Articles | Volume 18, issue 19
https://doi.org/10.5194/gmd-18-6767-2025
© Author(s) 2025. 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-18-6767-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
02 Oct 2025
Development and technical paper |
| 02 Oct 2025
| 02 Oct 2025
Improving annual fine mineral dust representation from the surface to the column in GEOS-Chem 14.4.1
Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States
Randall V. Martin
Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States
Xuan Liu
Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States
Scripps Institution of Oceanography, University of California San Diego, San Diego, California 92093, United States
Aaron van Donkelaar
Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States
Christopher R. Oxford
Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States
Yanshun Li
Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States
Department of Civil and Environmental Engineering, Washington State University, Pullman, Washington 99163, United States
Danny M. Leung
Atmospheric Chemistry Observations and Modeling Laboratory, National Science Foundation National Center for Atmospheric Research, Boulder, Colorado 80301, United States
Jasper F. Kok
Department of Atmospheric and Oceanic Sciences, University of California Los Angeles, Los Angeles, California 90095, United States
Longlei Li
Department of Earth and Atmospheric Sciences, Cornell University, Ithaca, New York 14853, United States
Haihui Zhu
Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States
Jay R. Turner
Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States
Yu Yan
Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States
Michael Brauer
School of Population and Public Health, University of British Columbia, Vancouver, British Columbia V6T 1Z3, Canada
Yinon Rudich
Department of Earth and Planetary Sciences, Weizmann Institute of Science, Rehovot 76100, Israel
Eli Windwer
Department of Earth and Planetary Sciences, Weizmann Institute of Science, Rehovot 76100, Israel
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Preprint withdrawn
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Haihui Zhu, Randall V. Martin, Betty Croft, Shixian Zhai, Chi Li, Liam Bindle, Jeffrey R. Pierce, Rachel Y.-W. Chang, Bruce E. Anderson, Luke D. Ziemba, Johnathan W. Hair, Richard A. Ferrare, Chris A. Hostetler, Inderjeet Singh, Deepangsu Chatterjee, Jose L. Jimenez, Pedro Campuzano-Jost, Benjamin A. Nault, Jack E. Dibb, Joshua S. Schwarz, and Andrew Weinheimer
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Lukas Eickhoff, Maddalena Bayer-Giraldi, Naama Reicher, Yinon Rudich, and Thomas Koop
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Randall V. Martin, Sebastian D. Eastham, Liam Bindle, Elizabeth W. Lundgren, Thomas L. Clune, Christoph A. Keller, William Downs, Dandan Zhang, Robert A. Lucchesi, Melissa P. Sulprizio, Robert M. Yantosca, Yanshun Li, Lucas Estrada, William M. Putman, Benjamin M. Auer, Atanas L. Trayanov, Steven Pawson, and Daniel J. Jacob
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Caroline C. Womack, Steven S. Brown, Steven J. Ciciora, Ru-Shan Gao, Richard J. McLaughlin, Michael A. Robinson, Yinon Rudich, and Rebecca A. Washenfelder
Atmos. Meas. Tech., 15, 6643–6652, https://doi.org/10.5194/amt-15-6643-2022, https://doi.org/10.5194/amt-15-6643-2022, 2022
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Longlei Li, Natalie M. Mahowald, Jasper F. Kok, Xiaohong Liu, Mingxuan Wu, Danny M. Leung, Douglas S. Hamilton, Louisa K. Emmons, Yue Huang, Neil Sexton, Jun Meng, and Jessica Wan
Geosci. Model Dev., 15, 8181–8219, https://doi.org/10.5194/gmd-15-8181-2022, https://doi.org/10.5194/gmd-15-8181-2022, 2022
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Qianqian Song, Zhibo Zhang, Hongbin Yu, Jasper F. Kok, Claudia Di Biagio, Samuel Albani, Jianyu Zheng, and Jiachen Ding
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This study developed a dataset that enables us to efficiently calculate dust direct radiative effect (DRE, i.e., cooling or warming our planet) for any given dust size distribution in addition to three sets of dust mineral components and two dust shapes. We demonstrate and validate the method of using this dataset to calculate dust DRE. Moreover, using this dataset we found that dust mineral composition is a more important factor in determining dust DRE than dust size and shape.
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.
Zhi-Hui Zhang, Elena Hartner, Battist Utinger, Benjamin Gfeller, Andreas Paul, Martin Sklorz, Hendryk Czech, Bin Xia Yang, Xin Yi Su, Gert Jakobi, Jürgen Orasche, Jürgen Schnelle-Kreis, Seongho Jeong, Thomas Gröger, Michal Pardo, Thorsten Hohaus, Thomas Adam, Astrid Kiendler-Scharr, Yinon Rudich, Ralf Zimmermann, and Markus Kalberer
Atmos. Chem. Phys., 22, 1793–1809, https://doi.org/10.5194/acp-22-1793-2022, https://doi.org/10.5194/acp-22-1793-2022, 2022
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Using a novel setup, we comprehensively characterized the formation of particle-bound reactive oxygen species (ROS) in anthropogenic and biogenic secondary organic aerosols (SOAs). We found that more than 90 % of all ROS components in both SOA types have a short lifetime. Our results also show that photochemical aging promotes particle-bound ROS production and enhances the oxidative potential of the aerosols. We found consistent results between chemical-based and biological-based ROS analyses.
Paola Formenti, Claudia Di Biagio, Yue Huang, Jasper Kok, Marc Daniel Mallet, Damien Boulanger, and Mathieu Cazaunau
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2021-403, https://doi.org/10.5194/amt-2021-403, 2021
Publication in AMT not foreseen
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This paper provides with standardized correction factors for the measurements of the most common instruments used in the atmosphere to measure the concentration per size of aerosol particles. These correction factors are provided to users with supplementary information for their use.
Akinori Ito, Adeyemi A. Adebiyi, Yue Huang, and Jasper F. Kok
Atmos. Chem. Phys., 21, 16869–16891, https://doi.org/10.5194/acp-21-16869-2021, https://doi.org/10.5194/acp-21-16869-2021, 2021
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We improve the simulated dust properties of size-resolved dust concentration and particle shape. The improved simulation suggests much less atmospheric radiative heating near the major source regions, because of enhanced longwave warming at the surface by the synergy of coarser size and aspherical shape. Less intensified atmospheric heating could substantially modify the vertical temperature profile in Earth system models and thus has important implications for the projection of dust feedback.
Shixian Zhai, Daniel J. Jacob, Jared F. Brewer, Ke Li, Jonathan M. Moch, Jhoon Kim, Seoyoung Lee, Hyunkwang Lim, Hyun Chul Lee, Su Keun Kuk, Rokjin J. Park, Jaein I. Jeong, Xuan Wang, Pengfei Liu, Gan Luo, Fangqun Yu, Jun Meng, Randall V. Martin, Katherine R. Travis, Johnathan W. Hair, Bruce E. Anderson, Jack E. Dibb, Jose L. Jimenez, Pedro Campuzano-Jost, Benjamin A. Nault, Jung-Hun Woo, Younha Kim, Qiang Zhang, and Hong Liao
Atmos. Chem. Phys., 21, 16775–16791, https://doi.org/10.5194/acp-21-16775-2021, https://doi.org/10.5194/acp-21-16775-2021, 2021
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Geostationary satellite aerosol optical depth (AOD) has tremendous potential for monitoring surface fine particulate matter (PM2.5). Our study explored the physical relationship between AOD and PM2.5 by integrating data from surface networks, aircraft, and satellites with the GEOS-Chem chemical transport model. We quantitatively showed that accurate simulation of aerosol size distributions, boundary layer depths, relative humidity, coarse particles, and diurnal variations in PM2.5 are essential.
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.
Quanfu He, Zheng Fang, Ofir Shoshanim, Steven S. Brown, and Yinon Rudich
Atmos. Chem. Phys., 21, 14927–14940, https://doi.org/10.5194/acp-21-14927-2021, https://doi.org/10.5194/acp-21-14927-2021, 2021
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Rayleigh scattering and absorption cross sections for CO2, N2O, SF6, O2, and CH4 were measured between 307 and 725 nm. New dispersion relations for N2O, SF6, and CH4 in the UV–vis range were derived. This study provides refractive index dispersion relations, scattering, and absorption cross sections which are highly needed for accurate instrument calibration and for improved accuracy of Rayleigh scattering parameterizations for major greenhouse gases in Earth's atmosphere.
Liam Bindle, Randall V. Martin, Matthew J. Cooper, Elizabeth W. Lundgren, Sebastian D. Eastham, Benjamin M. Auer, Thomas L. Clune, Hongjian Weng, Jintai Lin, Lee T. Murray, Jun Meng, Christoph A. Keller, William M. Putman, Steven Pawson, and Daniel J. Jacob
Geosci. Model Dev., 14, 5977–5997, https://doi.org/10.5194/gmd-14-5977-2021, https://doi.org/10.5194/gmd-14-5977-2021, 2021
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Atmospheric chemistry models like GEOS-Chem are versatile tools widely used in air pollution and climate studies. The simulations used in such studies can be very computationally demanding, and thus it is useful if the model can simulate a specific geographic region at a higher resolution than the rest of the globe. Here, we implement, test, and demonstrate a new variable-resolution capability in GEOS-Chem that is suitable for simulations conducted on supercomputers.
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.
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.
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.
Jingchuan Chen, Zhijun Wu, Jie Chen, Naama Reicher, Xin Fang, Yinon Rudich, and Min Hu
Atmos. Chem. Phys., 21, 3491–3506, https://doi.org/10.5194/acp-21-3491-2021, https://doi.org/10.5194/acp-21-3491-2021, 2021
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Asian mineral dust is a crucial contributor to global ice-nucleating particles (INPs), while its size-resolved information on freezing activity is extremely rare. Here we conducted the first known INP measurements of size-resolved airborne East Asian dust particles. An explicit size dependence of both INP concentration and surface
ice-active-site density was observed. The new parameterizations can be widely applied in models to better characterize and predict ice nucleation activities of dust.
Cited articles
Amato, F., Schaap, M., Denier van der Gon, H. A. C., Pandolfi, M., Alastuey, A., Keuken, M., and Querol, X.: Short-term variability of mineral dust, metals and carbon emission from road dust resuspension, Atmospheric Environment, 74, 134–140, https://doi.org/10.1016/j.atmosenv.2013.03.037, 2013.
Bagheri, G. and Bonadonna, C.: On the drag of freely falling non-spherical particles, Powder Technology, 301, 526–544, https://doi.org/10.1016/j.powtec.2016.06.015, 2016.
Bayon, G., Garzanti, E., Dinis, P., Beaufort, D., Barrat, J.-A., Germain, Y., Trinquier, A., Barbarano, M., Overare, B., Adeaga, O., and Braquet, N.: Contribution of Saharan dust to chemical weathering fluxes and associated phosphate release in West Africa, Earth and Planetary Science Letters, 641, 118845, https://doi.org/10.1016/j.epsl.2024.118845, 2024.
Bey, I., Jacob, D. J., Yantosca, R. M., Logan, J. A., Field, B. D., Fiore, A. M., Li, Q., Liu, H. Y., Mickley, L. J., and Schultz, M. G.: Global modeling of tropospheric chemistry with assimilated meteorology: Model description and evaluation, Journal of Geophysical Research: Atmospheres, 106, 23073–23095, https://doi.org/10.1029/2001JD000807, 2001.
Bouwman, A. F., Lee, D. S., Asman, W. A. H., Dentener, F. J., Van Der Hoek, K. W., and Olivier, J. G. J.: A global high-resolution emission inventory for ammonia, Global Biogeochemical Cycles, 11, 561–587, https://doi.org/10.1029/97GB02266, 1997.
Breider, T. J., Mickley, L. J., Jacob, D. J., Ge, C., Wang, J., Payer Sulprizio, M., Croft, B., Ridley, D. A., McConnell, J. R., Sharma, S., Husain, L., Dutkiewicz, V. A., Eleftheriadis, K., Skov, H., and Hopke, P. K.: Multidecadal trends in aerosol radiative forcing over the Arctic: Contribution of changes in anthropogenic aerosol to Arctic warming since 1980, Journal of Geophysical Research: Atmospheres, 122, 3573–3594, https://doi.org/10.1002/2016JD025321, 2017.
Cakmur, R. V., Miller, R. L., Perlwitz, J., Geogdzhayev, I. V., Ginoux, P., Koch, D., Kohfeld, K. E., Tegen, I., and Zender, C. S.: Constraining the magnitude of the global dust cycle by minimizing the difference between a model and observations, Journal of Geophysical Research: Atmospheres, 111, https://doi.org/10.1029/2005JD005791, 2006.
Cao, C., De Luccia, F. J., Xiong, X., Wolfe, R., and Weng, F.: Early On-Orbit Performance of the Visible Infrared Imaging Radiometer Suite Onboard the Suomi National Polar-Orbiting Partnership (S-NPP) Satellite, IEEE Transactions on Geoscience and Remote Sensing, 52, 1142–1156, https://doi.org/10.1109/TGRS.2013.2247768, 2014.
Comola, F., Kok, J. F., Chamecki, M., and Martin, R. L.: The Intermittency of Wind-Driven Sand Transport, Geophysical Research Letters, 46, 13430–13440, https://doi.org/10.1029/2019GL085739, 2019.
Croft, B., Wentworth, G. R., Martin, R. V., Leaitch, W. R., Murphy, J. G., Murphy, B. N., Kodros, J. K., Abbatt, J. P. D., and Pierce, J. R.: Contribution of Arctic seabird-colony ammonia to atmospheric particles and cloud-albedo radiative effect, Nature Communications, 7, 13444, https://doi.org/10.1038/ncomms13444, 2016.
Darmenova, K., Sokolik, I. N., Shao, Y., Marticorena, B., and Bergametti, G.: Development of a physically based dust emission module within the Weather Research and Forecasting (WRF) model: Assessment of dust emission parameterizations and input parameters for source regions in Central and East Asia, Journal of Geophysical Research: Atmospheres, 114, D14201, https://doi.org/10.1029/2008JD011236, 2009.
Eastham, S. D., Long, M. S., Keller, C. A., Lundgren, E., Yantosca, R. M., Zhuang, J. W., Li, C., Lee, C. J., Yannetti, M., Auer, B. M., Clune, T. L., Kouatchou, J., Putman, W. M., Thompson, M. A., Trayanov, A. L., Molod, A. M., Martin, R. V., and Jacob, D. J.: GEOS-Chem High Performance (GCHP v11-02c): a next-generation implementation of the GEOS-Chem chemical transport model for massively parallel applications, Geoscientific Model Development, 11, 2941–2953, https://doi.org/10.5194/gmd-11-2941-2018, 2018.
Emerson, E. W., Hodshire, A. L., DeBolt, H. M., Bilsback, K. R., Pierce, J. R., McMeeking, G. R., and Farmer, D. K.: Revisiting particle dry deposition and its role in radiative effect estimates, Proceedings of the National Academy of Sciences, 117, 26076–26082, https://doi.org/10.1073/pnas.2014761117, 2020.
Fairlie, T. D., Jacob, D. J., and Park, R. J.: The impact of transpacific transport of mineral dust in the United States, Atmospheric Environment, 41, 1251–1266, https://doi.org/10.1016/j.atmosenv.2006.09.048, 2007.
Fécan, F., Marticorena, B., and Bergametti, G.: Parametrization of the increase of the aeolian erosion threshold wind friction velocity due to soil moisture for arid and semi-arid areas, Annales Geophysicae, 17, 149–157, https://doi.org/10.1007/s00585-999-0149-7, 1999.
Feng, L., Smith, S. J., Braun, C., Crippa, M., Gidden, M. J., Hoesly, R., Klimont, Z., van Marle, M., van den Berg, M., and van der Werf, G. R.: The generation of gridded emissions data for CMIP6, Geosci. Model Dev., 13, 461–482, https://doi.org/10.5194/gmd-13-461-2020, 2020.
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, Atmospheric Environment, 45, 7301–7318, https://doi.org/10.1016/j.atmosenv.2011.08.030, 2011.
Giglio, L., Randerson, J. T., and van der Werf, G. R.: Analysis of daily, monthly, and annual burned area using the fourth-generation global fire emissions database (GFED4), Journal of Geophysical Research: Biogeosciences, 118, 317–328, https://doi.org/10.1002/jgrg.20042, 2013.
Giles, D. M., Sinyuk, A., Sorokin, M. G., Schafer, J. S., Smirnov, A., Slutsker, I., Eck, T. F., Holben, B. N., Lewis, J. R., Campbell, J. R., Welton, E. J., Korkin, S. V., and Lyapustin, A. I.: Advancements in the Aerosol Robotic Network (AERONET) Version 3 database – automated near-real-time quality control algorithm with improved cloud screening for Sun photometer aerosol optical depth (AOD) measurements, Atmos. Meas. Tech., 12, 169–209, https://doi.org/10.5194/amt-12-169-2019, 2019.
Ginoux, P., Chin, M., Tegen, I., Prospero, J. M., Holben, B., Dubovik, O., and Lin, S.-J.: Sources and distributions of dust aerosols simulated with the GOCART model, Journal of Geophysical Research: Atmospheres, 106, 20255–20273, https://doi.org/10.1029/2000JD000053, 2001.
González-Flórez, C., Klose, M., Alastuey, A., Dupont, S., Escribano, J., Etyemezian, V., Gonzalez-Romero, A., Huang, Y., Kandler, K., Nikolich, G., Panta, A., Querol, X., Reche, C., Yus-Díez, J., and Pérez García-Pando, C.: Insights into the size-resolved dust emission from field measurements in the Moroccan Sahara, Atmos. Chem. Phys., 23, 7177–7212, https://doi.org/10.5194/acp-23-7177-2023, 2023.
Harris, L., Zhou, L., Lin, S.-J., Chen, J.-H., Chen, X., Gao, K., Morin, M., Rees, S., Sun, Y., Tong, M., Xiang, B., Bender, M., Benson, R., Cheng, K.-Y., Clark, S., Elbert, O. D., Hazelton, A., Huff, J. J., Kaltenbaugh, A., Liang, Z., Marchok, T., Shin, H. H., and Stern, W.: GFDL SHiELD: A Unified System for Weather-to-Seasonal Prediction, Journal of Advances in Modeling Earth Systems, 12, e2020MS002223, https://doi.org/10.1029/2020MS002223, 2020.
Hsu, N. C., Lee, J., Sayer, A. M., Kim, W., Bettenhausen, C., and Tsay, S.-C.: VIIRS Deep Blue Aerosol Products Over Land: Extending the EOS Long-Term Aerosol Data Records, Journal of Geophysical Research: Atmospheres, 124, 4026–4053, https://doi.org/10.1029/2018JD029688, 2019.
Hu, L., Keller, C. A., Long, M. S., Sherwen, T., Auer, B., Da Silva, A., Nielsen, J. E., Pawson, S., Thompson, M. A., Trayanov, A. L., Travis, K. R., Grange, S. K., Evans, M. J., and Jacob, D. J.: Global simulation of tropospheric chemistry at 12.5 km resolution: performance and evaluation of the GEOS-Chem chemical module (v10-1) within the NASA GEOS Earth system model (GEOS-5 ESM), Geosci. Model Dev., 11, 4603–4620, https://doi.org/10.5194/gmd-11-4603-2018, 2018.
Huang, Y., Kok, J. F., Kandler, K., Lindqvist, H., Nousiainen, T., Sakai, T., Adebiyi, A., and Jokinen, O.: Climate Models and Remote Sensing Retrievals Neglect Substantial Desert Dust Asphericity, Geophysical Research Letters, 47, e2019GL086592, https://doi.org/10.1029/2019GL086592, 2020.
Huang, Y., Adebiyi, A. A., Formenti, P., and Kok, J. F.: Linking the Different Diameter Types of Aspherical Desert Dust Indicates That Models Underestimate Coarse Dust Emission, Geophysical Research Letters, 48, e2020GL092054, https://doi.org/10.1029/2020GL092054, 2021.
Huneeus, N., Schulz, M., Balkanski, Y., Griesfeller, J., Prospero, J., Kinne, S., Bauer, S., Boucher, O., Chin, M., Dentener, F., Diehl, T., Easter, R., Fillmore, D., Ghan, S., Ginoux, P., Grini, A., Horowitz, L., Koch, D., Krol, M. C., Landing, W., Liu, X., Mahowald, N., Miller, R., Morcrette, J.-J., Myhre, G., Penner, J., Perlwitz, J., Stier, P., Takemura, T., and Zender, C. S.: Global dust model intercomparison in AeroCom phase I, Atmos. Chem. Phys., 11, 7781–7816, https://doi.org/10.5194/acp-11-7781-2011, 2011.
Iversen, J. D. and White, B. R.: Saltation threshold on Earth, Mars and Venus, Sedimentology, 29, 111–119, https://doi.org/10.1111/j.1365-3091.1982.tb01713.x, 1982.
Jaeglé, L., Quinn, P. K., Bates, T. S., Alexander, B., and Lin, J.-T.: Global distribution of sea salt aerosols: new constraints from in situ and remote sensing observations, Atmos. Chem. Phys., 11, 3137–3157, https://doi.org/10.5194/acp-11-3137-2011, 2011.
Jickells, T. D., An, Z. S., Andersen, K. K., Baker, A. R., Bergametti, G., Brooks, N., Cao, J. J., Boyd, P. W., Duce, R. A., Hunter, K. A., Kawahata, H., Kubilay, N., laRoche, J., Liss, P. S., Mahowald, N., Prospero, J. M., Ridgwell, A. J., Tegen, I., and Torres, R.: Global Iron Connections Between Desert Dust, Ocean Biogeochemistry, and Climate, Science, 308, 67–71, https://doi.org/10.1126/science.1105959, 2005.
Jones, A. C., Hill, A., Hemmings, J., Lemaitre, P., Quérel, A., Ryder, C. L., and Woodward, S.: Below-cloud scavenging of aerosol by rain: a review of numerical modelling approaches and sensitivity simulations with mineral dust in the Met Office's Unified Model, Atmos. Chem. Phys., 22, 11381–11407, https://doi.org/10.5194/acp-22-11381-2022, 2022.
Kenny, L. C., Gussman, R., and Meyer, M.: Development of a Sharp-Cut Cyclone for Ambient Aerosol Monitoring Applications, Aerosol Science and Technology, 32, 338–358, https://doi.org/10.1080/027868200303669, 2000.
Kok, J. F.: A scaling theory for the size distribution of emitted dust aerosols suggests climate models underestimate the size of the global dust cycle, Proceedings of the National Academy of Sciences, 108, 1016–1021, https://doi.org/10.1073/pnas.1014798108, 2011.
Kok, J. F., Mahowald, N. M., Fratini, G., Gillies, J. A., Ishizuka, M., Leys, J. F., Mikami, M., Park, M.-S., Park, S.-U., Van Pelt, R. S., and Zobeck, T. M.: An improved dust emission model – Part 1: Model description and comparison against measurements, Atmos. Chem. Phys., 14, 13023–13041, https://doi.org/10.5194/acp-14-13023-2014, 2014.
Kok, J. F., Ridley, D. A., Zhou, Q., Miller, R. L., Zhao, C., Heald, C. L., Ward, D. S., Albani, S., and Haustein, K.: Smaller desert dust cooling effect estimated from analysis of dust size and abundance, Nature Geoscience, 10, 274–278, https://doi.org/10.1038/ngeo2912, 2017.
Kok, J. F., Adebiyi, A. A., Albani, S., Balkanski, Y., Checa-Garcia, R., Chin, M., Colarco, P. R., Hamilton, D. S., Huang, Y., Ito, A., Klose, M., Li, L., Mahowald, N. M., Miller, R. L., Obiso, V., Pérez García-Pando, C., Rocha-Lima, A., and Wan, J. S.: Contribution of the world's main dust source regions to the global cycle of desert dust, Atmos. Chem. Phys., 21, 8169–8193, https://doi.org/10.5194/acp-21-8169-2021, 2021a.
Kok, J. F., Adebiyi, A. A., Albani, S., Balkanski, Y., Checa-Garcia, R., Chin, M., Colarco, P. R., Hamilton, D. S., Huang, Y., Ito, A., Klose, M., Leung, D. M., Li, L., Mahowald, N. M., Miller, R. L., Obiso, V., Pérez García-Pando, C., Rocha-Lima, A., Wan, J. S., and Whicker, C. A.: Improved representation of the global dust cycle using observational constraints on dust properties and abundance, Atmos. Chem. Phys., 21, 8127–8167, https://doi.org/10.5194/acp-21-8127-2021, 2021b.
Koster, R. D., Reichle, R. H., Mahanama, S. P., Perket, J., Liu, Q., and Partyka, G.: Land-focused changes in the updated GEOS FP system (Version 5.25), 2020.
Latimer, R. N. C. and Martin, R. V.: Interpretation of measured aerosol mass scattering efficiency over North America using a chemical transport model, Atmos. Chem. Phys., 19, 2635–2653, https://doi.org/10.5194/acp-19-2635-2019, 2019.
Leung, D. M., Kok, J. F., Li, L., Okin, G. S., Prigent, C., Klose, M., Pérez García-Pando, C., Menut, L., Mahowald, N. M., Lawrence, D. M., and Chamecki, M.: A new process-based and scale-aware desert dust emission scheme for global climate models – Part I: Description and evaluation against inverse modeling emissions, Atmos. Chem. Phys., 23, 6487–6523, https://doi.org/10.5194/acp-23-6487-2023, 2023.
Leung, D. M., Kok, J. F., Li, L., Mahowald, N. M., Lawrence, D. M., Tilmes, S., Kluzek, E., Klose, M., and Pérez García-Pando, C.: A new process-based and scale-aware desert dust emission scheme for global climate models – Part II: Evaluation in the Community Earth System Model version 2 (CESM2), Atmos. Chem. Phys., 24, 2287–2318, https://doi.org/10.5194/acp-24-2287-2024, 2024.
Li, C., Martin, R. V., van Donkelaar, A., Boys, B. L., Hammer, M. S., Xu, J.-W., Marais, E. A., Reff, A., Strum, M., Ridley, D. A., Crippa, M., Brauer, M., and Zhang, Q.: Trends in Chemical Composition of Global and Regional Population-Weighted Fine Particulate Matter Estimated for 25 Years, Environ. Sci. Technol., 51, 11185–11195, https://doi.org/10.1021/acs.est.7b02530, 2017.
Li, L., Mahowald, N. M., Kok, J. F., Liu, X., Wu, M., Leung, D. M., Hamilton, D. S., Emmons, L. K., Huang, Y., Sexton, N., Meng, J., and Wan, J.: Data and codes for “Importance of different parameterization changes for the updated dust cycle modelling in the Community Atmosphere Model (version 6.1)”, Zenodo [data set], https://doi.org/10.5281/zenodo.6989502, 2022a.
Li, L., Mahowald, N. M., Kok, J. F., Liu, X., Wu, M., Leung, D. M., Hamilton, D. S., Emmons, L. K., Huang, Y., Sexton, N., Meng, J., and Wan, J.: Importance of different parameterization changes for the updated dust cycle modeling in the Community Atmosphere Model (version 6.1), Geosci. Model Dev., 15, 8181–8219, https://doi.org/10.5194/gmd-15-8181-2022, 2022b.
Liao, H. and Seinfeld, J. H.: Radiative forcing by mineral dust aerosols: Sensitivity to key variables, Journal of Geophysical Research: Atmospheres, 103, 31637–31645, https://doi.org/10.1029/1998JD200036, 1998.
Lin, H., Jacob, D. J., Lundgren, E. W., Sulprizio, M. P., Keller, C. A., Fritz, T. M., Eastham, S. D., Emmons, L. K., Campbell, P. C., Baker, B., Saylor, R. D., and Montuoro, R.: Harmonized Emissions Component (HEMCO) 3.0 as a versatile emissions component for atmospheric models: application in the GEOS-Chem, NASA GEOS, WRF-GC, CESM2, NOAA GEFS-Aerosol, and NOAA UFS models, Geosci. Model Dev., 14, 5487–5506, https://doi.org/10.5194/gmd-14-5487-2021, 2021.
Liu, H., Jacob, D. J., Bey, I., and Yantosca, R. M.: Constraints from 210Pb and 7Be on wet deposition and transport in a global three-dimensional chemical tracer model driven by assimilated meteorological fields, Journal of Geophysical Research: Atmospheres, 106, 12109–12128, https://doi.org/10.1029/2000JD900839, 2001.
Liu, X., Turner, J. R., Hand, J. L., Schichtel, B. A., and Martin, R. V.: A Global-Scale Mineral Dust Equation, Journal of Geophysical Research: Atmospheres, 127, e2022JD036937, https://doi.org/10.1029/2022JD036937, 2022.
Liu, X., Turner, J. R., Oxford, C. R., McNeill, J., Walsh, B., Le Roy, E., Weagle, C. L., Stone, E., Zhu, H., Liu, W., Wei, Z., Hyslop, N. P., Giacomo, J., Dillner, A. M., Salam, A., Hossen, A., Islam, Z., Abboud, I., Akoshile, C., Amador-Muñoz, O., Anh, N. X., Asfaw, A., Balasubramanian, R., Chang, R. Y.-W., Coburn, C., Dey, S., Diner, D. J., Dong, J., Farrah, T., Gahungu, P., Garland, R. M., Grutter de la Mora, M., Hasheminassab, S., John, J., Kim, J., Kim, J. S., Langerman, K., Lee, P.-C., Lestari, P., Liu, Y., Mamo, T., Martins, M., Mayol-Bracero, O. L., Naidoo, M., Park, S. S., Schechner, Y., Schofield, R., Tripathi, S. N., Windwer, E., Wu, M.-T., Zhang, Q., Brauer, M., Rudich, Y., and Martin, R. V.: Elemental Characterization of Ambient Particulate Matter for a Globally Distributed Monitoring Network: Methodology and Implications, ACS EST Air, 1, 283–293, https://doi.org/10.1021/acsestair.3c00069, 2024.
Mahowald, N., Kohfeld, K., Hansson, M., Balkanski, Y., Harrison, S. P., Prentice, I. C., Schulz, M., and Rodhe, H.: Dust sources and deposition during the last glacial maximum and current climate: A comparison of model results with paleodata from ice cores and marine sediments, Journal of Geophysical Research: Atmospheres, 104, 15895–15916, https://doi.org/10.1029/1999JD900084, 1999.
Mahowald, N., Albani, S., Kok, J. F., Engelstaeder, S., Scanza, R., Ward, D. S., and Flanner, M. G.: The size distribution of desert dust aerosols and its impact on the Earth system, Aeolian Research, 15, 53–71, https://doi.org/10.1016/j.aeolia.2013.09.002, 2014.
Marticorena, B. and Bergametti, G.: Modeling the atmospheric dust cycle: 1. Design of a soil-derived dust emission scheme, Journal of Geophysical Research: Atmospheres, 100, 16415–16430, https://doi.org/10.1029/95JD00690, 1995.
Martin, R. L. and Kok, J. F.: Distinct Thresholds for the Initiation and Cessation of Aeolian Saltation From Field Measurements, Journal of Geophysical Research: Earth Surface, 123, 1546–1565, https://doi.org/10.1029/2017JF004416, 2018.
Martin, R. V., Eastham, S. D., Bindle, L., Lundgren, E. W., Clune, T. L., Keller, C. A., Downs, W., Zhang, D., Lucchesi, R. A., Sulprizio, M. P., Yantosca, R. M., Li, Y., Estrada, L., Putman, W. M., Auer, B. M., Trayanov, A. L., Pawson, S., and Jacob, D. J.: Improved advection, resolution, performance, and community access in the new generation (version 13) of the high-performance GEOS-Chem global atmospheric chemistry model (GCHP), Geosci. Model Dev., 15, 8731–8748, https://doi.org/10.5194/gmd-15-8731-2022, 2022.
Meng, J., Martin, R. V., Ginoux, P., Hammer, M., Sulprizio, M. P., Ridley, D. A., and van Donkelaar, A.: Grid-independent high-resolution dust emissions (v1.0) for chemical transport models: application to GEOS-Chem (12.5.0), Geosci. Model Dev., 14, 4249–4260, https://doi.org/10.5194/gmd-14-4249-2021, 2021.
Meng, J., Huang, Y., Leung, D. M., Li, L., Adebiyi, A. A., Ryder, C. L., Mahowald, N. M., and Kok, J. F.: Improved Parameterization for the Size Distribution of Emitted Dust Aerosols Reduces Model Underestimation of Super Coarse Dust, Geophysical Research Letters, 49, e2021GL097287, https://doi.org/10.1029/2021GL097287, 2022.
Miller, S. J., Makar, P. A., and Lee, C. J.: HETerogeneous vectorized or Parallel (HETPv1.0): an updated inorganic heterogeneous chemistry solver for the metastable-state NH
Murray, L. T., Jacob, D. J., Logan, J. A., Hudman, R. C., and Koshak, W. J.: Optimized regional and interannual variability of lightning in a global chemical transport model constrained by LIS/OTD satellite data, Journal of Geophysical Research: Atmospheres, 117, D20307, https://doi.org/10.1029/2012JD017934, 2012.
Mytilinaios, M., Basart, S., Ciamprone, S., Cuesta, J., Dema, C., Di Tomaso, E., Formenti, P., Gkikas, A., Jorba, O., Kahn, R., Pérez García-Pando, C., Trippetta, S., and Mona, L.: Comparison of dust optical depth from multi-sensor products and MONARCH (Multiscale Online Non-hydrostatic AtmospheRe CHemistry) dust reanalysis over North Africa, the Middle East, and Europe, Atmos. Chem. Phys., 23, 5487–5516, https://doi.org/10.5194/acp-23-5487-2023, 2023.
Okin, G. S.: A new model of wind erosion in the presence of vegetation, Journal of Geophysical Research: Earth Surface, 113, https://doi.org/10.1029/2007JF000758, 2008.
Pai, S. J., Heald, C. L., Pierce, J. R., Farina, S. C., Marais, E. A., Jimenez, J. L., Campuzano-Jost, P., Nault, B. A., Middlebrook, A. M., Coe, H., Shilling, J. E., Bahreini, R., Dingle, J. H., and Vu, K.: An evaluation of global organic aerosol schemes using airborne observations, Atmos. Chem. Phys., 20, 2637–2665, https://doi.org/10.5194/acp-20-2637-2020, 2020.
Panofsky, H. A., Tennekes, H., Lenschow, D. H., and Wyngaard, J. C.: The characteristics of turbulent velocity components in the surface layer under convective conditions, Boundary-Layer Meteorology, 11, 355–361, https://doi.org/10.1007/BF02186086, 1977.
Park, R. J., Jacob, D. J., Field, B. D., Yantosca, R. M., and Chin, M.: Natural and transboundary pollution influences on sulfate-nitrate-ammonium aerosols in the United States: Implications for policy, Journal of Geophysical Research: Atmospheres, 109, D15204, https://doi.org/10.1029/2003jd004473, 2004.
Peters, T. M., Kenny, L. C., Gussman, R. A., and Vanderpool, R. W.: Evaluation of PM2.5 Size Selectors Used in Speciation Samplers, Aerosol Science and Technology, 34, 422–429, https://doi.org/10.1080/02786820119266, 2001.
Petroff, A. and Zhang, L.: Development and validation of a size-resolved particle dry deposition scheme for application in aerosol transport models, Geosci. Model Dev., 3, 753–769, https://doi.org/10.5194/gmd-3-753-2010, 2010.
Philip, S., Martin, R. V., Snider, G., Weagle, C. L., Donkelaar, A. van, Brauer, M., Henze, D. K., Klimont, Z., Venkataraman, C., Guttikunda, S. K., and Zhang, Q.: Anthropogenic fugitive, combustion and industrial dust is a significant, underrepresented fine particulate matter source in global atmospheric models, Environmental Research Letters, 12, 044018, https://doi.org/10.1088/1748-9326/aa65a4, 2017.
Pierre, C., Bergametti, G., Marticorena, B., Kergoat, L., Mougin, E., and Hiernaux, P.: Comparing drag partition schemes over a herbaceous Sahelian rangeland, Journal of Geophysical Research: Earth Surface, 119, 2291–2313, https://doi.org/10.1002/2014JF003177, 2014a.
Pierre, C., Bergametti, G., Marticorena, B., AbdourhamaneTouré, A., Rajot, J.-L., and Kergoat, L.: Modeling wind erosion flux and its seasonality from a cultivated sahelian surface: A case study in Niger, CATENA, 122, 61–71, https://doi.org/10.1016/j.catena.2014.06.006, 2014b.
Poggio, L., de Sousa, L. M., Batjes, N. H., Heuvelink, G. B. M., Kempen, B., Ribeiro, E., and Rossiter, D.: SoilGrids 2.0: producing soil information for the globe with quantified spatial uncertainty, SOIL, 7, 217–240, https://doi.org/10.5194/soil-7-217-2021, 2021.
Prigent, C., Tegen, I., Aires, F., Marticorena, B., and Zribi, M.: Estimation of the aerodynamic roughness length in arid and semi-arid regions over the globe with the ERS scatterometer, Journal of Geophysical Research: Atmospheres, 110, https://doi.org/10.1029/2004JD005370, 2005.
Prospero, J. M.: Long-range transport of mineral dust in the global atmosphere: Impact of African dust on the environment of the southeastern United States, Proceedings of the National Academy of Sciences, 96, 3396–3403, https://doi.org/10.1073/pnas.96.7.3396, 1999.
Reid, J. S., Jonsson, H. H., Maring, H. B., Smirnov, A., Savoie, D. L., Cliff, S. S., Reid, E. A., Livingston, J. M., Meier, M. M., Dubovik, O., and Tsay, S.-C.: Comparison of size and morphological measurements of coarse mode dust particles from Africa, Journal of Geophysical Research: Atmospheres, 108, https://doi.org/10.1029/2002JD002485, 2003.
Ridley, D. A., Heald, C. L., and Ford, B.: North African dust export and deposition: A satellite and model perspective, Journal of Geophysical Research: Atmospheres, 117, D02202, https://doi.org/10.1029/2011JD016794, 2012.
Ridley, D. A., Heald, C. L., Kok, J. F., and Zhao, C.: An observationally constrained estimate of global dust aerosol optical depth, Atmos. Chem. Phys., 16, 15097–15117, https://doi.org/10.5194/acp-16-15097-2016, 2016.
Ryder, C. L., Highwood, E. J., Rosenberg, P. D., Trembath, J., Brooke, J. K., Bart, M., Dean, A., Crosier, J., Dorsey, J., Brindley, H., Banks, J., Marsham, J. H., McQuaid, J. B., Sodemann, H., and Washington, R.: Optical properties of Saharan dust aerosol and contribution from the coarse mode as measured during the Fennec 2011 aircraft campaign, Atmos. Chem. Phys., 13, 303–325, https://doi.org/10.5194/acp-13-303-2013, 2013.
Ryu, Y.-H. and Min, S.-K.: Improving Wet and Dry Deposition of Aerosols in WRF-Chem: Updates to Below-Cloud Scavenging and Coarse-Particle Dry Deposition, Journal of Advances in Modeling Earth Systems, 14, e2021MS002792, https://doi.org/10.1029/2021MS002792, 2022.
Shangguan, W., Dai, Y., Duan, Q., Liu, B., and Yuan, H.: A global soil data set for earth system modeling, Journal of Advances in Modeling Earth Systems, 6, 249–263, https://doi.org/10.1002/2013MS000293, 2014.
Shao, Y. and Lu, H.: A simple expression for wind erosion threshold friction velocity, Journal of Geophysical Research: Atmospheres, 105, 22437–22443, https://doi.org/10.1029/2000JD900304, 2000.
Singh, I., Martin, R. V., Bindle, L., Chatterjee, D., Li, C., Oxford, C., Xu, X., and Wang, J.: Effect of Dust Morphology on Aerosol Optics in the GEOS-Chem Chemical Transport Model, on UV-Vis Trace Gas Retrievals, and on Surface Area Available for Reactive Uptake, Journal of Advances in Modeling Earth Systems, 16, e2023MS003746, https://doi.org/10.1029/2023MS003746, 2024.
Sinyuk, A., Torres, O., and Dubovik, O.: Combined use of satellite and surface observations to infer the imaginary part of refractive index of Saharan dust, Geophysical Research Letters, 30, https://doi.org/10.1029/2002GL016189, 2003.
Smith, R. J.: Use and misuse of the reduced major axis for line-fitting, American Journal of Physical Anthropology, 140, 476–486, https://doi.org/10.1002/ajpa.21090, 2009.
Snider, G., Weagle, C. L., Martin, R. V., van Donkelaar, A., Conrad, K., Cunningham, D., Gordon, C., Zwicker, M., Akoshile, C., Artaxo, P., Anh, N. X., Brook, J., Dong, J., Garland, R. M., Greenwald, R., Griffith, D., He, K., Holben, B. N., Kahn, R., Koren, I., Lagrosas, N., Lestari, P., Ma, Z., Vanderlei Martins, J., Quel, E. J., Rudich, Y., Salam, A., Tripathi, S. N., Yu, C., Zhang, Q., Zhang, Y., Brauer, M., Cohen, A., Gibson, M. D., and Liu, Y.: SPARTAN: a global network to evaluate and enhance satellite-based estimates of ground-level particulate matter for global health applications, Atmos. Meas. Tech., 8, 505–521, https://doi.org/10.5194/amt-8-505-2015, 2015.
Song, Q., Zhang, Z., Yu, H., Ginoux, P., and Shen, J.: Global dust optical depth climatology derived from CALIOP and MODIS aerosol retrievals on decadal timescales: regional and interannual variability, Atmos. Chem. Phys., 21, 13369–13395, https://doi.org/10.5194/acp-21-13369-2021, 2021.
Swap, R., Garstang, M., Greco, S., Talbot, R., and Kallberg, P.: Saharan dust in the Amazon Basin, Tellus B, 44, 133–149, https://doi.org/10.1034/j.1600-0889.1992.t01-1-00005.x, 1992.
Swenson, S. C. and Lawrence, D. M.: Assessing a dry surface layer-based soil resistance parameterization for the Community Land Model using GRACE and FLUXNET-MTE data, Journal of Geophysical Research: Atmospheres, 119, 10299–10312, https://doi.org/10.1002/2014JD022314, 2014.
The International GEOS-Chem User Community: geoschem/GCHP: GCHP 14.4.1, Zenodo [code], https://doi.org/10.5281/zenodo.12584305, 2024.
Tian, R., Ma, X., and Zhao, J.: A revised mineral dust emission scheme in GEOS-Chem: improvements in dust simulations over China, Atmos. Chem. Phys., 21, 4319–4337, https://doi.org/10.5194/acp-21-4319-2021, 2021.
Tindan, J. Z., Jin, Q., and Pu, B.: Understanding day–night differences in dust aerosols over the dust belt of North Africa, the Middle East, and Asia, Atmos. Chem. Phys., 23, 5435–5466, https://doi.org/10.5194/acp-23-5435-2023, 2023.
Uno, I., Wang, Z., Chiba, M., Chun, Y. S., Gong, S. L., Hara, Y., Jung, E., Lee, S.-S., Liu, M., Mikami, M., Music, S., Nickovic, S., Satake, S., Shao, Y., Song, Z., Sugimoto, N., Tanaka, T., and Westphal, D. L.: Dust model intercomparison (DMIP) study over Asia: Overview, Journal of Geophysical Research: Atmospheres, 111, https://doi.org/10.1029/2005JD006575, 2006.
Wang, Q., Jacob, D. J., Fisher, J. A., Mao, J., Leibensperger, E. M., Carouge, C. C., Le Sager, P., Kondo, Y., Jimenez, J. L., Cubison, M. J., and Doherty, S. J.: Sources of carbonaceous aerosols and deposited black carbon in the Arctic in winter-spring: implications for radiative forcing, Atmos. Chem. Phys., 11, 12453–12473, https://doi.org/10.5194/acp-11-12453-2011, 2011.
Wang, Q., Jacob, D. J., Spackman, J. R., Perring, A. E., Schwarz, J. P., Moteki, N., Marais, E. A., Ge, C., Wang, J., and Barrett, S. R. H.: Global budget and radiative forcing of black carbon aerosol: Constraints from pole-to-pole (HIPPO) observations across the Pacific, Journal of Geophysical Research: Atmospheres, 119, 195–206, https://doi.org/10.1002/2013jd020824, 2014a.
Wang, X., Zhang, L., and Moran, M. D.: Development of a new semi-empirical parameterization for below-cloud scavenging of size-resolved aerosol particles by both rain and snow, Geosci. Model Dev., 7, 799–819, https://doi.org/10.5194/gmd-7-799-2014, 2014b.
Wang, X., Jacob, D. J., Downs, W., Zhai, S., Zhu, L., Shah, V., Holmes, C. D., Sherwen, T., Alexander, B., Evans, M. J., Eastham, S. D., Neuman, J. A., Veres, P. R., Koenig, T. K., Volkamer, R., Huey, L. G., Bannan, T. J., Percival, C. J., Lee, B. H., and Thornton, J. A.: Global tropospheric halogen (Cl, Br, I) chemistry and its impact on oxidants, Atmos. Chem. Phys., 21, 13973–13996, https://doi.org/10.5194/acp-21-13973-2021, 2021.
Webb, N. P., Chappell, A., LeGrand, S. L., Ziegler, N. P., and Edwards, B. L.: A note on the use of drag partition in aeolian transport models, Aeolian Research, 42, 100560, https://doi.org/10.1016/j.aeolia.2019.100560, 2020.
Weng, H., Lin, J., Martin, R. V., Millet, D. B., Jaeglé, L., Ridley, D., Keller, C., Li, C., Du, M., and Meng, J.: Global high-resolution emissions of soil NOx, sea salt aerosols, and biogenic volatile organic compounds, Scientific Data, 7, 148, https://doi.org/10.1038/s41597-020-0488-5, 2020.
White, B. R.: Soil transport by winds on Mars, Journal of Geophysical Research: Solid Earth, 84, 4643–4651, https://doi.org/10.1029/JB084iB09p04643, 1979.
Wu, C., Lin, Z., and Liu, X.: The global dust cycle and uncertainty in CMIP5 (Coupled Model Intercomparison Project phase 5) models, Atmos. Chem. Phys., 20, 10401–10425, https://doi.org/10.5194/acp-20-10401-2020, 2020.
Wu, C., Lin, Z., Shao, Y., Liu, X., and Li, Y.: Drivers of recent decline in dust activity over East Asia, Nature Communications, 13, 7105, https://doi.org/10.1038/s41467-022-34823-3, 2022.
Young, S. A., Vaughan, M. A., Garnier, A., Tackett, J. L., Lambeth, J. D., and Powell, K. A.: Extinction and optical depth retrievals for CALIPSO's Version 4 data release, Atmos. Meas. Tech., 11, 5701–5727, https://doi.org/10.5194/amt-11-5701-2018, 2018.
Yu, Y., Kalashnikova, O. V., Garay, M. J., Lee, H., Choi, M., Okin, G. S., Yorks, J. E., Campbell, J. R., and Marquis, J.: A global analysis of diurnal variability in dust and dust mixture using CATS observations, Atmos. Chem. Phys., 21, 1427–1447, https://doi.org/10.5194/acp-21-1427-2021, 2021.
Yuan, H., Dai, Y., Xiao, Z., Ji, D., and Shangguan, W.: Reprocessing the MODIS Leaf Area Index products for land surface and climate modelling, Remote Sensing of Environment, 115, 1171–1187, https://doi.org/10.1016/j.rse.2011.01.001, 2011.
Zender, C. S., Bian, H., and Newman, D.: Mineral Dust Entrainment and Deposition (DEAD) model: Description and 1990s dust climatology, Journal of Geophysical Research: Atmospheres, 108, https://doi.org/10.1029/2002JD002775, 2003.
Zhang, D.: Improving Fine Mineral Dust Representation from the Surface to the Column in GEOS-Chem version 14.4.1, Zenodo [code], https://doi.org/10.5281/zenodo.14510793, 2024.
Zhang, J. and Shao, Y.: A new parameterization of particle dry deposition over rough surfaces, Atmos. Chem. Phys., 14, 12429–12440, https://doi.org/10.5194/acp-14-12429-2014, 2014.
Zhang, L., Gong, S., Padro, J., and Barrie, L.: A size-segregated particle dry deposition scheme for an atmospheric aerosol module, Atmospheric Environment, 35, 549–560, https://doi.org/10.1016/S1352-2310(00)00326-5, 2001.
Zhang, L., Kok, J. F., Henze, D. K., Li, Q., and Zhao, C.: Improving simulations of fine dust surface concentrations over the western United States by optimizing the particle size distribution, Geophysical Research Letters, 40, 3270–3275, https://doi.org/10.1002/grl.50591, 2013.
Zhao, A., Ryder, C. L., and Wilcox, L. J.: How well do the CMIP6 models simulate dust aerosols?, Atmos. Chem. Phys., 22, 2095–2119, https://doi.org/10.5194/acp-22-2095-2022, 2022.
Zhu, H., Martin, R. V., Croft, B., Zhai, S., Li, C., Bindle, L., Pierce, J. R., Chang, R. Y.-W., Anderson, B. E., Ziemba, L. D., Hair, J. W., Ferrare, R. A., Hostetler, C. A., Singh, I., Chatterjee, D., Jimenez, J. L., Campuzano-Jost, P., Nault, B. A., Dibb, J. E., Schwarz, J. S., and Weinheimer, A.: Parameterization of size of organic and secondary inorganic aerosol for efficient representation of global aerosol optical properties, Atmos. Chem. Phys., 23, 5023–5042, https://doi.org/10.5194/acp-23-5023-2023, 2023.
Short summary
This study develops the fine mineral dust simulation in GEOS-Chem by: 1) implementing a new dust emission scheme with further refinements; 2) revisiting the size distribution of emitted dust; 3) explicitly tracking fine dust for emission, transport and deposition in 4 size bins; 4) updating the parametrization for below-cloud scavenging. All revisions significantly reduce the overestimation of surface fine dust from 94 % to 35 % while retaining comparable skill in representing columnar abundance.
This study develops the fine mineral dust simulation in GEOS-Chem by: 1) implementing a new dust...
