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DOI10.5194/acp-20-55-2020
Retrieving the global distribution of the threshold of wind erosion from satellite data and implementing it into the Geophysical Fluid Dynamics Laboratory land-atmosphere model (GFDL AM4.0/LM4.0)
Pu B.; Ginoux P.; Guo H.; Christina Hsu N.; Kimball J.; Marticorena B.; Malyshev S.; Naik V.; O'Neill N.T.; Pérez García-Pando C.; Paireau J.; Prospero J.M.; Shevliakova E.; Zhao M.
发表日期2020
ISSN1680-7316
起始页码55
结束页码81
卷号20期号:1
英文摘要Dust emission is initiated when surface wind velocities exceed the threshold of wind erosion. Many dust models used constant threshold values globally. Here we use satellite products to characterize the frequency of dust events and land surface properties. By matching this frequency derived from Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue aerosol products with surface winds, we are able to retrieve a climatological monthly global distribution of the wind erosion threshold (Vthreshold) over dry and sparsely vegetated surfaces. This monthly two-dimensional threshold velocity is then implemented into the Geophysical Fluid Dynamics Laboratory coupled land-atmosphere model (AM4.0/LM4.0). It is found that the climatology of dust optical depth (DOD) and total aerosol optical depth, surface PM10 dust concentrations, and the seasonal cycle of DOD are better captured over the "dust belt" (i.e., northern Africa and the Middle East) by simulations with the new wind erosion threshold than those using the default globally constant threshold. The most significant improvement is the frequency distribution of dust events, which is generally ignored in model evaluation. By using monthly rather than annual mean Vthreshold, all comparisons with observations are further improved. The monthly global threshold of wind erosion can be retrieved under different spatial resolutions to match the resolution of dust models and thus can help improve the simulations of dust climatology and seasonal cycles as well as dust forecasting. © Author(s) 2020.
语种英语
scopus关键词atmospheric modeling; dust; frequency analysis; land surface; MODIS; satellite data; seasonality; temporal distribution; wind erosion
来源期刊ATMOSPHERIC CHEMISTRY AND PHYSICS
文献类型期刊论文
条目标识符http://gcip.llas.ac.cn/handle/2XKMVOVA/248070
作者单位Atmospheric and Oceanic Sciences Program, Princeton University, Princeton, NJ 08544, United States; NOAA Geophysical Fluid Dynamics Laboratory, Princeton, NJ 08540, United States; NASA Goddard Space Flight Center, Greenbelt, MD 20771, United States; Department of Ecosystem and Conservation Sciences, University of Montana, Missoula, MT 59812, United States; Laboratoire Interuniversitaire des Systèmes Atmosphériques, Universités Paris Est-Paris Diderot-Paris 7, UMR CNRS 7583, Créteil, France; Département de géomatique appliquée, Université de Sherbrooke, Sherbrooke, QC, Canada; Barcelona Supercomputing Center, Barcelona, 08034, Spain; ICREA, Passeig Lluís Companys 23, Barcelona, 08010, Spain; Department of Ecology and Evolutionary Biology, Princeton Environmental Institute, Princeton University, Princeton, NJ 08544, United States; Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR 2000, CNRS, Paris, 75015, France; Rosenstiel School of Marine and Atmospheric Sciences, University o...
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Pu B.,Ginoux P.,Guo H.,et al. Retrieving the global distribution of the threshold of wind erosion from satellite data and implementing it into the Geophysical Fluid Dynamics Laboratory land-atmosphere model (GFDL AM4.0/LM4.0)[J],2020,20(1).
APA Pu B..,Ginoux P..,Guo H..,Christina Hsu N..,Kimball J..,...&Zhao M..(2020).Retrieving the global distribution of the threshold of wind erosion from satellite data and implementing it into the Geophysical Fluid Dynamics Laboratory land-atmosphere model (GFDL AM4.0/LM4.0).ATMOSPHERIC CHEMISTRY AND PHYSICS,20(1).
MLA Pu B.,et al."Retrieving the global distribution of the threshold of wind erosion from satellite data and implementing it into the Geophysical Fluid Dynamics Laboratory land-atmosphere model (GFDL AM4.0/LM4.0)".ATMOSPHERIC CHEMISTRY AND PHYSICS 20.1(2020).
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