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摘要： 沙尘暴的起沙过程是沙尘循环中的重要部分，起沙过程模拟的准确性对于输送和沉降过程的准确模拟十分重要。WRF-Chem (Weather Research and Forecasting with Chemistry)是目前应用最广泛的沙尘暴模拟模式之一，但目前WRF-Chem对于起沙量的模拟具有很大的不确定性，受下垫面和土壤湿度的影响较大。WRF-Chem模式中的下垫面数据比较老旧，且驱动WRF-Chem模式的资料中土壤湿度是偏高的。土地覆被和土壤水分等遥感产品的日趋成熟，为WRF-Chem模拟沙尘暴提供了新的选择和契机，因此，将AMSR2 (the Advanced Microwave Scanning Radiometer 2) 土壤湿度和MODIS (Moderate Resolution Imaging Spectroradiometer) 土地利用遥感产品及实地调查资料替换WRF-Chem下垫面，利用WRF-Chem模拟了2018年3月26日至28日发生在我国华北地区的一场沙尘过程，用于探究下垫面参数对WRF-Chem模式模拟沙尘暴的精度产生的影响。共开展了4组实验，包括1组控制实验和3组对照实验，3组对照实验分别是在控制试验基础上仅替换土壤水分初始场、仅替换土地覆被和土壤质地以及同时替换土地覆被、土壤质地及土壤水分初始场。在加入遥感数据之后，3组对照实验的模拟精度比控制实验均有所提高，其中同时替换土壤水分初始场、土地覆被和土壤质地对模式模拟结果改善最大。改善后PM10模拟的相关系数提高了0.30，平均偏差减少了31.18 μg/m3，均方根误差减少了21.70 μg/m3；AOD (Aerosol Optical Depth) 的相关系数提高了0.14，平均偏差减少了0.29，均方根误差减少了0.18，仅替换土壤水分初始场效果次之，仅替换土地覆被和土壤质地对于模拟结果改善不大。以上结果表明：加入遥感资料可以有效提高WRF-Chem对沙尘过程的模拟精度。 关键词： 遥感产品;  土壤湿度;  土地覆被;  沙尘暴;  WRF-Chem     Abstract: Sand emission process of sandstorm is a fundamental part of sand-dust cycle. Sand emission process simulating accuracy plays a crucial role in correctly simulating sand transporting and settling process. As one of the most widely used sandstorm models, WRF-Chem (Weather Research and Forecasting with Chemistry) is used to simulate the sandstorm happened during March 26 and March 28, 2018 in northern China in this study. It is reported that uncertainties in underlying surface and soil moisture initial status in WRF-Chem can lead to great bias in its simulating results. Remote sensing products like land cover and soil moisture products have been widely accepted for their higher accuracy, which provides an opportunity for WRF-Chem simulating sandstorms better. Therefore, to examine the effects of initial field uncertainties on sandstorm simulating, we simulated a sandstorm using WRF-Chem by replacing the underlying surface and soil moisture initial field with new version soil database, MODIS (Moderate Resolution Imaging Spectroradiometer) land cover products and AMSR2 (the Advanced Microwave Scanning Radiometer 2) soil moisture products. Four experiments were carried out, including a control experiment and three contrast experiments. The three contrast experiments are organized by only replacing the soil moisture initial field, only replacing land cover and soil texture, and replacing both. After replacing traditional initial field with remote sensing data, the simulation accuracy all has improved. Among the three contrast experiments, replacing all three parameters (land cover, soil texture and soil moisture) has the greatest improvement: the correlation coefficient of PM10 increases by 0.30, the average deviation reduces by 31.18 μg/m3, the root mean square error reduces by 21.7 μg/m3, the correlation coefficient of AOD (Aerosol Optical Depth) improves by 0.14, the average deviation reduces by 0.29, the root mean square error reduces by 0.18. The contrast experiment which only replacing soil moisture performs the second, followed by only replacing land cover and soil texture which does not improve the simulation results much. In conclusion, the simulation accuracy of sandstorm is improved by introducing the remote sensing products.

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