCN). The relative importance of variability in hygroscopicity, mixing state, and activation kinetics for the activated fraction and maximum supersaturation is assessed. Our findings on uncertainties and sensitivities provide guidance on appropriate simplifications that can be used for modeling of smoke aerosols within general circulation models.
Olaf Morgenstern, Michaela I. Hegglin, Eugene Rozanov, Fiona M. O'Connor, N. Luke Abraham, Hideharu Akiyoshi, Alexander T. Archibald, Slimane Bekki, Neal Butchart, Martyn P. Chipperfield, Makoto Deushi, Sandip S. Dhomse, Rolando R. Garcia, Steven C. Hardiman, Larry W. Horowitz, Patrick Jöckel, Beatrice Josse, Douglas Kinnison, Meiyun Lin, Eva Mancini, Michael E. Manyin, Marion Marchand, Virginie Marécal, Martine Michou, Luke D. Oman, Giovanni Pitari, David A. Plummer, Laura E. Revell, David Saint-Martin, Robyn Schofield, Andrea Stenke, Kane Stone, Kengo Sudo, Taichu Y. Tanaka, Simone Tilmes, Yousuke Yamashita, Kohei Yoshida, and Guang Zeng
Geosci. Model Dev., 10, 639–671, https://doi.org/10.5194/gmd-10-639-2017, https://doi.org/10.5194/gmd-10-639-2017, 2017
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We present a review of the make-up of 20 models participating in the Chemistry–Climate Model Initiative (CCMI). In comparison to earlier such activities, most of these models comprise a whole-atmosphere chemistry, and several of them include an interactive ocean module. This makes them suitable for studying the interactions of tropospheric air quality, stratospheric ozone, and climate. The paper lays the foundation for other studies using the CCMI simulations for scientific analysis.
Saulo R. Freitas, Jairo Panetta, Karla M. Longo, Luiz F. Rodrigues, Demerval S. Moreira, Nilton E. Rosário, Pedro L. Silva Dias, Maria A. F. Silva Dias, Enio P. Souza, Edmilson D. Freitas, Marcos Longo, Ariane Frassoni, Alvaro L. Fazenda, Cláudio M. Santos e Silva, Cláudio A. B. Pavani, Denis Eiras, Daniela A. França, Daniel Massaru, Fernanda B. Silva, Fernando C. Santos, Gabriel Pereira, Gláuber Camponogara, Gonzalo A. Ferrada, Haroldo F. Campos Velho, Isilda Menezes, Julliana L. Freire, Marcelo F. Alonso, Madeleine S. Gácita, Maurício Zarzur, Rafael M. Fonseca, Rafael S. Lima, Ricardo A. Siqueira, Rodrigo Braz, Simone Tomita, Valter Oliveira, and Leila D. Martins
Geosci. Model Dev., 10, 189–222, https://doi.org/10.5194/gmd-10-189-2017, https://doi.org/10.5194/gmd-10-189-2017, 2017
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We present a new version of the Brazilian developments on the Regional Atmospheric Modeling System (BRAMS) where different previous versions for weather, chemistry, and the carbon cycle were unified in a single harmonized software system. This version also has a new set of state-of-the-art physical parametrizations and higher computational parallel and memory usage efficiency. BRAMS has been applied for research and operational weather and air quality forecasting, largely in South America.
Ben T. Johnson, James M. Haywood, Justin M. Langridge, Eoghan Darbyshire, William T. Morgan, Kate Szpek, Jennifer K. Brooke, Franco Marenco, Hugh Coe, Paulo Artaxo, Karla M. Longo, Jane P. Mulcahy, Graham W. Mann, Mohit Dalvi, and Nicolas Bellouin
Atmos. Chem. Phys., 16, 14657–14685, https://doi.org/10.5194/acp-16-14657-2016, https://doi.org/10.5194/acp-16-14657-2016, 2016
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Biomass burning is a large source of carbonaceous aerosols, which scatter and absorb solar radiation, and modify cloud properties. We evaluate the simulation of biomass burning aerosol processes and properties in the HadGEM3 climate model using observations, including those from the South American Biomass Burning Analysis. We find that modelled aerosol optical depths are underestimated unless aerosol emissions (Global Fire Emission Database v3) are increased by a factor of 1.6–2.0.
Bojan Sič, Laaziz El Amraoui, Andrea Piacentini, Virginie Marécal, Emanuele Emili, Daniel Cariolle, Michael Prather, and Jean-Luc Attié
Atmos. Meas. Tech., 9, 5535–5554, https://doi.org/10.5194/amt-9-5535-2016, https://doi.org/10.5194/amt-9-5535-2016, 2016
Line Jourdain, Tjarda Jane Roberts, Michel Pirre, and Beatrice Josse
Atmos. Chem. Phys., 16, 12099–12125, https://doi.org/10.5194/acp-16-12099-2016, https://doi.org/10.5194/acp-16-12099-2016, 2016
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Ambrym Volcano (Vanuatu, southwest Pacific) is one of the largest sources of continuous volcanic emissions worldwide. We performed a modeling study that confirms the strong influence of Ambrym emissions during an extreme degassing event of early 2005 on the composition of the atmosphere on the local and regional scales. It also stresses the importance of considering reactive halogen chemistry in the volcanic plume when assessing the impact of volcanic emissions on climate.
Carolin Walter, Saulo R. Freitas, Christoph Kottmeier, Isabel Kraut, Daniel Rieger, Heike Vogel, and Bernhard Vogel
Atmos. Chem. Phys., 16, 9201–9219, https://doi.org/10.5194/acp-16-9201-2016, https://doi.org/10.5194/acp-16-9201-2016, 2016
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Buoyancy produced by vegetation fires can lead to substantial plume rise with consequences for the dispersion of aerosol emitted by the fires. To study this effect a 1-D plume rise model was included into the regional online integrated model system COSMO-ART. Comparing model results and satellite data for a case study of 2010 Canadian wildfires shows, that the plume rise model outperforms prescribed emission height. The radiative impact of the aerosol leads to a pronounced temperature change.
Gabriel Pereira, Ricardo Siqueira, Nilton E. Rosário, Karla L. Longo, Saulo R. Freitas, Francielle S. Cardozo, Johannes W. Kaiser, and Martin J. Wooster
Atmos. Chem. Phys., 16, 6961–6975, https://doi.org/10.5194/acp-16-6961-2016, https://doi.org/10.5194/acp-16-6961-2016, 2016
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Fires associated with land use and land cover changes release large amounts of aerosols and trace gases into the atmosphere. Although several inventories of biomass burning emissions cover Brazil, there are still considerable uncertainties and differences among them. However, results indicate that emission derived via similar methods tend to agree with one other, but aerosol emissions from fires with particularly high biomass consumption still lead to an underestimation.
R. Paugam, M. Wooster, S. Freitas, and M. Val Martin
Atmos. Chem. Phys., 16, 907–925, https://doi.org/10.5194/acp-16-907-2016, https://doi.org/10.5194/acp-16-907-2016, 2016
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Landscape fire plume height controls fire emissions release in the atmosphere, in particular their transport that may also affect the longevity, chemical conversion, and fate of the plumes chemical constituents. Here, we review how such landscape-scale fire smoke plume injection heights are represented in large-scale atmospheric transport models aiming to represent the impacts of wildfire emissions on component of the Earth system.
J. Guth, B. Josse, V. Marécal, M. Joly, and P. Hamer
Geosci. Model Dev., 9, 137–160, https://doi.org/10.5194/gmd-9-137-2016, https://doi.org/10.5194/gmd-9-137-2016, 2016
P. D. Hamer, K. W. Bowman, D. K. Henze, J.-L. Attié, and V. Marécal
Atmos. Chem. Phys., 15, 10645–10667, https://doi.org/10.5194/acp-15-10645-2015, https://doi.org/10.5194/acp-15-10645-2015, 2015
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Using a simplified air quality forecasting model, we explore how characteristics of air quality observations affect our ability to understand and predict ozone air pollution. We show that the photochemical conditions can strongly influence the observing priorities for ozone prediction, such as which species are observed and how well, when, and how frequently. High-freqency observations of ozone, NOx and HCHO in combination during the morning and afternoon are particularly advantageous.
V. Marécal, V.-H. Peuch, C. Andersson, S. Andersson, J. Arteta, M. Beekmann, A. Benedictow, R. Bergström, B. Bessagnet, A. Cansado, F. Chéroux, A. Colette, A. Coman, R. L. Curier, H. A. C. Denier van der Gon, A. Drouin, H. Elbern, E. Emili, R. J. Engelen, H. J. Eskes, G. Foret, E. Friese, M. Gauss, C. Giannaros, J. Guth, M. Joly, E. Jaumouillé, B. Josse, N. Kadygrov, J. W. Kaiser, K. Krajsek, J. Kuenen, U. Kumar, N. Liora, E. Lopez, L. Malherbe, I. Martinez, D. Melas, F. Meleux, L. Menut, P. Moinat, T. Morales, J. Parmentier, A. Piacentini, M. Plu, A. Poupkou, S. Queguiner, L. Robertson, L. Rouïl, M. Schaap, A. Segers, M. Sofiev, L. Tarasson, M. Thomas, R. Timmermans, Á. Valdebenito, P. van Velthoven, R. van Versendaal, J. Vira, and A. Ung
Geosci. Model Dev., 8, 2777–2813, https://doi.org/10.5194/gmd-8-2777-2015, https://doi.org/10.5194/gmd-8-2777-2015, 2015
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This paper describes the air quality forecasting system over Europe put in place in the Monitoring Atmospheric Composition and Climate projects. It provides daily and 4-day forecasts and analyses for the previous day for major gas and particulate pollutants and their main precursors. These products are based on a multi-model approach using seven state-of-the-art models developed in Europe. An evaluation of the performance of the system is discussed in the paper.
V. Catoire, G. Krysztofiak, C. Robert, M. Chartier, P. Jacquet, C. Guimbaud, P. D. Hamer, and V. Marécal
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amtd-8-9165-2015, https://doi.org/10.5194/amtd-8-9165-2015, 2015
Preprint withdrawn
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A three-channel infrared laser absorption spectrometer has been developed for airborne measurements of trace gases up to the upper troposphere. More than three different species can be measured simultaneously with high time resolution using three individual Continuous Wave Quantum Cascade Lasers coupled to a single Robert multipass optical cell. The first deployment of this spectrometer was realized in convective outflows over South China Sea where enhancements of CO were detected.
M. Sofiev, U. Berger, M. Prank, J. Vira, J. Arteta, J. Belmonte, K.-C. Bergmann, F. Chéroux, H. Elbern, E. Friese, C. Galan, R. Gehrig, D. Khvorostyanov, R. Kranenburg, U. Kumar, V. Marécal, F. Meleux, L. Menut, A.-M. Pessi, L. Robertson, O. Ritenberga, V. Rodinkova, A. Saarto, A. Segers, E. Severova, I. Sauliene, P. Siljamo, B. M. Steensen, E. Teinemaa, M. Thibaudon, and V.-H. Peuch
Atmos. Chem. Phys., 15, 8115–8130, https://doi.org/10.5194/acp-15-8115-2015, https://doi.org/10.5194/acp-15-8115-2015, 2015
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The paper presents the first ensemble modelling experiment for forecasting the atmospheric dispersion of birch pollen in Europe. The study included 7 models of MACC-ENS tested over the season of 2010 and applied for 2013 in forecasting and reanalysis modes. The results were compared with observations in 11 countries, members of European Aeroallergen Network. The models successfully reproduced the timing of the unusually late season of 2013 but had more difficulties with absolute concentration.
J. Flemming, V. Huijnen, J. Arteta, P. Bechtold, A. Beljaars, A.-M. Blechschmidt, M. Diamantakis, R. J. Engelen, A. Gaudel, A. Inness, L. Jones, B. Josse, E. Katragkou, V. Marecal, V.-H. Peuch, A. Richter, M. G. Schultz, O. Stein, and A. Tsikerdekis
Geosci. Model Dev., 8, 975–1003, https://doi.org/10.5194/gmd-8-975-2015, https://doi.org/10.5194/gmd-8-975-2015, 2015
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We describe modules for atmospheric chemistry, wet and dry deposition and lightning NO production, which have been newly introduced in ECMWF's weather forecasting model. With that model, we want to forecast global air pollution as part of the European Copernicus Atmosphere Monitoring Service. We show that the new model results compare as well or better with in situ and satellite observations of ozone, CO, NO2, SO2 and formaldehyde as the previous model.
R. Paugam, M. Wooster, J. Atherton, S. R. Freitas, M. G. Schultz, and J. W. Kaiser
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-15-9815-2015, https://doi.org/10.5194/acpd-15-9815-2015, 2015
Revised manuscript not accepted
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The transport of Biomass Burning emissions in Chemical Transport Model rely on parametrization of plumes injection height. Using fire observation selected to ensure match-up of fire-atmosphere-plume dynamics; a popular plume rise model was improved and optimized. The resulting model shows response to the effect of atmospheric stability consistent with previous findings and is able to predict higher injection height than any other tested parametrizations, giving a closer match with observation.
S. Archer-Nicholls, D. Lowe, E. Darbyshire, W. T. Morgan, M. M. Bela, G. Pereira, J. Trembath, J. W. Kaiser, K. M. Longo, S. R. Freitas, H. Coe, and G. McFiggans
Geosci. Model Dev., 8, 549–577, https://doi.org/10.5194/gmd-8-549-2015, https://doi.org/10.5194/gmd-8-549-2015, 2015
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The regional WRF-Chem model was used to study aerosol particles from biomass burning in South America. The modelled estimates of fire plume injection heights were found to be too high, with serious implications for modelled aerosol vertical distribution, transport and impacts on local climate. A modified emission scenario was developed which improved the predicted injection height. Model results were compared and evaluated against in situ measurements from the 2012 SAMBBA flight campaign.
B. Sič, L. El Amraoui, V. Marécal, B. Josse, J. Arteta, J. Guth, M. Joly, and P. D. Hamer
Geosci. Model Dev., 8, 381–408, https://doi.org/10.5194/gmd-8-381-2015, https://doi.org/10.5194/gmd-8-381-2015, 2015
M. M. Bela, K. M. Longo, S. R. Freitas, D. S. Moreira, V. Beck, S. C. Wofsy, C. Gerbig, K. Wiedemann, M. O. Andreae, and P. Artaxo
Atmos. Chem. Phys., 15, 757–782, https://doi.org/10.5194/acp-15-757-2015, https://doi.org/10.5194/acp-15-757-2015, 2015
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In the Amazon Basin, gases that lead to the formation of ozone (O3), an air pollutant and greenhouse gas, are emitted from fire, urban and biogenic sources. This study presents the first basin wide aircraft measurements of O3 during the dry-to-wet and wet-to-dry transition seasons, which show extremely low values above undisturbed forest and increases from fires. This work also demonstrates the capabilities and limitations of regional atmospheric chemistry models in representing O3 in Amazonia.
J. Brito, L. V. Rizzo, W. T. Morgan, H. Coe, B. Johnson, J. Haywood, K. Longo, S. Freitas, M. O. Andreae, and P. Artaxo
Atmos. Chem. Phys., 14, 12069–12083, https://doi.org/10.5194/acp-14-12069-2014, https://doi.org/10.5194/acp-14-12069-2014, 2014
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This paper details the physical--chemical characteristics of aerosols in a region strongly impacted by biomass burning in the western part of the Brazilian Amazon region. For such, a large suite of state-of-the-art instruments for realtime analysis was deployed at a ground site. Among the key findings, we observe the strong prevalence of organic aerosols associated to fire emissions, with important climate effects, and indications of its very fast processing in the atmosphere.
T. J. Roberts, L. Jourdain, P. T. Griffiths, and M. Pirre
Atmos. Chem. Phys., 14, 11185–11199, https://doi.org/10.5194/acp-14-11185-2014, https://doi.org/10.5194/acp-14-11185-2014, 2014
J. R. Rozante, D. S. Moreira, R. C. M. Godoy, and A. A. Fernandes
Geosci. Model Dev., 7, 2333–2343, https://doi.org/10.5194/gmd-7-2333-2014, https://doi.org/10.5194/gmd-7-2333-2014, 2014
G. A. Grell and S. R. Freitas
Atmos. Chem. Phys., 14, 5233–5250, https://doi.org/10.5194/acp-14-5233-2014, https://doi.org/10.5194/acp-14-5233-2014, 2014
L. Grellier, V. Marécal, B. Josse, P. D. Hamer, T. J. Roberts, A. Aiuppa, and M. Pirre
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmdd-7-2581-2014, https://doi.org/10.5194/gmdd-7-2581-2014, 2014
Revised manuscript not accepted
R. Hossaini, H. Mantle, M. P. Chipperfield, S. A. Montzka, P. Hamer, F. Ziska, B. Quack, K. Krüger, S. Tegtmeier, E. Atlas, S. Sala, A. Engel, H. Bönisch, T. Keber, D. Oram, G. Mills, C. Ordóñez, A. Saiz-Lopez, N. Warwick, Q. Liang, W. Feng, F. Moore, B. R. Miller, V. Marécal, N. A. D. Richards, M. Dorf, and K. Pfeilsticker
Atmos. Chem. Phys., 13, 11819–11838, https://doi.org/10.5194/acp-13-11819-2013, https://doi.org/10.5194/acp-13-11819-2013, 2013
A. F. dos Santos, S. R. Freitas, J. G. Z. de Mattos, H. F. de Campos Velho, M. A. Gan, E. F. P. da Luz, and G. A. Grell
Adv. Geosci., 35, 123–136, https://doi.org/10.5194/adgeo-35-123-2013, https://doi.org/10.5194/adgeo-35-123-2013, 2013
D. S. Moreira, S. R. Freitas, J. P. Bonatti, L. M. Mercado, N. M. É. Rosário, K. M. Longo, J. B. Miller, M. Gloor, and L. V. Gatti
Geosci. Model Dev., 6, 1243–1259, https://doi.org/10.5194/gmd-6-1243-2013, https://doi.org/10.5194/gmd-6-1243-2013, 2013
V. Beck, C. Gerbig, T. Koch, M. M. Bela, K. M. Longo, S. R. Freitas, J. O. Kaplan, C. Prigent, P. Bergamaschi, and M. Heimann
Atmos. Chem. Phys., 13, 7961–7982, https://doi.org/10.5194/acp-13-7961-2013, https://doi.org/10.5194/acp-13-7961-2013, 2013
P. D. Hamer, V. Marécal, R. Hossaini, M. Pirre, N. Warwick, M. Chipperfield, A. A. Samah, N. Harris, A. Robinson, B. Quack, A. Engel, K. Krüger, E. Atlas, K. Subramaniam, D. Oram, Emma C. Leedham Elvidge, G. Mills, K. Pfeilsticker, S. Sala, T. Keber, H. Bönisch, L. K. Peng, M. S. M. Nadzir, P. T. Lim, A. Mujahid, A. Anton, H. Schlager, V. Catoire, G. Krysztofiak, S. Fühlbrügge, M. Dorf, and W. T. Sturges
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-13-20611-2013, https://doi.org/10.5194/acpd-13-20611-2013, 2013
Revised manuscript not accepted
M. Stuefer, S. R. Freitas, G. Grell, P. Webley, S. Peckham, S. A. McKeen, and S. D. Egan
Geosci. Model Dev., 6, 457–468, https://doi.org/10.5194/gmd-6-457-2013, https://doi.org/10.5194/gmd-6-457-2013, 2013
N. E. Rosário, K. M. Longo, S. R. Freitas, M. A. Yamasoe, and R. M. Fonseca
Atmos. Chem. Phys., 13, 2923–2938, https://doi.org/10.5194/acp-13-2923-2013, https://doi.org/10.5194/acp-13-2923-2013, 2013
S. Strada, S. R. Freitas, C. Mari, K. M. Longo, and R. Paugam
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmdd-6-721-2013, https://doi.org/10.5194/gmdd-6-721-2013, 2013
Preprint withdrawn
G. Lacressonnière, V.-H. Peuch, J. Arteta, B. Josse, M. Joly, V. Marécal, D. Saint Martin, M. Déqué, and L. Watson
Geosci. Model Dev., 5, 1565–1587, https://doi.org/10.5194/gmd-5-1565-2012, https://doi.org/10.5194/gmd-5-1565-2012, 2012
Related subject area
Atmospheric sciences
Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes
Exploring a high-level programming model for the NWP domain using ECMWF microphysics schemes
Quantifying uncertainties in satellite NO2 superobservations for data assimilation and model evaluation
ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool
Coupling the urban canopy model TEB (SURFEXv9.0) with the radiation model SPARTACUS-Urbanv0.6.1 for more realistic urban radiative exchange calculation
Forecasting contrail climate forcing for flight planning and air traffic management applications: the CocipGrid model in pycontrails 0.51.0
Simulation of the heat mitigation potential of unsealing measures in cities by parameterizing grass grid pavers for urban microclimate modelling with ENVI-met (V5)
AI-NAOS: an AI-based nonspherical aerosol optical scheme for the chemical weather model GRAPES_Meso5.1/CUACE
Orbital-Radar v1.0.0: a tool to transform suborbital radar observations to synthetic EarthCARE cloud radar data
The Modular and Integrated Data Assimilation System at Environment and Climate Change Canada (MIDAS v3.9.1)
Modeling of polycyclic aromatic hydrocarbons (PAHs) from global to regional scales: model development (IAP-AACM_PAH v1.0) and investigation of health risks in 2013 and 2018 in China
LIMA (v2.0): A full two-moment cloud microphysical scheme for the mesoscale non-hydrostatic model Meso-NH v5-6
SLUCM+BEM (v1.0): a simple parameterisation for dynamic anthropogenic heat and electricity consumption in WRF-Urban (v4.3.2)
NAQPMS-PDAF v2.0: a novel hybrid nonlinear data assimilation system for improved simulation of PM2.5 chemical components
Source-specific bias correction of US background and anthropogenic ozone modeled in CMAQ
Observational operator for fair model evaluation with ground NO2 measurements
Valid time shifting ensemble Kalman filter (VTS-EnKF) for dust storm forecasting
An updated parameterization of the unstable atmospheric surface layer in the Weather Research and Forecasting (WRF) modeling system
The impact of cloud microphysics and ice nucleation on Southern Ocean clouds assessed with single-column modeling and instrument simulators
An updated aerosol simulation in the Community Earth System Model (v2.1.3): dust and marine aerosol emissions and secondary organic aerosol formation
Exploring ship track spreading rates with a physics-informed Langevin particle parameterization
Do data-driven models beat numerical models in forecasting weather extremes? A comparison of IFS HRES, Pangu-Weather, and GraphCast
Development of the MPAS-CMAQ coupled system (V1.0) for multiscale global air quality modeling
Assessment of object-based indices to identify convective organization
The Global Forest Fire Emissions Prediction System version 1.0
Sensitivity Studies of Four‐Dimensional Local Ensemble Transform Kalman Filter Coupled With WRF-Chem Version 3.9.1 for Improving Particulate Matter Simulation Accuracy
Development of A Fast Radiative Transfer Model for Ground-based Microwave Radiometers (ARMS-gb v1.0): Validation and Comparison to RTTOV-gb
NEIVAv1.0: Next-generation Emissions InVentory expansion of Akagi et al. (2011) version 1.0
FLEXPART version 11: improved accuracy, efficiency, and flexibility
Challenges of high-fidelity air quality modeling in urban environments – PALM sensitivity study during stable conditions
Air quality modeling intercomparison and multiscale ensemble chain for Latin America
Recommended coupling to global meteorological fields for long-term tracer simulations with WRF-GHG
Selecting CMIP6 global climate models (GCMs) for Coordinated Regional Climate Downscaling Experiment (CORDEX) dynamical downscaling over Southeast Asia using a standardised benchmarking framework
Improved definition of prior uncertainties in CO2 and CO fossil fuel fluxes and its impact on multi-species inversion with GEOS-Chem (v12.5)
RASCAL v1.0: an open-source tool for climatological time series reconstruction and extension
Introducing graupel density prediction in Weather Research and Forecasting (WRF) double-moment 6-class (WDM6) microphysics and evaluation of the modified scheme during the ICE-POP field campaign
Enabling high-performance cloud computing for the Community Multiscale Air Quality Model (CMAQ) version 5.3.3: performance evaluation and benefits for the user community
Atmospheric-river-induced precipitation in California as simulated by the regionally refined Simple Convective Resolving E3SM Atmosphere Model (SCREAM) Version 0
Sensitivity of predicted ultrafine particle size distributions in Europe to different nucleation rate parameterizations using PMCAMx-UF v2.2
Recent improvements and maximum covariance analysis of aerosol and cloud properties in the EC-Earth3-AerChem model
GPU-HADVPPM4HIP V1.0: using the heterogeneous-compute interface for portability (HIP) to speed up the piecewise parabolic method in the CAMx (v6.10) air quality model on China's domestic GPU-like accelerator
Preliminary evaluation of the effect of electro-coalescence with conducting sphere approximation on the formation of warm cumulus clouds using SCALE-SDM version 0.2.5–2.3.0
Similarity-Based Analysis of Atmospheric Organic Compounds for Machine Learning Applications
Cell tracking -based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall
Exploring the footprint representation of microwave radiance observations in an Arctic limited-area data assimilation system
Analysis of model error in forecast errors of extended atmospheric Lorenz 05 systems and the ECMWF system
Description and validation of Vehicular Emissions from Road Traffic (VERT) 1.0, an R-based framework for estimating road transport emissions from traffic flows
Improving the EnSRF in the Community Inversion Framework: a case study with ICON-ART 2024.01
AeroMix v1.0.1: a Python package for modeling aerosol optical properties and mixing states
Impact of ITCZ width on global climate: ITCZ-MIP
Felipe Cifuentes, Henk Eskes, Enrico Dammers, Charlotte Bryan, and Folkert Boersma
Geosci. Model Dev., 18, 621–649, https://doi.org/10.5194/gmd-18-621-2025, https://doi.org/10.5194/gmd-18-621-2025, 2025
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We tested the capability of the flux divergence approach (FDA) to reproduce known NOx emissions using synthetic NO2 satellite column retrievals from high-resolution model simulations. The FDA accurately reproduced NOx emissions when column observations were limited to the boundary layer and when the variability of the NO2 lifetime, the NOx : NO2 ratio, and NO2 profile shapes were correctly modeled. This introduces strong model dependency, reducing the simplicity of the original FDA formulation.
Stefano Ubbiali, Christian Kühnlein, Christoph Schär, Linda Schlemmer, Thomas C. Schulthess, Michael Staneker, and Heini Wernli
Geosci. Model Dev., 18, 529–546, https://doi.org/10.5194/gmd-18-529-2025, https://doi.org/10.5194/gmd-18-529-2025, 2025
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We explore a high-level programming model for porting numerical weather prediction (NWP) model codes to graphics processing units (GPUs). We present a Python rewrite with the domain-specific library GT4Py (GridTools for Python) of two renowned cloud microphysics schemes and the associated tangent-linear and adjoint algorithms. We find excellent portability, competitive GPU performance, robust execution on diverse computing architectures, and enhanced code maintainability and user productivity.
Pieter Rijsdijk, Henk Eskes, Arlene Dingemans, K. Folkert Boersma, Takashi Sekiya, Kazuyuki Miyazaki, and Sander Houweling
Geosci. Model Dev., 18, 483–509, https://doi.org/10.5194/gmd-18-483-2025, https://doi.org/10.5194/gmd-18-483-2025, 2025
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Clustering high-resolution satellite observations into superobservations improves model validation and data assimilation applications. In our paper, we derive quantitative uncertainties for satellite NO2 column observations based on knowledge of the retrievals, including a detailed analysis of spatial error correlations and representativity errors. The superobservations and uncertainty estimates are tested in a global chemical data assimilation system and are found to improve the forecasts.
Dario Di Santo, Cenlin He, Fei Chen, and Lorenzo Giovannini
Geosci. Model Dev., 18, 433–459, https://doi.org/10.5194/gmd-18-433-2025, https://doi.org/10.5194/gmd-18-433-2025, 2025
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This paper presents the Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool (ML-AMPSIT), a computationally efficient tool that uses machine learning algorithms for sensitivity analysis in atmospheric models. It is tested with the Weather Research and Forecasting (WRF) model coupled with the Noah-Multiparameterization (Noah-MP) land surface model to investigate sea breeze circulation sensitivity to vegetation-related parameters.
Robert Schoetter, Robin James Hogan, Cyril Caliot, and Valéry Masson
Geosci. Model Dev., 18, 405–431, https://doi.org/10.5194/gmd-18-405-2025, https://doi.org/10.5194/gmd-18-405-2025, 2025
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Radiation is relevant to the atmospheric impact on people and infrastructure in cities as it can influence the urban heat island, building energy consumption, and human thermal comfort. A new urban radiation model, assuming a more realistic form of urban morphology, is coupled to the urban climate model Town Energy Balance (TEB). The new TEB is evaluated with a reference radiation model for a variety of urban morphologies, and an improvement in the simulated radiative observables is found.
Zebediah Engberg, Roger Teoh, Tristan Abbott, Thomas Dean, Marc E. J. Stettler, and Marc L. Shapiro
Geosci. Model Dev., 18, 253–286, https://doi.org/10.5194/gmd-18-253-2025, https://doi.org/10.5194/gmd-18-253-2025, 2025
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Contrails forming in some atmospheric conditions may persist and become strongly warming cirrus, while in other conditions may be neutral or cooling. We develop a contrail forecast model to predict contrail climate forcing for any arbitrary point in space and time and explore integration into flight planning and air traffic management. This approach enables contrail interventions to target high-probability high-climate-impact regions and reduce unintended consequences of contrail management.
Nils Eingrüber, Alina Domm, Wolfgang Korres, and Karl Schneider
Geosci. Model Dev., 18, 141–160, https://doi.org/10.5194/gmd-18-141-2025, https://doi.org/10.5194/gmd-18-141-2025, 2025
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Climate change adaptation measures like unsealings can reduce urban heat stress. As grass grid pavers have never been parameterized for microclimate model simulations with ENVI-met, a new parameterization was developed based on field measurements. To analyse the cooling potential, scenario analyses were performed for a densely developed area in Cologne. Statistically significant average cooling effects of up to −11.1 K were found for surface temperature and up to −2.9 K for 1 m air temperature.
Xuan Wang, Lei Bi, Hong Wang, Yaqiang Wang, Wei Han, Xueshun Shen, and Xiaoye Zhang
Geosci. Model Dev., 18, 117–139, https://doi.org/10.5194/gmd-18-117-2025, https://doi.org/10.5194/gmd-18-117-2025, 2025
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The Artificial-Intelligence-based Nonspherical Aerosol Optical Scheme (AI-NAOS) was developed to improve the estimation of the aerosol direct radiation effect and was coupled online with a chemical weather model. The AI-NAOS scheme considers black carbon as fractal aggregates and soil dust as super-spheroids, encapsulated with hygroscopic aerosols. Real-case simulations emphasize the necessity of accurately representing nonspherical and inhomogeneous aerosols in chemical weather models.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev., 18, 101–115, https://doi.org/10.5194/gmd-18-101-2025, https://doi.org/10.5194/gmd-18-101-2025, 2025
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The Python tool Orbital-Radar transfers suborbital radar data (ground-based, airborne, and forward-simulated numerical weather prediction model) into synthetic spaceborne cloud profiling radar data, mimicking platform-specific instrument characteristics, e.g. EarthCARE or CloudSat. The tool's novelty lies in simulating characteristic errors and instrument noise. Thus, existing data sets are transferred into synthetic observations and can be used for satellite calibration–validation studies.
Mark Buehner, Jean-Francois Caron, Ervig Lapalme, Alain Caya, Ping Du, Yves Rochon, Sergey Skachko, Maziar Bani Shahabadi, Sylvain Heilliette, Martin Deshaies-Jacques, Weiguang Chang, and Michael Sitwell
Geosci. Model Dev., 18, 1–18, https://doi.org/10.5194/gmd-18-1-2025, https://doi.org/10.5194/gmd-18-1-2025, 2025
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The Modular and Integrated Data Assimilation System (MIDAS) software is described. The flexible design of MIDAS enables both deterministic and ensemble prediction applications for the atmosphere and several other Earth system components. It is currently used for all main operational weather prediction systems in Canada and also for sea ice and sea surface temperature analysis. The use of MIDAS for multiple Earth system components will facilitate future research on coupled data assimilation.
Zichen Wu, Xueshun Chen, Zifa Wang, Huansheng Chen, Zhe Wang, Qing Mu, Lin Wu, Wending Wang, Xiao Tang, Jie Li, Ying Li, Qizhong Wu, Yang Wang, Zhiyin Zou, and Zijian Jiang
Geosci. Model Dev., 17, 8885–8907, https://doi.org/10.5194/gmd-17-8885-2024, https://doi.org/10.5194/gmd-17-8885-2024, 2024
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We developed a model to simulate polycyclic aromatic hydrocarbons (PAHs) from global to regional scales. The model can reproduce PAH distribution well. The concentration of BaP (indicator species for PAHs) could exceed the target values of 1 ng m-3 over some areas (e.g., in central Europe, India, and eastern China). The change in BaP is lower than that in PM2.5 from 2013 to 2018. China still faces significant potential health risks posed by BaP although the Action Plan has been implemented.
Marie Taufour, Jean-Pierre Pinty, Christelle Barthe, Benoît Vié, and Chien Wang
Geosci. Model Dev., 17, 8773–8798, https://doi.org/10.5194/gmd-17-8773-2024, https://doi.org/10.5194/gmd-17-8773-2024, 2024
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We have developed a complete two-moment version of the LIMA (Liquid Ice Multiple Aerosols) microphysics scheme. We have focused on collection processes, where the hydrometeor number transfer is often estimated in proportion to the mass transfer. The impact of these parameterizations on a convective system and the prospects for more realistic estimates of secondary parameters (reflectivity, hydrometeor size) are shown in a first test on an idealized case.
Yuya Takane, Yukihiro Kikegawa, Ko Nakajima, and Hiroyuki Kusaka
Geosci. Model Dev., 17, 8639–8664, https://doi.org/10.5194/gmd-17-8639-2024, https://doi.org/10.5194/gmd-17-8639-2024, 2024
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A new parameterisation for dynamic anthropogenic heat and electricity consumption is described. The model reproduced the temporal variation in and spatial distributions of electricity consumption and temperature well in summer and winter. The partial air conditioning was the most critical factor, significantly affecting the value of anthropogenic heat emission.
Hongyi Li, Ting Yang, Lars Nerger, Dawei Zhang, Di Zhang, Guigang Tang, Haibo Wang, Yele Sun, Pingqing Fu, Hang Su, and Zifa Wang
Geosci. Model Dev., 17, 8495–8519, https://doi.org/10.5194/gmd-17-8495-2024, https://doi.org/10.5194/gmd-17-8495-2024, 2024
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To accurately characterize the spatiotemporal distribution of particulate matter <2.5 µm chemical components, we developed the Nested Air Quality Prediction Model System with the Parallel Data Assimilation Framework (NAQPMS-PDAF) v2.0 for chemical components with non-Gaussian and nonlinear properties. NAQPMS-PDAF v2.0 has better computing efficiency, excels when used with a small ensemble size, and can significantly improve the simulation performance of chemical components.
T. Nash Skipper, Christian Hogrefe, Barron H. Henderson, Rohit Mathur, Kristen M. Foley, and Armistead G. Russell
Geosci. Model Dev., 17, 8373–8397, https://doi.org/10.5194/gmd-17-8373-2024, https://doi.org/10.5194/gmd-17-8373-2024, 2024
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Chemical transport model simulations are combined with ozone observations to estimate the bias in ozone attributable to US anthropogenic sources and individual sources of US background ozone: natural sources, non-US anthropogenic sources, and stratospheric ozone. Results indicate a positive bias correlated with US anthropogenic emissions during summer in the eastern US and a negative bias correlated with stratospheric ozone during spring.
Li Fang, Jianbing Jin, Arjo Segers, Ke Li, Ji Xia, Wei Han, Baojie Li, Hai Xiang Lin, Lei Zhu, Song Liu, and Hong Liao
Geosci. Model Dev., 17, 8267–8282, https://doi.org/10.5194/gmd-17-8267-2024, https://doi.org/10.5194/gmd-17-8267-2024, 2024
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Model evaluations against ground observations are usually unfair. The former simulates mean status over coarse grids and the latter the surrounding atmosphere. To solve this, we proposed the new land-use-based representative (LUBR) operator that considers intra-grid variance. The LUBR operator is validated to provide insights that align with satellite measurements. The results highlight the importance of considering fine-scale urban–rural differences when comparing models and observation.
Mijie Pang, Jianbing Jin, Arjo Segers, Huiya Jiang, Wei Han, Batjargal Buyantogtokh, Ji Xia, Li Fang, Jiandong Li, Hai Xiang Lin, and Hong Liao
Geosci. Model Dev., 17, 8223–8242, https://doi.org/10.5194/gmd-17-8223-2024, https://doi.org/10.5194/gmd-17-8223-2024, 2024
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The ensemble Kalman filter (EnKF) improves dust storm forecasts but faces challenges with position errors. The valid time shifting EnKF (VTS-EnKF) addresses this by adjusting for position errors, enhancing accuracy in forecasting dust storms, as proven in tests on 2021 events, even with smaller ensembles and time intervals.
Prabhakar Namdev, Maithili Sharan, Piyush Srivastava, and Saroj Kanta Mishra
Geosci. Model Dev., 17, 8093–8114, https://doi.org/10.5194/gmd-17-8093-2024, https://doi.org/10.5194/gmd-17-8093-2024, 2024
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Inadequate representation of surface–atmosphere interaction processes is a major source of uncertainty in numerical weather prediction models. Here, an effort has been made to improve the Weather Research and Forecasting (WRF) model version 4.2.2 by introducing a unique theoretical framework under convective conditions. In addition, to enhance the potential applicability of the WRF modeling system, various commonly used similarity functions under convective conditions have also been installed.
Andrew Gettelman, Richard Forbes, Roger Marchand, Chih-Chieh Chen, and Mark Fielding
Geosci. Model Dev., 17, 8069–8092, https://doi.org/10.5194/gmd-17-8069-2024, https://doi.org/10.5194/gmd-17-8069-2024, 2024
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Supercooled liquid clouds (liquid clouds colder than 0°C) are common at higher latitudes (especially over the Southern Ocean) and are critical for constraining climate projections. We compare a single-column version of a weather model to observations with two different cloud schemes and find that both the dynamical environment and atmospheric aerosols are important for reproducing observations.
Yujuan Wang, Peng Zhang, Jie Li, Yaman Liu, Yanxu Zhang, Jiawei Li, and Zhiwei Han
Geosci. Model Dev., 17, 7995–8021, https://doi.org/10.5194/gmd-17-7995-2024, https://doi.org/10.5194/gmd-17-7995-2024, 2024
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This study updates the CESM's aerosol schemes, focusing on dust, marine aerosol emissions, and secondary organic aerosol (SOA) . Dust emission modifications make deflation areas more continuous, improving results in North America and the sub-Arctic. Humidity correction to sea-salt emissions has a minor effect. Introducing marine organic aerosol emissions, coupled with ocean biogeochemical processes, and adding aqueous reactions for SOA formation advance the CESM's aerosol modelling results.
Lucas A. McMichael, Michael J. Schmidt, Robert Wood, Peter N. Blossey, and Lekha Patel
Geosci. Model Dev., 17, 7867–7888, https://doi.org/10.5194/gmd-17-7867-2024, https://doi.org/10.5194/gmd-17-7867-2024, 2024
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Marine cloud brightening (MCB) is a climate intervention technique to potentially cool the climate. Climate models used to gauge regional climate impacts associated with MCB often assume large areas of the ocean are uniformly perturbed. However, a more realistic representation of MCB application would require information about how an injected particle plume spreads. This work aims to develop such a plume-spreading model.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 7915–7962, https://doi.org/10.5194/gmd-17-7915-2024, https://doi.org/10.5194/gmd-17-7915-2024, 2024
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Data-driven models are becoming a viable alternative to physics-based models for weather forecasting up to 15 d into the future. However, it is unclear whether they are as reliable as physics-based models when forecasting weather extremes. We evaluate their performance in forecasting near-surface cold, hot, and windy extremes globally. We find that data-driven models can compete with physics-based models and that the choice of the best model mainly depends on the region and type of extreme.
David C. Wong, Jeff Willison, Jonathan E. Pleim, Golam Sarwar, James Beidler, Russ Bullock, Jerold A. Herwehe, Rob Gilliam, Daiwen Kang, Christian Hogrefe, George Pouliot, and Hosein Foroutan
Geosci. Model Dev., 17, 7855–7866, https://doi.org/10.5194/gmd-17-7855-2024, https://doi.org/10.5194/gmd-17-7855-2024, 2024
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This work describe how we linked the meteorological Model for Prediction Across Scales – Atmosphere (MPAS-A) with the Community Multiscale Air Quality (CMAQ) air quality model to form a coupled modelling system. This could be used to study air quality or climate and air quality interaction at a global scale. This new model scales well in high-performance computing environments and performs well with respect to ground surface networks in terms of ozone and PM2.5.
Giulio Mandorli and Claudia J. Stubenrauch
Geosci. Model Dev., 17, 7795–7813, https://doi.org/10.5194/gmd-17-7795-2024, https://doi.org/10.5194/gmd-17-7795-2024, 2024
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In recent years, several studies focused their attention on the disposition of convection. Lots of methods, called indices, have been developed to quantify the amount of convection clustering. These indices are evaluated in this study by defining criteria that must be satisfied and then evaluating the indices against these standards. None of the indices meet all criteria, with some only partially meeting them.
Kerry Anderson, Jack Chen, Peter Englefield, Debora Griffin, Paul A. Makar, and Dan Thompson
Geosci. Model Dev., 17, 7713–7749, https://doi.org/10.5194/gmd-17-7713-2024, https://doi.org/10.5194/gmd-17-7713-2024, 2024
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The Global Forest Fire Emissions Prediction System (GFFEPS) is a model that predicts smoke and carbon emissions from wildland fires. The model calculates emissions from the ground up based on satellite-detected fires, modelled weather and fire characteristics. Unlike other global models, GFFEPS uses daily weather conditions to capture changing burning conditions on a day-to-day basis. GFFEPS produced lower carbon emissions due to the changing weather not captured by the other models.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
EGUsphere, https://doi.org/10.5194/egusphere-2024-3321, https://doi.org/10.5194/egusphere-2024-3321, 2024
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The effectiveness of assimilation system and its sensitivity to ensemble member size and length of assimilation window have been investigated. This study advances our understanding about the selection of basic parameters in the four-dimension local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate matter polluted environment.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
EGUsphere, https://doi.org/10.5194/egusphere-2024-2884, https://doi.org/10.5194/egusphere-2024-2884, 2024
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Assimilating Ground-based microwave radiometers' observations into numerical weather prediction models holds significant promise for enhancing forecast accuracy. Radiative transfer models (RTM) are crucial for direct data assimilation. We propose a new RTM capable of simulating brightness temperatures observed by GMRs and their Jacobians. Several improvements are introduced to achieve higher accuracy.The RTM align with RTTOV-gb well and can achieve smaller STD in water vapor absorption channels.
Samiha Binte Shahid, Forrest G. Lacey, Christine Wiedinmyer, Robert J. Yokelson, and Kelley C. Barsanti
Geosci. Model Dev., 17, 7679–7711, https://doi.org/10.5194/gmd-17-7679-2024, https://doi.org/10.5194/gmd-17-7679-2024, 2024
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The Next-generation Emissions InVentory expansion of Akagi (NEIVA) v.1.0 is a comprehensive biomass burning emissions database that allows integration of new data and flexible querying. Data are stored in connected datasets, including recommended averages of ~1500 constituents for 14 globally relevant fire types. Individual compounds were mapped to common model species to allow better attribution of emissions in modeling studies that predict the effects of fires on air quality and climate.
Lucie Bakels, Daria Tatsii, Anne Tipka, Rona Thompson, Marina Dütsch, Michael Blaschek, Petra Seibert, Katharina Baier, Silvia Bucci, Massimo Cassiani, Sabine Eckhardt, Christine Groot Zwaaftink, Stephan Henne, Pirmin Kaufmann, Vincent Lechner, Christian Maurer, Marie D. Mulder, Ignacio Pisso, Andreas Plach, Rakesh Subramanian, Martin Vojta, and Andreas Stohl
Geosci. Model Dev., 17, 7595–7627, https://doi.org/10.5194/gmd-17-7595-2024, https://doi.org/10.5194/gmd-17-7595-2024, 2024
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Computer models are essential for improving our understanding of how gases and particles move in the atmosphere. We present an update of the atmospheric transport model FLEXPART. FLEXPART 11 is more accurate due to a reduced number of interpolations and a new scheme for wet deposition. It can simulate non-spherical aerosols and includes linear chemical reactions. It is parallelised using OpenMP and includes new user options. A new user manual details how to use FLEXPART 11.
Jaroslav Resler, Petra Bauerová, Michal Belda, Martin Bureš, Kryštof Eben, Vladimír Fuka, Jan Geletič, Radek Jareš, Jan Karel, Josef Keder, Pavel Krč, William Patiño, Jelena Radović, Hynek Řezníček, Matthias Sühring, Adriana Šindelářová, and Ondřej Vlček
Geosci. Model Dev., 17, 7513–7537, https://doi.org/10.5194/gmd-17-7513-2024, https://doi.org/10.5194/gmd-17-7513-2024, 2024
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Detailed modeling of urban air quality in stable conditions is a challenge. We show the unprecedented sensitivity of a large eddy simulation (LES) model to meteorological boundary conditions and model parameters in an urban environment under stable conditions. We demonstrate the crucial role of boundary conditions for the comparability of results with observations. The study reveals a strong sensitivity of the results to model parameters and model numerical instabilities during such conditions.
Jorge E. Pachón, Mariel A. Opazo, Pablo Lichtig, Nicolas Huneeus, Idir Bouarar, Guy Brasseur, Cathy W. Y. Li, Johannes Flemming, Laurent Menut, Camilo Menares, Laura Gallardo, Michael Gauss, Mikhail Sofiev, Rostislav Kouznetsov, Julia Palamarchuk, Andreas Uppstu, Laura Dawidowski, Nestor Y. Rojas, María de Fátima Andrade, Mario E. Gavidia-Calderón, Alejandro H. Delgado Peralta, and Daniel Schuch
Geosci. Model Dev., 17, 7467–7512, https://doi.org/10.5194/gmd-17-7467-2024, https://doi.org/10.5194/gmd-17-7467-2024, 2024
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Latin America (LAC) has some of the most populated urban areas in the world, with high levels of air pollution. Air quality management in LAC has been traditionally focused on surveillance and building emission inventories. This study performed the first intercomparison and model evaluation in LAC, with interesting and insightful findings for the region. A multiscale modeling ensemble chain was assembled as a first step towards an air quality forecasting system.
David Ho, Michał Gałkowski, Friedemann Reum, Santiago Botía, Julia Marshall, Kai Uwe Totsche, and Christoph Gerbig
Geosci. Model Dev., 17, 7401–7422, https://doi.org/10.5194/gmd-17-7401-2024, https://doi.org/10.5194/gmd-17-7401-2024, 2024
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Atmospheric model users often overlook the impact of the land–atmosphere interaction. This study accessed various setups of WRF-GHG simulations that ensure consistency between the model and driving reanalysis fields. We found that a combination of nudging and frequent re-initialization allows certain improvement by constraining the soil moisture fields and, through its impact on atmospheric mixing, improves atmospheric transport.
Phuong Loan Nguyen, Lisa V. Alexander, Marcus J. Thatcher, Son C. H. Truong, Rachael N. Isphording, and John L. McGregor
Geosci. Model Dev., 17, 7285–7315, https://doi.org/10.5194/gmd-17-7285-2024, https://doi.org/10.5194/gmd-17-7285-2024, 2024
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We use a comprehensive approach to select a subset of CMIP6 models for dynamical downscaling over Southeast Asia, taking into account model performance, model independence, data availability and the range of future climate projections. The standardised benchmarking framework is applied to assess model performance through both statistical and process-based metrics. Ultimately, we identify two independent model groups that are suitable for dynamical downscaling in the Southeast Asian region.
Ingrid Super, Tia Scarpelli, Arjan Droste, and Paul I. Palmer
Geosci. Model Dev., 17, 7263–7284, https://doi.org/10.5194/gmd-17-7263-2024, https://doi.org/10.5194/gmd-17-7263-2024, 2024
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Monitoring greenhouse gas emission reductions requires a combination of models and observations, as well as an initial emission estimate. Each component provides information with a certain level of certainty and is weighted to yield the most reliable estimate of actual emissions. We describe efforts for estimating the uncertainty in the initial emission estimate, which significantly impacts the outcome. Hence, a good uncertainty estimate is key for obtaining reliable information on emissions.
Álvaro González-Cervera and Luis Durán
Geosci. Model Dev., 17, 7245–7261, https://doi.org/10.5194/gmd-17-7245-2024, https://doi.org/10.5194/gmd-17-7245-2024, 2024
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RASCAL is an open-source Python tool designed for reconstructing daily climate observations, especially in regions with complex local phenomena. It merges large-scale weather patterns with local weather using the analog method. Evaluations in central Spain show that RASCAL outperforms ERA20C reanalysis in reconstructing precipitation and temperature. RASCAL offers opportunities for broad scientific applications, from short-term forecasts to local-scale climate change scenarios.
Sun-Young Park, Kyo-Sun Sunny Lim, Kwonil Kim, Gyuwon Lee, and Jason A. Milbrandt
Geosci. Model Dev., 17, 7199–7218, https://doi.org/10.5194/gmd-17-7199-2024, https://doi.org/10.5194/gmd-17-7199-2024, 2024
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We enhance the WDM6 scheme by incorporating predicted graupel density. The modification affects graupel characteristics, including fall velocity–diameter and mass–diameter relationships. Simulations highlight changes in graupel distribution and precipitation patterns, potentially influencing surface snow amounts. The study underscores the significance of integrating predicted graupel density for a more realistic portrayal of microphysical properties in weather models.
Christos I. Efstathiou, Elizabeth Adams, Carlie J. Coats, Robert Zelt, Mark Reed, John McGee, Kristen M. Foley, Fahim I. Sidi, David C. Wong, Steven Fine, and Saravanan Arunachalam
Geosci. Model Dev., 17, 7001–7027, https://doi.org/10.5194/gmd-17-7001-2024, https://doi.org/10.5194/gmd-17-7001-2024, 2024
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We present a summary of enabling high-performance computing of the Community Multiscale Air Quality Model (CMAQ) – a state-of-the-science community multiscale air quality model – on two cloud computing platforms through documenting the technologies, model performance, scaling and relative merits. This may be a new paradigm for computationally intense future model applications. We initiated this work due to a need to leverage cloud computing advances and to ease the learning curve for new users.
Peter A. Bogenschutz, Jishi Zhang, Qi Tang, and Philip Cameron-Smith
Geosci. Model Dev., 17, 7029–7050, https://doi.org/10.5194/gmd-17-7029-2024, https://doi.org/10.5194/gmd-17-7029-2024, 2024
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Using high-resolution and state-of-the-art modeling techniques we simulate five atmospheric river events for California to test the capability to represent precipitation for these events. We find that our model is able to capture the distribution of precipitation very well but suffers from overestimating the precipitation amounts over high elevation. Increasing the resolution further has no impact on reducing this bias, while increasing the domain size does have modest impacts.
David Patoulias, Kalliopi Florou, and Spyros N. Pandis
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-145, https://doi.org/10.5194/gmd-2024-145, 2024
Revised manuscript accepted for GMD
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The effect of the assumed atmospheric nucleation mechanism on particle number concentrations and size distribution was investigated. Two quite different mechanisms involving sulfuric acid and ammonia or a biogenic organic vapor gave quite similar results which were consistent with measurements in 26 measurement stations across Europe. The number of larger particles that serve as cloud condensation nuclei showed little sensitivity to the assumed nucleation mechanism.
Manu Anna Thomas, Klaus Wyser, Shiyu Wang, Marios Chatziparaschos, Paraskevi Georgakaki, Montserrat Costa-Surós, Maria Gonçalves Ageitos, Maria Kanakidou, Carlos Pérez García-Pando, Athanasios Nenes, Twan van Noije, Philippe Le Sager, and Abhay Devasthale
Geosci. Model Dev., 17, 6903–6927, https://doi.org/10.5194/gmd-17-6903-2024, https://doi.org/10.5194/gmd-17-6903-2024, 2024
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Aerosol–cloud interactions occur at a range of spatio-temporal scales. While evaluating recent developments in EC-Earth3-AerChem, this study aims to understand the extent to which the Twomey effect manifests itself at larger scales. We find a reduction in the warm bias over the Southern Ocean due to model improvements. While we see footprints of the Twomey effect at larger scales, the negative relationship between cloud droplet number and liquid water drives the shortwave radiative effect.
Kai Cao, Qizhong Wu, Lingling Wang, Hengliang Guo, Nan Wang, Huaqiong Cheng, Xiao Tang, Dongxing Li, Lina Liu, Dongqing Li, Hao Wu, and Lanning Wang
Geosci. Model Dev., 17, 6887–6901, https://doi.org/10.5194/gmd-17-6887-2024, https://doi.org/10.5194/gmd-17-6887-2024, 2024
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AMD’s heterogeneous-compute interface for portability was implemented to port the piecewise parabolic method solver from NVIDIA GPUs to China's GPU-like accelerators. The results show that the larger the model scale, the more acceleration effect on the GPU-like accelerator, up to 28.9 times. The multi-level parallelism achieves a speedup of 32.7 times on the heterogeneous cluster. By comparing the results, the GPU-like accelerators have more accuracy for the geoscience numerical models.
Ruyi Zhang, Limin Zhou, Shin-ichiro Shima, and Huawei Yang
Geosci. Model Dev., 17, 6761–6774, https://doi.org/10.5194/gmd-17-6761-2024, https://doi.org/10.5194/gmd-17-6761-2024, 2024
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Solar activity weakly ionises Earth's atmosphere, charging cloud droplets. Electro-coalescence is when oppositely charged droplets stick together. We introduce an analytical expression of electro-coalescence probability and use it in a warm-cumulus-cloud simulation. Results show that charge cases increase rain and droplet size, with the new method outperforming older ones. The new method requires longer computation time, but its impact on rain justifies inclusion in meteorology models.
Hilda Sandström and Patrick Rinke
EGUsphere, https://doi.org/10.48550/arXiv.2406.18171, https://doi.org/10.48550/arXiv.2406.18171, 2024
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Machine learning has the potential to aid the identification organic molecules involved in aerosol formation. Yet, progress is stalled by a lack of curated atmospheric molecular datasets. Here, we compared atmospheric compounds with large molecular datasets used in machine learning and found minimal overlap with similarity algorithms. Our result underlines the need for collaborative efforts to curate atmospheric molecular data to facilitate machine learning model in atmospheric sciences.
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-99, https://doi.org/10.5194/gmd-2024-99, 2024
Revised manuscript accepted for GMD
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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 rainfall. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and then the model skill is evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with 4 open-source models.
Máté Mile, Stephanie Guedj, and Roger Randriamampianina
Geosci. Model Dev., 17, 6571–6587, https://doi.org/10.5194/gmd-17-6571-2024, https://doi.org/10.5194/gmd-17-6571-2024, 2024
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Satellite observations provide crucial information about atmospheric constituents in a global distribution that helps to better predict the weather over sparsely observed regions like the Arctic. However, the use of satellite data is usually conservative and imperfect. In this study, a better spatial representation of satellite observations is discussed and explored by a so-called footprint function or operator, highlighting its added value through a case study and diagnostics.
Hynek Bednář and Holger Kantz
Geosci. Model Dev., 17, 6489–6511, https://doi.org/10.5194/gmd-17-6489-2024, https://doi.org/10.5194/gmd-17-6489-2024, 2024
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The forecast error growth of atmospheric phenomena is caused by initial and model errors. When studying the initial error growth, it may turn out that small-scale phenomena, which contribute little to the forecast product, significantly affect the ability to predict this product. With a negative result, we investigate in the extended Lorenz (2005) system whether omitting these phenomena will improve predictability. A theory explaining and describing this behavior is developed.
Giorgio Veratti, Alessandro Bigi, Sergio Teggi, and Grazia Ghermandi
Geosci. Model Dev., 17, 6465–6487, https://doi.org/10.5194/gmd-17-6465-2024, https://doi.org/10.5194/gmd-17-6465-2024, 2024
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In this study, we present VERT (Vehicular Emissions from Road Traffic), an R package designed to estimate transport emissions using traffic estimates and vehicle fleet composition data. Compared to other tools available in the literature, VERT stands out for its user-friendly configuration and flexibility of user input. Case studies demonstrate its accuracy in both urban and regional contexts, making it a valuable tool for air quality management and transport scenario planning.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
EGUsphere, https://doi.org/10.5194/egusphere-2024-2197, https://doi.org/10.5194/egusphere-2024-2197, 2024
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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 more efficient implementation of the serial and batch versions of the Ensemble Square Root Filter (EnSRF) algorithm in CIF.
Sam P. Raj, Puna Ram Sinha, Rohit Srivastava, Srinivas Bikkina, and Damu Bala Subrahamanyam
Geosci. Model Dev., 17, 6379–6399, https://doi.org/10.5194/gmd-17-6379-2024, https://doi.org/10.5194/gmd-17-6379-2024, 2024
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A Python successor to the aerosol module of the OPAC model, named AeroMix, has been developed, with enhanced capabilities to better represent real atmospheric aerosol mixing scenarios. AeroMix’s performance in modeling aerosol mixing states has been evaluated against field measurements, substantiating its potential as a versatile aerosol optical model framework for next-generation algorithms to infer aerosol mixing states and chemical composition.
Angeline G. Pendergrass, Michael P. Byrne, Oliver Watt-Meyer, Penelope Maher, and Mark J. Webb
Geosci. Model Dev., 17, 6365–6378, https://doi.org/10.5194/gmd-17-6365-2024, https://doi.org/10.5194/gmd-17-6365-2024, 2024
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The width of the tropical rain belt affects many aspects of our climate, yet we do not understand what controls it. To better understand it, we present a method to change it in numerical model experiments. We show that the method works well in four different models. The behavior of the width is unexpectedly simple in some ways, such as how strong the winds are as it changes, but in other ways, it is more complicated, especially how temperature increases with carbon dioxide.
Cited articles
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Alonso, M. F.: Previsão de Tempo Químico para a América do Sul: Impácto das Emissões Urbanas nas Escalas Local e Regional, Ph.D. thesis, Instituto Nacional de Pesquisas Espaciais, São José dos Campos, Brazil, 188 pp., available at: http://urlib.net/8JMKD3MGP8W/39R4K92, last access: 27 August 2013, 2011 (in Portuguese).
Andreae, M. O., Artaxo, P., Beck, V., Bela, M., Freitas, S., Gerbig, C., Longo, K., Munger, J. W., Wiedemann, K. T., and Wofsy, S. C.: Carbon monoxide and related trace gases and aerosols over the Amazon Basin during the wet and dry seasons, Atmos. Chem. Phys., 12, 6041–6065, https://doi.org/10.5194/acp-12-6041-2012, 2012.
Hernández, R. A. A.: Implementación del Modelo CCATT-BRAMS sobre la Zona Central de Chile y su Evaluación, MSc. Dissertation, Departamento de Geofísica, Universidad de Chile, available at: http://www.captura.uchile.cl/handle/2250/106744, last access: 27 August 2013, 2010 (in Spanish).
Arteta, J., Cautenet, S., Taghavi, M., and Audiffren, N.: Impact of two chemistry mechanisms fully coupled with mesoscale model on the atmospheric pollutants distribution, Atmos. Environ., 40, 7983–8001, 2006.
Arteta, J., Marécal, V., and Rivière, E. D.: Regional modelling of tracer transport by tropical convection – Part 1: Sensitivity to convection parameterization, Atmos. Chem. Phys., 9, 7081–7100, https://doi.org/10.5194/acp-9-7081-2009, 2009a.
Arteta, J., Marécal, V., and Rivière, E. D.: Regional modelling of tracer transport by tropical convection – Part 2: Sensitivity to model resolutions, Atmos. Chem. Phys., 9, 7101–7114, https://doi.org/10.5194/acp-9-7101-2009, 2009b.
Barth, M. C., Stuart, A. L., and Skamarock, W. C.: Numerical simulations of the July 10, 1996, Stratospheric-Tropospheric Experiment: Radiation, Aerosols, and Ozone (STERAO)-Deep Convection experiment storm: Redistribution of soluble tracers, J. Geophys. Res., 106, 12381–12400, 2001.
Barth, M. C., Kim, S.-W., Skamarock, W. C., Stuart, A. L., Pickering, K. E., and Ott, L. E.: Simulations of the redistribution of formaldehyde, formic acid, and peroxides in the July 10, 1996 STERAO deep convection strom, J. Goephys. Res., 112, D13310, https://doi.org/10.1029/2006JD008046, 2007a.
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Beck, V., Koch, T., Kretschmer, R., Marshall, J., Ahmadov, R., Gerbig, C., Pillai, D., and Heimann, M.: The WRF Greenhouse Gas Model (WRF-GHG), Technical Report No. 25, Max Planck Institute for Biogeochemistry, Jena, Germany, 2011.
Beck, V., Chen, H., Gerbig, C., Bergamaschi, P., Bruhwiler, L., Houweling, S., Röckmann, T., Kolle, O., Steinbach, J., Koch, T., Sapart, C. J., van der Veen, C., Frankenberg, C., Andreae, M. O., Artaxo, P., Longo, K. M., and Wofsy, S. C.: Methane airborne measurements and comparison to global models during BARCA, J. Geophys. Res., 117, D15310, https://doi.org/10.1029/2011JD017345, 2012.
Bela, M. M., Longo, K. M., Freitas, S. R., Moreira, D., Beck, V., Wofsy, S. C., Gerbig, C., Wiedemann, K., Artaxo, P., and Andreae, M. O.: Ozone Production and Transport over the Amazon Basin During Wet and Dry Season Transitions, in preparation, Atmos. Chem. Phys., 2013.
Berge, E.: Coupling of wet scavenging of sulphur to clouds in a numerical weather prediction model, Tellus B, 45, 1–22,1993.
Best, M. J., Pryor, M., Clark, D. B., Rooney, G. G., Essery, R .L. H., Ménard, C. B., Edwards, J. M., Hendry, M. A., Porson, A., Gedney, N., Mercado, L. M., Sitch, S., Blyth, E., Boucher, O., Cox, P. M., Grimmond, C. S. B., and Harding, R. J.: The Joint UK Land Environment Simulator (JULES), model description – Part 1: Energy and water fluxes, Geosci. Model Dev., 4, 677–699, https://doi.org/10.5194/gmd-4-677-2011, 2011.
Bousserez, N., Attié, J.-L., Peuch, V.-H., Michou, M., Pfister, G., Edwards, D., Avery, M., Sachse, G., Browell, E., and Ferrare E.: Evaluation of MOCAGE chemistry and transport model during the ICARTT/ITOP experiment, J. Geophys. Res., 112, D120S42, https://doi.org/10.1029/2006JD007595, 2007.
Brian, H. and Prather, M. J.: Fast-J2: Accurate simulation of stratospheric photolysis in global chemistry models, J. Atmos. Chem., 41, 281–296, 2002.
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