Improved representation of the global dust cycle using observational constraints on dust properties and abundance.
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, Chloe A Whicker
Author Information
Jasper F Kok: Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, CA 90095, USA.
Adeyemi A Adebiyi: Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, CA 90095, USA.
Samuel Albani: Department of Environmental and Earth Sciences, University of Milano-Bicocca, Milano, Italy.
Yves Balkanski: Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ-UPSaclay, Gif-sur-Yvette, France.
Ramiro Checa-Garcia: Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ-UPSaclay, Gif-sur-Yvette, France.
Mian Chin: Atmospheric Chemistry and Dynamics Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA.
Peter R Colarco: Atmospheric Chemistry and Dynamics Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA.
Douglas S Hamilton: Department of Earth and Atmospheric Sciences, Cornell University, Ithaca, NY 14850, USA.
Yue Huang: Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, CA 90095, USA.
Akinori Ito: Yokohama Institute for Earth Sciences, JAMSTEC, Yokohama, Kanagawa 236-0001, Japan.
Martina Klose: Barcelona Supercomputing Center (BSC), 08034 Barcelona, Spain.
Danny M Leung: Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, CA 90095, USA.
Longlei Li: Department of Earth and Atmospheric Sciences, Cornell University, Ithaca, NY 14850, USA.
Natalie M Mahowald: Department of Earth and Atmospheric Sciences, Cornell University, Ithaca, NY 14850, USA.
Ron L Miller: NASA Goddard Institute for Space Studies, New York NY10025 USA.
Vincenzo Obiso: Barcelona Supercomputing Center (BSC), 08034 Barcelona, Spain.
Carlos Pérez García-Pando: Barcelona Supercomputing Center (BSC), 08034 Barcelona, Spain.
Adriana Rocha-Lima: Physics Department, UMBC, Baltimore, Maryland, USA.
Jessica S Wan: Department of Earth and Atmospheric Sciences, Cornell University, Ithaca, NY 14850, USA.
Chloe A Whicker: Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, CA 90095, USA.
Even though desert dust is the most abundant aerosol by mass in Earth's atmosphere, atmospheric models struggle to accurately represent its spatial and temporal distribution. These model errors are partially caused by fundamental difficulties in simulating dust emission in coarse-resolution models and in accurately representing dust microphysical properties. Here we mitigate these problems by developing a new methodology that yields an improved representation of the global dust cycle. We present an analytical framework that uses inverse modeling to integrate an ensemble of global model simulations with observational constraints on the dust size distribution, extinction efficiency, and regional dust aerosol optical depth. We then compare the inverse model results against independent measurements of dust surface concentration and deposition flux and find that errors are reduced by approximately a factor of two relative to current model simulations of the Northern Hemisphere dust cycle. The inverse model results show smaller improvements in the less dusty Southern Hemisphere, most likely because both the model simulations and the observational constraints used in the inverse model are less accurate. On a global basis, we find that the emission flux of dust with geometric diameter up to 20 μm (PM) is approximately 5,000 Tg/year, which is greater than most models account for. This larger PM dust flux is needed to match observational constraints showing a large atmospheric loading of coarse dust. We obtain gridded data sets of dust emission, vertically integrated loading, dust aerosol optical depth, (surface) concentration, and wet and dry deposition fluxes that are resolved by season and particle size. As our results indicate that this data set is more accurate than current model simulations and the MERRA-2 dust reanalysis product, it can be used to improve quantifications of dust impacts on the Earth system.
