Articles | Volume 13, issue 11
https://doi.org/10.5194/gmd-13-5737-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-13-5737-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
25 Nov 2020
Model description paper |
| 25 Nov 2020
| 25 Nov 2020
A new parameterization of ice heterogeneous nucleation coupled to aerosol chemistry in WRF-Chem model version 3.5.1: evaluation through ISDAC measurements
Setigui Aboubacar Keita
CORRESPONDING AUTHOR
ESCER Centre, Department of Earth and Atmospheric Sciences, Université du Québec à Montréal, Montréal, Québec, Canada
Eric Girard
ESCER Centre, Department of Earth and Atmospheric Sciences, Université du Québec à Montréal, Montréal, Québec, Canada
deceased, 10 July 2017
Jean-Christophe Raut
ESCER Centre, Department of Earth and Atmospheric Sciences, Université du Québec à Montréal, Montréal, Québec, Canada
Laboratoire Atmosphères, Observations Spatiales (LATMOS)/IPSL, Sorbonne Université, UVSQ, CNRS, Paris, France
Maud Leriche
ESCER Centre, Department of Earth and Atmospheric Sciences, Université du Québec à Montréal, Montréal, Québec, Canada
Laboratoire d’Aérologie (LA), CNRS, Université Paul Sabatier, Toulouse, France
now at: Laboratoire de Météorologie Physique (LaMP), CNRS, Université Clermont-Auvergne, Aubière, France
Jean-Pierre Blanchet
ESCER Centre, Department of Earth and Atmospheric Sciences, Université du Québec à Montréal, Montréal, Québec, Canada
Jacques Pelon
Laboratoire Atmosphères, Observations Spatiales (LATMOS)/IPSL, Sorbonne Université, UVSQ, CNRS, Paris, France
Tatsuo Onishi
Laboratoire Atmosphères, Observations Spatiales (LATMOS)/IPSL, Sorbonne Université, UVSQ, CNRS, Paris, France
Ana Cirisan
ESCER Centre, Department of Earth and Atmospheric Sciences, Université du Québec à Montréal, Montréal, Québec, Canada
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Cynthia H. Whaley, Rashed Mahmood, Knut von Salzen, Barbara Winter, Sabine Eckhardt, Stephen Arnold, Stephen Beagley, Silvia Becagli, Rong-You Chien, Jesper Christensen, Sujay Manish Damani, Xinyi Dong, Konstantinos Eleftheriadis, Nikolaos Evangeliou, Gregory Faluvegi, Mark Flanner, Joshua S. Fu, Michael Gauss, Fabio Giardi, Wanmin Gong, Jens Liengaard Hjorth, Lin Huang, Ulas Im, Yugo Kanaya, Srinath Krishnan, Zbigniew Klimont, Thomas Kühn, Joakim Langner, Kathy S. Law, Louis Marelle, Andreas Massling, Dirk Olivié, Tatsuo Onishi, Naga Oshima, Yiran Peng, David A. Plummer, Olga Popovicheva, Luca Pozzoli, Jean-Christophe Raut, Maria Sand, Laura N. Saunders, Julia Schmale, Sangeeta Sharma, Ragnhild Bieltvedt Skeie, Henrik Skov, Fumikazu Taketani, Manu A. Thomas, Rita Traversi, Kostas Tsigaridis, Svetlana Tsyro, Steven Turnock, Vito Vitale, Kaley A. Walker, Minqi Wang, Duncan Watson-Parris, and Tahya Weiss-Gibbons
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Thibault Vaillant de Guélis, Gérard Ancellet, Anne Garnier, Laurent C.-Labonnote, Jacques Pelon, Mark A. Vaughan, Zhaoyan Liu, and David M. Winker
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not confidentV4 cloud classifications, and correct a few V4 misclassifications of cloud layers identified as dense dust or elevated smoke layers by CALIOP.
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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Lilian Loyer, Jean-Christophe Raut, Claudia Di Biagio, Julia Maillard, Vincent Mariage, and Jacques Pelon
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2021-326, https://doi.org/10.5194/amt-2021-326, 2021
Revised manuscript not accepted
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Gwendal Rivière, Meryl Wimmer, Philippe Arbogast, Jean-Marcel Piriou, Julien Delanoë, Carole Labadie, Quitterie Cazenave, and Jacques Pelon
Weather Clim. Dynam., 2, 1011–1031, https://doi.org/10.5194/wcd-2-1011-2021, https://doi.org/10.5194/wcd-2-1011-2021, 2021
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Inacurracies in representing processes occurring at spatial scales smaller than the grid scales of the weather forecast models are important sources of forecast errors. This is the case of deep convection representation in models with 10 km grid spacing. We performed simulations of a real extratropical cyclone using a model with different representations of deep convection. These forecasts lead to different behaviors in the ascending air masses of the cyclone and the jet stream aloft.
Liviu Ivănescu, Konstantin Baibakov, Norman T. O'Neill, Jean-Pierre Blanchet, and Karl-Heinz Schulz
Atmos. Meas. Tech., 14, 6561–6599, https://doi.org/10.5194/amt-14-6561-2021, https://doi.org/10.5194/amt-14-6561-2021, 2021
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Didier Bruneau and Jacques Pelon
Atmos. Meas. Tech., 14, 4375–4402, https://doi.org/10.5194/amt-14-4375-2021, https://doi.org/10.5194/amt-14-4375-2021, 2021
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Taking advantage of Aeolus success and of our airborne lidar system expertise, we present a new spaceborne wind lidar design for operational Aeolus follow-on missions, keeping most of the initial lidar system but relying on a single Mach–Zehnder interferometer to relax operational constraints and reduce measurement bias. System parameters are optimized. Random and systematic errors are shown to be compliant with the initial mission requirements. In addition, the system allows unbiased retrieval.
Anne Garnier, Jacques Pelon, Nicolas Pascal, Mark A. Vaughan, Philippe Dubuisson, Ping Yang, and David L. Mitchell
Atmos. Meas. Tech., 14, 3253–3276, https://doi.org/10.5194/amt-14-3253-2021, https://doi.org/10.5194/amt-14-3253-2021, 2021
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The IIR Level 2 data products include cloud effective emissivities and cloud microphysical properties such as effective diameter (De) and ice or liquid water path estimates. This paper (Part I) describes the improvements in the V4 algorithms compared to those used in the version 3 (V3) release, while results are presented in a companion paper (Part II).
Anne Garnier, Jacques Pelon, Nicolas Pascal, Mark A. Vaughan, Philippe Dubuisson, Ping Yang, and David L. Mitchell
Atmos. Meas. Tech., 14, 3277–3299, https://doi.org/10.5194/amt-14-3277-2021, https://doi.org/10.5194/amt-14-3277-2021, 2021
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The IIR Level 2 data products include cloud effective emissivities and cloud microphysical properties such as effective diameter (De) and ice or liquid water path estimates. This paper (Part II) shows retrievals over ocean and describes the improvements made with respect to version 3 as a result of the significant changes implemented in the version 4 algorithms, which are presented in a companion paper (Part I).
David L. A. Flack, Gwendal Rivière, Ionela Musat, Romain Roehrig, Sandrine Bony, Julien Delanoë, Quitterie Cazenave, and Jacques Pelon
Weather Clim. Dynam., 2, 233–253, https://doi.org/10.5194/wcd-2-233-2021, https://doi.org/10.5194/wcd-2-233-2021, 2021
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The representation of an extratropical cyclone in simulations of two climate models is studied by comparing them to observations of the international field campaign NAWDEX. We show that the current resolution used to run climate model projections (more than 100 km) is not enough to represent the life cycle accurately, but the use of 50 km resolution is good enough. Despite these encouraging results, cloud properties (partitioning liquid and solid) are found to be far from the observations.
Julia Maillard, François Ravetta, Jean-Christophe Raut, Vincent Mariage, and Jacques Pelon
Atmos. Chem. Phys., 21, 4079–4101, https://doi.org/10.5194/acp-21-4079-2021, https://doi.org/10.5194/acp-21-4079-2021, 2021
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Clouds remain a major source of uncertainty in understanding the Arctic climate, due in part to the lack of measurements over the sea ice. In this paper, we exploit a series of lidar profiles acquired from autonomous drifting buoys deployed in the Arctic Ocean and derive a statistic of low cloud frequency and macrophysical properties. We also show that clouds contribute to warm the surface in the shoulder seasons but not significantly from May to September.
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.
Melody A. Avery, Robert A. Ryan, Brian J. Getzewich, Mark A. Vaughan, David M. Winker, Yongxiang Hu, Anne Garnier, Jacques Pelon, and Carolus A. Verhappen
Atmos. Meas. Tech., 13, 4539–4563, https://doi.org/10.5194/amt-13-4539-2020, https://doi.org/10.5194/amt-13-4539-2020, 2020
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CALIOP data users will find more cloud layers detected in V4, with edges that extend further than in V3, for an increase in total atmospheric cloud volume of 6 %–9 % for high-confidence cloud phases and 1 %–2 % for all cloudy bins, including cloud fringes and unknown cloud phases. In V4 there are many fewer cloud layers identified as horizontally oriented ice, particularly in the 3° off-nadir view. Depolarization at 532 nm is the predominant parameter determining cloud thermodynamic phase.
Tuukka Petäjä, Ella-Maria Duplissy, Ksenia Tabakova, Julia Schmale, Barbara Altstädter, Gerard Ancellet, Mikhail Arshinov, Yurii Balin, Urs Baltensperger, Jens Bange, Alison Beamish, Boris Belan, Antoine Berchet, Rossana Bossi, Warren R. L. Cairns, Ralf Ebinghaus, Imad El Haddad, Beatriz Ferreira-Araujo, Anna Franck, Lin Huang, Antti Hyvärinen, Angelika Humbert, Athina-Cerise Kalogridis, Pavel Konstantinov, Astrid Lampert, Matthew MacLeod, Olivier Magand, Alexander Mahura, Louis Marelle, Vladimir Masloboev, Dmitri Moisseev, Vaios Moschos, Niklas Neckel, Tatsuo Onishi, Stefan Osterwalder, Aino Ovaska, Pauli Paasonen, Mikhail Panchenko, Fidel Pankratov, Jakob B. Pernov, Andreas Platis, Olga Popovicheva, Jean-Christophe Raut, Aurélie Riandet, Torsten Sachs, Rosamaria Salvatori, Roberto Salzano, Ludwig Schröder, Martin Schön, Vladimir Shevchenko, Henrik Skov, Jeroen E. Sonke, Andrea Spolaor, Vasileios K. Stathopoulos, Mikko Strahlendorff, Jennie L. Thomas, Vito Vitale, Sterios Vratolis, Carlo Barbante, Sabine Chabrillat, Aurélien Dommergue, Konstantinos Eleftheriadis, Jyri Heilimo, Kathy S. Law, Andreas Massling, Steffen M. Noe, Jean-Daniel Paris, André S. H. Prévôt, Ilona Riipinen, Birgit Wehner, Zhiyong Xie, and Hanna K. Lappalainen
Atmos. Chem. Phys., 20, 8551–8592, https://doi.org/10.5194/acp-20-8551-2020, https://doi.org/10.5194/acp-20-8551-2020, 2020
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The role of polar regions is increasing in terms of megatrends such as globalization, new transport routes, demography, and the use of natural resources with consequent effects on regional and transported pollutant concentrations. Here we summarize initial results from our integrative project exploring the Arctic environment and pollution to deliver data products, metrics, and indicators for stakeholders.
Antonin Zabukovec, Gerard Ancellet, Iwan E. Penner, Mikhail Arshinov, Valery Kozlov, Jacques Pelon, Jean-Daniel Paris, Grigory Kokhanenko, Yuri S. Balin, Dmitry Chernov, and Boris D. Belan
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-195, https://doi.org/10.5194/acp-2020-195, 2020
Preprint withdrawn
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Description of two aircraft campaigns results carried out over Siberia in 2013 and 2017 to characterize aerosol emission. A methodology is proposed to derive the aerosol types using transport model and satellite observations. The extinction to backscatter ratio for each aerosol types is reported as it is a key parameter to constrain their radiative impact. These results are compared to previous work conducted in other regions and to aerosol data products observed by spaceborne lidars.
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.
Quitterie Cazenave, Marie Ceccaldi, Julien Delanoë, Jacques Pelon, Silke Groß, and Andrew Heymsfield
Atmos. Meas. Tech., 12, 2819–2835, https://doi.org/10.5194/amt-12-2819-2019, https://doi.org/10.5194/amt-12-2819-2019, 2019
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The impact of ice clouds on the water cycle and radiative budget is still uncertain due to the complexity of cloud processes that makes it difficult to acquire adequate observations of ice cloud properties and parameterize them into climate and weather prediction models. In this paper we present the latest refinements brought to the DARDAR-CLOUD product, which contains ice cloud microphysical properties retrieved from the cloud radar and lidar measurements from the A-Train space mission.
Jonathan P. D. Abbatt, W. Richard Leaitch, Amir A. Aliabadi, Allan K. Bertram, Jean-Pierre Blanchet, Aude Boivin-Rioux, Heiko Bozem, Julia Burkart, Rachel Y. W. Chang, Joannie Charette, Jai P. Chaubey, Robert J. Christensen, Ana Cirisan, Douglas B. Collins, Betty Croft, Joelle Dionne, Greg J. Evans, Christopher G. Fletcher, Martí Galí, Roya Ghahreman, Eric Girard, Wanmin Gong, Michel Gosselin, Margaux Gourdal, Sarah J. Hanna, Hakase Hayashida, Andreas B. Herber, Sareh Hesaraki, Peter Hoor, Lin Huang, Rachel Hussherr, Victoria E. Irish, Setigui A. Keita, John K. Kodros, Franziska Köllner, Felicia Kolonjari, Daniel Kunkel, Luis A. Ladino, Kathy Law, Maurice Levasseur, Quentin Libois, John Liggio, Martine Lizotte, Katrina M. Macdonald, Rashed Mahmood, Randall V. Martin, Ryan H. Mason, Lisa A. Miller, Alexander Moravek, Eric Mortenson, Emma L. Mungall, Jennifer G. Murphy, Maryam Namazi, Ann-Lise Norman, Norman T. O'Neill, Jeffrey R. Pierce, Lynn M. Russell, Johannes Schneider, Hannes Schulz, Sangeeta Sharma, Meng Si, Ralf M. Staebler, Nadja S. Steiner, Jennie L. Thomas, Knut von Salzen, Jeremy J. B. Wentzell, Megan D. Willis, Gregory R. Wentworth, Jun-Wei Xu, and Jacqueline D. Yakobi-Hancock
Atmos. Chem. Phys., 19, 2527–2560, https://doi.org/10.5194/acp-19-2527-2019, https://doi.org/10.5194/acp-19-2527-2019, 2019
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The Arctic is experiencing considerable environmental change with climate warming, illustrated by the dramatic decrease in sea-ice extent. It is important to understand both the natural and perturbed Arctic systems to gain a better understanding of how they will change in the future. This paper summarizes new insights into the relationships between Arctic aerosol particles and climate, as learned over the past five or so years by a large Canadian research consortium, NETCARE.
Zhaoyan Liu, Jayanta Kar, Shan Zeng, Jason Tackett, Mark Vaughan, Melody Avery, Jacques Pelon, Brian Getzewich, Kam-Pui Lee, Brian Magill, Ali Omar, Patricia Lucker, Charles Trepte, and David Winker
Atmos. Meas. Tech., 12, 703–734, https://doi.org/10.5194/amt-12-703-2019, https://doi.org/10.5194/amt-12-703-2019, 2019
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We describe the enhancements made to the cloud–aerosol discrimination (CAD) algorithms used to produce the CALIPSO version 4 (V4) data products. Revisions to the CAD probability distribution functions have greatly improved the recognition of aerosol layers lofted into the upper troposphere, and CAD is now applied to all layers detected in the stratosphere and all layers detected at single-shot resolution. Detailed comparisons show significant improvements relative to previous versions.
Victoria E. Irish, Sarah J. Hanna, Megan D. Willis, Swarup China, Jennie L. Thomas, Jeremy J. B. Wentzell, Ana Cirisan, Meng Si, W. Richard Leaitch, Jennifer G. Murphy, Jonathan P. D. Abbatt, Alexander Laskin, Eric Girard, and Allan K. Bertram
Atmos. Chem. Phys., 19, 1027–1039, https://doi.org/10.5194/acp-19-1027-2019, https://doi.org/10.5194/acp-19-1027-2019, 2019
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Ice nucleating particles (INPs) are atmospheric particles that catalyse the formation of ice crystals in clouds. INPs influence the Earth's radiative balance and hydrological cycle. In this study we measured the concentrations of INPs in the Canadian Arctic marine boundary layer. Average INP concentrations fell within the range measured in other marine boundary layer locations. We also found that mineral dust is a more important contributor to the INP population than sea spray aerosol.
Gerard Ancellet, Iogannes E. Penner, Jacques Pelon, Vincent Mariage, Antonin Zabukovec, Jean Christophe Raut, Grigorii Kokhanenko, and Yuri S. Balin
Atmos. Meas. Tech., 12, 147–168, https://doi.org/10.5194/amt-12-147-2019, https://doi.org/10.5194/amt-12-147-2019, 2019
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Aerosol type seasonal variability and sources in Siberia are obtained from an automatic 808 nm micropulse lidar. A total of 540 aerosol backscatter vertical profiles have been retrieved using careful lidar calibration. Aerosol optical depth is retrieved using sun-photometer complementary observations and an aerosol source apportionment based on aerosol transport model simulations. Comparisons with satellite observations are discussed for three case studies.
Mark Vaughan, Anne Garnier, Damien Josset, Melody Avery, Kam-Pui Lee, Zhaoyan Liu, William Hunt, Jacques Pelon, Yongxiang Hu, Sharon Burton, Johnathan Hair, Jason L. Tackett, Brian Getzewich, Jayanta Kar, and Sharon Rodier
Atmos. Meas. Tech., 12, 51–82, https://doi.org/10.5194/amt-12-51-2019, https://doi.org/10.5194/amt-12-51-2019, 2019
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The version 4 (V4) release of the CALIPSO data products includes substantial improvements to the calibration of the CALIOP 1064 nm channel. In this paper we review the fundamentals of 1064 nm lidar calibration, explain the motivations for the changes made to the algorithm, and describe the mechanics of the V4 calibration technique. Internal consistency checks and comparisons to collocated high spectral resolution lidar measurements show the V4 1064 nm calibration coefficients to within ~ 3 %.
David L. Mitchell, Anne Garnier, Jacques Pelon, and Ehsan Erfani
Atmos. Chem. Phys., 18, 17325–17354, https://doi.org/10.5194/acp-18-17325-2018, https://doi.org/10.5194/acp-18-17325-2018, 2018
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To realistically model a changing climate, global measurements of cirrus cloud ice-particle number concentration (N) and size (De) are needed, through which one may infer the general mechanism of ice formation. A satellite remote sensing method was developed to measure N and De. It was found that N was highest and De lowest at high latitudes. In the Arctic, cirrus clouds occurred much more often during winter, which may have an impact on mid-latitude winter weather.
Patrick Chazette, Jean-Christophe Raut, and Julien Totems
Atmos. Chem. Phys., 18, 13075–13095, https://doi.org/10.5194/acp-18-13075-2018, https://doi.org/10.5194/acp-18-13075-2018, 2018
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We associate aerosol lidar measurements from the ground level and from an ultralight aircraft to improve our knowledge about aerosols above the Arctic circle; we highlight long-range transport of biomass burning aerosols and characterize the aerosol emissions from a flaring facility. The field experiment was performed as part of the Pollution in the ARCtic System (PARCS) project of the French Arctic Initiative, which took place from 13 to 26 May 2016 in northern Norway (over 70 °N).
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.
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
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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.
Anne Garnier, Thierry Trémas, Jacques Pelon, Kam-Pui Lee, Delphine Nobileau, Lydwine Gross-Colzy, Nicolas Pascal, Pascale Ferrage, and Noëlle A. Scott
Atmos. Meas. Tech., 11, 2485–2500, https://doi.org/10.5194/amt-11-2485-2018, https://doi.org/10.5194/amt-11-2485-2018, 2018
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Residual calibration biases affecting CALIPSO IIR Version 1 calibrated radiances in the Northern Hemisphere are analyzed and reduced through in-depth analysis of the IIR internal calibration procedure in conjunction with observations such as statistical comparisons with similar MODIS/Aqua channels.
Jayanta Kar, Mark A. Vaughan, Kam-Pui Lee, Jason L. Tackett, Melody A. Avery, Anne Garnier, Brian J. Getzewich, William H. Hunt, Damien Josset, Zhaoyan Liu, Patricia L. Lucker, Brian Magill, Ali H. Omar, Jacques Pelon, Raymond R. Rogers, Travis D. Toth, Charles R. Trepte, Jean-Paul Vernier, David M. Winker, and Stuart A. Young
Atmos. Meas. Tech., 11, 1459–1479, https://doi.org/10.5194/amt-11-1459-2018, https://doi.org/10.5194/amt-11-1459-2018, 2018
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We present the motivation for and the implementation of the version 4.1 nighttime 532 nm parallel-channel calibration of the CALIOP lidar. The accuracy of calibration is significantly improved by raising the molecular normalization altitude from 30–34 km to 36–39 km to substantially reduce stratospheric aerosol contamination. The new calibration procedure eliminates biases in earlier versions and leads to an improved representation of stratospheric aerosols.
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.
Louis Marelle, Jean-Christophe Raut, Kathy S. Law, Larry K. Berg, Jerome D. Fast, Richard C. Easter, Manish Shrivastava, and Jennie L. Thomas
Geosci. Model Dev., 10, 3661–3677, https://doi.org/10.5194/gmd-10-3661-2017, https://doi.org/10.5194/gmd-10-3661-2017, 2017
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We develop the WRF-Chem 3.5.1 model to improve simulations of aerosols and ozone in the Arctic. Both species are important air pollutants and climate forcers, but models often struggle to reproduce observations in the Arctic. Our developments concern pollutant emissions, mixing, chemistry, and removal, including processes related to snow and sea ice. The effect of these changes are quantitatively validated against observations, showing significant improvements compared to the original model.
Lucia T. Deaconu, Fabien Waquet, Damien Josset, Nicolas Ferlay, Fanny Peers, François Thieuleux, Fabrice Ducos, Nicolas Pascal, Didier Tanré, Jacques Pelon, and Philippe Goloub
Atmos. Meas. Tech., 10, 3499–3523, https://doi.org/10.5194/amt-10-3499-2017, https://doi.org/10.5194/amt-10-3499-2017, 2017
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This study presents a comparison between active (CALIOP) and passive (POLDER) remote sensing methods, developed for retrieving aerosol above-cloud optical and microphysical properties. Main results show a good agreement when the aerosol microphysics is dominated by fine-mode particles or coarse-mode dust or when the aerosol layer is well separated from the cloud below. The paper is also focused on understanding the differences between the retrievals and the limitations of each method.
Jean-Christophe Raut, Louis Marelle, Jerome D. Fast, Jennie L. Thomas, Bernadett Weinzierl, Katharine S. Law, Larry K. Berg, Anke Roiger, Richard C. Easter, Katharina Heimerl, Tatsuo Onishi, Julien Delanoë, and Hans Schlager
Atmos. Chem. Phys., 17, 10969–10995, https://doi.org/10.5194/acp-17-10969-2017, https://doi.org/10.5194/acp-17-10969-2017, 2017
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We study the cross-polar transport of plumes from Siberian fires to the Arctic in summer, both in terms of transport pathways and efficiency of deposition processes. Those plumes containing soot may originate from anthropogenic and biomass burning sources in mid-latitude regions and may impact the Arctic climate by depositing on snow and ice surfaces. We evaluate the role of the respective source contributions, investigate the transport of plumes and treat pathway-dependent removal of particles.
Leslie David, Olivier Bock, Christian Thom, Pierre Bosser, and Jacques Pelon
Atmos. Meas. Tech., 10, 2745–2758, https://doi.org/10.5194/amt-10-2745-2017, https://doi.org/10.5194/amt-10-2745-2017, 2017
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The Raman lidar ability to retrieve atmospheric water vapor with high accuracy makes it a premium instrument in different research fields such as climatology, meteorology, or calibration of GNSS altimetry data. In order to achieve long-term stability of the measurements, the system has to be carefully calibrated. In this work we strove to investigate and mitigate the error and instability sources through numerical simulations as well as experimental tests.
Anne Garnier, Noëlle A. Scott, Jacques Pelon, Raymond Armante, Laurent Crépeau, Bruno Six, and Nicolas Pascal
Atmos. Meas. Tech., 10, 1403–1424, https://doi.org/10.5194/amt-10-1403-2017, https://doi.org/10.5194/amt-10-1403-2017, 2017
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An assessment of IIR radiances after 9.5 years of nearly continuous operation since June 2006 is presented. First, IIR is compared with similar MODIS or SEVIRI channels in various conditions. Second, clear sky measurements in each channel are compared with simulations. The first approach detects biases and/or trends, and the second approach contributes to identifying which channel deviates from the other. The analyses are based on simulations using the 4A/OP radiative transfer model.
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.
Quentin Libois, Liviu Ivanescu, Jean-Pierre Blanchet, Hannes Schulz, Heiko Bozem, W. Richard Leaitch, Julia Burkart, Jonathan P. D. Abbatt, Andreas B. Herber, Amir A. Aliabadi, and Éric Girard
Atmos. Chem. Phys., 16, 15689–15707, https://doi.org/10.5194/acp-16-15689-2016, https://doi.org/10.5194/acp-16-15689-2016, 2016
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The first airborne measurements performed with the FIRR are presented. Vertical profiles of upwelling spectral radiance in the far-infrared are measured in the Arctic atmosphere for the first time. They show the impact of the temperature inversion on the radiative budget of the atmosphere, especially in the far-infrared. The presence of ice clouds also significantly alters the far-infrared budget, highlighting the critical interplay between water vapour and clouds in this very dry region.
Gerard Ancellet, Nikos Daskalakis, Jean Christophe Raut, David Tarasick, Jonathan Hair, Boris Quennehen, François Ravetta, Hans Schlager, Andrew J. Weinheimer, Anne M. Thompson, Bryan Johnson, Jennie L. Thomas, and Katharine S. Law
Atmos. Chem. Phys., 16, 13341–13358, https://doi.org/10.5194/acp-16-13341-2016, https://doi.org/10.5194/acp-16-13341-2016, 2016
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An integrated analysis of all the ozone observations (lidar, sondes, and airborne in situ measurements) conducted during the 2008 IPY campaigns is performed and the processes that determine summer ozone concentrations over Greenland and Canada are discussed. Combined with a regional model simulation (WRFChem), the analysis of ozone, CO, and PV latitudinal and vertical variability allows the determination of the influence of stratospheric sources and biomass burning and anthropogenic emissions.
B. Quennehen, J.-C. Raut, K. S. Law, N. Daskalakis, G. Ancellet, C. Clerbaux, S.-W. Kim, M. T. Lund, G. Myhre, D. J. L. Olivié, S. Safieddine, R. B. Skeie, J. L. Thomas, S. Tsyro, A. Bazureau, N. Bellouin, M. Hu, M. Kanakidou, Z. Klimont, K. Kupiainen, S. Myriokefalitakis, J. Quaas, S. T. Rumbold, M. Schulz, R. Cherian, A. Shimizu, J. Wang, S.-C. Yoon, and T. Zhu
Atmos. Chem. Phys., 16, 10765–10792, https://doi.org/10.5194/acp-16-10765-2016, https://doi.org/10.5194/acp-16-10765-2016, 2016
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This paper evaluates the ability of six global models and one regional model in reproducing short-lived pollutants (defined here as ozone and its precursors, aerosols and black carbon) concentrations over Asia using satellite, ground-based and airborne observations.
Key findings are that models homogeneously reproduce the trace gas observations although nitrous oxides are underestimated, whereas the aerosol distributions are heterogeneously reproduced, implicating important uncertainties.
Jean-Pierre Chaboureau, Cyrille Flamant, Thibaut Dauhut, Cécile Kocha, Jean-Philippe Lafore, Chistophe Lavaysse, Fabien Marnas, Mohamed Mokhtari, Jacques Pelon, Irene Reinares Martínez, Kerstin Schepanski, and Pierre Tulet
Atmos. Chem. Phys., 16, 6977–6995, https://doi.org/10.5194/acp-16-6977-2016, https://doi.org/10.5194/acp-16-6977-2016, 2016
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The Fennec field campaign conducted in June 2011 led to the first observational data set ever obtained that documents the Saharan atmospheric boundary layer under the influence of the heat low. In addition to the aircraft operation, four dust forecasts were run at low and high resolutions with convection-parameterizing and convection-permitting models, respectively. The unique airborne and ground-based data sets allowed the first ever intercomparison of dust forecasts over the western Sahara.
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.
Quentin Libois, Christian Proulx, Liviu Ivanescu, Laurence Coursol, Ludovick S. Pelletier, Yacine Bouzid, Francesco Barbero, Éric Girard, and Jean-Pierre Blanchet
Atmos. Meas. Tech., 9, 1817–1832, https://doi.org/10.5194/amt-9-1817-2016, https://doi.org/10.5194/amt-9-1817-2016, 2016
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Here we present a radiometer, FIRR, aimed at measuring atmospheric radiation in the far infrared, an underexplored region of the Earth spectrum. The FIRR is a prototype for the planned TICFIRE satellite mission dedicated to studying thin ice clouds in polar regions. Preliminary in situ measurements compare well with radiative transfer simulations. This highlights the high sensitivity of the FIRR to water vapor content and cloud physical properties, paving the way for new retrieval algorithms.
Gerard Ancellet, Jacques Pelon, Julien Totems, Patrick Chazette, Ariane Bazureau, Michaël Sicard, Tatiana Di Iorio, Francois Dulac, and Marc Mallet
Atmos. Chem. Phys., 16, 4725–4742, https://doi.org/10.5194/acp-16-4725-2016, https://doi.org/10.5194/acp-16-4725-2016, 2016
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A multi-lidar analysis conducted in the Mediterranean basin compares the impact of the long-range transport of North American biomass burning aerosols with the role of frequently observed Saharan dust outbreaks. This paper provides a detailed analysis of the potential North American aerosol sources, their transport to Europe and the mixing of different aerosol sources, using simulations of a particle dispersion model and lidar measurements of the aerosol optical properties.
Patrick Chazette, Julien Totems, Gérard Ancellet, Jacques Pelon, and Michaël Sicard
Atmos. Chem. Phys., 16, 2863–2875, https://doi.org/10.5194/acp-16-2863-2016, https://doi.org/10.5194/acp-16-2863-2016, 2016
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We performed synergetic active and passive remote-sensing observations at Minorca (Spain), over more than 3 weeks in spring 2013. We characterized the aerosol optical properties and type using a combination of Rayleigh–Mie–Raman lidar and sun-photometer data. Results show a high variability due to changing atmospheric transport regimes and aerosol sources. Such variability significantly influences the radiative balance through the entire atmosphere and then the climate of the Mediterranean area.
Louis Marelle, Jennie L. Thomas, Jean-Christophe Raut, Kathy S. Law, Jukka-Pekka Jalkanen, Lasse Johansson, Anke Roiger, Hans Schlager, Jin Kim, Anja Reiter, and Bernadett Weinzierl
Atmos. Chem. Phys., 16, 2359–2379, https://doi.org/10.5194/acp-16-2359-2016, https://doi.org/10.5194/acp-16-2359-2016, 2016
B. Vié, J.-P. Pinty, S. Berthet, and M. Leriche
Geosci. Model Dev., 9, 567–586, https://doi.org/10.5194/gmd-9-567-2016, https://doi.org/10.5194/gmd-9-567-2016, 2016
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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.
M. Mallet, F. Dulac, P. Formenti, P. Nabat, J. Sciare, G. Roberts, J. Pelon, G. Ancellet, D. Tanré, F. Parol, C. Denjean, G. Brogniez, A. di Sarra, L. Alados-Arboledas, J. Arndt, F. Auriol, L. Blarel, T. Bourrianne, P. Chazette, S. Chevaillier, M. Claeys, B. D'Anna, Y. Derimian, K. Desboeufs, T. Di Iorio, J.-F. Doussin, P. Durand, A. Féron, E. Freney, C. Gaimoz, P. Goloub, J. L. Gómez-Amo, M. J. Granados-Muñoz, N. Grand, E. Hamonou, I. Jankowiak, M. Jeannot, J.-F. Léon, M. Maillé, S. Mailler, D. Meloni, L. Menut, G. Momboisse, J. Nicolas, T. Podvin, V. Pont, G. Rea, J.-B. Renard, L. Roblou, K. Schepanski, A. Schwarzenboeck, K. Sellegri, M. Sicard, F. Solmon, S. Somot, B Torres, J. Totems, S. Triquet, N. Verdier, C. Verwaerde, F. Waquet, J. Wenger, and P. Zapf
Atmos. Chem. Phys., 16, 455–504, https://doi.org/10.5194/acp-16-455-2016, https://doi.org/10.5194/acp-16-455-2016, 2016
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The aim of this article is to present an experimental campaign over the Mediterranean focused on aerosol-radiation measurements and modeling. Results indicate an important atmospheric loading associated with a moderate absorbing ability of mineral dust. Observations suggest a complex vertical structure and size distributions characterized by large aerosols within dust plumes. The radiative effect is highly variable, with negative forcing over the Mediterranean and positive over northern Africa.
A. Stohl, B. Aamaas, M. Amann, L. H. Baker, N. Bellouin, T. K. Berntsen, O. Boucher, R. Cherian, W. Collins, N. Daskalakis, M. Dusinska, S. Eckhardt, J. S. Fuglestvedt, M. Harju, C. Heyes, Ø. Hodnebrog, J. Hao, U. Im, M. Kanakidou, Z. Klimont, K. Kupiainen, K. S. Law, M. T. Lund, R. Maas, C. R. MacIntosh, G. Myhre, S. Myriokefalitakis, D. Olivié, J. Quaas, B. Quennehen, J.-C. Raut, S. T. Rumbold, B. H. Samset, M. Schulz, Ø. Seland, K. P. Shine, R. B. Skeie, S. Wang, K. E. Yttri, and T. Zhu
Atmos. Chem. Phys., 15, 10529–10566, https://doi.org/10.5194/acp-15-10529-2015, https://doi.org/10.5194/acp-15-10529-2015, 2015
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This paper presents a summary of the findings of the ECLIPSE EU project. The project has investigated the climate and air quality impacts of short-lived climate pollutants (especially methane, ozone, aerosols) and has designed a global mitigation strategy that maximizes co-benefits between air quality and climate policy. Transient climate model simulations allowed quantifying the impacts on temperature (e.g., reduction in global warming by 0.22K for the decade 2041-2050) and precipitation.
C. Di Biagio, L. Doppler, C. Gaimoz, N. Grand, G. Ancellet, J.-C. Raut, M. Beekmann, A. Borbon, K. Sartelet, J.-L. Attié, F. Ravetta, and P. Formenti
Atmos. Chem. Phys., 15, 9611–9630, https://doi.org/10.5194/acp-15-9611-2015, https://doi.org/10.5194/acp-15-9611-2015, 2015
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Observations from this study indicate that continental pollution largely affects the atmospheric composition and structure of the western Mediterranean basin. Pollution plumes reach 3000-4000 m in altitude and present a very complex and highly stratified structure, characterized by fresh and aged layers both in the boundary layer and in the free troposphere. Also we report the observations of high levels of ultrafine particles over the basin, possibly linked to new particle formation events.
S. Eckhardt, B. Quennehen, D. J. L. Olivié, T. K. Berntsen, R. Cherian, J. H. Christensen, W. Collins, S. Crepinsek, N. Daskalakis, M. Flanner, A. Herber, C. Heyes, Ø. Hodnebrog, L. Huang, M. Kanakidou, Z. Klimont, J. Langner, K. S. Law, M. T. Lund, R. Mahmood, A. Massling, S. Myriokefalitakis, I. E. Nielsen, J. K. Nøjgaard, J. Quaas, P. K. Quinn, J.-C. Raut, S. T. Rumbold, M. Schulz, S. Sharma, R. B. Skeie, H. Skov, T. Uttal, K. von Salzen, and A. Stohl
Atmos. Chem. Phys., 15, 9413–9433, https://doi.org/10.5194/acp-15-9413-2015, https://doi.org/10.5194/acp-15-9413-2015, 2015
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The concentrations of sulfate, black carbon and other aerosols in the Arctic are characterized by high values in late winter and spring (so-called Arctic Haze) and low values in summer. Models have long been struggling to capture this seasonality. In this study, we evaluate sulfate and BC concentrations from different updated models and emissions against a comprehensive pan-Arctic measurement data set. We find that the models improved but still struggle to get the maximum concentrations.
A. Garnier, J. Pelon, M. A. Vaughan, D. M. Winker, C. R. Trepte, and P. Dubuisson
Atmos. Meas. Tech., 8, 2759–2774, https://doi.org/10.5194/amt-8-2759-2015, https://doi.org/10.5194/amt-8-2759-2015, 2015
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Cloud absorption optical depths retrieved at 12.05 microns are compared to extinction optical depths retrieved at 0.532 microns from perfectly co-located observations of single-layered semi-transparent cirrus over oceans made by the space-borne CALIPSO IIR infrared radiometer and CALIOP lidar. A new relationship describing the temperature-dependent effect of multiple scattering in the CALIOP retrievals is derived and discussed.
L. K. Emmons, S. R. Arnold, S. A. Monks, V. Huijnen, S. Tilmes, K. S. Law, J. L. Thomas, J.-C. Raut, I. Bouarar, S. Turquety, Y. Long, B. Duncan, S. Steenrod, S. Strode, J. Flemming, J. Mao, J. Langner, A. M. Thompson, D. Tarasick, E. C. Apel, D. R. Blake, R. C. Cohen, J. Dibb, G. S. Diskin, A. Fried, S. R. Hall, L. G. Huey, A. J. Weinheimer, A. Wisthaler, T. Mikoviny, J. Nowak, J. Peischl, J. M. Roberts, T. Ryerson, C. Warneke, and D. Helmig
Atmos. Chem. Phys., 15, 6721–6744, https://doi.org/10.5194/acp-15-6721-2015, https://doi.org/10.5194/acp-15-6721-2015, 2015
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Eleven 3-D tropospheric chemistry models have been compared and evaluated with observations in the Arctic during the International Polar Year (IPY 2008). Large differences are seen among the models, particularly related to the model chemistry of volatile organic compounds (VOCs) and reactive nitrogen (NOx, PAN, HNO3) partitioning. Consistency among the models in the underestimation of CO, ethane and propane indicates the emission inventory is too low for these compounds.
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
L. Marelle, J.-C. Raut, J. L. Thomas, K. S. Law, B. Quennehen, G. Ancellet, J. Pelon, A. Schwarzenboeck, and J. D. Fast
Atmos. Chem. Phys., 15, 3831–3850, https://doi.org/10.5194/acp-15-3831-2015, https://doi.org/10.5194/acp-15-3831-2015, 2015
S. A. Monks, S. R. Arnold, L. K. Emmons, K. S. Law, S. Turquety, B. N. Duncan, J. Flemming, V. Huijnen, S. Tilmes, J. Langner, J. Mao, Y. Long, J. L. Thomas, S. D. Steenrod, J. C. Raut, C. Wilson, M. P. Chipperfield, G. S. Diskin, A. Weinheimer, H. Schlager, and G. Ancellet
Atmos. Chem. Phys., 15, 3575–3603, https://doi.org/10.5194/acp-15-3575-2015, https://doi.org/10.5194/acp-15-3575-2015, 2015
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Multi-model simulations of Arctic CO, O3 and OH are evaluated using observations. Models show highly variable concentrations but the relative importance of emission regions and types is robust across the models, demonstrating the importance of biomass burning as a source. Idealised tracer experiments suggest that some of the model spread is due to variations in simulated transport from Europe in winter and from Asia throughout the year.
N. Bègue, P. Tulet, J. Pelon, B. Aouizerats, A. Berger, and A. Schwarzenboeck
Atmos. Chem. Phys., 15, 3497–3516, https://doi.org/10.5194/acp-15-3497-2015, https://doi.org/10.5194/acp-15-3497-2015, 2015
T. Fauchez, P. Dubuisson, C. Cornet, F. Szczap, A. Garnier, J. Pelon, and K. Meyer
Atmos. Meas. Tech., 8, 633–647, https://doi.org/10.5194/amt-8-633-2015, https://doi.org/10.5194/amt-8-633-2015, 2015
F. Marenco, V. Amiridis, E. Marinou, A. Tsekeri, and J. Pelon
Atmos. Chem. Phys., 14, 11871–11881, https://doi.org/10.5194/acp-14-11871-2014, https://doi.org/10.5194/acp-14-11871-2014, 2014
S. Safieddine, A. Boynard, P.-F. Coheur, D. Hurtmans, G. Pfister, B. Quennehen, J. L. Thomas, J.-C. Raut, K. S. Law, Z. Klimont, J. Hadji-Lazaro, M. George, and C. Clerbaux
Atmos. Chem. Phys., 14, 10119–10131, https://doi.org/10.5194/acp-14-10119-2014, https://doi.org/10.5194/acp-14-10119-2014, 2014
G. Ancellet, J. Pelon, Y. Blanchard, B. Quennehen, A. Bazureau, K. S. Law, and A. Schwarzenboeck
Atmos. Chem. Phys., 14, 8235–8254, https://doi.org/10.5194/acp-14-8235-2014, https://doi.org/10.5194/acp-14-8235-2014, 2014
C. Jouan, J. Pelon, E. Girard, G. Ancellet, J. P. Blanchet, and J. Delanoë
Atmos. Chem. Phys., 14, 1205–1224, https://doi.org/10.5194/acp-14-1205-2014, https://doi.org/10.5194/acp-14-1205-2014, 2014
P. Dubuisson, H. Herbin, F. Minvielle, M. Compiègne, F. Thieuleux, F. Parol, and J. Pelon
Atmos. Meas. Tech., 7, 359–371, https://doi.org/10.5194/amt-7-359-2014, https://doi.org/10.5194/amt-7-359-2014, 2014
J.-F. Gayet, V. Shcherbakov, L. Bugliaro, A. Protat, J. Delanoë, J. Pelon, and A. Garnier
Atmos. Chem. Phys., 14, 899–912, https://doi.org/10.5194/acp-14-899-2014, https://doi.org/10.5194/acp-14-899-2014, 2014
C. Tsamalis, A. Chédin, J. Pelon, and V. Capelle
Atmos. Chem. Phys., 13, 11235–11257, https://doi.org/10.5194/acp-13-11235-2013, https://doi.org/10.5194/acp-13-11235-2013, 2013
O. Bock, P. Bosser, T. Bourcy, L. David, F. Goutail, C. Hoareau, P. Keckhut, D. Legain, A. Pazmino, J. Pelon, K. Pipis, G. Poujol, A. Sarkissian, C. Thom, G. Tournois, and D. Tzanos
Atmos. Meas. Tech., 6, 2777–2802, https://doi.org/10.5194/amt-6-2777-2013, https://doi.org/10.5194/amt-6-2777-2013, 2013
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
O. Sourdeval, L. C. -Labonnote, G. Brogniez, O. Jourdan, J. Pelon, and A. Garnier
Atmos. Chem. Phys., 13, 8229–8244, https://doi.org/10.5194/acp-13-8229-2013, https://doi.org/10.5194/acp-13-8229-2013, 2013
J. L. Thomas, J.-C. Raut, K. S. Law, L. Marelle, G. Ancellet, F. Ravetta, J. D. Fast, G. Pfister, L. K. Emmons, G. S. Diskin, A. Weinheimer, A. Roiger, and H. Schlager
Atmos. Chem. Phys., 13, 3825–3848, https://doi.org/10.5194/acp-13-3825-2013, https://doi.org/10.5194/acp-13-3825-2013, 2013
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Evaluation of dust emission and land surface schemes in predicting a mega Asian dust storm over South Korea using WRF-Chem
Sensitivity studies of a four-dimensional local ensemble transform Kalman filter coupled with WRF-Chem version 3.9.1 for improving particulate matter simulation accuracy
A Bayesian method for predicting background radiation at environmental monitoring stations in local-scale networks
Inclusion of the ECMWF ecRad radiation scheme (v1.5.0) in the MAR (v3.14), regional evaluation for Belgium, and assessment of surface shortwave spectral fluxes at Uccle
Development of a fast radiative transfer model for ground-based microwave radiometers (ARMS-gb v1.0): validation and comparison to RTTOV-gb
Indian Institute of Tropical Meteorology (IITM) High-Resolution Global Forecast Model version 1: an attempt to resolve monsoon prediction deadlock
Cell-tracking-based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall
NeuralMie (v1.0): an aerosol optics emulator
Simulation performance of planetary boundary layer schemes in WRF v4.3.1 for near-surface wind over the western Sichuan Basin: a single-site assessment
FootNet v1.0: development of a machine learning emulator of atmospheric transport
Updates and evaluation of NOAA's online-coupled air quality model version 7 (AQMv7) within the Unified Forecast System
Quantifying the analysis uncertainty for nowcasting application
Improving the ensemble square root filter (EnSRF) in the Community Inversion Framework: a case study with ICON-ART 2024.01
The MESSy DWARF (based on MESSy v2.55.2)
An enhanced emission module for the PALM model system 23.10 with application for PM10 emission from urban domestic heating
Identifying lightning processes in ERA5 soundings with deep learning
Sensitivity of predicted ultrafine particle size distributions in Europe to different nucleation rate parameterizations using PMCAMx-UF v2.2
Explaining neural networks for detection of tropical cyclones and atmospheric rivers in gridded atmospheric simulation data
PALACE v1.0: Paranal Airglow Line And Continuum Emission model
Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes
Exploring a high-level programming model for the NWP domain using ECMWF microphysics schemes
Quantifying uncertainties in satellite NO2 superobservations for data assimilation and model evaluation
ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool
Coupling the urban canopy model TEB (SURFEXv9.0) with the radiation model SPARTACUS-Urbanv0.6.1 for more realistic urban radiative exchange calculation
Forecasting contrail climate forcing for flight planning and air traffic management applications: the CocipGrid model in pycontrails 0.51.0
Simulation of the heat mitigation potential of unsealing measures in cities by parameterizing grass grid pavers for urban microclimate modelling with ENVI-met (V5)
AI-NAOS: an AI-based nonspherical aerosol optical scheme for the chemical weather model GRAPES_Meso5.1/CUACE
Orbital-Radar v1.0.0: a tool to transform suborbital radar observations to synthetic EarthCARE cloud radar data
The Modular and Integrated Data Assimilation System at Environment and Climate Change Canada (MIDAS v3.9.1)
A new set of indicators for model evaluation complementing to FAIRMODE’s MQO
Modeling of polycyclic aromatic hydrocarbons (PAHs) from global to regional scales: model development (IAP-AACM_PAH v1.0) and investigation of health risks in 2013 and 2018 in China
LIMA (v2.0): A full two-moment cloud microphysical scheme for the mesoscale non-hydrostatic model Meso-NH v5-6
SLUCM+BEM (v1.0): a simple parameterisation for dynamic anthropogenic heat and electricity consumption in WRF-Urban (v4.3.2)
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Source-specific bias correction of US background and anthropogenic ozone modeled in CMAQ
Observational operator for fair model evaluation with ground NO2 measurements
Valid time shifting ensemble Kalman filter (VTS-EnKF) for dust storm forecasting
The third Met Office Unified Model-JULES Regional Atmosphere and Land Configuration, RAL3
An updated parameterization of the unstable atmospheric surface layer in the Weather Research and Forecasting (WRF) modeling system
The impact of cloud microphysics and ice nucleation on Southern Ocean clouds assessed with single-column modeling and instrument simulators
An updated aerosol simulation in the Community Earth System Model (v2.1.3): dust and marine aerosol emissions and secondary organic aerosol formation
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Development of the MPAS-CMAQ coupled system (V1.0) for multiscale global air quality modeling
UA-ICON with NWP physics package (version: ua-icon-2.1): mean state and variability of the middle atmosphere
Assessment of object-based indices to identify convective organization
Diagnosis of winter precipitation types using Spectral Bin Model (SBM): Comparison of five methods using ICE-POP 2018 field experiment data
The Global Forest Fire Emissions Prediction System version 1.0
Impact of Multiple Radar Wind Profilers Data Assimilation on Convective Scale Short-Term Rainfall Forecasts: OSSE Studies over the Beijing-Tianjin-Hebei region
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Ji Won Yoon, Seungyeon Lee, Ebony Lee, and Seon Ki Park
Geosci. Model Dev., 18, 2303–2328, https://doi.org/10.5194/gmd-18-2303-2025, https://doi.org/10.5194/gmd-18-2303-2025, 2025
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This study evaluates the Weather Research and Forecasting Model (WRF) coupled with Chemistry (WRF-Chem) to predict a mega Asian dust storm (ADS) over South Korea on 28–29 March 2021. We assessed combinations of five dust emission and four land surface schemes by analyzing meteorological and air quality variables. The best scheme combination reduced the root mean square error (RMSE) for particulate matter 10 (PM10) by up to 29.6 %, demonstrating the highest performance.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
Geosci. Model Dev., 18, 2231–2248, https://doi.org/10.5194/gmd-18-2231-2025, https://doi.org/10.5194/gmd-18-2231-2025, 2025
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The effectiveness of this assimilation system and its sensitivity to the ensemble member size and length of the assimilation window are investigated. This study advances our understanding of the selection of basic parameters in the four-dimensional local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate-matter-polluted environment.
Jens Peter Karolus Wenceslaus Frankemölle, Johan Camps, Pieter De Meutter, and Johan Meyers
Geosci. Model Dev., 18, 1989–2003, https://doi.org/10.5194/gmd-18-1989-2025, https://doi.org/10.5194/gmd-18-1989-2025, 2025
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To detect anomalous radioactivity in the environment, it is paramount that we understand the natural background level. In this work, we propose a statistical model to describe the most likely background level and the associated uncertainty in a network of dose rate detectors. We train, verify, and validate the model using real environmental data. Using the model, we show that we can correctly predict the background level in a subset of the detector network during a known
anomalous event.
Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, David Bolsée, Xavier Fettweis, and Marilaure Grégoire
Geosci. Model Dev., 18, 1965–1988, https://doi.org/10.5194/gmd-18-1965-2025, https://doi.org/10.5194/gmd-18-1965-2025, 2025
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The MAR (Modèle Régional Atmosphérique) is a regional climate model used for weather forecasting and studying the climate over various regions. This paper presents an update of MAR thanks to which it can precisely decompose solar radiation, in particular in the UV (ultraviolet) and photosynthesis ranges, both being critical to human health and ecosystems. As a first application of this new capability, this paper presents a method for predicting UV indices with MAR.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
Geosci. Model Dev., 18, 1947–1964, https://doi.org/10.5194/gmd-18-1947-2025, https://doi.org/10.5194/gmd-18-1947-2025, 2025
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Direct assimilation of observations from ground-based microwave radiometers (GMRs) holds significant potential for improving forecast accuracy. Radiative transfer models (RTMs) play a crucial role in direct data assimilation. In this study, we introduce a new RTM, the Advanced Radiative Transfer Modeling System – Ground-Based (ARMS-gb), designed to simulate brightness temperatures observed by GMRs along with their Jacobians. Several enhancements have been incorporated to achieve higher accuracy.
R. Phani Murali Krishna, Siddharth Kumar, A. Gopinathan Prajeesh, Peter Bechtold, Nils Wedi, Kumar Roy, Malay Ganai, B. Revanth Reddy, Snehlata Tirkey, Tanmoy Goswami, Radhika Kanase, Sahadat Sarkar, Medha Deshpande, and Parthasarathi Mukhopadhyay
Geosci. Model Dev., 18, 1879–1894, https://doi.org/10.5194/gmd-18-1879-2025, https://doi.org/10.5194/gmd-18-1879-2025, 2025
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The High-Resolution Global Forecast Model (HGFM) is an advanced iteration of the operational Global Forecast System (GFS) model. HGFM can produce forecasts at a spatial scale of ~6 km in tropics. It demonstrates improved accuracy in short- to medium-range weather prediction over the Indian region, with notable success in predicting extreme events. Further, the model will be entrusted to operational forecasting agencies after validation and testing.
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev., 18, 1851–1878, https://doi.org/10.5194/gmd-18-1851-2025, https://doi.org/10.5194/gmd-18-1851-2025, 2025
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Nowcasting models struggle with the rapid evolution of heavy rain, and common verification methods are unable to describe how accurately the models predict the growth and decay of heavy rain. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and the model skill is then evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with four open-source models.
Andrew Geiss and Po-Lun Ma
Geosci. Model Dev., 18, 1809–1827, https://doi.org/10.5194/gmd-18-1809-2025, https://doi.org/10.5194/gmd-18-1809-2025, 2025
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Particles in the Earth's atmosphere strongly impact the planet's energy budget, and atmosphere simulations require accurate representation of their interaction with light. This work introduces two approaches to represent light scattering by small particles. The first is a scattering simulator based on Mie theory implemented in Python. The second is a neural network emulator that is more accurate than existing methods and is fast enough to be used in climate and weather simulations.
Qin Wang, Bo Zeng, Gong Chen, and Yaoting Li
Geosci. Model Dev., 18, 1769–1784, https://doi.org/10.5194/gmd-18-1769-2025, https://doi.org/10.5194/gmd-18-1769-2025, 2025
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This study evaluates the performance of four planetary boundary layer (PBL) schemes in near-surface wind fields over the Sichuan Basin, China. Using 112 sensitivity experiments with the Weather Research and Forecasting (WRF) model and focusing on 28 wind events, it is found that wind direction was less sensitive to the PBL schemes. The quasi-normal scale elimination (QNSE) scheme captured temporal variations best, while the Mellor–Yamada–Janjić (MYJ) scheme had the least error in wind speed.
Tai-Long He, Nikhil Dadheech, Tammy M. Thompson, and Alexander J. Turner
Geosci. Model Dev., 18, 1661–1671, https://doi.org/10.5194/gmd-18-1661-2025, https://doi.org/10.5194/gmd-18-1661-2025, 2025
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It is computationally expensive to infer greenhouse gas (GHG) emissions using atmospheric observations. This is partly due to the detailed model used to represent atmospheric transport. We demonstrate how a machine learning (ML) model can be used to simulate high-resolution atmospheric transport. This type of ML model will help estimate GHG emissions using dense observations, which are becoming increasingly common with the proliferation of urban monitoring networks and geostationary satellites.
Wei Li, Beiming Tang, Patrick C. Campbell, Youhua Tang, Barry Baker, Zachary Moon, Daniel Tong, Jianping Huang, Kai Wang, Ivanka Stajner, and Raffaele Montuoro
Geosci. Model Dev., 18, 1635–1660, https://doi.org/10.5194/gmd-18-1635-2025, https://doi.org/10.5194/gmd-18-1635-2025, 2025
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The study describes the updates of NOAA's current UFS-AQMv7 air quality forecast model by incorporating the latest scientific and structural changes in CMAQv5.4. An evaluation during the summer of 2023 shows that the updated model overall improves the simulation of MDA8 O3 by reducing the bias by 8%–12% in the contiguous US. PM2.5 predictions have mixed results due to wildfire, highlighting the need for future refinements.
Yanwei Zhu, Aitor Atencia, Markus Dabernig, and Yong Wang
Geosci. Model Dev., 18, 1545–1559, https://doi.org/10.5194/gmd-18-1545-2025, https://doi.org/10.5194/gmd-18-1545-2025, 2025
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Most works have delved into convective weather nowcasting, and only a few works have discussed the nowcasting uncertainty for variables at the surface level. Hence, we proposed a method to estimate uncertainty. Generating appropriate noises associated with the characteristic of the error in analysis can simulate the uncertainty of nowcasting. This method can contribute to the estimation of near–surface analysis uncertainty in both nowcasting applications and ensemble nowcasting development.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
Geosci. Model Dev., 18, 1505–1544, https://doi.org/10.5194/gmd-18-1505-2025, https://doi.org/10.5194/gmd-18-1505-2025, 2025
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The Community Inversion Framework (CIF) brings together methods for estimating greenhouse gas fluxes from atmospheric observations. The initial ensemble method implemented in CIF was found to be incomplete and could hardly be compared to other ensemble methods employed in the inversion community. In this paper, we present and evaluate a new implementation of the ensemble mode, building upon the initial developments.
Astrid Kerkweg, Timo Kirfel, Duong H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev., 18, 1265–1286, https://doi.org/10.5194/gmd-18-1265-2025, https://doi.org/10.5194/gmd-18-1265-2025, 2025
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Normally, the Modular Earth Submodel System (MESSy) is linked to complete dynamic models to create chemical climate models. However, the modular concept of MESSy and the newly developed DWARF component presented here make it possible to create simplified models that contain only one or a few process descriptions. This is very useful for technical optimisation, such as porting to GPUs, and can be used to create less complex models, such as a chemical box model.
Edward C. Chan, Ilona J. Jäkel, Basit Khan, Martijn Schaap, Timothy M. Butler, Renate Forkel, and Sabine Banzhaf
Geosci. Model Dev., 18, 1119–1139, https://doi.org/10.5194/gmd-18-1119-2025, https://doi.org/10.5194/gmd-18-1119-2025, 2025
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An enhanced emission module has been developed for the PALM model system, improving flexibility and scalability of emission source representation across different sectors. A model for parametrized domestic emissions has also been included, for which an idealized model run is conducted for particulate matter (PM10). The results show that, in addition to individual sources and diurnal variations in energy consumption, vertical transport and urban topology play a role in concentration distribution.
Gregor Ehrensperger, Thorsten Simon, Georg J. Mayr, and Tobias Hell
Geosci. Model Dev., 18, 1141–1153, https://doi.org/10.5194/gmd-18-1141-2025, https://doi.org/10.5194/gmd-18-1141-2025, 2025
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As lightning is a brief and localized event, it is not explicitly resolved in atmospheric models. Instead, expert-based auxiliary descriptions are used to assess it. This study explores how AI can improve our understanding of lightning without relying on traditional expert knowledge. We reveal that AI independently identified the key factors known to experts as essential for lightning in the Alps region. This shows how knowledge discovery could be sped up in areas with limited expert knowledge.
David Patoulias, Kalliopi Florou, and Spyros N. Pandis
Geosci. Model Dev., 18, 1103–1118, https://doi.org/10.5194/gmd-18-1103-2025, https://doi.org/10.5194/gmd-18-1103-2025, 2025
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The effect of the assumed atmospheric nucleation mechanism on particle number concentrations and size distribution was investigated. Two quite different mechanisms involving sulfuric acid and ammonia or a biogenic organic vapor gave quite similar results which were consistent with measurements at 26 measurement stations across Europe. The number of larger particles that serve as cloud condensation nuclei showed little sensitivity to the assumed nucleation mechanism.
Tim Radke, Susanne Fuchs, Christian Wilms, Iuliia Polkova, and Marc Rautenhaus
Geosci. Model Dev., 18, 1017–1039, https://doi.org/10.5194/gmd-18-1017-2025, https://doi.org/10.5194/gmd-18-1017-2025, 2025
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In our study, we built upon previous work to investigate the patterns artificial intelligence (AI) learns to detect atmospheric features like tropical cyclones (TCs) and atmospheric rivers (ARs). As primary objective, we adopt a method to explain the AI used and investigate the plausibility of learned patterns. We find that plausible patterns are learned for both TCs and ARs. Hence, the chosen method is very useful for gaining confidence in the AI-based detection of atmospheric features.
Stefan Noll, Carsten Schmidt, Patrick Hannawald, Wolfgang Kausch, and Stefan Kimeswenger
EGUsphere, https://doi.org/10.5194/egusphere-2024-3512, https://doi.org/10.5194/egusphere-2024-3512, 2025
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Non-thermal emission from chemical reactions in the Earth's middle und upper atmosphere strongly contributes to the brightness of the night sky below about 2.3 µm. The new Paranal Airglow Line and Continuum Emission model calculates the emission spectrum and its variability with an unprecedented accuracy. Relying on a large spectroscopic data set from astronomical spectrographs and theoretical molecular/atomic data, it is valuable for airglow research and astronomical observatories.
Felipe Cifuentes, Henk Eskes, Enrico Dammers, Charlotte Bryan, and Folkert Boersma
Geosci. Model Dev., 18, 621–649, https://doi.org/10.5194/gmd-18-621-2025, https://doi.org/10.5194/gmd-18-621-2025, 2025
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We tested the capability of the flux divergence approach (FDA) to reproduce known NOx emissions using synthetic NO2 satellite column retrievals from high-resolution model simulations. The FDA accurately reproduced NOx emissions when column observations were limited to the boundary layer and when the variability of the NO2 lifetime, the NOx : NO2 ratio, and NO2 profile shapes were correctly modeled. This introduces strong model dependency, reducing the simplicity of the original FDA formulation.
Stefano Ubbiali, Christian Kühnlein, Christoph Schär, Linda Schlemmer, Thomas C. Schulthess, Michael Staneker, and Heini Wernli
Geosci. Model Dev., 18, 529–546, https://doi.org/10.5194/gmd-18-529-2025, https://doi.org/10.5194/gmd-18-529-2025, 2025
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We explore a high-level programming model for porting numerical weather prediction (NWP) model codes to graphics processing units (GPUs). We present a Python rewrite with the domain-specific library GT4Py (GridTools for Python) of two renowned cloud microphysics schemes and the associated tangent-linear and adjoint algorithms. We find excellent portability, competitive GPU performance, robust execution on diverse computing architectures, and enhanced code maintainability and user productivity.
Pieter Rijsdijk, Henk Eskes, Arlene Dingemans, K. Folkert Boersma, Takashi Sekiya, Kazuyuki Miyazaki, and Sander Houweling
Geosci. Model Dev., 18, 483–509, https://doi.org/10.5194/gmd-18-483-2025, https://doi.org/10.5194/gmd-18-483-2025, 2025
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Clustering high-resolution satellite observations into superobservations improves model validation and data assimilation applications. In our paper, we derive quantitative uncertainties for satellite NO2 column observations based on knowledge of the retrievals, including a detailed analysis of spatial error correlations and representativity errors. The superobservations and uncertainty estimates are tested in a global chemical data assimilation system and are found to improve the forecasts.
Dario Di Santo, Cenlin He, Fei Chen, and Lorenzo Giovannini
Geosci. Model Dev., 18, 433–459, https://doi.org/10.5194/gmd-18-433-2025, https://doi.org/10.5194/gmd-18-433-2025, 2025
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This paper presents the Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool (ML-AMPSIT), a computationally efficient tool that uses machine learning algorithms for sensitivity analysis in atmospheric models. It is tested with the Weather Research and Forecasting (WRF) model coupled with the Noah-Multiparameterization (Noah-MP) land surface model to investigate sea breeze circulation sensitivity to vegetation-related parameters.
Robert Schoetter, Robin James Hogan, Cyril Caliot, and Valéry Masson
Geosci. Model Dev., 18, 405–431, https://doi.org/10.5194/gmd-18-405-2025, https://doi.org/10.5194/gmd-18-405-2025, 2025
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Radiation is relevant to the atmospheric impact on people and infrastructure in cities as it can influence the urban heat island, building energy consumption, and human thermal comfort. A new urban radiation model, assuming a more realistic form of urban morphology, is coupled to the urban climate model Town Energy Balance (TEB). The new TEB is evaluated with a reference radiation model for a variety of urban morphologies, and an improvement in the simulated radiative observables is found.
Zebediah Engberg, Roger Teoh, Tristan Abbott, Thomas Dean, Marc E. J. Stettler, and Marc L. Shapiro
Geosci. Model Dev., 18, 253–286, https://doi.org/10.5194/gmd-18-253-2025, https://doi.org/10.5194/gmd-18-253-2025, 2025
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Contrails forming in some atmospheric conditions may persist and become strongly warming cirrus, while in other conditions may be neutral or cooling. We develop a contrail forecast model to predict contrail climate forcing for any arbitrary point in space and time and explore integration into flight planning and air traffic management. This approach enables contrail interventions to target high-probability high-climate-impact regions and reduce unintended consequences of contrail management.
Nils Eingrüber, Alina Domm, Wolfgang Korres, and Karl Schneider
Geosci. Model Dev., 18, 141–160, https://doi.org/10.5194/gmd-18-141-2025, https://doi.org/10.5194/gmd-18-141-2025, 2025
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Climate change adaptation measures like unsealings can reduce urban heat stress. As grass grid pavers have never been parameterized for microclimate model simulations with ENVI-met, a new parameterization was developed based on field measurements. To analyse the cooling potential, scenario analyses were performed for a densely developed area in Cologne. Statistically significant average cooling effects of up to −11.1 K were found for surface temperature and up to −2.9 K for 1 m air temperature.
Xuan Wang, Lei Bi, Hong Wang, Yaqiang Wang, Wei Han, Xueshun Shen, and Xiaoye Zhang
Geosci. Model Dev., 18, 117–139, https://doi.org/10.5194/gmd-18-117-2025, https://doi.org/10.5194/gmd-18-117-2025, 2025
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The Artificial-Intelligence-based Nonspherical Aerosol Optical Scheme (AI-NAOS) was developed to improve the estimation of the aerosol direct radiation effect and was coupled online with a chemical weather model. The AI-NAOS scheme considers black carbon as fractal aggregates and soil dust as super-spheroids, encapsulated with hygroscopic aerosols. Real-case simulations emphasize the necessity of accurately representing nonspherical and inhomogeneous aerosols in chemical weather models.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev., 18, 101–115, https://doi.org/10.5194/gmd-18-101-2025, https://doi.org/10.5194/gmd-18-101-2025, 2025
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The Python tool Orbital-Radar transfers suborbital radar data (ground-based, airborne, and forward-simulated numerical weather prediction model) into synthetic spaceborne cloud profiling radar data, mimicking platform-specific instrument characteristics, e.g. EarthCARE or CloudSat. The tool's novelty lies in simulating characteristic errors and instrument noise. Thus, existing data sets are transferred into synthetic observations and can be used for satellite calibration–validation studies.
Mark Buehner, Jean-Francois Caron, Ervig Lapalme, Alain Caya, Ping Du, Yves Rochon, Sergey Skachko, Maziar Bani Shahabadi, Sylvain Heilliette, Martin Deshaies-Jacques, Weiguang Chang, and Michael Sitwell
Geosci. Model Dev., 18, 1–18, https://doi.org/10.5194/gmd-18-1-2025, https://doi.org/10.5194/gmd-18-1-2025, 2025
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The Modular and Integrated Data Assimilation System (MIDAS) software is described. The flexible design of MIDAS enables both deterministic and ensemble prediction applications for the atmosphere and several other Earth system components. It is currently used for all main operational weather prediction systems in Canada and also for sea ice and sea surface temperature analysis. The use of MIDAS for multiple Earth system components will facilitate future research on coupled data assimilation.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, and Enrico Pisoni
EGUsphere, https://doi.org/10.5194/egusphere-2024-3690, https://doi.org/10.5194/egusphere-2024-3690, 2025
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We assess the relevance and utility indicators developed within FAIRMODE by evaluating 9 CAMS models in calculated air pollutant values. For NO2, the results highlight difficulties at traffic stations. For PM2.5 and PM10 the bias and Winter-Summer gradients reveal issues. O3 evaluation shows that e.g. seasonal gradients are useful. Overall, the indicators provide valuable insights into model limitations, yet there is a need to reconsider the strictness of some indicators for certain pollutants.
Zichen Wu, Xueshun Chen, Zifa Wang, Huansheng Chen, Zhe Wang, Qing Mu, Lin Wu, Wending Wang, Xiao Tang, Jie Li, Ying Li, Qizhong Wu, Yang Wang, Zhiyin Zou, and Zijian Jiang
Geosci. Model Dev., 17, 8885–8907, https://doi.org/10.5194/gmd-17-8885-2024, https://doi.org/10.5194/gmd-17-8885-2024, 2024
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We developed a model to simulate polycyclic aromatic hydrocarbons (PAHs) from global to regional scales. The model can reproduce PAH distribution well. The concentration of BaP (indicator species for PAHs) could exceed the target values of 1 ng m-3 over some areas (e.g., in central Europe, India, and eastern China). The change in BaP is lower than that in PM2.5 from 2013 to 2018. China still faces significant potential health risks posed by BaP although the Action Plan has been implemented.
Marie Taufour, Jean-Pierre Pinty, Christelle Barthe, Benoît Vié, and Chien Wang
Geosci. Model Dev., 17, 8773–8798, https://doi.org/10.5194/gmd-17-8773-2024, https://doi.org/10.5194/gmd-17-8773-2024, 2024
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We have developed a complete two-moment version of the LIMA (Liquid Ice Multiple Aerosols) microphysics scheme. We have focused on collection processes, where the hydrometeor number transfer is often estimated in proportion to the mass transfer. The impact of these parameterizations on a convective system and the prospects for more realistic estimates of secondary parameters (reflectivity, hydrometeor size) are shown in a first test on an idealized case.
Yuya Takane, Yukihiro Kikegawa, Ko Nakajima, and Hiroyuki Kusaka
Geosci. Model Dev., 17, 8639–8664, https://doi.org/10.5194/gmd-17-8639-2024, https://doi.org/10.5194/gmd-17-8639-2024, 2024
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A new parameterisation for dynamic anthropogenic heat and electricity consumption is described. The model reproduced the temporal variation in and spatial distributions of electricity consumption and temperature well in summer and winter. The partial air conditioning was the most critical factor, significantly affecting the value of anthropogenic heat emission.
Hongyi Li, Ting Yang, Lars Nerger, Dawei Zhang, Di Zhang, Guigang Tang, Haibo Wang, Yele Sun, Pingqing Fu, Hang Su, and Zifa Wang
Geosci. Model Dev., 17, 8495–8519, https://doi.org/10.5194/gmd-17-8495-2024, https://doi.org/10.5194/gmd-17-8495-2024, 2024
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To accurately characterize the spatiotemporal distribution of particulate matter <2.5 µm chemical components, we developed the Nested Air Quality Prediction Model System with the Parallel Data Assimilation Framework (NAQPMS-PDAF) v2.0 for chemical components with non-Gaussian and nonlinear properties. NAQPMS-PDAF v2.0 has better computing efficiency, excels when used with a small ensemble size, and can significantly improve the simulation performance of chemical components.
T. Nash Skipper, Christian Hogrefe, Barron H. Henderson, Rohit Mathur, Kristen M. Foley, and Armistead G. Russell
Geosci. Model Dev., 17, 8373–8397, https://doi.org/10.5194/gmd-17-8373-2024, https://doi.org/10.5194/gmd-17-8373-2024, 2024
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Chemical transport model simulations are combined with ozone observations to estimate the bias in ozone attributable to US anthropogenic sources and individual sources of US background ozone: natural sources, non-US anthropogenic sources, and stratospheric ozone. Results indicate a positive bias correlated with US anthropogenic emissions during summer in the eastern US and a negative bias correlated with stratospheric ozone during spring.
Li Fang, Jianbing Jin, Arjo Segers, Ke Li, Ji Xia, Wei Han, Baojie Li, Hai Xiang Lin, Lei Zhu, Song Liu, and Hong Liao
Geosci. Model Dev., 17, 8267–8282, https://doi.org/10.5194/gmd-17-8267-2024, https://doi.org/10.5194/gmd-17-8267-2024, 2024
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Model evaluations against ground observations are usually unfair. The former simulates mean status over coarse grids and the latter the surrounding atmosphere. To solve this, we proposed the new land-use-based representative (LUBR) operator that considers intra-grid variance. The LUBR operator is validated to provide insights that align with satellite measurements. The results highlight the importance of considering fine-scale urban–rural differences when comparing models and observation.
Mijie Pang, Jianbing Jin, Arjo Segers, Huiya Jiang, Wei Han, Batjargal Buyantogtokh, Ji Xia, Li Fang, Jiandong Li, Hai Xiang Lin, and Hong Liao
Geosci. Model Dev., 17, 8223–8242, https://doi.org/10.5194/gmd-17-8223-2024, https://doi.org/10.5194/gmd-17-8223-2024, 2024
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The ensemble Kalman filter (EnKF) improves dust storm forecasts but faces challenges with position errors. The valid time shifting EnKF (VTS-EnKF) addresses this by adjusting for position errors, enhancing accuracy in forecasting dust storms, as proven in tests on 2021 events, even with smaller ensembles and time intervals.
Mike Bush, David L. A. Flack, Huw W. Lewis, Sylvia I. Bohnenstengel, Chris J. Short, Charmaine Franklin, Adrian P. Lock, Martin Best, Paul Field, Anne McCabe, Kwinten Van Weverberg, Segolene Berthou, Ian Boutle, Jennifer K. Brooke, Seb Cole, Shaun Cooper, Gareth Dow, John Edwards, Anke Finnenkoetter, Kalli Furtado, Kate Halladay, Kirsty Hanley, Margaret A. Hendry, Adrian Hill, Aravindakshan Jayakumar, Richard W. Jones, Humphrey Lean, Joshua C. K. Lee, Andy Malcolm, Marion Mittermaier, Saji Mohandas, Stuart Moore, Cyril Morcrette, Rachel North, Aurore Porson, Susan Rennie, Nigel Roberts, Belinda Roux, Claudio Sanchez, Chun-Hsu Su, Simon Tucker, Simon Vosper, David Walters, James Warner, Stuart Webster, Mark Weeks, Jonathan Wilkinson, Michael Whitall, Keith D. Williams, and Hugh Zhang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-201, https://doi.org/10.5194/gmd-2024-201, 2024
Revised manuscript accepted for GMD
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RAL configurations define settings for the Unified Model atmosphere and Joint UK Land Environment Simulator. The third version of the Regional Atmosphere and Land (RAL3) science configuration for kilometre and sub-km scale modelling represents a major advance compared to previous versions (RAL2) by delivering a common science definition for applications in tropical and mid-latitude regions. RAL3 has more realistic precipitation distributions and improved representation of clouds and visibility.
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.
Markus Kunze, Christoph Zülicke, Tarique Adnan Siddiqui, Claudia Christine Stephan, Yosuke Yamazaki, Claudia Stolle, Sebastian Borchert, and Hauke Schmidt
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-191, https://doi.org/10.5194/gmd-2024-191, 2024
Revised manuscript accepted for GMD
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We present the Icosahedral Nonhydrostatic (ICON) general circulation model with upper atmosphere extension with the physics package for numerical weather prediction (UA-ICON(NWP)). The parameters for the gravity wave parameterizations were optimized, and realistic modelling of the thermal and dynamic state of the mesopause regions was achieved. UA-ICON(NWP) now shows a realistic frequency of major sudden stratospheric warmings and well-represented solar tides in temperature.
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.
Wonbae Bang, Jacob Carlin, Kwonil Kim, Alexander Ryzhkov, Guosheng Liu, and Gyuwon Lee
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-179, https://doi.org/10.5194/gmd-2024-179, 2024
Revised manuscript accepted for GMD
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Microphysics model-based diagnosis such as the spectral bin model (SBM) recently has been attempted to diagnose winter precipitation types. In this study, the accuracy of SBM-based precipitation type diagnosis is compared with other traditional methods. SBM have relatively higher accuracy about snow and wetsnow events whereas lower accuracy about rain event. When microphysics scheme in the SBM was optimized for the corresponding region, accuracy about rain events was improved.
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.
Juan Zhao, Jianping Guo, and Xiaohui Zheng
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-194, https://doi.org/10.5194/gmd-2024-194, 2024
Revised manuscript accepted for GMD
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A series of observing system simulation experiments are conducted to assess the impact of multiple radar wind profiler (RWP) networks on convective scale numerical weather prediction. Results from three southwest-type heavy rainfall cases in the Beijing-Tianjin-Hebei region suggest the added forecast skill of ridge and foothill networks associated with the Taihang Mountains over the existing RWP network. This research provides valuable guidance for designing optimal RWP networks in the region.
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.
Cited articles
Abbatt, J. P. D., Leaitch, W. R., Aliabadi, A. A., Bertram, A. K., Blanchet, J.-P., Boivin-Rioux, A., Bozem, H., Burkart, J., Chang, R. Y. W., Charette, J., Chaubey, J. P., Christensen, R. J., Cirisan, A., Collins, D. B., Croft, B., Dionne, J., Evans, G. J., Fletcher, C. G., Galí, M., Ghahremaninezhad, R., Girard, E., Gong, W., Gosselin, M., Gourdal, M., Hanna, S. J., Hayashida, H., Herber, A. B., Hesaraki, S., Hoor, P., Huang, L., Hussherr, R., Irish, V. E., Keita, S. A., Kodros, J. K., Köllner, F., Kolonjari, F., Kunkel, D., Ladino, L. A., Law, K., Levasseur, M., Libois, Q., Liggio, J., Lizotte, M., Macdonald, K. M., Mahmood, R., Martin, R. V., Mason, R. H., Miller, L. A., Moravek, A., Mortenson, E., Mungall, E. L., Murphy, J. G., Namazi, M., Norman, A.-L., O'Neill, N. T., Pierce, J. R., Russell, L. M., Schneider, J., Schulz, H., Sharma, S., Si, M., Staebler, R. M., Steiner, N. S., Thomas, J. L., von Salzen, K., Wentzell, J. J. B., Willis, M. D., Wentworth, G. R., Xu, J.-W., and Yakobi-Hancock, J. D.: Overview paper: New insights into aerosol and climate in the Arctic, Atmos. Chem. Phys., 19, 2527–2560, https://doi.org/10.5194/acp-19-2527-2019, 2019. a, b
Archuleta, C. M., DeMott, P. J., and Kreidenweis, S. M.: Ice nucleation by surrogates for atmospheric mineral dust and mineral dust/sulfate particles at cirrus temperatures, Atmos. Chem. Phys., 5, 2617–2634, https://doi.org/10.5194/acp-5-2617-2005, 2005. a
Atmospheric Radiation Measurement (ARM) user facility: CLDMICROPROP-51, available at: https://www.arm.gov/data/data-sources/cldmicroprop-51, last access: September 2020. a
Atkinson, D. E., Sassen, K., Hayashi, M., Cahill, C. F., Shaw, G., Harrigan, D., and Fuelberg, H.: Aerosol properties over Interior Alaska from lidar, DRUM Impactor sampler, and OPC-sonde measurements and their meteorological context during ARCTAS-A, April 2008, Atmos. Chem. Phys., 13, 1293–1310, https://doi.org/10.5194/acp-13-1293-2013, 2013. a, b
Berg, L. K., Shrivastava, M., Easter, R. C., Fast, J. D., Chapman, E. G., Liu, Y., and Ferrare, R. A.: A new WRF-Chem treatment for studying regional-scale impacts of cloud processes on aerosol and trace gases in parameterized cumuli, Geosci. Model Dev., 8, 409–429, https://doi.org/10.5194/gmd-8-409-2015, 2015. a
Bigg, E. K.: The formation of atmospheric ice crystals by the freezing of
droplets, Q. J. Roy. Meteor. Soc., 79,
510–519, https://doi.org/10.1002/qj.49707934207,
1953. a
Blanchet, J.-P. and Girard, E.: Arctic “greenhouse effect”, Nature, 371, p. 383,
https://doi.org/10.1038/371383a0, 1994. a
Boucher, O., Randall, D., Artaxo, P., Bretherton, C., Feingold, G., Forster,
P., Kerminen, V.-M., Kondo, Y., Liao, H., Lohmann, U., Rasch, P., Satheesh,
S., Sherwood, S., B., S., and Zhang, X.: Clouds and Aerosols, in: Climate
Change 2013: The Physical Science Basis, Contribution of Working Group I to
the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge University
Press, Cambridge, United Kingdom and New York, NY, USA, 2013. a
Burton, S. P., Ferrare, R. A., Hostetler, C. A., Hair, J. W., Rogers, R. R., Obland, M. D., Butler, C. F., Cook, A. L., Harper, D. B., and Froyd, K. D.: Aerosol classification using airborne High Spectral Resolution Lidar measurements – methodology and examples, Atmos. Meas. Tech., 5, 73–98, https://doi.org/10.5194/amt-5-73-2012, 2012. a
Chen, F. and Dudhia, J.: Coupling an Advanced Land Surface–Hydrology Model
with the Penn State–NCAR MM5 Modeling System. Part I: Model Implementation
and Sensitivity, Mon. Weather Rev. 129, 569–585,
https://doi.org/10.1175/1520-0493(2001)129<0569:CAALSH>2.0.CO;2, 2001. a
Chen, J.-P., Hazra, A., and Levin, Z.: Parameterizing ice nucleation rates using contact angle and activation energy derived from laboratory data, Atmos. Chem. Phys., 8, 7431–7449, https://doi.org/10.5194/acp-8-7431-2008, 2008. a, b
Chin, M., Rood, R. B., Lin, S.-J., Müller, J.-F., and Thompson, A. M.:
Atmospheric sulfur cycle simulated in the global model GOCART: Model
description and global properties, J. Geophys. Res.-Atmos., 105, 24671–24687, https://doi.org/10.1029/2000jd900384, 2000. a
Cirisan, A., Girard, E., Blanchet, J.-P., Keita, S., Gong, W., Irish, V., and
Bertam, A.: Modellings of the observed INP concentration during Arctic summer
campaigns, Atmosphere, 11, 916, https://doi.org/10.3390/atmos11090916, 2020. a, b, c
Connolly, P. J., Möhler, O., Field, P. R., Saathoff, H., Burgess, R., Choularton, T. W., and Gallagher, M. W.: Corrigendum to: “Studies of heterogeneous freezing by three different desert dust samples;;, Atmos. Chem. Phys., 9, 2805–2824, 2009, Atmos. Chem. Phys., 13, 10079–10080, https://doi.org/10.5194/acp-13-10079-2013, 2013. a
Cooper, W. A.: Ice Initiation in Natural Clouds, Meteor. Mon.,
43, 29–32, https://doi.org/10.1175/0065-9401-21.43.29, 1986. a
Curry, J. A., Schramm, J. L., Rossow, W. B., and Randall, D.: Overview of
Arctic Cloud and Radiation Characteristics, J. Climate, 9,
1731–1764, https://doi.org/10.1175/1520-0442(1996)009<1731:OOACAR>2.0.CO;2, 1996. a
DeMott, P. J., Meyers, M. P., and Cotton, W. R.: Parameterization and Impact
of Ice initiation Processes Relevant to Numerical Model Simulations of Cirrus
Clouds, J. Atmos. Sci., 51, 77–90,
https://doi.org/10.1175/1520-0469(1994)051<0077:PAIOII>2.0.CO;2, 1994. a
DeMott, P. J., Prenni, A. J., Liu, X., Kreidenweis, S. M., Petters, M. D.,
Twohy, C. H., Richardson, M. S., Eidhammer, T., and Rogers, D. C.: Predicting
global atmospheric ice nuclei distributions and their impacts on climate,
P. Natl. Acad. Sci. USA, 107, 11217–11222, https://doi.org/10.1073/pnas.0910818107,
2010. a, b, c
DeMott, P. J., Prenni, A. J., McMeeking, G. R., Sullivan, R. C., Petters, M. D., Tobo, Y., Niemand, M., Möhler, O., Snider, J. R., Wang, Z., and Kreidenweis, S. M.: Integrating laboratory and field data to quantify the immersion freezing ice nucleation activity of mineral dust particles, Atmos. Chem. Phys., 15, 393–409, https://doi.org/10.5194/acp-15-393-2015, 2015. a
Eastwood, M. L., Cremel, S., Gehrke, C., Girard, E., and Bertram, A. K.: Ice
nucleation on mineral dust particles: Onset conditions, nucleation rates and
contact angles, J. Geophys. Res., 113, D22203,
https://doi.org/10.1029/2008jd010639, 2008. a, b, c, d
Eastwood, M. L., Cremel, S., Wheeler, M., Murray, B. J., Girard, E., and
Bertram, A. K.: Effects of sulfuric acid and ammonium sulfate coatings on the
ice nucleation properties of kaolinite particles, Geophys. Res.
Lett., 36, L02811,
https://doi.org/10.1029/2008gl035997, 2009. a, b, c, d
Eckhardt, S., Quennehen, B., Olivié, D. J. L., Berntsen, T. K., and Cherian,
R.: Corrigendum to “Current model capabilities for simulating black carbon and sulfateconcentrations in the Arctic atmosphere: a multi-model evaluationusing a comprehensive measurement data set” published in Atmos. Chem. Phys., 15, 9413–9433, 2015, Atmos. Chem. Phys.,
https://doi.org/10.5194/acp-15-9413-2015-corrigendum, 2015. a
Eidhammer, T., DeMott, P. J., and Kreidenweis, S. M.: A comparison of
heterogeneous ice nucleation parameterizations using a parcel model
framework, J. Geophys. Res., 114, D06202, https://doi.org/10.1029/2008jd011095,
2009. a
Emmons, L. K., Walters, S., Hess, P. G., Lamarque, J.-F., Pfister, G. G., Fillmore, D., Granier, C., Guenther, A., Kinnison, D., Laepple, T., Orlando, J., Tie, X., Tyndall, G., Wiedinmyer, C., Baughcum, S. L., and Kloster, S.: Description and evaluation of the Model for Ozone and Related chemical Tracers, version 4 (MOZART-4), Geosci. Model Dev., 3, 43–67, https://doi.org/10.5194/gmd-3-43-2010, 2010. a, b
Fisher, J. A., Jacob, D. J., Wang, Q., Bahreini, R., Carouge, C. C., Cubison,
M. J., Dibb, J. E., Diehl, T., Jimenez, J. L., Leibensperger, E. M., Lu, Z.,
Meinders, M. B. J., Pye, H. O. T., Quinn, P. K., Sharma, S., Streets, D. G.,
van Donkelaar, A., and Yantosca, R. M.: Sources, distribution, and acidity of
sulfate–ammonium aerosol in the Arctic in winter–spring, Atmos.
Environ., 45, 7301–7318, https://doi.org/10.1016/j.atmosenv.2011.08.030, 2011. a, b, c, d, e, f
Fletcher, N. H.: The physics of rainclouds, Cambridge University Press, 1962. a
Fornea, A. P., Brooks, S. D., Dooley, J. B., and Saha, A.: Heterogeneous
freezing of ice on atmospheric aerosols containing ash, soot, and soil,
J. Geophys. Res., 114, D13201,
https://doi.org/10.1029/2009jd011958, 2009. a
Glaccum, R. A. and Prospero, J. M.: Saharan aerosols over the tropical North
Atlantic – Mineralogy, Mar. Geol., 37, 295–321,
https://doi.org/10.1016/0025-3227(80)90107-3, 1980. a
Grell, G. A., Peckham, S. E., Schmitz, R., McKeen, S. A., Frost, G., Skamarock,
W. C., and Eder, B.: Fully coupled “online” chemistry within the WRF
model, Atmos. Environ., 39, 6957–6975,
https://doi.org/10.1016/j.atmosenv.2005.04.027, 2005. a, b
Grenier, P. and Blanchet, J.-P.: Investigation of the sulphate-induced freezing
inhibition effect from CloudSat and CALIPSO measurements, J.
Geophys. Res., 115, D22205, https://doi.org/10.1029/2010jd013905, 2010. a
Grenier, P., Blanchet, J., and Muñoz‐Alpizar, R.: Study of polar thin ice
clouds and aerosols seen by CloudSat and CALIPSO during midwinter 2007,
J. Geophys. Res., 114, D09201, https://doi.org/10.1029/2008jd010927, 2009. a
Guenther, A.: Corrigendum to ”Estimates of global terrestrial isoprene emissions using MEGAN (Model of Emissions of Gases and Aerosols from Nature)” published in Atmos. Chem. Phys., 6, 3181–3210, 2006, Atmos. Chem. Phys., 7, 4327–4327, https://doi.org/10.5194/acp-7-4327-2007, 2007. a
Hoose, C. and Möhler, O.: Heterogeneous ice nucleation on atmospheric aerosols: a review of results from laboratory experiments, Atmos. Chem. Phys., 12, 9817–9854, https://doi.org/10.5194/acp-12-9817-2012, 2012. a
Hoose, C., Kristjánsson, J. E., Chen, J.-P., and Hazra, A.: A
Classical-Theory-Based Parameterization of Heterogeneous Ice Nucleation by
Mineral Dust, Soot, and Biological Particles in a Global Climate Model,
J. Atmos. Sci., 67, 2483–2503,
https://doi.org/10.1175/2010jas3425.1, 2010. a
Hung, H., Malinowski, A., and Scot, T. M.: Kinetics of Heterogeneous Ice
Nucleation on the Surfaces of Mineral Dust Cores Inserted into Aqueous
Ammonium Sulfate Particles, J. Phys. Chem. A, 107, 1296–1306,
https://doi.org/10.1021/jp021593y, 2003. a
Iacono, M. J., Delamere, J. S., Mlawer, E. J., Shephard, M. W., Clough, S. A.,
and Collins, W. D.: Radiative forcing by long-lived greenhouse gases:
Calculations with the AER radiative transfer models, J. Geophys.
Res., 113, D13103, https://doi.org/10.1029/2008jd009944, 2008. a, b
IPCC: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 1535 pp., 2013. a
Janjić, Z. I.: The Step-Mountain Eta Coordinate Model: Further Developments
of the Convection, Viscous Sublayer, and Turbulence Closure Schemes, Mon.
Weather Rev., 122, 927–945,
https://doi.org/10.1175/1520-0493(1994)122<0927:TSMECM>2.0.CO;2, 1994. a, b
Jouan, C., Pelon, J., Girard, E., Ancellet, G., Blanchet, J. P., and Delanoë, J.: On the relationship between Arctic ice clouds and polluted air masses over the North Slope of Alaska in April 2008, Atmos. Chem. Phys., 14, 1205–1224, https://doi.org/10.5194/acp-14-1205-2014, 2014. a, b, c
Kanji, Z. A. and Abbatt, J. P. D.: Ice Nucleation onto Arizona Test Dust at
Cirrus Temperatures: Effect of Temperature and Aerosol Size on Onset Relative
Humidity, Am. Chem. Soc., 114, 935–941, https://doi.org/10.1021/jp908661m,
2010. a
Kanji, Z. A., Ladino, L. A., Wex, H., Boose, Y., Burkert-Kohn, M., Cziczo,
D. J., and Krämer, M.: Overview of Ice Nucleating Particles, Meteor.
Mon., 58, 1.1–1.33, https://doi.org/10.1175/amsmonographs-d-16-0006.1, 2017. a
Kay, J. E., L'Ecuyer, T., Chepfer, H., Loeb, N., Morrison, A., and Cesana,
G.: Recent Advances in Arctic Cloud and Climate Research, Current Climate
Change Reports, 2, 159–169, https://doi.org/10.1007/s40641-016-0051-9, 2016. a
Keita, S., Girard, E., Raut, J.-C., Pelon, J., Blanchet, J.-P., Lemoine, O.,
and Onishi, T.: Simulating Arctic Ice Clouds during Spring Using an Advanced
Ice Cloud Microphysics in the WRF Model, Atmosphere, 10, 433,
https://doi.org/10.3390/atmos10080433, 2019. a, b, c, d, e, f, g, h, i, j, k, l, m, n
Keita, S. A., Girard, E., Raut, J.-C., Leriche, M., Blanchet, J.-P., Pelon, J., Onishi, T., and Keita, A. C.: paper_gmd-2020-50 (Version 1.0), Zenodo, https://doi.org/10.5281/zenodo.4033654, 2020. a
Khvorostyanov, V. I. and Curry, J. A.: Critical humidities of homogeneous and
heterogeneous ice nucleation: Inferences from extended classical nucleation
theory, J. Geophys. Res., 114, D04207,
https://doi.org/10.1029/2008jd011197,
2009. a, b
Kong, F. and Yau, M. K.: An explicit approach to microphysics in MC2,
Atmosphere-Ocean, 35, 257–291, https://doi.org/10.1080/07055900.1997.9649594, 1997. a
Kulkarni, G., Sanders, C., Zhang, K., Liu, X., and Zhao, C.: Ice nucleation of
bare and sulfuric acid-coated mineral dust particles and implication for
cloud properties, J. Geophys. Res.-Atmos., 119,
9993–10 011, https://doi.org/10.1002/2014JD021567, 2014. a
Kumar, A., Marcolli, C., Luo, B., and Peter, T.: Ice nucleation activity of silicates and aluminosilicates in pure water and aqueous solutions – Part 1: The K-feldspar microcline, Atmos. Chem. Phys., 18, 7057–7079, https://doi.org/10.5194/acp-18-7057-2018, 2018. a
Kumar, A., Marcolli, C., and Peter, T.: Ice nucleation activity of silicates and aluminosilicates in pure water and aqueous solutions – Part 2: Quartz and amorphous silica, Atmos. Chem. Phys., 19, 6035–6058, https://doi.org/10.5194/acp-19-6035-2019, 2019a. a
Kumar, A., Marcolli, C., and Peter, T.: Ice nucleation activity of silicates and aluminosilicates in pure water and aqueous solutions – Part 3: Aluminosilicates, Atmos. Chem. Phys., 19, 6059–6084, https://doi.org/10.5194/acp-19-6059-2019, 2019b. a
Lawson, R. P., Woods, S., Jensen, E., Erfani, E., Gurganus, C., Gallagher, M.,
Connolly, P., Whiteway, J., Baran, A. J., May, P., Heymsfield, A., Schmitt,
C. G., McFarquhar, G., Um, J., Protat, A., Bailey, M., Lance, S., Muehlbauer,
A., Stith, J., Korolev, A., Toon, O. B., and Krämer, M.: A Review of Ice
Particle Shapes in Cirrus formed In Situ and in Anvils, J. Geophys. Res.-Atmos., 124, 10049–10090,
https://doi.org/10.1029/2018JD030122, 2019. a
Liu, X., Penner, J. E., Ghan, S. J., and Wang, M.: Inclusion of Ice
Microphysics in the NCAR Community Atmospheric Model Version 3 (CAM3),
J. Climate, 20, 4526–4547, https://doi.org/10.1175/jcli4264.1, 2007. a, b
Marcolli, C., Gedamke, S., Peter, T., and Zobrist, B.: Efficiency of immersion mode ice nucleation on surrogates of mineral dust, Atmos. Chem. Phys., 7, 5081–5091, https://doi.org/10.5194/acp-7-5081-2007, 2007. a
Martin, S. T.: Phase Transitions of Aqueous Atmospheric Particles, Chem.
Rev., 100, 3403–3454, https://doi.org/10.1021/cr990034t, 2000. a
Matrosov, S. Y., Maahn, M., and de Boer, G.: Observational and Modeling Study
of Ice Hydrometeor Radar Dual-Wavelength Ratios, J. Appl.
Meteorol. Clim., 58, 2005–2017, https://doi.org/10.1175/JAMC-D-19-0018.1,
2019. a
McFarquhar, G. M., Ghan, S., Verlinde, J., Korolev, A., Strapp, J. W., Schmid,
B., Tomlinson, J. M., Wolde, M., Brooks, S. D., Cziczo, D., Dubey, M. K.,
Fan, J., Flynn, C., Gultepe, I., Hubbe, J., Gilles, M. K., Laskin, A.,
Lawson, P., Leaitch, W. R., Liu, P., Liu, X., Lubin, D., Mazzoleni, C.,
Macdonald, A.-M., Moffet, R. C., Morrison, H., Ovchinnikov, M., Shupe, M. D.,
Turner, D. D., Xie, S., Zelenyuk, A., Bae, K., Freer, M., and Glen, A.:
Indirect and Semi-direct Aerosol Campaign, B. Am.
Meteorol. Soc., 92, 183–201, https://doi.org/10.1175/2010bams2935.1, 2011. a, b, c
McFarquhar, G. M., Baumgardner, D., and Heymsfield, A. J.: Background and
Overview, Meteor. Mon., 58, v–ix,
https://doi.org/10.1175/amsmonographs-d-16-0018.1, 2017. a
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,
https://doi.org/10.1175/1520-0450(1992)031<0708:NPINPI>2.0.CO;2, 1992. a, b, c, d
Mölders, N., Tran, H. N. Q., Quinn, P., Sassen, K., Shaw, G. E., and Kramm,
G.: Assessment of WRF/Chem to simulate sub–Arctic boundary layer
characteristics during low solar irradiation using radiosonde, SODAR, and
surface data, Atmos. Pollut. Res., 2, 283–299,
https://doi.org/10.5094/apr.2011.035, 2011. a, b, c
Morrison, H., Curry, J. A., and Khvorostyanov, V. I.: A New Double-Moment
Microphysics Parameterization for Application in Cloud and Climate Models.
Part I: Description, J. Atmos. Sci., 62, 1665–1677,
https://doi.org/10.1175/JAS3446.1, 2005a. a
Morrison, H., Curry, J. A., Shupe, M. D., and Zuidema, P.: A New Double-Moment
Microphysics Parameterization for Application in Cloud and Climate Models.
Part II: Single-Column Modeling of Arctic Clouds, J. Atmos.
Sci., 62, 1678–1693, https://doi.org/10.1175/JAS3447.1, 2005b. a
Murray, B. J., O'Sullivan, D., Atkinson, J. D., and Webb, M. E.: Ice nucleation
by particles immersed in supercooled cloud droplets, Chem. Soc. Rev., 41,
6519–6554, https://doi.org/10.1039/c2cs35200a, 2012. a, b
National Center for Atmospheric Research (NCAR) and University Corporation for Atmospheric Research (UCAR): WRF Source Codes and Graphics Software, available at: https://www2.mmm.ucar.edu/wrf/users/download/get_source.html, last access: September 2020a. a
National Center for Atmospheric Research (NCAR) and University Corporation for Atmospheric Research (UCAR): NCEP FNL Operational Model Global Tropospheric Analyses, continuing from July 1999, available at: https://doi.org/10.5065/D6M043C6, last access: September 2020b. a
Niedermeier, D., Ervens, B., Clauss, T., Voigtländer, J., Wex, H., Hartmann,
S., and Stratmann, F.: A computationally efficient description of
heterogeneous freezing: A simplified version of the Soccer ball model,
Geophys. Res. Lett., 41, 736–741, https://doi.org/10.1002/2013gl058684, 2014. a
Panda, A. K., Mishra, B., Mishra, D., and Singh, R.: Effect of sulphuric acid
treatment on the physico-chemical characteristics of kaolin clay, Colloids
and Surface. A, 363, 98–104,
https://doi.org/10.1016/j.colsurfa.2010.04.022, 2010. a
Pant, A., Fok, A., Parsons, M. T., Mak, J., and Bertram, A. K.: Deliquescence
and crystallization of ammonium sulfate-glutaric acid and sodium
chloride-glutaric acid particles, Geophys. Res. Lett., 31, L12111,
https://doi.org/10.1029/2004GL020025, 2004. a
Pant, A., Parsons, M. T., and Bertram, A. K.: Crystallization of Aqueous
Ammonium Sulfate Particles Internally Mixed with Soot and Kaolinite:
Crystallization Relative Humidities and Nucleation Rates, J.
Phys. Chem. A, 110, 8701–8709, https://doi.org/10.1021/jp060985s, 2006. a
Parsons, M. T., Mak, J., Lipetz, S. R., and Bertram, A. K.: Deliquescence of
malonic, succinic, glutaric, and adipic acid particles, J. Geophys. Res.-Atmos., 109, D06212, https://doi.org/10.1029/2003jd004075,
2004b. a
Phillips, V. T. J., 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,
https://doi.org/10.1175/jas-d-12-080.1, 2013. a
Prenni, A. J., Petters, M. D., Kreidenweis, S. M., DeMott, P. J., and Ziemann,
P. J.: Cloud droplet activation of secondary organic aerosol, J. Geophys. Res.-Atmos., 112, D10223, https://doi.org/10.1029/2006jd007963, 2007. a
Raut, J.-C., Marelle, L., Fast, J. D., Thomas, J. L., Weinzierl, B., Law, K. S., Berg, L. K., Roiger, A., Easter, R. C., Heimerl, K., Onishi, T., Delanoë, J., and Schlager, H.: Cross-polar transport and scavenging of Siberian aerosols containing black carbon during the 2012 ACCESS summer campaign, Atmos. Chem. Phys., 17, 10969–10995, https://doi.org/10.5194/acp-17-10969-2017, 2017. a
Schoenberg Ferrier, B.: A Double-Moment Multiple-Phase Four-Class Bulk Ice
Scheme. Part I: Description, J. Atmos. Sci., 51,
249–280, https://doi.org/10.1175/1520-0469(1994)051<0249:ADMMPF>2.0.CO;2, 1994. a, b, c
Schwarz, J. P., Gao, R. S., Perring, A. E., Spackman, J. R., and Fahey, D. W.:
Black carbon aerosol size in snow, Sci. Rep., 3, 1356, https://doi.org/10.1038/srep01356,
2013. a
Shantz, N. C., Gultepe, I., Andrews, E., Zelenyuk, A., Earle, M. E., Macdonald,
A. M., Liu, P. S. K., and Leaitch, W. R.: Optical, physical, and chemical
properties of springtime aerosol over Barrow Alaska in 2008, International
J. Climatol., 34, 3125–3138, https://doi.org/10.1002/joc.3898, 2014. a
Shaw, W. J., Jerry Allwine, K., Fritz, B. G., Rutz, F. C., Rishel, J. P., and
Chapman, E. G.: An evaluation of the wind erosion module in DUSTRAN,
Atmos. Environ., 42, 1907–1921, 2008. a
Shindell, D. and Faluvegi, G.: Climate response to regional radiative forcing
during the twentieth century, Nat. Geosci., 2, 294–300,
https://doi.org/10.1038/ngeo473, 2009. a
Shindell, D. T., Chin, M., Dentener, F., Doherty, R. M., Faluvegi, G., Fiore, A. M., Hess, P., Koch, D. M., MacKenzie, I. A., Sanderson, M. G., Schultz, M. G., Schulz, M., Stevenson, D. S., Teich, H., Textor, C., Wild, O., Bergmann, D. J., Bey, I., Bian, H., Cuvelier, C., Duncan, B. N., Folberth, G., Horowitz, L. W., Jonson, J., Kaminski, J. W., Marmer, E., Park, R., Pringle, K. J., Schroeder, S., Szopa, S., Takemura, T., Zeng, G., Keating, T. J., and Zuber, A.: A multi-model assessment of pollution transport to the Arctic, Atmos. Chem. Phys., 8, 5353–5372, https://doi.org/10.5194/acp-8-5353-2008, 2008. a
Sullivan, R. C., Petters, M. D., DeMott, P. J., Kreidenweis, S. M., Wex, H., Niedermeier, D., Hartmann, S., Clauss, T., Stratmann, F., Reitz, P., Schneider, J., and Sierau, B.: Irreversible loss of ice nucleation active sites in mineral dust particles caused by sulphuric acid condensation, Atmos. Chem. Phys., 10, 11471–11487, https://doi.org/10.5194/acp-10-11471-2010, 2010. a, b
Vali, G.: Interpretation of freezing nucleation experiments: singular and stochastic; sites and surfaces, Atmos. Chem. Phys., 14, 5271–5294, https://doi.org/10.5194/acp-14-5271-2014, 2014. a
Vali, G., DeMott, P. J., Möhler, O., and Whale, T. F.: Technical Note: A proposal for ice nucleation terminology, Atmos. Chem. Phys., 15, 10263–10270, https://doi.org/10.5194/acp-15-10263-2015, 2015. a, b
Welti, A., Lüönd, F., Stetzer, O., and Lohmann, U.: Influence of particle size on the ice nucleating ability of mineral dusts, Atmos. Chem. Phys., 9, 6705–6715, https://doi.org/10.5194/acp-9-6705-2009, 2009. a
Welti, A., Lüönd, F., Kanji, Z. A., Stetzer, O., and Lohmann, U.: Time dependence of immersion freezing: an experimental study on size selected kaolinite particles, Atmos. Chem. Phys., 12, 9893–9907, https://doi.org/10.5194/acp-12-9893-2012, 2012. a, b
Wheeler, M. J. and Bertram, A. K.: Deposition nucleation on mineral dust particles: a case against classical nucleation theory with the assumption of a single contact angle, Atmos. Chem. Phys., 12, 1189–1201, https://doi.org/10.5194/acp-12-1189-2012, 2012. a
Wiedinmyer, C., Akagi, S. K., Yokelson, R. J., Emmons, L. K., Al-Saadi, J. A., Orlando, J. J., and Soja, A. J.: The Fire INventory from NCAR (FINN): a high resolution global model to estimate the emissions from open burning, Geosci. Model Dev., 4, 625–641, https://doi.org/10.5194/gmd-4-625-2011, 2011. a, b
Wild, O., Zhu, X., and J., P. M.: Fast-J: Accurate Simulation of In- and
Below-Cloud Photolysis in Tropospheric Chemical Models, J.
Atmos. Chem., 37, 245–282, https://doi.org/10.1023/A:1006415919030, 2000. a, b
Wright, T. P. and Petters, M. D.: The role of time in heterogeneous freezing
nucleation, J. Geophys. Res.-Atmos., 118, 3731–3743,
https://doi.org/10.1002/jgrd.50365, 2013. a
Yang, F., Tan, J., Zhao, Q., Du, Z., He, K., Ma, Y., Duan, F., Chen, G., and Zhao, Q.: Characteristics of PM2.5 speciation in representative megacities and across China, Atmos. Chem. Phys., 11, 5207–5219, https://doi.org/10.5194/acp-11-5207-2011, 2011. a
Young, K. C.: A Numerical Simulation of Wintertime, Orographic Precipitation:
Part I. Description of Model Microphysics and Numerical Techniques, J. Atmos. Sci., 31, 1735–1748,
https://doi.org/10.1175/1520-0469(1974)031<1735:ANSOWO>2.0.CO;2, 1974. a
Zaveri, R. A. and Peters, L. K.: A new lumped structure photochemical mechanism
for large-scale applications, J. Geophys. Res.-Atmos.,
104, 30387–30415, https://doi.org/10.1029/1999jd900876, 1999. a
Zaveri, R. A., Easter, R. C., Fast, J. D., and Peters, L. K.: Model for
Simulating Aerosol Interactions and Chemistry (MOSAIC), J. Geophys. Res.-Atmos., 113, D13204, https://doi.org/10.1029/2007JD008782, 2008. a, b, c
Zhang, Q., Jimenez, J. L., Worsnop, D. R., and Canagaratna, M.: A Case Study of
Urban Particle Acidity and Its Influence on Secondary Organic Aerosol,
Environ. Sci. Technol., 41, 3213–3219, https://doi.org/10.1021/es061812j,
2007.
a
Zhao, C. and Garrett, T. J.: Effects of Arctic haze on surface cloud radiative
forcing, Geophys. Res. Lett., 42, 557–564,
https://doi.org/10.1002/2014gl062015, 2015. a
