Articles | Volume 12, issue 10
https://doi.org/10.5194/gmd-12-4245-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/gmd-12-4245-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development of turbulent scheme in the FLEXPART-AROME v1.2.1 Lagrangian particle dispersion model
Bert Verreyken
CORRESPONDING AUTHOR
Laboratoire de l’Atmosphère et des Cyclones, UMR 8105 CNRS, University of Réunion Island, Réunion, France
Belgian Institute for Space Aeronomy, Ringlaan 3, 1180 Brussels, Belgium
Department of Chemistry, Ghent University, Krijgslaan 281-S3, 9000 Ghent, Belgium
Jérome Brioude
Laboratoire de l’Atmosphère et des Cyclones, UMR 8105 CNRS, University of Réunion Island, Réunion, France
Stéphanie Evan
Laboratoire de l’Atmosphère et des Cyclones, UMR 8105 CNRS, University of Réunion Island, Réunion, France
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Aerosol particles in the atmosphere play a role in the climate change and in the air pollution. A large part of aerosol particles is formed from the oxidation of volatile organic compounds (secondary organic aerosols – SOA). An important field campaign was organized at Réunion Island on March–April 2019 to understand the formation of SOA in tropical atmosphere mostly influenced by VOC emitted by forest and in presence of clouds. This work syntheses results obtained from this campaign.
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The global distribution of mercury, a potent neurotoxin, depends on atmospheric transport, chemistry, and interactions between the Earth’s surface and the air. Our understanding of these processes is still hampered by insufficient observations. Here, we present new data from a mountain observatory in the Southern Hemisphere. We give insights into mercury concentrations in air masses coming from aloft, and we show that tropical mountain vegetation may be a daytime source of mercury to the air.
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Atmos. Chem. Phys., 21, 17017–17029, https://doi.org/10.5194/acp-21-17017-2021, https://doi.org/10.5194/acp-21-17017-2021, 2021
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The tropical Indian Ocean (IO) is expected to be a significant source of water-soluble organic carbon (WSOC), which is relevant to cloud formation. Our study showed that marine secondary organic formation dominantly contributed to the aerosol WSOC mass at the high-altitude observatory in the southwest IO in the wet season in both marine boundary layer and free troposphere (FT). This suggests that the effect of marine secondary sources is important up to FT, a process missing in climate models.
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Atmos. Chem. Phys., 21, 12965–12988, https://doi.org/10.5194/acp-21-12965-2021, https://doi.org/10.5194/acp-21-12965-2021, 2021
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We present a 2-year dataset of trace gas concentrations, specifically an array of volatile organic compounds (VOCs), recorded at the Maïdo observatory, a remote tropical high-altitude site located on a small island in the southwest Indian Ocean. We found that island-scale transport is an important driver for the daily cycle of VOC concentrations. During the day, surface emissions from the island affect the atmospheric composition at Maïdo greatly, while at night this impact is strongly reduced.
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Biomass burning (BB) plumes arriving at the Maïdo observatory located in the south-west Indian Ocean during August 2018 and August 2019 are studied using trace gas measurements, Lagrangian transport models and the CAMS near-real-time atmospheric composition service. We investigate (i) secondary production of volatile organic compounds during transport, (ii) efficacy of the CAMS model to reproduce the chemical makeup of BB plumes and (iii) the impact of BB on the remote marine boundary layer.
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Atmos. Chem. Phys., 24, 3785–3812, https://doi.org/10.5194/acp-24-3785-2024, https://doi.org/10.5194/acp-24-3785-2024, 2024
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Using mass spectrometry data collected at the Maïdo Observatory (2160 m a.s.l., Réunion), we provide the first detailed analysis of molecular cluster chemical composition specifically in the marine free troposphere. The abundance of the identified species is related both to in situ meteorological parameters and air mass history, which also provide insight into their origin. Our work makes an important contribution to documenting the chemistry and physics of the marine free troposphere.
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Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-531, https://doi.org/10.5194/essd-2023-531, 2024
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EGUsphere, https://doi.org/10.5194/egusphere-2023-2574, https://doi.org/10.5194/egusphere-2023-2574, 2023
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Atmos. Chem. Phys., 23, 13355–13367, https://doi.org/10.5194/acp-23-13355-2023, https://doi.org/10.5194/acp-23-13355-2023, 2023
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The 2022 Hunga Tonga eruption injected a large amount of water into the stratosphere. Ozone depletion was observed inside the volcanic plume. Chlorine and water vapor injected by this eruption exceeded the normal range, which made the ozone chemistry during this event occur at a higher temperature than polar ozone depletion. Unlike polar ozone chemistry where chlorine nitrate is more important, hypochlorous acid plays a large role in the in-plume chlorine balance and heterogeneous processes.
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Aerosol particles in the atmosphere play a role in the climate change and in the air pollution. A large part of aerosol particles is formed from the oxidation of volatile organic compounds (secondary organic aerosols – SOA). An important field campaign was organized at Réunion Island on March–April 2019 to understand the formation of SOA in tropical atmosphere mostly influenced by VOC emitted by forest and in presence of clouds. This work syntheses results obtained from this campaign.
Alkuin M. Koenig, Olivier Magand, Bert Verreyken, Jerome Brioude, Crist Amelynck, Niels Schoon, Aurélie Colomb, Beatriz Ferreira Araujo, Michel Ramonet, Mahesh K. Sha, Jean-Pierre Cammas, Jeroen E. Sonke, and Aurélien Dommergue
Atmos. Chem. Phys., 23, 1309–1328, https://doi.org/10.5194/acp-23-1309-2023, https://doi.org/10.5194/acp-23-1309-2023, 2023
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The global distribution of mercury, a potent neurotoxin, depends on atmospheric transport, chemistry, and interactions between the Earth’s surface and the air. Our understanding of these processes is still hampered by insufficient observations. Here, we present new data from a mountain observatory in the Southern Hemisphere. We give insights into mercury concentrations in air masses coming from aloft, and we show that tropical mountain vegetation may be a daytime source of mercury to the air.
Sieglinde Callewaert, Jérôme Brioude, Bavo Langerock, Valentin Duflot, Dominique Fonteyn, Jean-François Müller, Jean-Marc Metzger, Christian Hermans, Nicolas Kumps, Michel Ramonet, Morgan Lopez, Emmanuel Mahieu, and Martine De Mazière
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Andrew O. Langford, Christoph J. Senff, Raul J. Alvarez II, Ken C. Aikin, Sunil Baidar, Timothy A. Bonin, W. Alan Brewer, Jerome Brioude, Steven S. Brown, Joel D. Burley, Dani J. Caputi, Stephen A. Conley, Patrick D. Cullis, Zachary C. J. Decker, Stéphanie Evan, Guillaume Kirgis, Meiyun Lin, Mariusz Pagowski, Jeff Peischl, Irina Petropavlovskikh, R. Bradley Pierce, Thomas B. Ryerson, Scott P. Sandberg, Chance W. Sterling, Ann M. Weickmann, and Li Zhang
Atmos. Chem. Phys., 22, 1707–1737, https://doi.org/10.5194/acp-22-1707-2022, https://doi.org/10.5194/acp-22-1707-2022, 2022
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The Fires, Asian, and Stratospheric Transport–Las Vegas Ozone Study (FAST-LVOS) combined lidar, aircraft, and in situ measurements with global models to investigate the contributions of stratospheric intrusions, regional and Asian pollution, and wildfires to background ozone in the southwestern US during May and June 2017 and demonstrated that these processes contributed to background ozone levels that exceeded 70 % of the US National Ambient Air Quality Standard during the 6-week campaign.
Sharmine Akter Simu, Yuzo Miyazaki, Eri Tachibana, Henning Finkenzeller, Jérôme Brioude, Aurélie Colomb, Olivier Magand, Bert Verreyken, Stephanie Evan, Rainer Volkamer, and Trissevgeni Stavrakou
Atmos. Chem. Phys., 21, 17017–17029, https://doi.org/10.5194/acp-21-17017-2021, https://doi.org/10.5194/acp-21-17017-2021, 2021
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The tropical Indian Ocean (IO) is expected to be a significant source of water-soluble organic carbon (WSOC), which is relevant to cloud formation. Our study showed that marine secondary organic formation dominantly contributed to the aerosol WSOC mass at the high-altitude observatory in the southwest IO in the wet season in both marine boundary layer and free troposphere (FT). This suggests that the effect of marine secondary sources is important up to FT, a process missing in climate models.
Bert Verreyken, Crist Amelynck, Niels Schoon, Jean-François Müller, Jérôme Brioude, Nicolas Kumps, Christian Hermans, Jean-Marc Metzger, Aurélie Colomb, and Trissevgeni Stavrakou
Atmos. Chem. Phys., 21, 12965–12988, https://doi.org/10.5194/acp-21-12965-2021, https://doi.org/10.5194/acp-21-12965-2021, 2021
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We present a 2-year dataset of trace gas concentrations, specifically an array of volatile organic compounds (VOCs), recorded at the Maïdo observatory, a remote tropical high-altitude site located on a small island in the southwest Indian Ocean. We found that island-scale transport is an important driver for the daily cycle of VOC concentrations. During the day, surface emissions from the island affect the atmospheric composition at Maïdo greatly, while at night this impact is strongly reduced.
Clémence Rose, Matti P. Rissanen, Siddharth Iyer, Jonathan Duplissy, Chao Yan, John B. Nowak, Aurélie Colomb, Régis Dupuy, Xu-Cheng He, Janne Lampilahti, Yee Jun Tham, Daniela Wimmer, Jean-Marc Metzger, Pierre Tulet, Jérôme Brioude, Céline Planche, Markku Kulmala, and Karine Sellegri
Atmos. Chem. Phys., 21, 4541–4560, https://doi.org/10.5194/acp-21-4541-2021, https://doi.org/10.5194/acp-21-4541-2021, 2021
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Sulfuric acid (H2SO4) is commonly accepted as a key precursor for atmospheric new particle formation. However, direct measurements of [H2SO4] remain challenging, motivating the development of proxies. Using data collected in two different volcanic plumes, we show, under these specific conditions, the good performance of a proxy from the literature and also highlight the benefit of the newly developed proxies for the prediction of the highest [H2SO4] values.
Bert Verreyken, Crist Amelynck, Jérôme Brioude, Jean-François Müller, Niels Schoon, Nicolas Kumps, Aurélie Colomb, Jean-Marc Metzger, Christopher F. Lee, Theodore K. Koenig, Rainer Volkamer, and Trissevgeni Stavrakou
Atmos. Chem. Phys., 20, 14821–14845, https://doi.org/10.5194/acp-20-14821-2020, https://doi.org/10.5194/acp-20-14821-2020, 2020
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Biomass burning (BB) plumes arriving at the Maïdo observatory located in the south-west Indian Ocean during August 2018 and August 2019 are studied using trace gas measurements, Lagrangian transport models and the CAMS near-real-time atmospheric composition service. We investigate (i) secondary production of volatile organic compounds during transport, (ii) efficacy of the CAMS model to reproduce the chemical makeup of BB plumes and (iii) the impact of BB on the remote marine boundary layer.
Damien Héron, Stephanie Evan, Joris Pianezze, Thibaut Dauhut, Jerome Brioude, Karen Rosenlof, Vincent Noel, Soline Bielli, Christelle Barthe, and Jean-Pierre Cammas
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-870, https://doi.org/10.5194/acp-2020-870, 2020
Publication in ACP not foreseen
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Upward transport within tropical cyclones of water vapor from the low troposphere into the colder upper troposphere/lower stratosphere can result in the moistening of this region. Balloon observations and model simulations of tropical cyclone Enawo in the less-observed Southwest Indian Ocean (the third most tropical cyclone active region on Earth) are used to show how convective overshoots within Enawo penetrate the tropopause directly, injecting water/ice into the stratosphere.
Stephanie Evan, Jerome Brioude, Karen Rosenlof, Sean M. Davis, Holger Vömel, Damien Héron, Françoise Posny, Jean-Marc Metzger, Valentin Duflot, Guillaume Payen, Hélène Vérèmes, Philippe Keckhut, and Jean-Pierre Cammas
Atmos. Chem. Phys., 20, 10565–10586, https://doi.org/10.5194/acp-20-10565-2020, https://doi.org/10.5194/acp-20-10565-2020, 2020
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The role of deep convection in the southwest Indian Ocean (the 3rd most active tropical cyclone basin) on the composition of the tropical tropopause layer (TTL) and the climate system is less understood due to scarce observations. Balloon-borne lidar and satellite measurements in the southwest Indian Ocean were used to study tropical cyclones' influence on TTL composition. This study compares the impact of a tropical storm and cyclone on the humidification of the TTL over the SW Indian Ocean.
Damien Héron, Stéphanie Evan, Jérôme Brioude, Karen Rosenlof, Françoise Posny, Jean-Marc Metzger, and Jean-Pierre Cammas
Atmos. Chem. Phys., 20, 8611–8626, https://doi.org/10.5194/acp-20-8611-2020, https://doi.org/10.5194/acp-20-8611-2020, 2020
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Using a statistical method, summer variations (between 2013 and 2016) of ozone and water vapor are characterized in the upper troposphere above Réunion island (21° S, 55° E). It suggests a convective influence between 9 and 13 km. As deep convection is rarely observed near Réunion island, this study provides new insights on the long-range impact of deep convective outflow from the Intertropical Convergence Zone (ITCZ) on the upper troposphere over a subtropical site.
Baye T. P. Thera, Pamela Dominutti, Fatma Öztürk, Thérèse Salameh, Stéphane Sauvage, Charbel Afif, Banu Çetin, Cécile Gaimoz, Melek Keleş, Stéphanie Evan, and Agnès Borbon
Atmos. Chem. Phys., 19, 15131–15156, https://doi.org/10.5194/acp-19-15131-2019, https://doi.org/10.5194/acp-19-15131-2019, 2019
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A large set of volatile organic compound observations was collected for the first time in Istanbul in September 2014. A source–receptor approach has been carried out to apportion emission sources, estimate anthropogenic emissions, and evaluate emission inventories. Unexpectedly, transport was not the most dominant source in this study. Our work stresses the need to better represent VOC emissions in the eastern Mediterranean region with an effort on non-traffic sources and oxygenated VOCs.
Ignacio Pisso, Espen Sollum, Henrik Grythe, Nina I. Kristiansen, Massimo Cassiani, Sabine Eckhardt, Delia Arnold, Don Morton, Rona L. Thompson, Christine D. Groot Zwaaftink, Nikolaos Evangeliou, Harald Sodemann, Leopold Haimberger, Stephan Henne, Dominik Brunner, John F. Burkhart, Anne Fouilloux, Jerome Brioude, Anne Philipp, Petra Seibert, and Andreas Stohl
Geosci. Model Dev., 12, 4955–4997, https://doi.org/10.5194/gmd-12-4955-2019, https://doi.org/10.5194/gmd-12-4955-2019, 2019
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We present the latest release of the Lagrangian transport model FLEXPART, which simulates the transport, diffusion, dry and wet deposition, radioactive decay, and 1st-order chemical reactions of atmospheric tracers. The model has been recently updated both technically and in the representation of physicochemical processes. We describe the changes, document the most recent input and output files, provide working examples, and introduce testing capabilities.
Pierre Tulet, Andréa Di Muro, Aurélie Colomb, Cyrielle Denjean, Valentin Duflot, Santiago Arellano, Brice Foucart, Jérome Brioude, Karine Sellegri, Aline Peltier, Alessandro Aiuppa, Christelle Barthe, Chatrapatty Bhugwant, Soline Bielli, Patrice Boissier, Guillaume Boudoire, Thierry Bourrianne, Christophe Brunet, Fréderic Burnet, Jean-Pierre Cammas, Franck Gabarrot, Bo Galle, Gaetano Giudice, Christian Guadagno, Fréderic Jeamblu, Philippe Kowalski, Jimmy Leclair de Bellevue, Nicolas Marquestaut, Dominique Mékies, Jean-Marc Metzger, Joris Pianezze, Thierry Portafaix, Jean Sciare, Arnaud Tournigand, and Nicolas Villeneuve
Atmos. Chem. Phys., 17, 5355–5378, https://doi.org/10.5194/acp-17-5355-2017, https://doi.org/10.5194/acp-17-5355-2017, 2017
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The STRAP campaign was conducted in 2015 to investigate the volcanic plumes of Piton de La Fournaise (La Réunion, France). For the first time, measurements were conducted at the local (near the vent) and regional scales around the island. The STRAP 2015 campaign gave a unique set of multi-disciplinary data that can now be used by modellers to improve the numerical parameterisations of the physical and chemical evolution of the volcanic plumes.
Hélène Vérèmes, Guillaume Payen, Philippe Keckhut, Valentin Duflot, Jean-Luc Baray, Jean-Pierre Cammas, Jimmy Leclair De Bellevue, Stéphanie Evan, Françoise Posny, Franck Gabarrot, Jean-Marc Metzger, Nicolas Marquestaut, Susanne Meier, Holger Vömel, and Ruud Dirksen
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2017-32, https://doi.org/10.5194/amt-2017-32, 2017
Preprint withdrawn
Elton Chan, Douglas Chan, Misa Ishizawa, Felix Vogel, Jerome Brioude, Andy Delcloo, Yuehua Wu, and Baisuo Jin
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2016-213, https://doi.org/10.5194/gmd-2016-213, 2016
Revised manuscript not accepted
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The main objective of this study is to examine the impacts of errors introduced by different components in our newly developed inversion system on flux estimates with a series of controlled experiments. It is very critical for any inversion system to be fully evaluated prior to applying to real observations. As demonstrated, the results can be very sensitive to the model setup and region. It is not reasonable to expect realistic results can always be obtained using the same approach.
Carsten Warneke, Michael Trainer, Joost A. de Gouw, David D. Parrish, David W. Fahey, A. R. Ravishankara, Ann M. Middlebrook, Charles A. Brock, James M. Roberts, Steven S. Brown, Jonathan A. Neuman, Brian M. Lerner, Daniel Lack, Daniel Law, Gerhard Hübler, Iliana Pollack, Steven Sjostedt, Thomas B. Ryerson, Jessica B. Gilman, Jin Liao, John Holloway, Jeff Peischl, John B. Nowak, Kenneth C. Aikin, Kyung-Eun Min, Rebecca A. Washenfelder, Martin G. Graus, Mathew Richardson, Milos Z. Markovic, Nick L. Wagner, André Welti, Patrick R. Veres, Peter Edwards, Joshua P. Schwarz, Timothy Gordon, William P. Dube, Stuart A. McKeen, Jerome Brioude, Ravan Ahmadov, Aikaterini Bougiatioti, Jack J. Lin, Athanasios Nenes, Glenn M. Wolfe, Thomas F. Hanisco, Ben H. Lee, Felipe D. Lopez-Hilfiker, Joel A. Thornton, Frank N. Keutsch, Jennifer Kaiser, Jingqiu Mao, and Courtney D. Hatch
Atmos. Meas. Tech., 9, 3063–3093, https://doi.org/10.5194/amt-9-3063-2016, https://doi.org/10.5194/amt-9-3063-2016, 2016
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In this paper we describe the experimental approach, the science goals and early results of the NOAA SENEX campaign, which was focused on studying the interactions between biogenic and anthropogenic emissions to form secondary pollutants.
During SENEX, the NOAA WP-3D aircraft conducted 20 research flights between 27 May and 10 July 2013 based out of Smyrna, TN. The SENEX flights included day- and nighttime flights in the Southeast as well as flights over areas with intense shale gas extraction.
E. Chan, D. Chan, M. Ishizawa, F. Vogel, J. Brioude, A. Delcloo, Y. Wu, and B. Jin
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-15-22715-2015, https://doi.org/10.5194/acpd-15-22715-2015, 2015
Revised manuscript not accepted
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This paper uses synthetic data experiments to investigate the impacts of different error sources associated with prior flux, transport model and optimisation method on the atmospheric greenhouse gas inverse estimates. Results indicate that estimation errors are dominated by the transport model error and can propagate to the flux estimates non-linearly. It is necessary to obtain stable and realistic results in synthetic data experiments before a real observation-based inversion is performed.
W. M. Angevine, J. Brioude, S. McKeen, and J. S. Holloway
Geosci. Model Dev., 7, 2817–2829, https://doi.org/10.5194/gmd-7-2817-2014, https://doi.org/10.5194/gmd-7-2817-2014, 2014
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Uncertainty in Lagrangian particle dispersion model simulations was evaluated using an ensemble of WRF meteorological model runs. Uncertainty of tracer concentrations due solely to meteorological uncertainty is 30-40%. Spatial and temporal averaging reduces the uncertainty marginally. Tracer age uncertainty due solely to meteorological uncertainty is 15-20%. These are lower bounds on the uncertainty, because a number of processes are not accounted for in the analysis.
Y. Y. Cui, A. Hodzic, J. N. Smith, J. Ortega, J. Brioude, H. Matsui, E. J. T. Levin, A. Turnipseed, P. Winkler, and B. de Foy
Atmos. Chem. Phys., 14, 11011–11029, https://doi.org/10.5194/acp-14-11011-2014, https://doi.org/10.5194/acp-14-11011-2014, 2014
C. Knote, A. Hodzic, J. L. Jimenez, R. Volkamer, J. J. Orlando, S. Baidar, J. Brioude, J. Fast, D. R. Gentner, A. H. Goldstein, P. L. Hayes, W. B. Knighton, H. Oetjen, A. Setyan, H. Stark, R. Thalman, G. Tyndall, R. Washenfelder, E. Waxman, and Q. Zhang
Atmos. Chem. Phys., 14, 6213–6239, https://doi.org/10.5194/acp-14-6213-2014, https://doi.org/10.5194/acp-14-6213-2014, 2014
D. R. Gentner, E. Ormeño, S. Fares, T. B. Ford, R. Weber, J.-H. Park, J. Brioude, W. M. Angevine, J. F. Karlik, and A. H. Goldstein
Atmos. Chem. Phys., 14, 5393–5413, https://doi.org/10.5194/acp-14-5393-2014, https://doi.org/10.5194/acp-14-5393-2014, 2014
D. R. Gentner, T. B. Ford, A. Guha, K. Boulanger, J. Brioude, W. M. Angevine, J. A. de Gouw, C. Warneke, J. B. Gilman, T. B. Ryerson, J. Peischl, S. Meinardi, D. R. Blake, E. Atlas, W. A. Lonneman, T. E. Kleindienst, M. R. Beaver, J. M. St. Clair, P. O. Wennberg, T. C. VandenBoer, M. Z. Markovic, J. G. Murphy, R. A. Harley, and A. H. Goldstein
Atmos. Chem. Phys., 14, 4955–4978, https://doi.org/10.5194/acp-14-4955-2014, https://doi.org/10.5194/acp-14-4955-2014, 2014
J. Brioude, D. Arnold, A. Stohl, M. Cassiani, D. Morton, P. Seibert, W. Angevine, S. Evan, A. Dingwell, J. D. Fast, R. C. Easter, I. Pisso, J. Burkhart, and G. Wotawa
Geosci. Model Dev., 6, 1889–1904, https://doi.org/10.5194/gmd-6-1889-2013, https://doi.org/10.5194/gmd-6-1889-2013, 2013
J. Brioude, W. M. Angevine, R. Ahmadov, S.-W. Kim, S. Evan, S. A. McKeen, E.-Y. Hsie, G. J. Frost, J. A. Neuman, I. B. Pollack, J. Peischl, T. B. Ryerson, J. Holloway, S. S. Brown, J. B. Nowak, J. M. Roberts, S. C. Wofsy, G. W. Santoni, T. Oda, and M. Trainer
Atmos. Chem. Phys., 13, 3661–3677, https://doi.org/10.5194/acp-13-3661-2013, https://doi.org/10.5194/acp-13-3661-2013, 2013
Related subject area
Atmospheric sciences
MEXPLORER 1.0.0 – a mechanism explorer for analysis and visualization of chemical reaction pathways based on graph theory
Advances and prospects of deep learning for medium-range extreme weather forecasting
An overview of the Western United States Dynamically Downscaled Dataset (WUS-D3)
cloudbandPy 1.0: an automated algorithm for the detection of tropical–extratropical cloud bands
PyRTlib: an educational Python-based library for non-scattering atmospheric microwave radiative transfer computations
Deep learning applied to CO2 power plant emissions quantification using simulated satellite images
Sensitivity of the WRF-Chem v4.4 simulations of ozone and formaldehyde and their precursors to multiple bottom-up emission inventories over East Asia during the KORUS-AQ 2016 field campaign
Optimising urban measurement networks for CO2 flux estimation: a high-resolution observing system simulation experiment using GRAMM/GRAL
Assessment of climate biases in OpenIFS version 43r3 across model horizontal resolutions and time steps
High-resolution multi-scaling of outdoor human thermal comfort and its intra-urban variability based on machine learning
Effects of vertical grid spacing on the climate simulated in the ICON-Sapphire global storm-resolving model
Development of the tangent linear and adjoint models of the global online chemical transport model MPAS-CO2 v7.3
Impacts of updated reaction kinetics on the global GEOS-Chem simulation of atmospheric chemistry
Spatial spin-up of precipitation in limited-area convection-permitting simulations over North America using the CRCM6/GEM5.0 model
Sensitivity of atmospheric rivers to aerosol treatment in regional climate simulations: insights from the AIRA identification algorithm
The implementation of dust mineralogy in COSMO5.05-MUSCAT
Implementation of the ISORROPIA-lite aerosol thermodynamics model into the EMAC chemistry climate model (based on MESSy v2.55): implications for aerosol composition and acidity
Evaluation of surface shortwave downward radiation forecasts by the numerical weather prediction model AROME
GEO4PALM v1.1: an open-source geospatial data processing toolkit for the PALM model system
Modeling collision–coalescence in particle microphysics: numerical convergence of mean and variance of precipitation in cloud simulations using the University of Warsaw Lagrangian Cloud Model (UWLCM) 2.1
Modeling below-cloud scavenging of size-resolved particles in GEM-MACHv3.1
Impacts of a double-moment bulk cloud microphysics scheme (NDW6-G23) on aerosol fields in NICAM.19 with a global 14 km grid resolution
Sensitivity of air quality model responses to emission changes: comparison of results based on four EU inventories through FAIRMODE benchmarking methodology
A simple and realistic aerosol emission approach for use in the Thompson–Eidhammer microphysics scheme in the NOAA UFS Weather Model (version GSL global-24Feb2022)
On the formation of biogenic secondary organic aerosol in chemical transport models: an evaluation of the WRF-CHIMERE (v2020r2) model with a focus over the Finnish boreal forest
The first application of a numerically exact, higher-order sensitivity analysis approach for atmospheric modelling: implementation of the hyperdual-step method in the Community Multiscale Air Quality Model (CMAQ) version 5.3.2
GAN-argcPredNet v2.0: a radar echo extrapolation model based on spatiotemporal process enhancement
Analysis of the GEFS-Aerosols annual budget to better understand aerosol predictions simulated in the model
A model for rapid PM2.5 exposure estimates in wildfire conditions using routinely available data: rapidfire v0.1.3
BoundaryLayerDynamics.jl v1.0: a modern codebase for atmospheric boundary-layer simulations
The wave-age-dependent stress parameterisation (WASP) for momentum and heat turbulent fluxes at sea in SURFEX v8.1
Spherical air mass factors in one and two dimensions with SASKTRAN 1.6.0
An improved version of the piecewise parabolic method advection scheme: description and performance assessment in a bidimensional test case with stiff chemistry in toyCTM v1.0.1
INCHEM-Py v1.2: a community box model for indoor air chemistry
Implementation and evaluation of updated photolysis rates in the EMEP MSC-W chemistry-transport model using Cloud-J v7.3e
Representation of atmosphere-induced heterogeneity in land–atmosphere interactions in E3SM–MMFv2
Assimilation of GNSS Tropospheric Gradients into the Weather Research and Forecasting Model Version 4.4.1
A global grid model for the estimation of zenith tropospheric delay considering the variations at different altitudes
Data assimilation for the Model for Prediction Across Scales – Atmosphere with the Joint Effort for Data assimilation Integration (JEDI-MPAS 2.0.0-beta): ensemble of 3D ensemble-variational (En-3DEnVar) assimilations
A Grid Model for Vertical Correction of Precipitable Water Vapor over the Chinese Mainland and Surrounding Areas Using Random Forest
Simulations of 7Be and 10Be with the GEOS-Chem global model v14.0.2 using state-of-the-art production rates
Comprehensive evaluation of typical planetary boundary layer (PBL) parameterization schemes in China – Part 2: Influence of uncertainty factors
A mountain-induced moist baroclinic wave test case for the dynamical cores of atmospheric general circulation models
The effect of emission source chemical profiles on simulated PM2.5 components: sensitivity analysis with the Community Multiscale Air Quality (CMAQ) modeling system version 5.0.2
Challenges of constructing and selecting the "perfect" initial and boundary conditions for the LES model PALM
Comprehensive evaluation of typical planetary boundary layer (PBL) parameterization schemes in China – Part 1: Understanding expressiveness of schemes for different regions from the mechanism perspective
Evaluating 3 decades of precipitation in the Upper Colorado River basin from a high-resolution regional climate model
Efficient and Stable Coupling of the SuperdropNet Deep Learning-based Cloud Microphysics (v0.1.0) to the ICON Climate and Weather Model (v2.6.5)
How non-equilibrium aerosol chemistry impacts particle acidity: the GMXe AERosol CHEMistry (GMXe–AERCHEM, v1.0) sub-submodel of MESSy
Implementation of a satellite-based tool for the quantification of CH4 emissions over Europe (AUMIA v1.0) – Part 1: forward modelling evaluation against near-surface and satellite data
Rolf Sander
Geosci. Model Dev., 17, 2419–2425, https://doi.org/10.5194/gmd-17-2419-2024, https://doi.org/10.5194/gmd-17-2419-2024, 2024
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The open-source software MEXPLORER 1.0.0 is presented here. The program can be used to analyze, reduce, and visualize complex chemical reaction mechanisms. The mathematics behind the tool is based on graph theory: chemical species are represented as vertices, and reactions as edges. MEXPLORER is a community model published under the GNU General Public License.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 2347–2358, https://doi.org/10.5194/gmd-17-2347-2024, https://doi.org/10.5194/gmd-17-2347-2024, 2024
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In the last decades, weather forecasting up to 15 d into the future has been dominated by physics-based numerical models. Recently, deep learning models have challenged this paradigm. However, the latter models may struggle when forecasting weather extremes. In this article, we argue for deep learning models specifically designed to handle extreme events, and we propose a foundational framework to develop such models.
Stefan Rahimi, Lei Huang, Jesse Norris, Alex Hall, Naomi Goldenson, Will Krantz, Benjamin Bass, Chad Thackeray, Henry Lin, Di Chen, Eli Dennis, Ethan Collins, Zachary J. Lebo, Emily Slinskey, Sara Graves, Surabhi Biyani, Bowen Wang, Stephen Cropper, and the UCLA Center for Climate Science Team
Geosci. Model Dev., 17, 2265–2286, https://doi.org/10.5194/gmd-17-2265-2024, https://doi.org/10.5194/gmd-17-2265-2024, 2024
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Here, we project future climate across the western United States through the end of the 21st century using a regional climate model, embedded within 16 latest-generation global climate models, to provide the community with a high-resolution physically based ensemble of climate data for use at local scales. Strengths and weaknesses of the data are frankly discussed as we overview the downscaled dataset.
Romain Pilon and Daniela I. V. Domeisen
Geosci. Model Dev., 17, 2247–2264, https://doi.org/10.5194/gmd-17-2247-2024, https://doi.org/10.5194/gmd-17-2247-2024, 2024
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This paper introduces a new method for detecting atmospheric cloud bands to identify long convective cloud bands that extend from the tropics to the midlatitudes. The algorithm allows for easy use and enables researchers to study the life cycle and climatology of cloud bands and associated rainfall. This method provides insights into the large-scale processes involved in cloud band formation and their connections between different regions, as well as differences across ocean basins.
Salvatore Larosa, Domenico Cimini, Donatello Gallucci, Saverio Teodosio Nilo, and Filomena Romano
Geosci. Model Dev., 17, 2053–2076, https://doi.org/10.5194/gmd-17-2053-2024, https://doi.org/10.5194/gmd-17-2053-2024, 2024
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PyRTlib is an attractive educational tool because it provides a flexible and user-friendly way to broadly simulate how electromagnetic radiation travels through the atmosphere as it interacts with atmospheric constituents (such as gases, aerosols, and hydrometeors). PyRTlib is a so-called radiative transfer model; these are commonly used to simulate and understand remote sensing observations from ground-based, airborne, or satellite instruments.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 17, 1995–2014, https://doi.org/10.5194/gmd-17-1995-2024, https://doi.org/10.5194/gmd-17-1995-2024, 2024
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Our research presents an innovative approach to estimating power plant CO2 emissions from satellite images of the corresponding plumes such as those from the forthcoming CO2M satellite constellation. The exploitation of these images is challenging due to noise and meteorological uncertainties. To overcome these obstacles, we use a deep learning neural network trained on simulated CO2 images. Our method outperforms alternatives, providing a positive perspective for the analysis of CO2M images.
Kyoung-Min Kim, Si-Wan Kim, Seunghwan Seo, Donald R. Blake, Seogju Cho, James H. Crawford, Louisa K. Emmons, Alan Fried, Jay R. Herman, Jinkyu Hong, Jinsang Jung, Gabriele G. Pfister, Andrew J. Weinheimer, Jung-Hun Woo, and Qiang Zhang
Geosci. Model Dev., 17, 1931–1955, https://doi.org/10.5194/gmd-17-1931-2024, https://doi.org/10.5194/gmd-17-1931-2024, 2024
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Three emission inventories were evaluated for East Asia using data acquired during a field campaign in 2016. The inventories successfully reproduced the daily variations of ozone and nitrogen dioxide. However, the spatial distributions of model ozone did not fully agree with the observations. Additionally, all simulations underestimated carbon monoxide and volatile organic compound (VOC) levels. Increasing VOC emissions over South Korea resulted in improved ozone simulations.
Sanam Noreen Vardag and Robert Maiwald
Geosci. Model Dev., 17, 1885–1902, https://doi.org/10.5194/gmd-17-1885-2024, https://doi.org/10.5194/gmd-17-1885-2024, 2024
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We use the atmospheric transport model GRAMM/GRAL in a Bayesian inversion to estimate urban CO2 emissions on a neighbourhood scale. We analyse the effect of varying number, precision and location of CO2 sensors for CO2 flux estimation. We further test the inclusion of co-emitted species and correlation in the inversion. The study showcases the general usefulness of GRAMM/GRAL in measurement network design.
Abhishek Savita, Joakim Kjellsson, Robin Pilch Kedzierski, Mojib Latif, Tabea Rahm, Sebastian Wahl, and Wonsun Park
Geosci. Model Dev., 17, 1813–1829, https://doi.org/10.5194/gmd-17-1813-2024, https://doi.org/10.5194/gmd-17-1813-2024, 2024
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The OpenIFS model is used to examine the impact of horizontal resolutions (HR) and model time steps. We find that the surface wind biases over the oceans, in particular the Southern Ocean, are sensitive to the model time step and HR, with the HR having the smallest biases. When using a coarse-resolution model with a shorter time step, a similar improvement is also found. Climate biases can be reduced in the OpenIFS model at a cheaper cost by reducing the time step rather than increasing the HR.
Ferdinand Briegel, Jonas Wehrle, Dirk Schindler, and Andreas Christen
Geosci. Model Dev., 17, 1667–1688, https://doi.org/10.5194/gmd-17-1667-2024, https://doi.org/10.5194/gmd-17-1667-2024, 2024
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We present a new approach to model heat stress in cities using artificial intelligence (AI). We show that the AI model is fast in terms of prediction but accurate when evaluated with measurements. The fast-predictive AI model enables several new potential applications, including heat stress prediction and warning; downscaling of potential future climates; evaluation of adaptation effectiveness; and, more fundamentally, development of guidelines to support urban planning and policymaking.
Hauke Schmidt, Sebastian Rast, Jiawei Bao, Amrit Cassim, Shih-Wei Fang, Diego Jimenez-de la Cuesta, Paul Keil, Lukas Kluft, Clarissa Kroll, Theresa Lang, Ulrike Niemeier, Andrea Schneidereit, Andrew I. L. Williams, and Bjorn Stevens
Geosci. Model Dev., 17, 1563–1584, https://doi.org/10.5194/gmd-17-1563-2024, https://doi.org/10.5194/gmd-17-1563-2024, 2024
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A recent development in numerical simulations of the global atmosphere is the increase in horizontal resolution to grid spacings of a few kilometers. However, the vertical grid spacing of these models has not been reduced at the same rate as the horizontal grid spacing. Here, we assess the effects of much finer vertical grid spacings, in particular the impacts on cloud quantities and the atmospheric energy balance.
Tao Zheng, Sha Feng, Jeffrey Steward, Xiaoxu Tian, David Baker, and Martin Baxter
Geosci. Model Dev., 17, 1543–1562, https://doi.org/10.5194/gmd-17-1543-2024, https://doi.org/10.5194/gmd-17-1543-2024, 2024
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The tangent linear and adjoint models have been successfully implemented in the MPAS-CO2 system, which has undergone rigorous accuracy testing. This development lays the groundwork for a global carbon flux data assimilation system, which offers the flexibility of high-resolution focus on specific areas, while maintaining a coarser resolution elsewhere. This approach significantly reduces computational costs and is thus perfectly suited for future CO2 geostationery and imager satellites.
Kelvin H. Bates, Mathew J. Evans, Barron H. Henderson, and Daniel J. Jacob
Geosci. Model Dev., 17, 1511–1524, https://doi.org/10.5194/gmd-17-1511-2024, https://doi.org/10.5194/gmd-17-1511-2024, 2024
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Accurate representation of rates and products of chemical reactions in atmospheric models is crucial for simulating concentrations of pollutants and climate forcers. We update the widely used GEOS-Chem atmospheric chemistry model with reaction parameters from recent compilations of experimental data and demonstrate the implications for key atmospheric chemical species. The updates decrease tropospheric CO mixing ratios and increase stratospheric nitrogen oxide mixing ratios, among other changes.
François Roberge, Alejandro Di Luca, René Laprise, Philippe Lucas-Picher, and Julie Thériault
Geosci. Model Dev., 17, 1497–1510, https://doi.org/10.5194/gmd-17-1497-2024, https://doi.org/10.5194/gmd-17-1497-2024, 2024
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Our study addresses a challenge in dynamical downscaling using regional climate models, focusing on the lack of small-scale features near the boundaries. We introduce a method to identify this “spatial spin-up” in precipitation simulations. Results show spin-up distances up to 300 km, varying by season and driving variable. Double nesting with comprehensive variables (e.g. microphysical variables) offers advantages. Findings will help optimize simulations for better climate projections.
Eloisa Raluy-López, Juan Pedro Montávez, and Pedro Jiménez-Guerrero
Geosci. Model Dev., 17, 1469–1495, https://doi.org/10.5194/gmd-17-1469-2024, https://doi.org/10.5194/gmd-17-1469-2024, 2024
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Atmospheric rivers (ARs) represent a significant source of water but are also related to extreme precipitation events. Here, we present a new regional-scale AR identification algorithm and apply it to three simulations that include aerosol interactions at different levels. The results show that aerosols modify the intensity and trajectory of ARs and redistribute the AR-related precipitation. Thus, the correct inclusion of aerosol effects is important in the simulation of AR behavior.
Sofía Gómez Maqueo Anaya, Dietrich Althausen, Matthias Faust, Holger Baars, Bernd Heinold, Julian Hofer, Ina Tegen, Albert Ansmann, Ronny Engelmann, Annett Skupin, Birgit Heese, and Kerstin Schepanski
Geosci. Model Dev., 17, 1271–1295, https://doi.org/10.5194/gmd-17-1271-2024, https://doi.org/10.5194/gmd-17-1271-2024, 2024
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Mineral dust aerosol particles vary greatly in their composition depending on source region, which leads to different physicochemical properties. Most atmosphere–aerosol models consider mineral dust aerosols to be compositionally homogeneous, which ultimately increases model uncertainty. Here, we present an approach to explicitly consider the heterogeneity of the mineralogical composition for simulations of the Saharan atmospheric dust cycle with regard to dust transport towards the Atlantic.
Alexandros Milousis, Alexandra P. Tsimpidi, Holger Tost, Spyros N. Pandis, Athanasios Nenes, Astrid Kiendler-Scharr, and Vlassis A. Karydis
Geosci. Model Dev., 17, 1111–1131, https://doi.org/10.5194/gmd-17-1111-2024, https://doi.org/10.5194/gmd-17-1111-2024, 2024
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This study aims to evaluate the newly developed ISORROPIA-lite aerosol thermodynamic module within the EMAC model and explore discrepancies in global atmospheric simulations of aerosol composition and acidity by utilizing different aerosol phase states. Even though local differences were found in regions where the RH ranged from 20 % to 60 %, on a global scale the results are similar. Therefore, ISORROPIA-lite can be a reliable and computationally effective alternative to ISORROPIA II in EMAC.
Marie-Adèle Magnaldo, Quentin Libois, Sébastien Riette, and Christine Lac
Geosci. Model Dev., 17, 1091–1109, https://doi.org/10.5194/gmd-17-1091-2024, https://doi.org/10.5194/gmd-17-1091-2024, 2024
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With the worldwide development of the solar energy sector, the need for reliable solar radiation forecasts has significantly increased. However, meteorological models that predict, among others things, solar radiation have errors. Therefore, we wanted to know in which situtaions these errors are most significant. We found that errors mostly occur in cloudy situations, and different errors were highlighted depending on the cloud altitude. Several potential sources of errors were identified.
Dongqi Lin, Jiawei Zhang, Basit Khan, Marwan Katurji, and Laura E. Revell
Geosci. Model Dev., 17, 815–845, https://doi.org/10.5194/gmd-17-815-2024, https://doi.org/10.5194/gmd-17-815-2024, 2024
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GEO4PALM is an open-source tool to generate static input for the Parallelized Large-Eddy Simulation (PALM) model system. Geospatial static input is essential for realistic PALM simulations. However, existing tools fail to generate PALM's geospatial static input for most regions. GEO4PALM is compatible with diverse geospatial data sources and provides access to free data sets. In addition, this paper presents two application examples, which show successful PALM simulations using GEO4PALM.
Piotr Zmijewski, Piotr Dziekan, and Hanna Pawlowska
Geosci. Model Dev., 17, 759–780, https://doi.org/10.5194/gmd-17-759-2024, https://doi.org/10.5194/gmd-17-759-2024, 2024
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In computer simulations of clouds it is necessary to model the myriad of droplets that constitute a cloud. A popular method for this is to use so-called super-droplets (SDs), each representing many real droplets. It has remained a challenge to model collisions of SDs. We study how precipitation in a cumulus cloud depends on the number of SDs. Surprisingly, we do not find convergence in mean precipitation even for numbers of SDs much larger than typically used in simulations.
Roya Ghahreman, Wanmin Gong, Paul A. Makar, Alexandru Lupu, Amanda Cole, Kulbir Banwait, Colin Lee, and Ayodeji Akingunola
Geosci. Model Dev., 17, 685–707, https://doi.org/10.5194/gmd-17-685-2024, https://doi.org/10.5194/gmd-17-685-2024, 2024
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The article explores the impact of different representations of below-cloud scavenging on model biases. A new scavenging scheme and precipitation-phase partitioning improve the model's performance, with better SO42- scavenging and wet deposition of NO3- and NH4+.
Daisuke Goto, Tatsuya Seiki, Kentaroh Suzuki, Hisashi Yashiro, and Toshihiko Takemura
Geosci. Model Dev., 17, 651–684, https://doi.org/10.5194/gmd-17-651-2024, https://doi.org/10.5194/gmd-17-651-2024, 2024
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Global climate models with coarse grid sizes include uncertainties about the processes in aerosol–cloud–precipitation interactions. To reduce these uncertainties, here we performed numerical simulations using a new version of our global aerosol transport model with a finer grid size over a longer period than in our previous study. As a result, we found that the cloud microphysics module influences the aerosol distributions through both aerosol wet deposition and aerosol–cloud interactions.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, Enrico Pisoni, and Bertrand Bessagnet
Geosci. Model Dev., 17, 587–606, https://doi.org/10.5194/gmd-17-587-2024, https://doi.org/10.5194/gmd-17-587-2024, 2024
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In our study the robustness of the model responses to emission reductions in the EU is assessed when the emission data are changed. Our findings are particularly important to better understand the uncertainties associated to the emission inventories and how these uncertainties impact the level of accuracy of the resulting air quality modelling, which is a key for designing air quality plans. Also crucial is the choice of indicator to avoid misleading interpretations of the results.
Haiqin Li, Georg A. Grell, Ravan Ahmadov, Li Zhang, Shan Sun, Jordan Schnell, and Ning Wang
Geosci. Model Dev., 17, 607–619, https://doi.org/10.5194/gmd-17-607-2024, https://doi.org/10.5194/gmd-17-607-2024, 2024
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We developed a simple and realistic method to provide aerosol emissions for aerosol-aware microphysics in a numerical weather forecast model. The cloud-radiation differences between the experimental (EXP) and control (CTL) experiments responded to the aerosol differences. The strong positive precipitation biases over North America and Europe from the CTL run were significantly reduced in the EXP run. This study shows that a realistic representation of aerosol emissions should be considered.
Giancarlo Ciarelli, Sara Tahvonen, Arineh Cholakian, Manuel Bettineschi, Bruno Vitali, Tuukka Petäjä, and Federico Bianchi
Geosci. Model Dev., 17, 545–565, https://doi.org/10.5194/gmd-17-545-2024, https://doi.org/10.5194/gmd-17-545-2024, 2024
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The terrestrial ecosystem releases large quantities of biogenic gases in the Earth's Atmosphere. These gases can effectively be converted into so-called biogenic aerosol particles and, eventually, affect the Earth's climate. Climate prediction varies greatly depending on how these processes are represented in model simulations. In this study, we present a detailed model evaluation analysis aimed at understanding the main source of uncertainty in predicting the formation of biogenic aerosols.
Jiachen Liu, Eric Chen, and Shannon L. Capps
Geosci. Model Dev., 17, 567–585, https://doi.org/10.5194/gmd-17-567-2024, https://doi.org/10.5194/gmd-17-567-2024, 2024
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Air pollution harms human life and ecosystems, but its sources are complex. Scientists and policy makers use air pollution models to advance knowledge and inform control strategies. We implemented a recently developed numeral system to relate any set of model inputs, like pollutant emissions from a given activity, to all model outputs, like concentrations of pollutants harming human health. This approach will be straightforward to update when scientists discover new processes in the atmosphere.
Kun Zheng, Qiya Tan, Huihua Ruan, Jinbiao Zhang, Cong Luo, Siyu Tang, Yunlei Yi, Yugang Tian, and Jianmei Cheng
Geosci. Model Dev., 17, 399–413, https://doi.org/10.5194/gmd-17-399-2024, https://doi.org/10.5194/gmd-17-399-2024, 2024
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Radar echo extrapolation is the common method in precipitation nowcasting. Deep learning has potential in extrapolation. However, the existing models have low prediction accuracy for heavy rainfall. In this study, the prediction accuracy is improved by suppressing the blurring effect of rain distribution and reducing the negative bias. The results show that our model has better performance, which is useful for urban operation and flood prevention.
Li Pan, Partha S. Bhattacharjee, Li Zhang, Raffaele Montuoro, Barry Baker, Jeff McQueen, Georg A. Grell, Stuart A. McKeen, Shobha Kondragunta, Xiaoyang Zhang, Gregory J. Frost, Fanglin Yang, and Ivanka Stajner
Geosci. Model Dev., 17, 431–447, https://doi.org/10.5194/gmd-17-431-2024, https://doi.org/10.5194/gmd-17-431-2024, 2024
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A GEFS-Aerosols simulation was conducted from 1 September 2019 to 30 September 2020 to evaluate the model performance of GEFS-Aerosols. The purpose of this study was to understand how aerosol chemical and physical processes affect ambient aerosol concentrations by placing aerosol wet deposition, dry deposition, reactions, gravitational deposition, and emissions into the aerosol mass balance equation.
Sean Raffuse, Susan O'Neill, and Rebecca Schmidt
Geosci. Model Dev., 17, 381–397, https://doi.org/10.5194/gmd-17-381-2024, https://doi.org/10.5194/gmd-17-381-2024, 2024
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Large wildfires are increasing throughout the western United States, and wildfire smoke is hazardous to public health. We developed a suite of tools called rapidfire for estimating particle pollution during wildfires using routinely available data sets. rapidfire uses official air monitoring, satellite data, meteorology, smoke modeling, and low-cost sensors. Estimates from rapidfire compare well with ground monitors and are being used in public health studies across California.
Manuel F. Schmid, Marco G. Giometto, Gregory A. Lawrence, and Marc B. Parlange
Geosci. Model Dev., 17, 321–333, https://doi.org/10.5194/gmd-17-321-2024, https://doi.org/10.5194/gmd-17-321-2024, 2024
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Turbulence-resolving flow models have strict performance requirements, as simulations often run for weeks using hundreds of processes. Many flow scenarios also require the flexibility to modify physical and numerical models for problem-specific requirements. With a new code written in Julia we hope to make such adaptations easier without compromising on performance. In this paper we discuss the modeling approach and present validation and performance results.
Marie-Noëlle Bouin, Cindy Lebeaupin Brossier, Sylvie Malardel, Aurore Voldoire, and César Sauvage
Geosci. Model Dev., 17, 117–141, https://doi.org/10.5194/gmd-17-117-2024, https://doi.org/10.5194/gmd-17-117-2024, 2024
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In numerical models, the turbulent exchanges of heat and momentum at the air–sea interface are not represented explicitly but with parameterisations depending on the surface parameters. A new parameterisation of turbulent fluxes (WASP) has been implemented in the surface model SURFEX v8.1 and validated on four case studies. It combines a close fit to observations including cyclonic winds, a dependency on the wave growth rate, and the possibility of being used in atmosphere–wave coupled models.
Lukas Fehr, Chris McLinden, Debora Griffin, Daniel Zawada, Doug Degenstein, and Adam Bourassa
Geosci. Model Dev., 16, 7491–7507, https://doi.org/10.5194/gmd-16-7491-2023, https://doi.org/10.5194/gmd-16-7491-2023, 2023
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This work highlights upgrades to SASKTRAN, a model that simulates sunlight interacting with the atmosphere to help measure trace gases. The upgrades were verified by detailed comparisons between different numerical methods. A case study was performed using SASKTRAN’s multidimensional capabilities, which found that ignoring horizontal variation in the atmosphere (a common practice in the field) can introduce non-negligible errors where there is snow or high pollution.
Sylvain Mailler, Romain Pennel, Laurent Menut, and Arineh Cholakian
Geosci. Model Dev., 16, 7509–7526, https://doi.org/10.5194/gmd-16-7509-2023, https://doi.org/10.5194/gmd-16-7509-2023, 2023
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We show that a new advection scheme named PPM + W (piecewise parabolic method + Walcek) offers geoscientific modellers an alternative, high-performance scheme designed for Cartesian-grid advection, with improved performance over the classical PPM scheme. The computational cost of PPM + W is not higher than that of PPM. With improved accuracy and controlled computational cost, this new scheme may find applications in chemistry-transport models, ocean models or atmospheric circulation models.
David R. Shaw, Toby J. Carter, Helen L. Davies, Ellen Harding-Smith, Elliott C. Crocker, Georgia Beel, Zixu Wang, and Nicola Carslaw
Geosci. Model Dev., 16, 7411–7431, https://doi.org/10.5194/gmd-16-7411-2023, https://doi.org/10.5194/gmd-16-7411-2023, 2023
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Exposure to air pollution is one of the greatest risks to human health, and it is indoors, where we spend upwards of 90 % of our time, that our exposure is greatest. The INdoor CHEMical model in Python (INCHEM-Py) is a new, community-led box model that tracks the evolution and fate of atmospheric chemical pollutants indoors. We have shown the processes simulated by INCHEM-Py, its ability to model experimental data and how it may be used to develop further understanding of indoor air chemistry.
Willem E. van Caspel, David Simpson, Jan Eiof Jonson, Anna M. K. Benedictow, Yao Ge, Alcide di Sarra, Giandomenico Pace, Massimo Vieno, Hannah L. Walker, and Mathew R. Heal
Geosci. Model Dev., 16, 7433–7459, https://doi.org/10.5194/gmd-16-7433-2023, https://doi.org/10.5194/gmd-16-7433-2023, 2023
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Radiation coming from the sun is essential to atmospheric chemistry, driving the breakup, or photodissociation, of atmospheric molecules. This in turn affects the chemical composition and reactivity of the atmosphere. The representation of photodissociation effects is therefore essential in atmospheric chemistry modeling. One such model is the EMEP MSC-W model, for which a new way of calculating the photodissociation rates is tested and evaluated in this paper.
Jungmin Lee, Walter M. Hannah, and David C. Bader
Geosci. Model Dev., 16, 7275–7287, https://doi.org/10.5194/gmd-16-7275-2023, https://doi.org/10.5194/gmd-16-7275-2023, 2023
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Representing accurate land–atmosphere interaction processes is overlooked in weather and climate models. In this study, we propose three methods to represent land–atmosphere coupling in the Energy Exascale Earth System Model (E3SM) with the Multi-scale Modeling Framework (MMF) approach. In this study, we introduce spatially homogeneous and heterogeneous land–atmosphere interaction processes within the cloud-resolving model domain. Our 5-year simulations reveal only small differences.
Rohith Muraleedharan Thundathil, Florian Zus, Galina Dick, and Jens Wickert
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-202, https://doi.org/10.5194/gmd-2023-202, 2023
Revised manuscript accepted for GMD
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Global Navigation Satellite Systems provide moisture observations through its densely distributed ground station network. In this research, we assimilated a new type of observation called tropospheric gradient observations, which was never incorporated into a weather model. Here, we have developed a forward operator for gradient observations and performed impact studies. Promising improvements were observed in the humidity fields of the model in the assimilation study.
Liangke Huang, Shengwei Lan, Ge Zhu, Fade Chen, Junyu Li, and Lilong Liu
Geosci. Model Dev., 16, 7223–7235, https://doi.org/10.5194/gmd-16-7223-2023, https://doi.org/10.5194/gmd-16-7223-2023, 2023
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The existing zenith tropospheric delay (ZTD) models have limitations such as using a single fitting function, neglecting daily cycle variations, and relying on only one resolution grid data point for modeling. This model considers the daily cycle variation and latitude factor of ZTD, using the sliding window algorithm based on ERA5 atmospheric reanalysis data. The ZTD data from 545 radiosonde stations and MERRA-2 atmospheric reanalysis data are used to validate the accuracy of the GGZTD-P model.
Jonathan J. Guerrette, Zhiquan Liu, Chris Snyder, Byoung-Joo Jung, Craig S. Schwartz, Junmei Ban, Steven Vahl, Yali Wu, Ivette Hernández Baños, Yonggang G. Yu, Soyoung Ha, Yannick Trémolet, Thomas Auligné, Clementine Gas, Benjamin Ménétrier, Anna Shlyaeva, Mark Miesch, Stephen Herbener, Emily Liu, Daniel Holdaway, and Benjamin T. Johnson
Geosci. Model Dev., 16, 7123–7142, https://doi.org/10.5194/gmd-16-7123-2023, https://doi.org/10.5194/gmd-16-7123-2023, 2023
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We demonstrate an ensemble of variational data assimilations (EDA) with the Model for Prediction Across Scales and the Joint Effort for Data assimilation Integration (JEDI) software framework. When compared to 20-member ensemble forecasts from operational initial conditions, those from 80-member EDA-generated initial conditions improve flow-dependent error covariances and subsequent 10 d forecasts. These experiments are repeatable for any atmospheric model with a JEDI interface.
Junyu Li, Yuxin Wang, Lilong Liu, Yibin Yao, Liangke Hang, and Feijuan Li
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-201, https://doi.org/10.5194/gmd-2023-201, 2023
Revised manuscript accepted for GMD
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In this study, we have developed a model (RF-PWV) to characterize PWV variation with altitude in the study area. The RF-PWV can significantly reduce errors in vertical correction, enhance PWV fusion product accuracy, and provide insights into PWV vertical distribution, thereby contributing to climate research.
Minjie Zheng, Hongyu Liu, Florian Adolphi, Raimund Muscheler, Zhengyao Lu, Mousong Wu, and Nønne L. Prisle
Geosci. Model Dev., 16, 7037–7057, https://doi.org/10.5194/gmd-16-7037-2023, https://doi.org/10.5194/gmd-16-7037-2023, 2023
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The radionuclides 7Be and 10Be are useful tracers for atmospheric transport studies. Here we use the GEOS-Chem to simulate 7Be and 10Be with different production rates: the default production rate in GEOS-Chem and two from the state-of-the-art beryllium production model. We demonstrate that reduced uncertainties in the production rates can enhance the utility of 7Be and 10Be as tracers for evaluating transport and scavenging processes in global models.
Wenxing Jia, Xiaoye Zhang, Hong Wang, Yaqiang Wang, Deying Wang, Junting Zhong, Wenjie Zhang, Lei Zhang, Lifeng Guo, Yadong Lei, Jizhi Wang, Yuanqin Yang, and Yi Lin
Geosci. Model Dev., 16, 6833–6856, https://doi.org/10.5194/gmd-16-6833-2023, https://doi.org/10.5194/gmd-16-6833-2023, 2023
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In addition to the dominant role of the PBL scheme on the results of the meteorological field, many factors in the model are influenced by large uncertainties. This study focuses on the uncertainties that influence numerical simulation results (including horizontal resolution, vertical resolution, near-surface scheme, initial and boundary conditions, underlying surface update, and update of model version), hoping to provide a reference for scholars conducting research on the model.
Owen K. Hughes and Christiane Jablonowski
Geosci. Model Dev., 16, 6805–6831, https://doi.org/10.5194/gmd-16-6805-2023, https://doi.org/10.5194/gmd-16-6805-2023, 2023
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Atmospheric models benefit from idealized tests that assess their accuracy in a simpler simulation. A new test with artificial mountains is developed for models on a spherical earth. The mountains trigger the development of both planetary-scale and small-scale waves. These can be analyzed in dry or moist environments, with a simple rainfall mechanism. Four atmospheric models are intercompared. This sheds light on the pros and cons of the model design and the impact of mountains on the flow.
Zhongwei Luo, Yan Han, Kun Hua, Yufen Zhang, Jianhui Wu, Xiaohui Bi, Qili Dai, Baoshuang Liu, Yang Chen, Xin Long, and Yinchang Feng
Geosci. Model Dev., 16, 6757–6771, https://doi.org/10.5194/gmd-16-6757-2023, https://doi.org/10.5194/gmd-16-6757-2023, 2023
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This study explores how the variation in the source profiles adopted in chemical transport models (CTMs) impacts the simulated results of chemical components in PM2.5 based on sensitivity analysis. The impact on PM2.5 components cannot be ignored, and its influence can be transmitted and linked between components. The representativeness and timeliness of the source profile should be paid adequate attention in air quality simulation.
Jelena Radovic, Michal Belda, Jaroslav Resler, Kryštof Eben, Martin Bureš, Jan Geletič, Pavel Krč, Hynek Řezníček, and Vladimír Fuka
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-197, https://doi.org/10.5194/gmd-2023-197, 2023
Revised manuscript accepted for GMD
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The initial and boundary conditions are of crucial importance for numerical model (e.g., PALM model) validation studies and have a large influence on the model results especially in the case of studying the atmosphere of a real, complex, and densely built urban environments. Our experiments with different driving conditions for the LES model PALM show its strong dependency on them which is important for the proper separation of errors coming from the boundary conditions and the model itself.
Wenxing Jia, Xiaoye Zhang, Hong Wang, Yaqiang Wang, Deying Wang, Junting Zhong, Wenjie Zhang, Lei Zhang, Lifeng Guo, Yadong Lei, Jizhi Wang, Yuanqin Yang, and Yi Lin
Geosci. Model Dev., 16, 6635–6670, https://doi.org/10.5194/gmd-16-6635-2023, https://doi.org/10.5194/gmd-16-6635-2023, 2023
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Most current studies on planetary boundary layer (PBL) parameterization schemes are relatively fragmented and lack systematic in-depth analysis and discussion. In this study, we comprehensively evaluate the performance capability of the PBL scheme in five typical regions of China in different seasons from the mechanism of the scheme and the effects of PBL schemes on the near-surface meteorological parameters, vertical structures of the PBL, PBL height, and turbulent diffusion.
William Rudisill, Alejandro Flores, and Rosemary Carroll
Geosci. Model Dev., 16, 6531–6552, https://doi.org/10.5194/gmd-16-6531-2023, https://doi.org/10.5194/gmd-16-6531-2023, 2023
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It is important to know how well atmospheric models do in mountains, but there are not very many weather stations. We evaluate rain and snow from a model from 1987–2020 in the Upper Colorado River basin against the available data. The model works rather well, but there are still some uncertainties in remote locations. We then use snow maps collected by aircraft, streamflow measurements, and some advanced statistics to help identify how well the model works in ways we could not do before.
Caroline Arnold, Shivani Sharma, Tobias Weigel, and David Greenberg
EGUsphere, https://doi.org/10.5194/egusphere-2023-2047, https://doi.org/10.5194/egusphere-2023-2047, 2023
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In weather and climate models, rain formation is simplified by parameterizations to be computationally efficient. We trained a machine learning algorithm, SuperdropNet, to emulate rain formation in warm clouds based on physically more accurate super-droplet simulations. Here, we validate SuperdropNet coupled to ICON in a warm bubble experiment. We find the coupled simulation runs stable and produces reasonable results, and present a computational benchmark for the coupling software.
Simon Rosanka, Holger Tost, Rolf Sander, Patrick Jöckel, Astrid Kerkweg, and Domenico Taraborrelli
EGUsphere, https://doi.org/10.5194/egusphere-2023-2587, https://doi.org/10.5194/egusphere-2023-2587, 2023
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The capabilities of the Modular Earth Submodel System (MESSy) are extended to account for non-equilibrium aqueous-phase chemistry in the representation of deliquescent aerosols. When applying the new development in a global simulation we find that MESSy’s bias in modelling routinely observed inorganic aerosol mass concentrations is reduced. Furthermore, the representation of fine aerosol pH is particularly improved in the marine boundary layer.
Angel Liduvino Vara-Vela, Christoffer Karoff, Noelia Rojas Benavente, and Janaina P. Nascimento
Geosci. Model Dev., 16, 6413–6431, https://doi.org/10.5194/gmd-16-6413-2023, https://doi.org/10.5194/gmd-16-6413-2023, 2023
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A 1-year simulation of atmospheric CH4 over Europe is performed and evaluated against observations based on the TROPOspheric Monitoring Instrument (TROPOMI). A good general model–observation agreement is found, with discrepancies reaching their minimum and maximum values during the summer peak season and winter months, respectively. A huge and under-explored potential for CH4 inverse modeling using improved TROPOMI XCH4 data sets in large-scale applications is identified.
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Short summary
The Lagrangian particle dispersion model FLEXPART-AROME was built to study air mass transport around La Réunion, a volcanic island in the southwest Indian Ocean. To harmonize turbulent transport between the numerical weather prediction model and the transport model, turbulent kinetic energy from AROME is directly used in FLEXPART-AROME using discrete interfaces between different turbulent regions. An adaptive time step was implemented to satisfy physical constraints on turbulent transport.
The Lagrangian particle dispersion model FLEXPART-AROME was built to study air mass transport...
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