Articles | Volume 24, issue 12
https://doi.org/10.5194/acp-24-7421-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-24-7421-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Modeling impacts of dust mineralogy on fast climate response
Qianqian Song
CORRESPONDING AUTHOR
Atmospheric and Oceanic Sciences Program, Princeton University, Princeton, NJ, USA
Paul Ginoux
NOAA Geophysical Fluid Dynamics Laboratory, Princeton, NJ, USA
María Gonçalves Ageitos
Projects and Construction Engineering Department, Universitat Politècnica de Catalunya-Barcelona TECH, Terrassa, Spain
Barcelona Supercomputing Center, Barcelona, Spain
Ron L. Miller
NASA Goddard Institute for Space Studies, New York, NY, USA
Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY, USA
Vincenzo Obiso
NASA Goddard Institute for Space Studies, New York, NY, USA
Carlos Pérez García-Pando
Barcelona Supercomputing Center, Barcelona, Spain
ICREA, Catalan Institution for Research and Advanced Studies, Barcelona, Spain
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Ruth A. R. Digby, Nathan P. Gillett, Adam H. Monahan, Knut von Salzen, Antonis Gkikas, Qianqian Song, and Zhibo Zhang
Atmos. Chem. Phys., 24, 2077–2097, https://doi.org/10.5194/acp-24-2077-2024, https://doi.org/10.5194/acp-24-2077-2024, 2024
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The COVID-19 lockdowns reduced aerosol emissions. We ask whether these reductions affected regional aerosol optical depth (AOD) and compare the observed changes to predictions from Earth system models. Only India has an observed AOD reduction outside of typical variability. Models overestimate the response in some regions, but when key biases have been addressed, the agreement is improved. Our results suggest that current models can realistically predict the effects of future emission changes.
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Atmos. Meas. Tech., 18, 2183–2200, https://doi.org/10.5194/amt-18-2183-2025, https://doi.org/10.5194/amt-18-2183-2025, 2025
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Manon Gaillard, Vincent Vionnet, Matthieu Lafaysse, Marie Dumont, and Paul Ginoux
The Cryosphere, 19, 769–792, https://doi.org/10.5194/tc-19-769-2025, https://doi.org/10.5194/tc-19-769-2025, 2025
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This study presents an efficient method to improve large-scale snow albedo simulations by considering the spatial variability in light-absorbing particles (LAPs) like black carbon and dust. A global climatology of LAP deposition was created and used to optimize a parameter in the Crocus snow model. Testing at 10 global sites improved albedo predictions by 10 % on average and over 25 % in the Arctic. This method can enhance other snow models' predictions without complex simulations.
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Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-43, https://doi.org/10.5194/essd-2025-43, 2025
Revised manuscript accepted for ESSD
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The Copernicus Atmosphere Monitoring Service – Regional Production delivers daily forecasts, analyses, and reanalyses of air quality in Europe. The Service relies on a distributed modelling production by eleven leading European modelling teams following stringent requirements with an operational design which has no equivalent in the world. All the products are full, free, open and quality assured and disseminated with a high level of reliability.
Dene Bowdalo, Sara Basart, Marc Guevara, Oriol Jorba, Carlos Pérez García-Pando, Monica Jaimes Palomera, Olivia Rivera Hernandez, Melissa Puchalski, David Gay, Jörg Klausen, Sergio Moreno, Stoyka Netcheva, and Oksana Tarasova
Earth Syst. Sci. Data, 16, 4417–4495, https://doi.org/10.5194/essd-16-4417-2024, https://doi.org/10.5194/essd-16-4417-2024, 2024
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Enrico Zorzetto, Sergey Malyshev, Paul Ginoux, and Elena Shevliakova
Geosci. Model Dev., 17, 7219–7244, https://doi.org/10.5194/gmd-17-7219-2024, https://doi.org/10.5194/gmd-17-7219-2024, 2024
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We describe a new snow scheme developed for use in global climate models, which simulates the interactions of snowpack with vegetation, atmosphere, and soil. We test the new snow model over a set of sites where in situ observations are available. We find that when compared to a simpler snow model, this model improves predictions of seasonal snow and of soil temperature under the snowpack, important variables for simulating both the hydrological cycle and the global climate system.
Manu Anna Thomas, Klaus Wyser, Shiyu Wang, Marios Chatziparaschos, Paraskevi Georgakaki, Montserrat Costa-Surós, Maria Gonçalves Ageitos, Maria Kanakidou, Carlos Pérez García-Pando, Athanasios Nenes, Twan van Noije, Philippe Le Sager, and Abhay Devasthale
Geosci. Model Dev., 17, 6903–6927, https://doi.org/10.5194/gmd-17-6903-2024, https://doi.org/10.5194/gmd-17-6903-2024, 2024
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Adolfo González-Romero, Cristina González-Flórez, Agnesh Panta, Jesús Yus-Díez, Patricia Córdoba, Andres Alastuey, Natalia Moreno, Melani Hernández-Chiriboga, Konrad Kandler, Martina Klose, Roger N. Clark, Bethany L. Ehlmann, Rebecca N. Greenberger, Abigail M. Keebler, Phil Brodrick, Robert Green, Paul Ginoux, Xavier Querol, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 24, 9155–9176, https://doi.org/10.5194/acp-24-9155-2024, https://doi.org/10.5194/acp-24-9155-2024, 2024
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Kevin Oliveira, Marc Guevara, Oriol Jorba, Hervé Petetin, Dene Bowdalo, Carles Tena, Gilbert Montané Pinto, Franco López, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 24, 7137–7177, https://doi.org/10.5194/acp-24-7137-2024, https://doi.org/10.5194/acp-24-7137-2024, 2024
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Adolfo González-Romero, Cristina González-Flórez, Agnesh Panta, Jesús Yus-Díez, Patricia Córdoba, Andres Alastuey, Natalia Moreno, Konrad Kandler, Martina Klose, Roger N. Clark, Bethany L. Ehlmann, Rebecca N. Greenberger, Abigail M. Keebler, Phil Brodrick, Robert O. Green, Xavier Querol, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 24, 6883–6910, https://doi.org/10.5194/acp-24-6883-2024, https://doi.org/10.5194/acp-24-6883-2024, 2024
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Vincenzo Obiso, María Gonçalves Ageitos, Carlos Pérez García-Pando, Jan P. Perlwitz, Gregory L. Schuster, Susanne E. Bauer, Claudia Di Biagio, Paola Formenti, Kostas Tsigaridis, and Ron L. Miller
Atmos. Chem. Phys., 24, 5337–5367, https://doi.org/10.5194/acp-24-5337-2024, https://doi.org/10.5194/acp-24-5337-2024, 2024
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We calculate the dust direct radiative effect (DRE) in an Earth system model accounting for regionally varying soil mineralogy through a new observationally constrained method. Linking dust absorption at solar wavelengths to the varying amount of specific minerals (i.e., iron oxides) improves the modeled range of dust single scattering albedo compared to observations and increases the global cooling by dust. Our results may contribute to improved estimates of the dust DRE and its climate impact.
Danny M. Leung, Jasper F. Kok, Longlei Li, Natalie M. Mahowald, David M. Lawrence, Simone Tilmes, Erik Kluzek, Martina Klose, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 24, 2287–2318, https://doi.org/10.5194/acp-24-2287-2024, https://doi.org/10.5194/acp-24-2287-2024, 2024
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This study uses a premier Earth system model to evaluate a new desert dust emission scheme proposed in our companion paper. We show that our scheme accounts for more dust emission physics, hence matching better against observations than other existing dust emission schemes do. Our scheme's dust emissions also couple tightly with meteorology, hence likely improving the modeled dust sensitivity to climate change. We believe this work is vital for improving dust representation in climate models.
Ruth A. R. Digby, Nathan P. Gillett, Adam H. Monahan, Knut von Salzen, Antonis Gkikas, Qianqian Song, and Zhibo Zhang
Atmos. Chem. Phys., 24, 2077–2097, https://doi.org/10.5194/acp-24-2077-2024, https://doi.org/10.5194/acp-24-2077-2024, 2024
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The COVID-19 lockdowns reduced aerosol emissions. We ask whether these reductions affected regional aerosol optical depth (AOD) and compare the observed changes to predictions from Earth system models. Only India has an observed AOD reduction outside of typical variability. Models overestimate the response in some regions, but when key biases have been addressed, the agreement is improved. Our results suggest that current models can realistically predict the effects of future emission changes.
Natalie M. Mahowald, Longlei Li, Julius Vira, Marje Prank, Douglas S. Hamilton, Hitoshi Matsui, Ron L. Miller, Louis Lu, Ezgi Akyuz, Daphne Meidan, Peter Hess, Heikki Lihavainen, Christine Wiedinmyer, Jenny Hand, Maria Grazia Alaimo, Célia Alves, Andres Alastuey, Paulo Artaxo, Africa Barreto, Francisco Barraza, Silvia Becagli, Giulia Calzolai, Shankarararman Chellam, Ying Chen, Patrick Chuang, David D. Cohen, Cristina Colombi, Evangelia Diapouli, Gaetano Dongarra, Konstantinos Eleftheriadis, Corinne Galy-Lacaux, Cassandra Gaston, Dario Gomez, Yenny González Ramos, Hannele Hakola, Roy M. Harrison, Chris Heyes, Barak Herut, Philip Hopke, Christoph Hüglin, Maria Kanakidou, Zsofia Kertesz, Zbiginiw Klimont, Katriina Kyllönen, Fabrice Lambert, Xiaohong Liu, Remi Losno, Franco Lucarelli, Willy Maenhaut, Beatrice Marticorena, Randall V. Martin, Nikolaos Mihalopoulos, Yasser Morera-Gomez, Adina Paytan, Joseph Prospero, Sergio Rodríguez, Patricia Smichowski, Daniela Varrica, Brenna Walsh, Crystal Weagle, and Xi Zhao
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-1, https://doi.org/10.5194/essd-2024-1, 2024
Preprint withdrawn
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Aerosol particles can interact with incoming solar radiation and outgoing long wave radiation, change cloud properties, affect photochemistry, impact surface air quality, and when deposited impact surface albedo of snow and ice, and modulate carbon dioxide uptake by the land and ocean. Here we present a new compilation of aerosol observations including composition, a methodology for comparing the datasets to model output, and show the implications of these results using one model.
Marc Guevara, Santiago Enciso, Carles Tena, Oriol Jorba, Stijn Dellaert, Hugo Denier van der Gon, and Carlos Pérez García-Pando
Earth Syst. Sci. Data, 16, 337–373, https://doi.org/10.5194/essd-16-337-2024, https://doi.org/10.5194/essd-16-337-2024, 2024
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A global dataset of emissions from thermal power plants was created for the year 2018. The resulting catalogue reports annual emissions of CO2 and co-emitted species (NOx, CO, SO2 and CH4) for more than 16000 individual facilities at their exact geographical locations. Information on the temporal and vertical distributions of the emissions is also provided at the facility level. The dataset is intended to support current and future satellite emission monitoring and inverse modelling efforts.
Adolfo González-Romero, Cristina González-Flórez, Agnesh Panta, Jesús Yus-Díez, Cristina Reche, Patricia Córdoba, Natalia Moreno, Andres Alastuey, Konrad Kandler, Martina Klose, Clarissa Baldo, Roger N. Clark, Zongbo Shi, Xavier Querol, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 23, 15815–15834, https://doi.org/10.5194/acp-23-15815-2023, https://doi.org/10.5194/acp-23-15815-2023, 2023
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The effect of dust emitted from desertic surfaces upon climate and ecosystems depends on size and mineralogy, but data from soil mineral atlases of desert soils are scarce. We performed particle-size distribution, mineralogy, and Fe speciation in southern Morocco. Results show coarser particles with high quartz proportion are near the elevated areas, while in depressed areas, sizes are finer, and proportions of clays and nano-Fe oxides are higher. This difference is important for dust modelling.
María Gonçalves Ageitos, Vincenzo Obiso, Ron L. Miller, Oriol Jorba, Martina Klose, Matt Dawson, Yves Balkanski, Jan Perlwitz, Sara Basart, Enza Di Tomaso, Jerónimo Escribano, Francesca Macchia, Gilbert Montané, Natalie M. Mahowald, Robert O. Green, David R. Thompson, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 23, 8623–8657, https://doi.org/10.5194/acp-23-8623-2023, https://doi.org/10.5194/acp-23-8623-2023, 2023
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Dust aerosols affect our climate differently depending on their mineral composition. We include dust mineralogy in an atmospheric model considering two existing soil maps, which still have large associated uncertainties. The soil data and the distribution of the minerals in different aerosol sizes are key to our model performance. We find significant regional variations in climate-relevant variables, which supports including mineralogy in our current models and the need for improved soil maps.
Jianyu Zheng, Zhibo Zhang, Hongbin Yu, Anne Garnier, Qianqian Song, Chenxi Wang, Claudia Di Biagio, Jasper F. Kok, Yevgeny Derimian, and Claire Ryder
Atmos. Chem. Phys., 23, 8271–8304, https://doi.org/10.5194/acp-23-8271-2023, https://doi.org/10.5194/acp-23-8271-2023, 2023
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We developed a multi-year satellite-based retrieval of dust optical depth at 10 µm and the coarse-mode dust effective diameter over global oceans. It reveals climatological coarse-mode dust transport patterns and regional differences over the North Atlantic, the Indian Ocean and the North Pacific.
Marc Guevara, Hervé Petetin, Oriol Jorba, Hugo Denier van der Gon, Jeroen Kuenen, Ingrid Super, Claire Granier, Thierno Doumbia, Philippe Ciais, Zhu Liu, Robin D. Lamboll, Sabine Schindlbacher, Bradley Matthews, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 23, 8081–8101, https://doi.org/10.5194/acp-23-8081-2023, https://doi.org/10.5194/acp-23-8081-2023, 2023
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This study provides an intercomparison of European 2020 emission changes derived from official inventories, which are reported by countries under the framework of several international conventions and directives, and non-official near-real-time estimates, the use of which has significantly grown since the COVID-19 outbreak. The results of the work are used to produce recommendations on how best to approach and make use of near-real-time emissions for modelling and monitoring applications.
Cristina González-Flórez, Martina Klose, Andrés Alastuey, Sylvain Dupont, Jerónimo Escribano, Vicken Etyemezian, Adolfo Gonzalez-Romero, Yue Huang, Konrad Kandler, George Nikolich, Agnesh Panta, Xavier Querol, Cristina Reche, Jesús Yus-Díez, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 23, 7177–7212, https://doi.org/10.5194/acp-23-7177-2023, https://doi.org/10.5194/acp-23-7177-2023, 2023
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Atmospheric mineral dust consists of tiny mineral particles that are emitted by wind erosion from arid regions. Its particle size distribution (PSD) affects its impact on the Earth's system. Nowadays, there is an incomplete understanding of the emitted dust PSD and a lot of debate about its variability. Here, we try to address these issues based on the measurements performed during a wind erosion and dust emission field campaign in the Moroccan Sahara within the framework of FRAGMENT project.
Danny M. Leung, Jasper F. Kok, Longlei Li, Gregory S. Okin, Catherine Prigent, Martina Klose, Carlos Pérez García-Pando, Laurent Menut, Natalie M. Mahowald, David M. Lawrence, and Marcelo Chamecki
Atmos. Chem. Phys., 23, 6487–6523, https://doi.org/10.5194/acp-23-6487-2023, https://doi.org/10.5194/acp-23-6487-2023, 2023
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Desert dust modeling is important for understanding climate change, as dust regulates the atmosphere's greenhouse effect and radiation. This study formulates and proposes a more physical and realistic desert dust emission scheme for global and regional climate models. By considering more aeolian processes in our emission scheme, our simulations match better against dust observations than existing schemes. We believe this work is vital in improving dust representation in climate models.
Aleksander Lacima, Hervé Petetin, Albert Soret, Dene Bowdalo, Oriol Jorba, Zhaoyue Chen, Raúl F. Méndez Turrubiates, Hicham Achebak, Joan Ballester, and Carlos Pérez García-Pando
Geosci. Model Dev., 16, 2689–2718, https://doi.org/10.5194/gmd-16-2689-2023, https://doi.org/10.5194/gmd-16-2689-2023, 2023
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Understanding how air pollution varies across space and time is of key importance for the safeguarding of human health. This work arose in the context of the project EARLY-ADAPT, for which the Barcelona Supercomputing Center developed an air pollution database covering all of Europe. Through different statistical methods, we compared two global pollution models against measurements from ground stations and found significant discrepancies between the observed and the modeled surface pollution.
Michail Mytilinaios, Sara Basart, Sergio Ciamprone, Juan Cuesta, Claudio Dema, Enza Di Tomaso, Paola Formenti, Antonis Gkikas, Oriol Jorba, Ralph Kahn, Carlos Pérez García-Pando, Serena Trippetta, and Lucia Mona
Atmos. Chem. Phys., 23, 5487–5516, https://doi.org/10.5194/acp-23-5487-2023, https://doi.org/10.5194/acp-23-5487-2023, 2023
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Multiscale Online Non-hydrostatic AtmospheRe CHemistry model (MONARCH) dust reanalysis provides a high-resolution 3D reconstruction of past dust conditions, allowing better quantification of climate and socioeconomic dust impacts. We assess the performance of the reanalysis needed to reproduce dust optical depth using dust-related products retrieved from satellite and ground-based observations and show that it reproduces the spatial distribution and seasonal variability of atmospheric dust well.
Alvaro Criado, Jan Mateu Armengol, Hervé Petetin, Daniel Rodriguez-Rey, Jaime Benavides, Marc Guevara, Carlos Pérez García-Pando, Albert Soret, and Oriol Jorba
Geosci. Model Dev., 16, 2193–2213, https://doi.org/10.5194/gmd-16-2193-2023, https://doi.org/10.5194/gmd-16-2193-2023, 2023
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This work aims to derive and evaluate a general statistical post-processing tool specifically designed for the street scale that can be applied to any urban air quality system. Our data fusion methodology corrects NO2 fields based on continuous hourly observations and experimental campaigns. This study enables us to obtain exceedance probability maps of air quality standards. In 2019, 13 % of the Barcelona area had a 70 % or higher probability of exceeding the annual legal NO2 limit of 40 µg/m3.
Hervé Petetin, Marc Guevara, Steven Compernolle, Dene Bowdalo, Pierre-Antoine Bretonnière, Santiago Enciso, Oriol Jorba, Franco Lopez, Albert Soret, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 23, 3905–3935, https://doi.org/10.5194/acp-23-3905-2023, https://doi.org/10.5194/acp-23-3905-2023, 2023
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This study analyses the potential of the TROPOMI space sensor for monitoring the variability of NO2 pollution over the Iberian Peninsula. A reduction of NO2 levels is observed during the weekend and in summer, especially over most urbanized areas, in agreement with surface observations. An enhancement of NO2 is found during summer with TROPOMI over croplands, potentially related to natural soil NO emissions, which illustrates the outstanding value of TROPOMI for complementing surface networks.
Agnesh Panta, Konrad Kandler, Andres Alastuey, Cristina González-Flórez, Adolfo González-Romero, Martina Klose, Xavier Querol, Cristina Reche, Jesús Yus-Díez, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 23, 3861–3885, https://doi.org/10.5194/acp-23-3861-2023, https://doi.org/10.5194/acp-23-3861-2023, 2023
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Desert dust is a major aerosol component of the Earth system and affects the climate. Dust properties are influenced by particle size, mineralogy, shape, and mixing state. This work characterizes freshly emitted individual mineral dust particles from a major source region using electron microscopy. Our new insights into critical particle-specific information will contribute to better constraining climate models that consider mineralogical variations in their representation of the dust cycle.
Zhao-Yue Chen, Raul Méndez, Hervé Petetin, Aleksander Lacima, Carlos Pérez García-Pando, and Joan Ballester
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-104, https://doi.org/10.5194/essd-2023-104, 2023
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Given in the limitations of existing AOD and its size fraction information, a new 18-year daily Aerosol Optical Depth (AOD) dataset over Europe has been developed based on quantile machine learning (QML) models. This dataset improves the ability to monitor and analyse fine-mode and coarse-mode aerosols. They provide better tools to investigate negatively affect human health and have impacts on climate, visibility, and biogeochemical cycling.
Marios Chatziparaschos, Nikos Daskalakis, Stelios Myriokefalitakis, Nikos Kalivitis, Athanasios Nenes, María Gonçalves Ageitos, Montserrat Costa-Surós, Carlos Pérez García-Pando, Medea Zanoli, Mihalis Vrekoussis, and Maria Kanakidou
Atmos. Chem. Phys., 23, 1785–1801, https://doi.org/10.5194/acp-23-1785-2023, https://doi.org/10.5194/acp-23-1785-2023, 2023
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Ice formation is enabled by ice-nucleating particles (INP) at higher temperatures than homogeneous formation and can profoundly affect the properties of clouds. Our global model results show that K-feldspar is the most important contributor to INP concentrations globally, affecting mid-level mixed-phase clouds. However, quartz can significantly contribute and dominates the lowest and the highest altitudes of dust-derived INP, affecting mainly low-level and high-level mixed-phase clouds.
Hervé Petetin, Dene Bowdalo, Pierre-Antoine Bretonnière, Marc Guevara, Oriol Jorba, Jan Mateu Armengol, Margarida Samso Cabre, Kim Serradell, Albert Soret, and Carlos Pérez Garcia-Pando
Atmos. Chem. Phys., 22, 11603–11630, https://doi.org/10.5194/acp-22-11603-2022, https://doi.org/10.5194/acp-22-11603-2022, 2022
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This study investigates the extent to which ozone forecasts provided by the Copernicus Atmospheric Monitoring Service (CAMS) can be improved using surface observations and state-of-the-art statistical methods. Through a case study over the Iberian Peninsula in 2018–2019, it unambiguously demonstrates the value of these methods for improving the raw CAMS O3 forecasts while at the same time highlighting the complexity of improving the detection of the highest O3 concentrations.
Qirui Zhong, Nick Schutgens, Guido van der Werf, Twan van Noije, Kostas Tsigaridis, Susanne E. Bauer, Tero Mielonen, Alf Kirkevåg, Øyvind Seland, Harri Kokkola, Ramiro Checa-Garcia, David Neubauer, Zak Kipling, Hitoshi Matsui, Paul Ginoux, Toshihiko Takemura, Philippe Le Sager, Samuel Rémy, Huisheng Bian, Mian Chin, Kai Zhang, Jialei Zhu, Svetlana G. Tsyro, Gabriele Curci, Anna Protonotariou, Ben Johnson, Joyce E. Penner, Nicolas Bellouin, Ragnhild B. Skeie, and Gunnar Myhre
Atmos. Chem. Phys., 22, 11009–11032, https://doi.org/10.5194/acp-22-11009-2022, https://doi.org/10.5194/acp-22-11009-2022, 2022
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Aerosol optical depth (AOD) errors for biomass burning aerosol (BBA) are evaluated in 18 global models against satellite datasets. Notwithstanding biases in satellite products, they allow model evaluations. We observe large and diverse model biases due to errors in BBA. Further interpretations of AOD diversities suggest large biases exist in key processes for BBA which require better constraining. These results can contribute to further model improvement and development.
Enza Di Tomaso, Jerónimo Escribano, Sara Basart, Paul Ginoux, Francesca Macchia, Francesca Barnaba, Francesco Benincasa, Pierre-Antoine Bretonnière, Arnau Buñuel, Miguel Castrillo, Emilio Cuevas, Paola Formenti, María Gonçalves, Oriol Jorba, Martina Klose, Lucia Mona, Gilbert Montané Pinto, Michail Mytilinaios, Vincenzo Obiso, Miriam Olid, Nick Schutgens, Athanasios Votsis, Ernest Werner, and Carlos Pérez García-Pando
Earth Syst. Sci. Data, 14, 2785–2816, https://doi.org/10.5194/essd-14-2785-2022, https://doi.org/10.5194/essd-14-2785-2022, 2022
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MONARCH reanalysis of desert dust aerosols extends the existing observation-based information for mineral dust monitoring by providing 3-hourly upper-air, surface and total column key geophysical variables of the dust cycle over Northern Africa, the Middle East and Europe, at a 0.1° horizontal resolution in a rotated grid, from 2007 to 2016. This work provides evidence of the high accuracy of this data set and its suitability for air quality and health and climate service applications.
Marc Guevara, Hervé Petetin, Oriol Jorba, Hugo Denier van der Gon, Jeroen Kuenen, Ingrid Super, Jukka-Pekka Jalkanen, Elisa Majamäki, Lasse Johansson, Vincent-Henri Peuch, and Carlos Pérez García-Pando
Earth Syst. Sci. Data, 14, 2521–2552, https://doi.org/10.5194/essd-14-2521-2022, https://doi.org/10.5194/essd-14-2521-2022, 2022
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To control the spread of the COVID-19 disease, European governments implemented mobility restriction measures that resulted in an unprecedented drop in anthropogenic emissions. This work presents a dataset of emission adjustment factors that allows quantifying changes in 2020 European primary emissions per country and pollutant sector at the daily scale. The resulting dataset can be used as input in modelling studies aiming at quantifying the impact of COVID-19 on air quality levels.
Stelios Myriokefalitakis, Elisa Bergas-Massó, María Gonçalves-Ageitos, Carlos Pérez García-Pando, Twan van Noije, Philippe Le Sager, Akinori Ito, Eleni Athanasopoulou, Athanasios Nenes, Maria Kanakidou, Maarten C. Krol, and Evangelos Gerasopoulos
Geosci. Model Dev., 15, 3079–3120, https://doi.org/10.5194/gmd-15-3079-2022, https://doi.org/10.5194/gmd-15-3079-2022, 2022
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We here describe the implementation of atmospheric multiphase processes in the EC-Earth Earth system model. We provide global budgets of oxalate, sulfate, and iron-containing aerosols, along with an analysis of the links among atmospheric composition, aqueous-phase processes, and aerosol dissolution, supported by comparison to observations. This work is a first step towards an interactive calculation of the deposition of bioavailable atmospheric iron coupled to the model’s ocean component.
Antonis Gkikas, Emmanouil Proestakis, Vassilis Amiridis, Stelios Kazadzis, Enza Di Tomaso, Eleni Marinou, Nikos Hatzianastassiou, Jasper F. Kok, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 22, 3553–3578, https://doi.org/10.5194/acp-22-3553-2022, https://doi.org/10.5194/acp-22-3553-2022, 2022
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We present a comprehensive climatological analysis of dust optical depth (DOD) relying on the MIDAS dataset. MIDAS provides columnar mid-visible (550 nm) DOD at fine spatial resolution (0.1° × 0.1°) over a 15-year period (2003–2017). In the current study, the analysis is performed at various spatial (from regional to global) and temporal (from months to years) scales. More specifically, focus is given to specific regions hosting the major dust sources as well as downwind areas of the planet.
Sujung Go, Alexei Lyapustin, Gregory L. Schuster, Myungje Choi, Paul Ginoux, Mian Chin, Olga Kalashnikova, Oleg Dubovik, Jhoon Kim, Arlindo da Silva, Brent Holben, and Jeffrey S. Reid
Atmos. Chem. Phys., 22, 1395–1423, https://doi.org/10.5194/acp-22-1395-2022, https://doi.org/10.5194/acp-22-1395-2022, 2022
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This paper presents a retrieval algorithm of iron-oxide species (hematite, goethite) content in the atmosphere from DSCOVR EPIC observations. Our results display variations within the published range of hematite and goethite over the main dust-source regions but show significant seasonal and spatial variability. This implies a single-viewing satellite instrument with UV–visible channels may provide essential information on shortwave dust direct radiative effects for climate modeling.
Jerónimo Escribano, Enza Di Tomaso, Oriol Jorba, Martina Klose, Maria Gonçalves Ageitos, Francesca Macchia, Vassilis Amiridis, Holger Baars, Eleni Marinou, Emmanouil Proestakis, Claudia Urbanneck, Dietrich Althausen, Johannes Bühl, Rodanthi-Elisavet Mamouri, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 22, 535–560, https://doi.org/10.5194/acp-22-535-2022, https://doi.org/10.5194/acp-22-535-2022, 2022
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We explore the benefits and consistency in adding lidar dust observations in a dust optical depth assimilation. We show that adding lidar data to a dust optical depth assimilation has valuable benefits and the dust analysis improves. We discuss the impact of the narrow satellite footprint of the lidar dust observations on the assimilation.
Maria Sand, Bjørn H. Samset, Gunnar Myhre, Jonas Gliß, Susanne E. Bauer, Huisheng Bian, Mian Chin, Ramiro Checa-Garcia, Paul Ginoux, Zak Kipling, Alf Kirkevåg, Harri Kokkola, Philippe Le Sager, Marianne T. Lund, Hitoshi Matsui, Twan van Noije, Dirk J. L. Olivié, Samuel Remy, Michael Schulz, Philip Stier, Camilla W. Stjern, Toshihiko Takemura, Kostas Tsigaridis, Svetlana G. Tsyro, and Duncan Watson-Parris
Atmos. Chem. Phys., 21, 15929–15947, https://doi.org/10.5194/acp-21-15929-2021, https://doi.org/10.5194/acp-21-15929-2021, 2021
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Absorption of shortwave radiation by aerosols can modify precipitation and clouds but is poorly constrained in models. A total of 15 different aerosol models from AeroCom phase III have reported total aerosol absorption, and for the first time, 11 of these models have reported in a consistent experiment the contributions to absorption from black carbon, dust, and organic aerosol. Here, we document the model diversity in aerosol absorption.
Martina Klose, Oriol Jorba, María Gonçalves Ageitos, Jeronimo Escribano, Matthew L. Dawson, Vincenzo Obiso, Enza Di Tomaso, Sara Basart, Gilbert Montané Pinto, Francesca Macchia, Paul Ginoux, Juan Guerschman, Catherine Prigent, Yue Huang, Jasper F. Kok, Ron L. Miller, and Carlos Pérez García-Pando
Geosci. Model Dev., 14, 6403–6444, https://doi.org/10.5194/gmd-14-6403-2021, https://doi.org/10.5194/gmd-14-6403-2021, 2021
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Mineral soil dust is a major atmospheric airborne particle type. We present and evaluate MONARCH, a model used for regional and global dust-weather prediction. An important feature of the model is that it allows different approximations to represent dust, ranging from more simplified to more complex treatments. Using these different treatments, MONARCH can help us better understand impacts of dust in the Earth system, such as its interactions with radiation.
Twan van Noije, Tommi Bergman, Philippe Le Sager, Declan O'Donnell, Risto Makkonen, María Gonçalves-Ageitos, Ralf Döscher, Uwe Fladrich, Jost von Hardenberg, Jukka-Pekka Keskinen, Hannele Korhonen, Anton Laakso, Stelios Myriokefalitakis, Pirkka Ollinaho, Carlos Pérez García-Pando, Thomas Reerink, Roland Schrödner, Klaus Wyser, and Shuting Yang
Geosci. Model Dev., 14, 5637–5668, https://doi.org/10.5194/gmd-14-5637-2021, https://doi.org/10.5194/gmd-14-5637-2021, 2021
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This paper documents the global climate model EC-Earth3-AerChem, one of the members of the EC-Earth3 family of models participating in CMIP6. We give an overview of the model and describe in detail how it differs from its predecessor and the other EC-Earth3 configurations. The model's performance is characterized using coupled simulations conducted for CMIP6. The model has an effective equilibrium climate sensitivity of 3.9 °C and a transient climate response of 2.1 °C.
Qianqian Song, Zhibo Zhang, Hongbin Yu, Paul Ginoux, and Jerry Shen
Atmos. Chem. Phys., 21, 13369–13395, https://doi.org/10.5194/acp-21-13369-2021, https://doi.org/10.5194/acp-21-13369-2021, 2021
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We present a satellite-derived global dust climatological record over the last two decades, including the monthly mean visible dust optical depth (DAOD) and vertical distribution of dust extinction coefficient at a 2º × 5º spatial resolution derived from CALIOP and MODIS. In addition, the CALIOP climatological dataset also includes dust vertical extinction profiles. Based on these two datasets, we carried out a comprehensive comparative study of the spatial and temporal climatology of dust.
Jun Meng, Randall V. Martin, Paul Ginoux, Melanie Hammer, Melissa P. Sulprizio, David A. Ridley, and Aaron van Donkelaar
Geosci. Model Dev., 14, 4249–4260, https://doi.org/10.5194/gmd-14-4249-2021, https://doi.org/10.5194/gmd-14-4249-2021, 2021
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Dust emissions in models, for example, GEOS-Chem, have a strong nonlinear dependence on meteorology, which means dust emission strengths calculated from different resolution meteorological fields are different. Offline high-resolution dust emissions with an optimized global dust strength, presented in this work, can be implemented into GEOS-Chem as offline emission inventory so that it could promote model development by harmonizing dust emissions across simulations of different resolutions.
Yan Yu and Paul Ginoux
Atmos. Chem. Phys., 21, 8511–8530, https://doi.org/10.5194/acp-21-8511-2021, https://doi.org/10.5194/acp-21-8511-2021, 2021
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Despite Australian dust’s critical role in the regional climate and surrounding marine ecosystems, the controlling factors of its spatiotemporal variations are not fully understood. This study establishes the connection between large-scale climate variability and regional dust emission, leading to a better understanding of the spatiotemporal variation in dust activity and improved prediction of dust's climate and ecological influences.
Jasper F. Kok, Adeyemi A. Adebiyi, Samuel Albani, Yves Balkanski, Ramiro Checa-Garcia, Mian Chin, Peter R. Colarco, Douglas S. Hamilton, Yue Huang, Akinori Ito, Martina Klose, Danny M. Leung, Longlei Li, Natalie M. Mahowald, Ron L. Miller, Vincenzo Obiso, Carlos Pérez García-Pando, Adriana Rocha-Lima, Jessica S. Wan, and Chloe A. Whicker
Atmos. Chem. Phys., 21, 8127–8167, https://doi.org/10.5194/acp-21-8127-2021, https://doi.org/10.5194/acp-21-8127-2021, 2021
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Desert dust interacts with virtually every component of the Earth system, including the climate system. We develop a new methodology to represent the global dust cycle that integrates observational constraints on the properties and abundance of desert dust with global atmospheric model simulations. We show that the resulting representation of the global dust cycle is more accurate than what can be obtained from a large number of current climate global atmospheric models.
Jasper F. Kok, Adeyemi A. Adebiyi, Samuel Albani, Yves Balkanski, Ramiro Checa-Garcia, Mian Chin, Peter R. Colarco, Douglas S. Hamilton, Yue Huang, Akinori Ito, Martina Klose, Longlei Li, Natalie M. Mahowald, Ron L. Miller, Vincenzo Obiso, Carlos Pérez García-Pando, Adriana Rocha-Lima, and Jessica S. Wan
Atmos. Chem. Phys., 21, 8169–8193, https://doi.org/10.5194/acp-21-8169-2021, https://doi.org/10.5194/acp-21-8169-2021, 2021
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The many impacts of dust on the Earth system depend on dust mineralogy, which varies between dust source regions. We constrain the contribution of the world’s main dust source regions by integrating dust observations with global model simulations. We find that Asian dust contributes more and that North African dust contributes less than models account for. We obtain a dataset of each source region’s contribution to the dust cycle that can be used to constrain dust impacts on the Earth system.
Jérôme Barré, Hervé Petetin, Augustin Colette, Marc Guevara, Vincent-Henri Peuch, Laurence Rouil, Richard Engelen, Antje Inness, Johannes Flemming, Carlos Pérez García-Pando, Dene Bowdalo, Frederik Meleux, Camilla Geels, Jesper H. Christensen, Michael Gauss, Anna Benedictow, Svetlana Tsyro, Elmar Friese, Joanna Struzewska, Jacek W. Kaminski, John Douros, Renske Timmermans, Lennart Robertson, Mario Adani, Oriol Jorba, Mathieu Joly, and Rostislav Kouznetsov
Atmos. Chem. Phys., 21, 7373–7394, https://doi.org/10.5194/acp-21-7373-2021, https://doi.org/10.5194/acp-21-7373-2021, 2021
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This study provides a comprehensive assessment of air quality changes across the main European urban areas induced by the COVID-19 lockdown using satellite observations, surface site measurements, and the forecasting system from the Copernicus Atmospheric Monitoring Service (CAMS). We demonstrate the importance of accounting for weather and seasonal variability when calculating such estimates.
Longlei Li, Natalie M. Mahowald, Ron L. Miller, Carlos Pérez García-Pando, Martina Klose, Douglas S. Hamilton, Maria Gonçalves Ageitos, Paul Ginoux, Yves Balkanski, Robert O. Green, Olga Kalashnikova, Jasper F. Kok, Vincenzo Obiso, David Paynter, and David R. Thompson
Atmos. Chem. Phys., 21, 3973–4005, https://doi.org/10.5194/acp-21-3973-2021, https://doi.org/10.5194/acp-21-3973-2021, 2021
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For the first time, this study quantifies the range of the dust direct radiative effect due to uncertainty in the soil mineral abundance using all currently available information. We show that the majority of the estimated direct radiative effect range is due to uncertainty in the simulated mass fractions of iron oxides and thus their soil abundance, which is independent of the model employed. We therefore prove the necessity of considering mineralogy for understanding dust–climate interactions.
Marc Guevara, Oriol Jorba, Carles Tena, Hugo Denier van der Gon, Jeroen Kuenen, Nellie Elguindi, Sabine Darras, Claire Granier, and Carlos Pérez García-Pando
Earth Syst. Sci. Data, 13, 367–404, https://doi.org/10.5194/essd-13-367-2021, https://doi.org/10.5194/essd-13-367-2021, 2021
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The temporal variability of atmospheric emissions is linked to changes in activity patterns, emission processes and meteorology. Accounting for the change in temporal emission characteristics is a key aspect for modelling the trends of air pollutants. This work presents a dataset of global and European emission temporal profiles to be used for air quality modelling purposes. The profiles were constructed considering the influences of local sociodemographic factors and climatological conditions.
Marc Guevara, Oriol Jorba, Albert Soret, Hervé Petetin, Dene Bowdalo, Kim Serradell, Carles Tena, Hugo Denier van der Gon, Jeroen Kuenen, Vincent-Henri Peuch, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 21, 773–797, https://doi.org/10.5194/acp-21-773-2021, https://doi.org/10.5194/acp-21-773-2021, 2021
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Most European countries have imposed lockdowns to combat the spread of the COVID-19 pandemic. Such a socioeconomic disruption has resulted in a sudden drop of atmospheric emissions and air pollution levels. This study quantifies the daily reductions in national emissions and associated levels of nitrogen dioxide (NO2) due to the COVID-19 lockdowns in Europe, by making use of multiple open-access measured activity data as well as artificial intelligence and modelling techniques.
Antonis Gkikas, Emmanouil Proestakis, Vassilis Amiridis, Stelios Kazadzis, Enza Di Tomaso, Alexandra Tsekeri, Eleni Marinou, Nikos Hatzianastassiou, and Carlos Pérez García-Pando
Atmos. Meas. Tech., 14, 309–334, https://doi.org/10.5194/amt-14-309-2021, https://doi.org/10.5194/amt-14-309-2021, 2021
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We present the development of the MIDAS (ModIs Dust AeroSol) data set, providing daily dust optical depth (DOD; 550 nm) at a global scale and fine spatial resolution (0.1° x 0.1°) over a 15-year period (2003–2017). It has been developed via the synergy of MODIS-Aqua and MERRA-2 data, while CALIOP and AERONET retrievals are used for its assessment. MIDAS upgrades existing dust observational capabilities, and it is suitable for dust climatological studies, model evaluation, and data assimilation.
Jonas Gliß, Augustin Mortier, Michael Schulz, Elisabeth Andrews, Yves Balkanski, Susanne E. Bauer, Anna M. K. Benedictow, Huisheng Bian, Ramiro Checa-Garcia, Mian Chin, Paul Ginoux, Jan J. Griesfeller, Andreas Heckel, Zak Kipling, Alf Kirkevåg, Harri Kokkola, Paolo Laj, Philippe Le Sager, Marianne Tronstad Lund, Cathrine Lund Myhre, Hitoshi Matsui, Gunnar Myhre, David Neubauer, Twan van Noije, Peter North, Dirk J. L. Olivié, Samuel Rémy, Larisa Sogacheva, Toshihiko Takemura, Kostas Tsigaridis, and Svetlana G. Tsyro
Atmos. Chem. Phys., 21, 87–128, https://doi.org/10.5194/acp-21-87-2021, https://doi.org/10.5194/acp-21-87-2021, 2021
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Simulated aerosol optical properties as well as the aerosol life cycle are investigated for 14 global models participating in the AeroCom initiative. Considerable diversity is found in the simulated aerosol species emissions and lifetimes, also resulting in a large diversity in the simulated aerosol mass, composition, and optical properties. A comparison with observations suggests that, on average, current models underestimate the direct effect of aerosol on the atmosphere radiation budget.
Augustin Mortier, Jonas Gliß, Michael Schulz, Wenche Aas, Elisabeth Andrews, Huisheng Bian, Mian Chin, Paul Ginoux, Jenny Hand, Brent Holben, Hua Zhang, Zak Kipling, Alf Kirkevåg, Paolo Laj, Thibault Lurton, Gunnar Myhre, David Neubauer, Dirk Olivié, Knut von Salzen, Ragnhild Bieltvedt Skeie, Toshihiko Takemura, and Simone Tilmes
Atmos. Chem. Phys., 20, 13355–13378, https://doi.org/10.5194/acp-20-13355-2020, https://doi.org/10.5194/acp-20-13355-2020, 2020
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We present a multiparameter analysis of the aerosol trends over the last 2 decades in the different regions of the world. In most of the regions, ground-based observations show a decrease in aerosol content in both the total atmospheric column and at the surface. The use of climate models, assessed against these observations, reveals however an increase in the total aerosol load, which is not seen with the sole use of observation due to partial coverage in space and time.
Hervé Petetin, Dene Bowdalo, Albert Soret, Marc Guevara, Oriol Jorba, Kim Serradell, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 20, 11119–11141, https://doi.org/10.5194/acp-20-11119-2020, https://doi.org/10.5194/acp-20-11119-2020, 2020
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To control the spread of the COVID-19 coronavirus, the Spanish Government recently implemented a strict lockdown of the population, which strongly reduced the levels of nitrogen dioxide (NO2), one of the most critical air pollutants in Spain. This study quantifies the contribution of the lockdown on these reduced NO2 levels in Spain, taking the confounding effect of meteorology on artificial intelligence techniques into account.
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Short summary
We implement and simulate the distribution of eight dust minerals in the GFDL AM4.0 model. We found that resolving the eight minerals reduces dust absorption compared to the homogeneous dust used in the standard GFDL AM4.0 model that assumes a globally uniform hematite content of 2.7 % by volume. Resolving dust mineralogy results in significant impacts on radiation, land surface temperature, surface winds, and precipitation over North Africa in summer.
We implement and simulate the distribution of eight dust minerals in the GFDL AM4.0 model. We...
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