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To determine the location of the potential dust source regions and to evaluate the dust emission frequencies over the arid and semiarid areas of China and Mongolia (35.5°N–47°N; 73°E–125°E), we established a map of Z 0 from the composition of protrusion coefficient (PC) derived from the POLDER‐1 bidirectional reflectance distribution function (BRDF). Using a ° × ° resolution Z 0 data set, we derived a map of the 10‐m erosion threshold wind velocity for the Chinese and Mongolian deserts. The retrieved erosion thresholds range from 7 m s −1 in the sandy deserts (Taklimakan, Badain Jaran, and Tengger deserts) to up to 20 m s −1 in the Gobi desert. They are comparable to the minimum wind velocity measured in meteorological stations during dust storms in the Taklimakan (6–8 m s −1 ) and in the Gobi desert (11–20 m s −1 ). These erosion thresholds were combined with surface wind fields, soil moisture, and snow cover to simulate the dust emission frequencies of the eastern Asian deserts over 3 years (1997–1999). The simulations point out the Taklimakan desert and the deserts of northern China as the most frequent sources of dust emissions. The simulated seasonal cycle is characterized by a maximum in late spring and a minimum in late autumn and winter. The comparison with climatologic studies of dust storms derived from synoptic observations confirms the importance of these two source areas and the reliability of the simulated seasonal cycle. It reveals an underestimation of the dust emission frequency in the Gobi desert, because of a low frequency of high wind velocities. Our results also suggest that soil moisture and snow cover are not the main factors controlling the seasonal cycle or the interannual variability of the dust emission frequencies. We finally compared the simulated dust event frequencies to occurrences of Total Ozone Mapping Spectrometer (TOMS) Absorbing Aerosol Index (AAI) higher than 0.7 over the Taklimakan desert, where mineral dust is expected to be the dominant absorbing aerosol. A very good agreement is obtained between the simulated frequencies and the TOMS AAI frequencies on monthly and seasonal timescales.
Laurent et al. (Thu,) studied this question.
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