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Case Study of Atmospheric Retrievals of MWHTS aboard FY-3C Satellite

机译:FY-3C卫星MWHTS大气反演的案例研究

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The mesoscale numerical model WRF is used to simulate the No. 8 hurricane Matthew in 2016. The radar and radiometer observations are assimilated by WRF Var. With the verification to the real situation, the process of the hurricane rainstorm is well simulated by WRF in this case that it could basically show the hurricane evolution. We use the simulation results which are model outputs with high spatial and temporal resolution to do diagnostic analysis on the short term heavy rainstorm caused by Matthew, with a comparison between the best track and forecasting tracks using active and passive microwave observations from WRFDA model. In order to analyze the inner structure, the nadiral satellite-based observations were matched between the Microwave Humidity and Temperature Sounder (MWHTS) instrument aboard the FY-3C polar-orbiting platform since Sept 30, 2013 and dual-frequency radar named PR aboard GPM satellite and then separate retrievals are demonstrated in data assimilation for extreme weather with the retrieved root-mean-square errors of about 0.9 K and 17% and 10 mm/h for precipitation products, which demonstrates the impact of 118 GHz observations in data assimilation model.
机译:中尺度数值模型WRF被用于模拟2016年的8号飓风马修。雷达和辐射计观测被WRF Var吸收。通过对真实情况的验证,在这种情况下WRF很好地模拟了飓风暴雨的过程,可以基本显示飓风的演变。我们使用模拟结果(具有高时空分辨率的模型输出)对Matthew造成的短期暴雨进行诊断分析,并使用WRFDA模型的主动和被动微波观测结果比较最佳航迹和预报航迹。为了分析内部结构,自2013年9月30日起将FY-3C极地轨道平台上的微波温湿度探测器(MWHTS)与双频雷达GPM上的天基卫星观测值进行了匹配卫星,然后在极端天气的数据同化中进行了单独的反演,所反演的均方根误差约为0.9 K,降水产物的均方根误差约为17%,且速度为10 mm / h,这证明了118 GHz观测对数据同化模型的影响。

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