Articles | Volume 9, issue 2
https://doi.org/10.5194/gmd-9-567-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-9-567-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model description paper
| 
10 Feb 2016
Model description paper |
| 10 Feb 2016
LIMA (v1.0): A quasi two-moment microphysical scheme driven by a multimodal population of cloud condensation and ice freezing nuclei
CNRM-GAME, Météo-France & CNRS, 42 avenue Gaspard Coriolis, 31057 Toulouse, France
J.-P. Pinty
Laboratoire d'Aérologie, University of Toulouse/CNRS, 14 avenue Edouard Belin, 31400 Toulouse, France
S. Berthet
Laboratoire d'Etudes en Géophysique et Océanographie Spatiales, CNRS/IRD/University of Toulouse/CNES, 14 avenue Edouard Belin, 31400 Toulouse, France
M. Leriche
Laboratoire d'Aérologie, University of Toulouse/CNRS, 14 avenue Edouard Belin, 31400 Toulouse, France
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Marie Taufour, Jean-Pierre Pinty, Christelle Barthe, Benoît Vié, and Chien Wang
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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.
Ian Boutle, Wayne Angevine, Jian-Wen Bao, Thierry Bergot, Ritthik Bhattacharya, Andreas Bott, Leo Ducongé, Richard Forbes, Tobias Goecke, Evelyn Grell, Adrian Hill, Adele L. Igel, Innocent Kudzotsa, Christine Lac, Bjorn Maronga, Sami Romakkaniemi, Juerg Schmidli, Johannes Schwenkel, Gert-Jan Steeneveld, and Benoît Vié
Atmos. Chem. Phys., 22, 319–333, https://doi.org/10.5194/acp-22-319-2022, https://doi.org/10.5194/acp-22-319-2022, 2022
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Fog forecasting is one of the biggest problems for numerical weather prediction. By comparing many models used for fog forecasting with others used for fog research, we hoped to help guide forecast improvements. We show some key processes that, if improved, will help improve fog forecasting, such as how water is deposited on the ground. We also showed that research models were not themselves a suitable baseline for comparison, and we discuss what future observations are required to improve them.
Samira Khodayar, Silvio Davolio, Paolo Di Girolamo, Cindy Lebeaupin Brossier, Emmanouil Flaounas, Nadia Fourrie, Keun-Ok Lee, Didier Ricard, Benoit Vie, Francois Bouttier, Alberto Caldas-Alvarez, and Veronique Ducrocq
Atmos. Chem. Phys., 21, 17051–17078, https://doi.org/10.5194/acp-21-17051-2021, https://doi.org/10.5194/acp-21-17051-2021, 2021
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Heavy precipitation (HP) constitutes a major meteorological threat in the western Mediterranean. Every year, recurrent events affect the area with fatal consequences. Despite this being a well-known issue, open questions still remain. The understanding of the underlying mechanisms and the modeling representation of the events must be improved. In this article we present the most recent lessons learned from the Hydrological Cycle in the Mediterranean Experiment (HyMeX).
Alistair Bell, Pauline Martinet, Olivier Caumont, Benoît Vié, Julien Delanoë, Jean-Charles Dupont, and Mary Borderies
Atmos. Meas. Tech., 14, 4929–4946, https://doi.org/10.5194/amt-14-4929-2021, https://doi.org/10.5194/amt-14-4929-2021, 2021
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This paper presents work towards making retrievals on the liquid water content in fog and low clouds. Future retrievals will rely on a radar simulator and high-resolution forecast. In this work, real observations are used to assess the errors associated with the simulator and forecast. A selection method to reduce errors associated with the forecast is proposed. It is concluded that the distribution of errors matches the requirements for future retrievals.
Christine Lac, Jean-Pierre Chaboureau, Valéry Masson, Jean-Pierre Pinty, Pierre Tulet, Juan Escobar, Maud Leriche, Christelle Barthe, Benjamin Aouizerats, Clotilde Augros, Pierre Aumond, Franck Auguste, Peter Bechtold, Sarah Berthet, Soline Bielli, Frédéric Bosseur, Olivier Caumont, Jean-Martial Cohard, Jeanne Colin, Fleur Couvreux, Joan Cuxart, Gaëlle Delautier, Thibaut Dauhut, Véronique Ducrocq, Jean-Baptiste Filippi, Didier Gazen, Olivier Geoffroy, François Gheusi, Rachel Honnert, Jean-Philippe Lafore, Cindy Lebeaupin Brossier, Quentin Libois, Thibaut Lunet, Céline Mari, Tomislav Maric, Patrick Mascart, Maxime Mogé, Gilles Molinié, Olivier Nuissier, Florian Pantillon, Philippe Peyrillé, Julien Pergaud, Emilie Perraud, Joris Pianezze, Jean-Luc Redelsperger, Didier Ricard, Evelyne Richard, Sébastien Riette, Quentin Rodier, Robert Schoetter, Léo Seyfried, Joël Stein, Karsten Suhre, Marie Taufour, Odile Thouron, Sandra Turner, Antoine Verrelle, Benoît Vié, Florian Visentin, Vincent Vionnet, and Philippe Wautelet
Geosci. Model Dev., 11, 1929–1969, https://doi.org/10.5194/gmd-11-1929-2018, https://doi.org/10.5194/gmd-11-1929-2018, 2018
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This paper presents the Meso-NH model version 5.4, which is an atmospheric non-hydrostatic research model that is applied on synoptic to turbulent scales. The model includes advanced numerical techniques and state-of-the-art physics parameterization schemes. It has been expanded to provide capabilities for a range of Earth system prediction applications such as chemistry and aerosols, electricity and lightning, hydrology, wildland fires, volcanic eruptions, and cyclones with ocean coupling.
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
Short summary
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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.
Lucas Pailler, Laurent Deguillaume, Hélène Lavanant, Isabelle Schmitz, Marie Hubert, Edith Nicol, Mickaël Ribeiro, Jean-Marc Pichon, Mickaël Vaïtilingom, Pamela Dominutti, Frédéric Burnet, Pierre Tulet, Maud Leriche, and Angelica Bianco
Atmos. Chem. Phys., 24, 5567–5584, https://doi.org/10.5194/acp-24-5567-2024, https://doi.org/10.5194/acp-24-5567-2024, 2024
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The composition of dissolved organic matter of cloud water has been investigated through non-targeted high-resolution mass spectrometry on only a few samples collected in the Northern Hemisphere. In this work, the chemical composition of samples collected at Réunion Island (SH) is investigated and compared to samples collected at Puy de Dôme (NH). Sampling, analysis and data treatment with the same methodology produced a unique dataset for investigating the molecular composition of clouds.
Maud Leriche, Pierre Tulet, Laurent Deguillaume, Frédéric Burnet, Aurélie Colomb, Agnès Borbon, Corinne Jambert, Valentin Duflot, Stéphan Houdier, Jean-Luc Jaffrezo, Mickaël Vaïtilingom, Pamela Dominutti, Manon Rocco, Camille Mouchel-Vallon, Samira El Gdachi, Maxence Brissy, Maroua Fathalli, Nicolas Maury, Bert Verreyken, Crist Amelynck, Niels Schoon, Valérie Gros, Jean-Marc Pichon, Mickael Ribeiro, Eric Pique, Emmanuel Leclerc, Thierry Bourrianne, Axel Roy, Eric Moulin, Joël Barrie, Jean-Marc Metzger, Guillaume Péris, Christian Guadagno, Chatrapatty Bhugwant, Jean-Mathieu Tibere, Arnaud Tournigand, Evelyn Freney, Karine Sellegri, Anne-Marie Delort, Pierre Amato, Muriel Joly, Jean-Luc Baray, Pascal Renard, Angelica Bianco, Anne Réchou, and Guillaume Payen
Atmos. Chem. Phys., 24, 4129–4155, https://doi.org/10.5194/acp-24-4129-2024, https://doi.org/10.5194/acp-24-4129-2024, 2024
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Aerosol particles in the atmosphere play a key role in climate change and air pollution. A large number of aerosol particles are formed from the oxidation of volatile organic compounds (VOCs and secondary organic aerosols – SOA). An important field campaign was organized on Réunion in March–April 2019 to understand the formation of SOA in a tropical atmosphere mostly influenced by VOCs emitted by forest and in the presence of clouds. This work synthesizes the results of this campaign.
Pamela A. Dominutti, Pascal Renard, Mickaël Vaïtilingom, Angelica Bianco, Jean-Luc Baray, Agnès Borbon, Thierry Bourianne, Frédéric Burnet, Aurélie Colomb, Anne-Marie Delort, Valentin Duflot, Stephan Houdier, Jean-Luc Jaffrezo, Muriel Joly, Martin Leremboure, Jean-Marc Metzger, Jean-Marc Pichon, Mickaël Ribeiro, Manon Rocco, Pierre Tulet, Anthony Vella, Maud Leriche, and Laurent Deguillaume
Atmos. Chem. Phys., 22, 505–533, https://doi.org/10.5194/acp-22-505-2022, https://doi.org/10.5194/acp-22-505-2022, 2022
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We present here the results obtained during an intensive field campaign conducted in March to April 2019 in Reunion. Our study integrates a comprehensive chemical and microphysical characterization of cloud water. Our investigations reveal that air mass history and cloud microphysical properties do not fully explain the variability observed in their chemical composition. This highlights the complexity of emission sources, multiphasic exchanges, and transformations in clouds.
Ian Boutle, Wayne Angevine, Jian-Wen Bao, Thierry Bergot, Ritthik Bhattacharya, Andreas Bott, Leo Ducongé, Richard Forbes, Tobias Goecke, Evelyn Grell, Adrian Hill, Adele L. Igel, Innocent Kudzotsa, Christine Lac, Bjorn Maronga, Sami Romakkaniemi, Juerg Schmidli, Johannes Schwenkel, Gert-Jan Steeneveld, and Benoît Vié
Atmos. Chem. Phys., 22, 319–333, https://doi.org/10.5194/acp-22-319-2022, https://doi.org/10.5194/acp-22-319-2022, 2022
Short summary
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Fog forecasting is one of the biggest problems for numerical weather prediction. By comparing many models used for fog forecasting with others used for fog research, we hoped to help guide forecast improvements. We show some key processes that, if improved, will help improve fog forecasting, such as how water is deposited on the ground. We also showed that research models were not themselves a suitable baseline for comparison, and we discuss what future observations are required to improve them.
Samira Khodayar, Silvio Davolio, Paolo Di Girolamo, Cindy Lebeaupin Brossier, Emmanouil Flaounas, Nadia Fourrie, Keun-Ok Lee, Didier Ricard, Benoit Vie, Francois Bouttier, Alberto Caldas-Alvarez, and Veronique Ducrocq
Atmos. Chem. Phys., 21, 17051–17078, https://doi.org/10.5194/acp-21-17051-2021, https://doi.org/10.5194/acp-21-17051-2021, 2021
Short summary
Short summary
Heavy precipitation (HP) constitutes a major meteorological threat in the western Mediterranean. Every year, recurrent events affect the area with fatal consequences. Despite this being a well-known issue, open questions still remain. The understanding of the underlying mechanisms and the modeling representation of the events must be improved. In this article we present the most recent lessons learned from the Hydrological Cycle in the Mediterranean Experiment (HyMeX).
Alistair Bell, Pauline Martinet, Olivier Caumont, Benoît Vié, Julien Delanoë, Jean-Charles Dupont, and Mary Borderies
Atmos. Meas. Tech., 14, 4929–4946, https://doi.org/10.5194/amt-14-4929-2021, https://doi.org/10.5194/amt-14-4929-2021, 2021
Short summary
Short summary
This paper presents work towards making retrievals on the liquid water content in fog and low clouds. Future retrievals will rely on a radar simulator and high-resolution forecast. In this work, real observations are used to assess the errors associated with the simulator and forecast. A selection method to reduce errors associated with the forecast is proposed. It is concluded that the distribution of errors matches the requirements for future retrievals.
Keun-Ok Lee, Brice Barret, Eric L. Flochmoën, Pierre Tulet, Silvia Bucci, Marc von Hobe, Corinna Kloss, Bernard Legras, Maud Leriche, Bastien Sauvage, Fabrizio Ravegnani, and Alexey Ulanovsky
Atmos. Chem. Phys., 21, 3255–3274, https://doi.org/10.5194/acp-21-3255-2021, https://doi.org/10.5194/acp-21-3255-2021, 2021
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This paper focuses on the emission sources and pathways of pollution from the boundary layer to the Asian monsoon anticyclone (AMA) during the StratoClim aircraft campaign period. Simulations with the Meso-NH cloud-chemistry model at a horizontal resolution of 15 km are performed over the Asian region to characterize the impact of monsoon deep convection on the composition of AMA and on the formation of the Asian tropopause aerosol layer during the StratoClim campaign.
Setigui Aboubacar Keita, Eric Girard, Jean-Christophe Raut, Maud Leriche, Jean-Pierre Blanchet, Jacques Pelon, Tatsuo Onishi, and Ana Cirisan
Geosci. Model Dev., 13, 5737–5755, https://doi.org/10.5194/gmd-13-5737-2020, https://doi.org/10.5194/gmd-13-5737-2020, 2020
Émilie Poirier, Julie M. Thériault, and Maud Leriche
Hydrol. Earth Syst. Sci., 23, 4097–4111, https://doi.org/10.5194/hess-23-4097-2019, https://doi.org/10.5194/hess-23-4097-2019, 2019
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The impact of phase changes aloft on the precipitation distribution in the Kananaskis Valley, Alberta, was studied. The model reproduces well the atmospheric conditions and precipitation pattern. In this region, sublimation has a greater impact on the evolution of the precipitation than melting. The trajectories of hydrometeors explain the precipitation distribution in the valley, which can impact snowpacks. The amount of snow at the surface also depends on the strength of the downslope flow.
Christine Lac, Jean-Pierre Chaboureau, Valéry Masson, Jean-Pierre Pinty, Pierre Tulet, Juan Escobar, Maud Leriche, Christelle Barthe, Benjamin Aouizerats, Clotilde Augros, Pierre Aumond, Franck Auguste, Peter Bechtold, Sarah Berthet, Soline Bielli, Frédéric Bosseur, Olivier Caumont, Jean-Martial Cohard, Jeanne Colin, Fleur Couvreux, Joan Cuxart, Gaëlle Delautier, Thibaut Dauhut, Véronique Ducrocq, Jean-Baptiste Filippi, Didier Gazen, Olivier Geoffroy, François Gheusi, Rachel Honnert, Jean-Philippe Lafore, Cindy Lebeaupin Brossier, Quentin Libois, Thibaut Lunet, Céline Mari, Tomislav Maric, Patrick Mascart, Maxime Mogé, Gilles Molinié, Olivier Nuissier, Florian Pantillon, Philippe Peyrillé, Julien Pergaud, Emilie Perraud, Joris Pianezze, Jean-Luc Redelsperger, Didier Ricard, Evelyne Richard, Sébastien Riette, Quentin Rodier, Robert Schoetter, Léo Seyfried, Joël Stein, Karsten Suhre, Marie Taufour, Odile Thouron, Sandra Turner, Antoine Verrelle, Benoît Vié, Florian Visentin, Vincent Vionnet, and Philippe Wautelet
Geosci. Model Dev., 11, 1929–1969, https://doi.org/10.5194/gmd-11-1929-2018, https://doi.org/10.5194/gmd-11-1929-2018, 2018
Short summary
Short summary
This paper presents the Meso-NH model version 5.4, which is an atmospheric non-hydrostatic research model that is applied on synoptic to turbulent scales. The model includes advanced numerical techniques and state-of-the-art physics parameterization schemes. It has been expanded to provide capabilities for a range of Earth system prediction applications such as chemistry and aerosols, electricity and lightning, hydrology, wildland fires, volcanic eruptions, and cyclones with ocean coupling.
Fabien Brosse, Maud Leriche, Céline Mari, and Fleur Couvreux
Atmos. Chem. Phys., 18, 6601–6624, https://doi.org/10.5194/acp-18-6601-2018, https://doi.org/10.5194/acp-18-6601-2018, 2018
Short summary
Short summary
The cleansing capacity of the atmosphere is studied through the hydroxyl radical (OH) chemical reactivity in numerical simulations of natural and urban environments. Turbulence-driven segregation of chemical compounds in the atmospheric boundary layer is explored and may partially explain discrepancies between observed and modeled OH reactivity in both environments.
Clémence Rose, Nadine Chaumerliac, Laurent Deguillaume, Hélène Perroux, Camille Mouchel-Vallon, Maud Leriche, Luc Patryl, and Patrick Armand
Atmos. Chem. Phys., 18, 2225–2242, https://doi.org/10.5194/acp-18-2225-2018, https://doi.org/10.5194/acp-18-2225-2018, 2018
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A detailed aqueous phase mechanism CLEPS 1.1 is coupled with warm microphysics including activation of aerosol particles into cloud droplets. Simulated aqueous concentrations of carboxylic acids are close to the long-term measurements conducted at Puy de Dôme (France). Sensitivity tests show that formic and acetic acids mainly originate from the gas phase with highly variable aqueous-phase reactivity depending on cloud pH, while C3–C4 carboxylic acids mainly originate from the particulate phase.
Camille Mouchel-Vallon, Laurent Deguillaume, Anne Monod, Hélène Perroux, Clémence Rose, Giovanni Ghigo, Yoann Long, Maud Leriche, Bernard Aumont, Luc Patryl, Patrick Armand, and Nadine Chaumerliac
Geosci. Model Dev., 10, 1339–1362, https://doi.org/10.5194/gmd-10-1339-2017, https://doi.org/10.5194/gmd-10-1339-2017, 2017
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The Cloud Explicit Physico-chemical Scheme (CLEPS 1.0) describes oxidation of water-soluble organic compounds resulting from isoprene oxidation. It is based on structure activity relationships (SARs) (global rate constants and branching ratios for HO• abstraction and addition) and GROMHE SAR (Henry's law constants for undocumented species). It is coupled to the MCM gas phase mechanism and is included in a model using the DSMACC model and KPP to analyze experimental and field data.
Alicia Gressent, Bastien Sauvage, Daniel Cariolle, Mathew Evans, Maud Leriche, Céline Mari, and Valérie Thouret
Atmos. Chem. Phys., 16, 5867–5889, https://doi.org/10.5194/acp-16-5867-2016, https://doi.org/10.5194/acp-16-5867-2016, 2016
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In chemical transport models, NOx emitted by lightning (LNOx) is instantaneously diluted into the grid. A plume-in-grid parameterization to account for the sub-grid chemistry of LNOx is presented. This approach was implemented into the GEOS-Chem model and leads to a relative increase of NOx and O3 (18 % and 2 %, respectively, in July) on a large scale downwind of lightning emissions and a relative decrease (25 % and 8 %, respectively, over central Africa in July) over the regions of emissions.
C. Barbet, L. Deguillaume, N. Chaumerliac, M. Leriche, A. Berger, E. Freney, A. Colomb, K. Sellegri, L. Patryl, and P. Armand
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-15-13395-2015, https://doi.org/10.5194/acpd-15-13395-2015, 2015
Preprint withdrawn
M. Leriche, J.-P. Pinty, C. Mari, and D. Gazen
Geosci. Model Dev., 6, 1275–1298, https://doi.org/10.5194/gmd-6-1275-2013, https://doi.org/10.5194/gmd-6-1275-2013, 2013
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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
Short summary
Short summary
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.
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.
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.
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.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-129, https://doi.org/10.5194/gmd-2024-129, 2024
Revised manuscript accepted for GMD
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Orbital-radar is a Python tool transferring sub-orbital radar data (ground-based, airborne, and forward-simulated NWP) into synthetical space-borne cloud profiling radar data mimicking the platform characteristics, e.g. EarthCARE or CloudSat CPR. The novelty of orbital-radar is the simulation platform characteristic noise floors and errors. By this long time data sets can be transformed into synthetic observations for Cal/Valor sensitivity studies for new or future satellite missions.
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.
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.
Tianning Su and Yunyan Zhang
Geosci. Model Dev., 17, 6319–6336, https://doi.org/10.5194/gmd-17-6319-2024, https://doi.org/10.5194/gmd-17-6319-2024, 2024
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Using 2 decades of field observations over the Southern Great Plains, this study developed a deep-learning model to simulate the complex dynamics of boundary layer clouds. The deep-learning model can serve as the cloud parameterization within reanalysis frameworks, offering insights into improving the simulation of low clouds. By quantifying biases due to various meteorological factors and parameterizations, this deep-learning-driven approach helps bridge the observation–modeling divide.
Siyuan Chen, Yi Zhang, Yiming Wang, Zhuang Liu, Xiaohan Li, and Wei Xue
Geosci. Model Dev., 17, 6301–6318, https://doi.org/10.5194/gmd-17-6301-2024, https://doi.org/10.5194/gmd-17-6301-2024, 2024
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This study explores strategies and techniques for implementing mixed-precision code optimization within an atmosphere model dynamical core. The coded equation terms in the governing equations that are sensitive (or insensitive) to the precision level have been identified. The performance of mixed-precision computing in weather and climate simulations was analyzed.
Sam O. Owens, Dipanjan Majumdar, Chris E. Wilson, Paul Bartholomew, and Maarten van Reeuwijk
Geosci. Model Dev., 17, 6277–6300, https://doi.org/10.5194/gmd-17-6277-2024, https://doi.org/10.5194/gmd-17-6277-2024, 2024
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Designing cities that are resilient, sustainable, and beneficial to health requires an understanding of urban climate and air quality. This article presents an upgrade to the multi-physics numerical model uDALES, which can simulate microscale airflow, heat transfer, and pollutant dispersion in urban environments. This upgrade enables it to resolve realistic urban geometries more accurately and to take advantage of the resources available on current and future high-performance computing systems.
Felipe Cifuentes, Henk Eskes, Folkert Boersma, Enrico Dammers, and Charlotte Bryan
EGUsphere, https://doi.org/10.5194/egusphere-2024-2225, https://doi.org/10.5194/egusphere-2024-2225, 2024
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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 derived 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 NO2 lifetime, NOX:NO2 ratio, and NO2 profile shapes were correctly modeled. This introduces a strong model dependency, reducing the simplicity of the original FDA formulation.
Allison A. Wing, Levi G. Silvers, and Kevin A. Reed
Geosci. Model Dev., 17, 6195–6225, https://doi.org/10.5194/gmd-17-6195-2024, https://doi.org/10.5194/gmd-17-6195-2024, 2024
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This paper presents the experimental design for a model intercomparison project to study tropical clouds and climate. It is a follow-up from a prior project that used a simplified framework for tropical climate. The new project adds one new component – a specified pattern of sea surface temperatures as the lower boundary condition. We provide example results from one cloud-resolving model and one global climate model and test the sensitivity to the experimental parameters.
Astrid Kerkweg, Timo Kirfel, Doung H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-117, https://doi.org/10.5194/gmd-2024-117, 2024
Revised manuscript accepted for GMD
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This article introduces the MESSy DWARF. Usually, the Modular Earth Submodel System (MESSy) is linked to full dynamical models to build chemistry climate models. However, due to the modular concept of MESSy, and the newly developed DWARF component, it is now possible to create simplified models containing just one or some process descriptions. This renders very useful for technical optimisation (e.g., GPU porting) and can be used to create less complex models, e.g., a chemical box model.
Philip G. Sansom and Jennifer L. Catto
Geosci. Model Dev., 17, 6137–6151, https://doi.org/10.5194/gmd-17-6137-2024, https://doi.org/10.5194/gmd-17-6137-2024, 2024
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Weather fronts bring a lot of rain and strong winds to many regions of the mid-latitudes. We have developed an updated method of identifying these fronts in gridded data that can be used on new datasets with small grid spacing. The method can be easily applied to different datasets due to the use of open-source software for its development and shows improvements over similar previous methods. We present an updated estimate of the average frequency of fronts over the past 40 years.
Kelly M. Núñez Ocasio and Zachary L. Moon
Geosci. Model Dev., 17, 6035–6049, https://doi.org/10.5194/gmd-17-6035-2024, https://doi.org/10.5194/gmd-17-6035-2024, 2024
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TAMS is an open-source Python-based package for tracking and classifying mesoscale convective systems that can be used to study observed and simulated systems. Each step of the algorithm is described in this paper with examples showing how to make use of visualization and post-processing tools within the package. A unique and valuable feature of this tracker is its support for unstructured grids in the identification stage and grid-independent tracking.
Irene C. Dedoussi, Daven K. Henze, Sebastian D. Eastham, Raymond L. Speth, and Steven R. H. Barrett
Geosci. Model Dev., 17, 5689–5703, https://doi.org/10.5194/gmd-17-5689-2024, https://doi.org/10.5194/gmd-17-5689-2024, 2024
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Atmospheric model gradients provide a meaningful tool for better understanding the underlying atmospheric processes. Adjoint modeling enables computationally efficient gradient calculations. We present the adjoint of the GEOS-Chem unified chemistry extension (UCX). With this development, the GEOS-Chem adjoint model can capture stratospheric ozone and other processes jointly with tropospheric processes. We apply it to characterize the Antarctic ozone depletion potential of active halogen species.
Sylvain Mailler, Sotirios Mallios, Arineh Cholakian, Vassilis Amiridis, Laurent Menut, and Romain Pennel
Geosci. Model Dev., 17, 5641–5655, https://doi.org/10.5194/gmd-17-5641-2024, https://doi.org/10.5194/gmd-17-5641-2024, 2024
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We propose two explicit expressions to calculate the settling speed of solid atmospheric particles with prolate spheroidal shapes. The first formulation is based on theoretical arguments only, while the second one is based on computational fluid dynamics calculations. We show that the first method is suitable for virtually all atmospheric aerosols, provided their shape can be adequately described as a prolate spheroid, and we provide an implementation of the first method in AerSett v2.0.2.
Hejun Xie, Lei Bi, and Wei Han
Geosci. Model Dev., 17, 5657–5688, https://doi.org/10.5194/gmd-17-5657-2024, https://doi.org/10.5194/gmd-17-5657-2024, 2024
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A radar operator plays a crucial role in utilizing radar observations to enhance numerical weather forecasts. However, developing an advanced radar operator is challenging due to various complexities associated with the wave scattering by non-spherical hydrometeors, radar beam propagation, and multiple platforms. In this study, we introduce a novel radar operator named the Accurate and Efficient Radar Operator developed by ZheJiang University (ZJU-AERO) which boasts several unique features.
Jonathan J. Day, Gunilla Svensson, Barbara Casati, Taneil Uttal, Siri-Jodha Khalsa, Eric Bazile, Elena Akish, Niramson Azouz, Lara Ferrighi, Helmut Frank, Michael Gallagher, Øystein Godøy, Leslie M. Hartten, Laura X. Huang, Jareth Holt, Massimo Di Stefano, Irene Suomi, Zen Mariani, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Teresa Remes, Rostislav Fadeev, Amy Solomon, Johanna Tjernström, and Mikhail Tolstykh
Geosci. Model Dev., 17, 5511–5543, https://doi.org/10.5194/gmd-17-5511-2024, https://doi.org/10.5194/gmd-17-5511-2024, 2024
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The YOPP site Model Intercomparison Project (YOPPsiteMIP), which was designed to facilitate enhanced weather forecast evaluation in polar regions, is discussed here, focussing on describing the archive of forecast data and presenting a multi-model evaluation at Arctic supersites during February and March 2018. The study highlights an underestimation in boundary layer temperature variance that is common across models and a related inability to forecast cold extremes at several of the sites.
Hossain Mohammed Syedul Hoque, Kengo Sudo, Hitoshi Irie, Yanfeng He, and Md Firoz Khan
Geosci. Model Dev., 17, 5545–5571, https://doi.org/10.5194/gmd-17-5545-2024, https://doi.org/10.5194/gmd-17-5545-2024, 2024
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Using multi-platform observations, we validated global formaldehyde (HCHO) simulations from a chemistry transport model. HCHO is a crucial intermediate in the chemical catalytic cycle that governs the ozone formation in the troposphere. The model was capable of replicating the observed spatiotemporal variability in HCHO. In a few cases, the model's capability was limited. This is attributed to the uncertainties in the observations and the model parameters.
Zijun Liu, Li Dong, Zongxu Qiu, Xingrong Li, Huiling Yuan, Dongmei Meng, Xiaobin Qiu, Dingyuan Liang, and Yafei Wang
Geosci. Model Dev., 17, 5477–5496, https://doi.org/10.5194/gmd-17-5477-2024, https://doi.org/10.5194/gmd-17-5477-2024, 2024
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In this study, we completed a series of simulations with MPAS-Atmosphere (version 7.3) to study the extreme precipitation event of Henan, China, during 20–22 July 2021. We found the different performance of two built-in parameterization scheme suites (mesoscale and convection-permitting suites) with global quasi-uniform and variable-resolution meshes. This study holds significant implications for advancing the understanding of the scale-aware capability of MPAS-Atmosphere.
Laurent Menut, Arineh Cholakian, Romain Pennel, Guillaume Siour, Sylvain Mailler, Myrto Valari, Lya Lugon, and Yann Meurdesoif
Geosci. Model Dev., 17, 5431–5457, https://doi.org/10.5194/gmd-17-5431-2024, https://doi.org/10.5194/gmd-17-5431-2024, 2024
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A new version of the CHIMERE model is presented. This version contains both computational and physico-chemical changes. The computational changes make it easy to choose the variables to be extracted as a result, including values of maximum sub-hourly concentrations. Performance tests show that the model is 1.5 to 2 times faster than the previous version for the same setup. Processes such as turbulence, transport schemes and dry deposition have been modified and updated.
G. Alexander Sokolowsky, Sean W. Freeman, William K. Jones, Julia Kukulies, Fabian Senf, Peter J. Marinescu, Max Heikenfeld, Kelcy N. Brunner, Eric C. Bruning, Scott M. Collis, Robert C. Jackson, Gabrielle R. Leung, Nils Pfeifer, Bhupendra A. Raut, Stephen M. Saleeby, Philip Stier, and Susan C. van den Heever
Geosci. Model Dev., 17, 5309–5330, https://doi.org/10.5194/gmd-17-5309-2024, https://doi.org/10.5194/gmd-17-5309-2024, 2024
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Building on previous analysis tools developed for atmospheric science, the original release of the Tracking and Object-Based Analysis (tobac) Python package, v1.2, was open-source, modular, and insensitive to the type of gridded input data. Here, we present the latest version of tobac, v1.5, which substantially improves scientific capabilities and computational efficiency from the previous version. These enhancements permit new uses for tobac in atmospheric science and potentially other fields.
Cited articles
ACPC: Aerosols, Clouds, Precipitation and Climate, Steering Committee:
Science Plan and Implementation Strategy, Tech. rep., IGAC (International
Global Atmospheric Chemistry), Boulder, available at:
http://www.igacproject.org/sites/all/themes/bluemasters/images/2009_ACPC_SciencePlan_FINAL.pdf
(last access: 2 September 2015), 2009.
Albrecht, B. A.: Aerosols, cloud microphysics, and fractional cloudiness,
Science, 245, 1227–1230, 1989.
Andreae, M. O., Rosenfeld, D., Artaxo, P., Costa, A., Frank, G., Longo, K.,
and Silva-Dias, M.: Smoking rain clouds over the Amazon, Science, 303,
1337–1342, 2004.
Aouizerats, B., Thouron, O., Tulet, P., Mallet, M., Gomes, L., and Henzing,
J. S.: Development of an online radiative module for the computation of
aerosol optical properties in 3-D atmospheric models: validation during the
EUCAARI campaign, Geosci. Model Dev., 3, 553–564,
https://doi.org/10.5194/gmd-3-553-2010, 2010.
Barahona, D. and Nenes, A.: Parameterizing the competition between
homogeneous and heterogeneous freezing in ice cloud formation – polydisperse
ice nuclei, Atmos. Chem. Phys., 9, 5933–5948, https://doi.org/10.5194/acp-9-5933-2009,
2009.
Beheng, K. D.: Microphysical properties of glaciating cumulus clouds:
comparison of measurements with a numerical simulation, Q. J. Roy. Meteor.
Soc., 113, 1377–1382,
https://doi.org/10.1002/qj.49711347815,
1987.
Berry, E. X. and Reinhardt, R. L.: An analysis of cloud drop growth by
collection Part II. Single initial distributions, J. Atmos. Sci., 31,
1825–1831, 1974.
Berthet, S., Leriche, M., Pinty, J.-P., Cuesta, J., and Pigeon, G.:
Scavenging of aerosol particles by rain in a cloud resolving model, Atmos.
Res., 96, 325–336, 2010.
Caniaux, G., Redelsperger, J., and Lafore, J.: A numerical study of the
stratiform region of a fast-moving squall line. Part I: General description
and water and heat budgets, J. Atmos. Sci., 51, 2046–2074, 1994.
Chou, C., Formenti, P., Maille, M., Ausset, P., Helas, G., Harrison, M., and
Osborne, S.: Size distribution, shape, and composition of mineral dust
aerosols collected during the African Monsoon Multidisciplinary Analysis
Special Observation Period 0: dust and biomass-burning experiment field
campaign in Niger, January 2006, J. Geophys. Res.-Atmos.,
113, D00C10,
https://doi.org/10.1029/2008JD009897, 2008.
Cohard, J.-M. and Pinty, J.-P.: A comprehensive two-moment warm microphysical
bulk scheme. I: Description and tests, Q. J. Roy. Meteor. Soc., 126,
1815–1842,
https://doi.org/10.1002/qj.49712656613,
2000a.
Cohard, J.-M. and Pinty, J.-P.: A comprehensive two-moment warm microphysical
bulk scheme. II: 2D experiments with a non-hydrostatic model, Q. J. Roy.
Meteor. Soc., 126, 1843–1859,
https://doi.org/10.1002/qj.49712656614,
2000b.
Cohard, J.-M., Pinty, J.-P., and Bedos, C.: Extending Twomey's analytical
estimate of nucleated cloud droplet concentrations from CCN spectra, J.
Atmos. Sci., 55, 3348–3357, 1998.
Cohard, J.-M., Pinty, J.-P., and Suhre, K.: On the parameterization of
activation spectra from cloud condensation nuclei microphysical properties,
J. Geophys. Res.-Atmos., 105, 11753–11766,
https://doi.org/10.1029/1999JD901195,
2000.
DeMott, P., Prenni, A., Liu, X., Kreidenweis, S., Petters, M., Twohy, C.,
Richardson, M., Eidhammer, T., and Rogers, D.: Predicting global atmospheric
ice nuclei distributions and their impacts on climate, P. Natl. Acad. Sci.
USA, 107, 11217–11222, 2010.
Diehl, K. and Wurzler, S.: Heterogeneous drop freezing in the immersion mode:
model calculations considering soluble and insoluble particles in the drops,
J. Atmos. Sci., 61, 2063–2072, 2004.
Ferek, R. J., Garrett, T., Hobbs, P. V., Strader, S., Johnson, D.,
Taylor, J. P., Nielsen, K., Ackerman, A. S., Kogan, Y., Liu, Q.,
Albrecht, B. A., and Babb, D.: Drizzle suppression in ship tracks, J. Atmos.
Sci., 57, 2707–2728, 2000.
Fouquart, Y. and Bonnel, B.: Computations of solar heating of the earth's
atmosphere – a new parameterization, Beitraege zur Physik der Atmosphaere,
53, 35–62, 1980.
Geoffroy, O., Brenguier, J.-L., and Sandu, I.: Relationship between drizzle
rate, liquid water path and droplet concentration at the scale of a
stratocumulus cloud system, Atmos. Chem. Phys., 8, 4641–4654,
https://doi.org/10.5194/acp-8-4641-2008, 2008.
Gilmore, M. S. and Straka, J. M.: The Berry and Reinhardt autoconversion
parameterization: a digest, J. Appl. Meteorol. Clim., 47, 375–396, 2008.
Hallett, J. and Mossop, S. C.: Production of secondary ice particles during
the riming process, Nature, 249, 26–28,
https://doi.org/10.1038/249026a0, 1974.
Harrington, J. Y., Meyers, M. P., Walko, R. L., and Cotton, W. R.:
Parameterization of ice crystal conversion processes due to vapor deposition
for mesoscale models using double-moment basis functions. Part I: Basic
formulation and parcel model results, J. Atmos. Sci., 52, 4344–4366,
https://doi.org/10.1175/1520-0469(1995)052<4344:POICCP>2.0.CO;2,
1995.
Johnson, B., Shine, K., and Forster, P.: The semi-direct aerosol effect:
impact of absorbing aerosols on marine stratocumulus, Q. J. Roy. Meteor.
Soc., 130, 1407–1422, 2004.
Kärcher, B. and Lohmann, U.: A parameterization of cirrus cloud
formation: homogeneous freezing of supercooled aerosols, J. Geophys.
Res.-Atmos.,
107, AAC4.1–AAC4.10,
https://doi.org/10.1029/2001JD000470, 2002.
Khairoutdinov, M. and Kogan, Y.: A new cloud physics parameterization in a
large-eddy simulation model of marine stratocumulus, Mon. Weather Rev., 128,
229–243, 2000.
Khvorostyanov, V. I. and Curry, J. A.: The theory of ice nucleation by
heterogeneous freezing of deliquescent mixed CC N. Part I: Critical radius,
energy, and nucleation rate, J. Atmos. Sci., 61, 2676–2691, 2004.
Kogan, Y.: A cumulus cloud microphysics parameterization for cloud-resolving
models, J. Atmos. Sci., 70, 1423–1436, 2013.
Lafore, J. P., Stein, J., Asencio, N., Bougeault, P.,
Ducrocq, V., Duron, J., Fischer, C., Héreil, P., Mascart, P., Masson, V.,
Pinty, J. P., Redelsperger, J. L., Richard, E., and Vilà-Guerau de
Arellano, J.: The Meso-NH Atmospheric Simulation System. Part I: adiabatic
formulation and control simulations, Ann. Geophys., 16, 90–109,
https://doi.org/10.1007/s00585-997-0090-6,
1998.
Lascaux, F., Richard, E., and Pinty, J.-P.: Numerical simulations of three
different MAP IOPs and the associated microphysical processes, Q. J. Roy.
Meteor. Soc., 132, 1907–1926, 2006.
Lebo, Z. J. and Morrison, H.: A novel Scheme for parameterizing aerosol
processing in warm clouds, J. Atmos. Sci., 70, 3576–3598, 2013.
Lim, K.-S. S. and Hong, S.-Y.: Development of an effective double-moment
cloud microphysics scheme with prognostic cloud condensation nuclei (CCN) for
weather and climate models, Mon. Weather Rev., 138, 1587–1612, 2010.
Long, A. B.: Solutions to the droplet collection equation for polynomial
kernels, J. Atmos. Sci., 31, 1040–1052, 1974.
Meyers, M. P., DeMott, P. J., and Cotton, W. R.: New primary ice-nucleation
parameterizations in an explicit cloud model, J. Appl. Meteorol., 31,
708–721, 1992.
Meyers, M. P., Walko, R. L., Harrington, J. Y., and Cotton, W. R.: New RAMS
cloud microphysics parameterization. Part II: The two-moment scheme, Atmos.
Res., 45, 3–39, 1997.
Milbrandt, J. and Yau, M.: A multimoment bulk microphysics parameterization.
Part I: Analysis of the role of the spectral shape parameter, J. Atmos. Sci.,
62, 3051–3064, 2005a.
Milbrandt, J. and Yau, M.: A multimoment bulk microphysics parameterization.
Part II: A proposed three-moment closure and scheme description, J. Atmos.
Sci., 62, 3065–3081, 2005b.
Mlawer, E. J., Taubman, S. J., Brown, P. D., Iacono, M. J., and
Clough, S. A.: Radiative transfer for inhomogeneous atmospheres: RRTM, a
validated correlated-k model for the longwave, J. Geophys. Res.-Atmos., 102,
16663–16682, 1997.
Morrison, H. and Grabowski, W. W.: Comparison of bulk and bin warm-rain
microphysics models using a kinematic framework, J. Atmos. Sci., 64,
2839–2861, 2007.
Morrison, H. and Grabowski, W. W.: A novel approach for representing ice
microphysics in models: description and tests using a kinematic framework, J.
Atmos. Sci., 65, 1528–1548, 2008.
Morrison, H., Curry, J., and Khvorostyanov, V.: A new double-moment
microphysics parameterization for application in cloud and climate models.
Part I: Description, J. Atmos. Sci., 62, 1665–1677, 2005.
Morrison, H., Thompson, G., and Tatarskii, V.: Impact of cloud microphysics
on the development of trailing stratiform precipitation in a simulated squall
line: comparison of one-and two-moment schemes, Mon. Weather Rev., 137,
991–1007, 2009.
Muhlbauer, A. and Lohmann, U.: Orographic mixed-phase stratiform cloud case,
in: WMO Cloud Modeling Workshop, Cozumel, Mexico, 14–17 July 2008, available
at:
http://www.rap.ucar.edu/~gthompsn/workshop2008/case1_description.pdf
(last access: 2 September 2015), 1–22, 2008.
Muhlbauer, A., Grabowski, W. W., Malinowski, S. P., Ackerman, T. P., Bryan,
G. H., Lebo, Z. J., Milbrandt, J. A., Morrison, H., Ovchinnikov, M.,
Tessendorf, S., Thériault, J. M., and Thompson, G.: Reexamination of the
state of the art of cloud modeling shows real improvements, B. Am. Meteorol.
Soc., 94, ES45–ES48, 2013.
Niedermeier, D., Shaw, R. A., Hartmann, S., Wex, H., Clauss, T.,
Voigtländer, J., and Stratmann, F.: Heterogeneous ice nucleation:
exploring the transition from stochastic to singular freezing behavior,
Atmos. Chem. Phys., 11, 8767–8775, https://doi.org/10.5194/acp-11-8767-2011, 2011.
Phillips, V. T., DeMott, P. J., and Andronache, C.: An empirical
parameterization of heterogeneous ice nucleation for multiple chemical
species of aerosol, J. Atmos. Sci., 65, 2757–2783, 2008.
Phillips, V. T., Demott, P. J., Andronache, C., Pratt, K. A., Prather, K. A.,
Subramanian, R., and Twohy, C.: Improvements to an empirical parameterization
of heterogeneous ice nucleation and its comparison with observations, J.
Atmos. Sci., 70, 378–409, 2013.
Pinty, J. and Jabouille, P.: A mixed-phase cloud parameterization for use in
a mesoscale non-hydrostatic model: simulations of a squall line and of
orographic precipitations, in: Conf. on Cloud Physics, 17–21 August 1998,
Everett, Washington, 217–220, 1998.
Press, W. H., Teukolsky, S. A., Vetterling, W. T., and Flannery, B. P.:
Numerical Recipes in FORTRAN: The Art of Scientific Computing, Cambridge
Univ. Press, New York, 963 pp., 1992.
Pruppacher, H. R.: A new look at homogeneous ice nucleation in supercooled
water drops, J. Atmos. Sci., 52, 1924–1933,
https://doi.org/10.1175/1520-0469(1995)052<1924:ANLAHI>2.0.CO;2,
1995.
Pruppacher, H. R. and Klett, J. D.: Microphysics of Clouds and Precipitation,
Kluwer Academic Publishers, Dordrecht and Boston, 1997.
Reisin, T., Levin, Z., and Tzivion, S.: Rain production in convective clouds
as simulated in an axisymmetric model with detailed microphysics. Part I:
Description of the model, J. Atmos. Sci., 53, 497–519, 1996.
Rosenfeld, D., Lohmann, U., Raga, G. B., O'Dowd, C. D., Kulmala, M.,
Fuzzi, S., Reissell, A., and Andreae, M. O.: Flood or drought: how do
aerosols affect precipitation?, Science, 321, 1309–1313, 2008.
Saleeby, S. M. and van den Heever, S. C.: Developments in the CSU-RAMS
aerosol model: emissions, nucleation, regeneration, deposition, and
radiation, J. Appl. Meteorol. Clim., 52, 2601–2622, 2013.
Schär, C., Leuenberger, D., Fuhrer, O., Lüthi, D., and Girard, C.: A
new terrain-following vertical coordinate formulation for atmospheric
prediction models, Mon. Weather Rev., 130, 2459–2480, 2002.
Seifert, A. and Beheng, K.: A two-moment cloud microphysics parameterization
for mixed-phase clouds. Part 1: Model description, Meteorol. Atmos. Phys.,
92, 45–66, 2006.
Seity, Y., Brousseau, P., Malardel, S., Hello, G., Bénard, P.,
Bouttier, F., Lac, C., and Masson, V.: The AROME-France convective-scale
operational model, Mon. Weather Rev., 139, 976–991, 2011.
Slinn, W.: Precipitation scavenging, in: Atmospheric Sciences and Power
Production – 1979, Division of biomedical environment research, US
department of energy, Washington D.C., chapter 11, 1983.
Storer, R. L., van den Heever, S. C., and L'Ecuyer, T. S.: Observations of
aerosol-induced convective invigoration in the tropical east Atlantic, J.
Geophys. Res.-Atmos., 119, 3963–3975,
https://doi.org/10.1002/2013jd020272,
2014.
Tao, W.-K., Chen, J.-P., Li, Z., Wang, C., and Zhang, C.: Impact of aerosols
on convective clouds and precipitation, Rev. Geophys., 50, RG2001,
https://doi.org/10.1029/2011RG000369, 2012.
Thompson, G. and Eidhammer, T.: A study of aerosol impacts on clouds and
precipitation development in a large winter cyclone, J. Atmos. Sci., 71,
3636–3658, 2014.
Thompson, G., Field, P. R., Rasmussen, R. M., and Hall, W. D.: Explicit
forecasts of winter precipitation using an improved bulk microphysics scheme.
Part II: Implementation of a new snow parameterization, Mon. Weather Rev.,
136, 5095–5115, 2008.
Tripoli, G. J., Flatau, P. J., and Cotton, W. R.: Generalized microphysics
scheme for use in mesoscale/cloud models, in: reprints from the 10th
International Cloud Physics Conference, 15–20 August 1988, Bad Homburg,
Germany, Vol. 1, 109–111, available at:
http://adsabs.harvard.edu/abs/1988clph.conf..109T (last access: 2
September 2015), 1988.
Tulet, P., Crassier, V., Cousin, F., Suhre, K., and Rosset, R.: ORILAM, a
three-moment lognormal aerosol scheme for mesoscale atmospheric model: online
coupling into the Meso-NH-C model and validation on the Escompte campaign, J.
Geophys. Res.-Atmos., 110, D18201, https://doi.org/10.1029/2004JD005716, 2005.
Twomey, S.: The nuclei of natural cloud formation part II: The
supersaturation in natural clouds and the variation of cloud droplet
concentration, Geofisica pura e applicata, 43, 243–249, 1959.
Twomey, S.: The influence of pollution on the shortwave albedo of clouds, J.
Atmos. Sci., 34, 1149–1152, 1977.
Tzivion, S., Feingold, G., and Levin, Z.: The evolution of raindrop spectra.
Part II: Collisional collection/breakup and evaporation in a rainshaft, J.
Atmos. Sci., 46, 3312–3328, 1989.
Vié, B. and Pinty, J.-P.: LIMA: a two-moment mixed-phase microphysical
scheme driven by a multimodal population of cloud condensation nuclei and ice
freezing nuclei, in: 14th AMS conference on cloud physics, 7–11 July, poster
number 27, Boston, 2014.
Wall, C., Zipser, E., and Liu, C.: An investigation of the aerosol indirect
effect on convective intensity using satellite observations, J. Atmos. Sci.,
71, 430–447, 2014.
Short summary
LIMA, a new quasi two-moment, mixed-phase microphysical scheme, is introduced. LIMA relies on the prognostic evolution of a multimodal aerosol population and the careful description of their nucleating properties that enable cloud droplets and pristine ice to form. This paper describes LIMA and illustrates its ability to represent aerosol-cloud interactions for 2-D idealized simulations of a squall line and orographic cold clouds.
LIMA, a new quasi two-moment, mixed-phase microphysical scheme, is introduced. LIMA relies on...
