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The effect of the dynamic surface bareness on dust source function, emission,...

Kim, D., M. Chin, H. Bian, Q. Tan, M. E. Brown, T. Zheng, R. You, T. Diehl, P. Ginoux, and T. Kucsera (2013), The effect of the dynamic surface bareness on dust source function, emission, and distribution, J. Geophys. Res., 118, 1-16, doi:10.1029/2012JD017907.

In this study we report the development of a time dependency of global dust source and its impact on dust simulation in the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model. We determine the surface bareness using the 8 km normalized difference vegetation index (NDVI) observed from the advanced very high resolution radiometer satellite. The results are used to analyze the temporal variations of surface bareness in 22 global dust source regions. One half of these regions can be considered permanent dust source regions where NDVI is always less than 0.15, while the other half shows substantial seasonality of NDVI. This NDVI-based surface bareness map is then used, along with the soil and topographic characteristics, to construct a dynamic dust source function for simulating dust emissions with the GOCART model. We divide the 22 dust source regions into three groups of (I) permanent desert, (II) seasonally changing bareness that regulates dust emissions, and (III) seasonally changing bareness that has little effect on dust emission. Compared with the GOCART results with the previously employed static dust source function, the simulation with the new dynamic source function shows significant improvements in category II regions. Even though the global improvement of the aerosol optical depth (AOD) is rather small when compared with satellite and ground-based remote sensing observations, we found a clear and significant effect of the new dust source on seasonal variation of dust emission and dust optical depth near the source regions. Globally, we have found that the permanent bare land contributes to 88% of the total dust emission, whereas the grassland and cultivated crops land contribute to about 12%. Our results suggest the potential of using NDVI over a vegetated area to link the dust emission with land cover and land use change for air quality and climate change studies.

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Atmospheric Composition Modeling and Analysis Program (ACMAP)
Modeling Analysis and Prediction Program (MAP)