Top-down estimate of dust emissions through integration of MODIS and MISR aerosol retrievals with the GEOS-Chem adjoint model

Jun Wang; Xiaoguang Xu; Daven K Henze; Jing Zeng; Qiang Ji; Si-Chee Tsay; Jianping Huang

doi:10.1029/2012GL051136

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Top-down estimate of dust emissions through integration of MODIS and MISR aerosol retrievals with the GEOS-Chem adjoint model

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Top-down estimate of dust emissions through integration of MODIS and MISR aerosol retrievals with the GEOS-Chem adjoint model

Jun Wang, Xiaoguang Xu, Daven K Henze, Jing Zeng, Qiang Ji, Si-Chee Tsay and Jianping Huang

Geophysical research letters, Vol.39(8), L088022

04/2012

DOI: 10.1029/2012GL051136

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Abstract

[1] Predicting the influences of dust on atmospheric composition, climate, and human health requires accurate knowledge of dust emissions, but large uncertainties persist in quantifying mineral sources. This study presents a new method for combined use of satellite-measured radiances and inverse modeling to spatially constrain the amount and location of dust emissions. The technique is illustrated with a case study in May 2008; the dust emissions in Taklimakan and Gobi deserts are spatially optimized using the GEOS-Chem chemical transport model and its adjoint constrained by aerosol optical depth (AOD) that are derived over the downwind dark-surface region in China from MODIS (Moderate Resolution Imaging Spectroradiometer) reflectance with the aerosol single scattering properties consistent with GEOS-chem. The adjoint inverse modeling yields an overall 51% decrease in prior dust emissions estimated by GEOS-Chem over the Taklimakan-Gobi area, with more significant reductions south of the Gobi Desert. The model simulation with optimized dust emissions shows much better agreement with independent observations from MISR (Multi-angle Imaging SpectroRadiometer) AOD and MODIS Deep Blue AOD over the dust source region and surface PM10concentrations. The technique of this study can be applied to global multi-sensor remote sensing data for constraining dust emissions at various temporal and spatial scales, and hence improving the quantification of dust effects on climate, air quality, and human health.

dust emission

dust radiative forcing

adjoint inverse modeling

MODIS

MISR

aerosol optical depth

Details

Title: Subtitle: Top-down estimate of dust emissions through integration of MODIS and MISR aerosol retrievals with the GEOS-Chem adjoint model
Creators: Jun Wang - Department of Earth and Atmospheric Sciences, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
Xiaoguang Xu - Department of Earth and Atmospheric Sciences, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
Daven K Henze - Department of Mechanical Engineering, University of Colorado at Boulder, Boulder, Colorado, USA
Jing Zeng - Department of Earth and Atmospheric Sciences, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
Qiang Ji - Earth System Science Interdisciplinary Center, University of Maryland, College Park, Maryland, USA
Si-Chee Tsay - NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
Jianping Huang - College of Atmospheric Sciences, Lanzhou University, Lanzhou, China
Resource Type: Journal article
Publication Details: Geophysical research letters, Vol.39(8), L088022
DOI: 10.1029/2012GL051136
ISSN: 0094-8276
eISSN: 1944-8007
Publisher: Blackwell Publishing Ltd
Number of pages: 6
Language: English
Date published: 04/2012
Academic Unit: Electrical and Computer Engineering; Civil and Environmental Engineering; Iowa Technology Institute; Physics and Astronomy; Chemical and Biochemical Engineering
Record Identifier: 9984104807502771

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