2012
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

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… Show more

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Cited by 102 publications
(91 citation statements)
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References 28 publications
(38 reference statements)
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“…Several offline CTMs already have adjoints for constraining aerosol and aerosol precursor emissions, including GEOS-Chem (Henze et al, 2007), Sulfur Transport dEposition Model (STEM) Hakami et al, 2005), Community Multi-scale Air Quality Model (CMAQ) (Turner et al, 2015), Goddard Chemistry Aerosol Radiation and Transport model (GOCART) (Dubovik et al, 2008), and Laboratoire de Météorologie Dynamique (LMDz) . Inverse modeling has been used to constrain aerosol emissions with 4D-Var, but only in offline models (e.g., Hakami et al, 2005;Dubovik et al, 2008;Henze et al, 2009;Wang et al, 2012). In addition to inverse modeling, derivatives calculated from CTM adjoints have been used to analyze sensitivities of model estimates to emissions (e.g., Turner et al, 2012).…”
Section: Introductionmentioning
confidence: 99%
“…Several offline CTMs already have adjoints for constraining aerosol and aerosol precursor emissions, including GEOS-Chem (Henze et al, 2007), Sulfur Transport dEposition Model (STEM) Hakami et al, 2005), Community Multi-scale Air Quality Model (CMAQ) (Turner et al, 2015), Goddard Chemistry Aerosol Radiation and Transport model (GOCART) (Dubovik et al, 2008), and Laboratoire de Météorologie Dynamique (LMDz) . Inverse modeling has been used to constrain aerosol emissions with 4D-Var, but only in offline models (e.g., Hakami et al, 2005;Dubovik et al, 2008;Henze et al, 2009;Wang et al, 2012). In addition to inverse modeling, derivatives calculated from CTM adjoints have been used to analyze sensitivities of model estimates to emissions (e.g., Turner et al, 2012).…”
Section: Introductionmentioning
confidence: 99%
“…The dust simulation in GEOS-Chem has been able to capture the magnitude and seasonal cycle of dust over the northeast Pacific and the timing and vertical structure of dust outflow in the free troposphere from Asia . Moreover, the positive biases of the dust simulations of both concentration and AOD in GEOS-Chem over the dust source regions and downwind areas (Generoso et al, 2008;Fairlie et al, 2010;Johnson et al, 2012;Ridley et al, 2012;Wang et al, 2012) have been improved in our current study.…”
Section: Zhang Et Al: Dust Vertical Profile Impact On Global Radimentioning
confidence: 87%
“…However, Fushimi et al (2011) and Chatani et al (2014) suggested that the difference in the EC concentrations between WRF-CMAQ and the measurements is largely attributed to an underestimation of the EC emission inventory, especially open biomass burning from domestic 252 D. Goto et al: Application of a global nonhydrostatic model to regional aerosol simulations around Japan sources. The local EC emission can be estimated by a combination of the data assimilation and intensive measurements (Schutgens et al, 2012;Wang et al, 2012;Yumimoto and Takemura, 2013).…”
Section: Uncertainty In the Simulationmentioning
confidence: 99%