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)
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Published:2020-01-03
Issue:1
Volume:20
Page:55-81
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ISSN:1680-7324
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Container-title:Atmospheric Chemistry and Physics
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language:en
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Short-container-title:Atmos. Chem. Phys.
Author:
Pu BingORCID, Ginoux PaulORCID, Guo HuanORCID, Hsu N. Christina, Kimball John, Marticorena Beatrice, Malyshev SergeyORCID, Naik Vaishali, O'Neill Norman T., Pérez García-Pando CarlosORCID, Paireau Juliette, Prospero Joseph M., Shevliakova Elena, Zhao Ming
Abstract
Abstract. 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.
Funder
NASA Astrobiology Institute
Publisher
Copernicus GmbH
Subject
Atmospheric Science
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