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Improving a Precipitation Forecast by Assimilating All-Sky Himawari-8 Satellite Radiances: A Case of Typhoon Malakas (2016)

机译:通过同化全天的Himawari-8卫星广域来改善降水预测:一个Typhoon Malakas(2016)的案例

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Tropical cyclones (TCs) and associated heavy precipitation have large impacts in Japan. This study aims to find how data assimilation (DA) of every-10-minute all-sky Himawari-8 radiances could improve the quantitative precipitation forecast (QPF) for TC cases. As the first step, this study performs a single case study of Typhoon Malakas (2016) using a regional atmospheric model from the Scalable Computing for Advanced Library and Environment (SCALE) coupled with the local ensemble Kalman filter (LETKF). The results show that the all-sky Himawari-8 radiance DA at 6-km resolution improves the representation of Malakas and may provide more accurate deterministic and probabilistic precipitation forecasts if the horizontal localization scale is chosen appropriately.
机译:热带旋风分离器(TCS)和相关的重度降水在日本产生了很大的影响。本研究旨在了解每10分钟全天Himawari-8辐射的数据同化(DA)如何改善TC案例的定量降水预测(QPF)。作为第一步,本研究使用来自用于本地集合Kalman滤波器(Letkf)的高级文库和环境(比例)的可扩展计算,使用区域大气模型对Typhoon Malakas(2016)进行单一案例研究。结果表明,6公里处的全天Himawari-8 Radiance DA改善了Malakas的代表,如果适当地选择水平定位尺度,可以提供更准确的确定性和概率降水预测。

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