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于晓晶, 韩威, 马秀梅, 杜娟. 2018: 卫星微波辐射资料同化在新疆降水预报中的应用初探. 暴雨灾害, 37(4): 337-346. DOI: 10.3969/j.issn.1004-9045.2018.04.006
引用本文: 于晓晶, 韩威, 马秀梅, 杜娟. 2018: 卫星微波辐射资料同化在新疆降水预报中的应用初探. 暴雨灾害, 37(4): 337-346. DOI: 10.3969/j.issn.1004-9045.2018.04.006
YU Xiaojing, HAN Wei, MA Xiumei, DU Juan. 2018: Implementation of microwave radiance data assimilation in precipitation forecast in Xinjiang. Torrential Rain and Disasters, 37(4): 337-346. DOI: 10.3969/j.issn.1004-9045.2018.04.006
Citation: YU Xiaojing, HAN Wei, MA Xiumei, DU Juan. 2018: Implementation of microwave radiance data assimilation in precipitation forecast in Xinjiang. Torrential Rain and Disasters, 37(4): 337-346. DOI: 10.3969/j.issn.1004-9045.2018.04.006

卫星微波辐射资料同化在新疆降水预报中的应用初探

Implementation of microwave radiance data assimilation in precipitation forecast in Xinjiang

  • 摘要: 基于新疆区域同化预报系统(简称“DOGRAFS”),选取新疆伊犁河谷地区2016年7月31日—8月1日的强降水过程,利用常规观测资料和卫星微波辐射资料进行同化敏感试验,其中控制试验仅同化常规地面和探空资料,敏感试验在常规观测基础上分别增加微波温度(AMSU-A)、湿度(MHS)和温、湿度(AMSU-A、MHS)资料,并对2016年7月进行连续试验,以初步探究卫星微波温、湿度资料同化对新疆降水预报的影响。从关键要素增量的垂直和水平分布来看,仅同化AMSU-A资料与同时同化AMSU-A和MHS资料对初始场温度、位势高度和湿度的调整均比较显著,其低层温度和位势高度为正增量,中、高层为负增量,湿度场增量中心集中在800—600 hPa。而仅同化MHS资料对温度和位势高度的影响较小,对湿度场有所“微调”,但可更好地修正补充降水过程中的水汽信息。从降水预报和客观检验结果来看,同化AMSU-A资料总体为负效果;而同化MHS资料对于整个降水落区和大阈值降水的预报均有明显优势。

     

    Abstract: Based on the Desert Oasis Gobi Regional Assimilation and Forecasting System (DOGRAFS), four experiments are designed for a heavy precipitation occurred in the Yili vally of Xinjiang from 31 July to 1 August 2016, and a continuous test in July 2016, to investigate the impacts of microwave radiance data assimilation on rainstorm forecasts in Xinjiang. Four experiments were conducted, including (1) conventional synoptic and sounding data only (Ctrl), (2) a combination of conventional and AMSU-A data (Exp1), (3) a combination of conventional and MHS data (Exp2), (4) a combination of conventional, AMSU-A and MHS data (Exp3). The results showed that the adjustments to the initial temperature, geopotential height and humidity were notably larger by assimilating AMSU-A data (Exp1 and Exp3) than MHS data (Exp2). The adjustments to temperature and geopotential height were positive in low level and negative in middle-high level, while there were several negative centers of humidity adjustments focusing between 800-600 hPa. However, assimilating MHS data had a very weak impact on the temperature and geopotential height and a fine-tuning to the humidity. From the precipitation forecasts and objective verifications, assimilating MHS data had an advantage on the rainfall area and large threshold rainfall while the AMSU-A data had a negative effect.

     

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