理化学研究所 計算科学研究センター

メニュー
メニュー

第160回 第1部

第160回 第1部
日時: 2019年2月1日(金)、13:00 - 14:00
場所: R-CCS 6階講堂

・講演題目:Regional-scale data assimilation with Himawari-8 satellite radiances
・講演者:本田 匠(データ同化研究チーム)
※発表・スライド共に英語

講演要旨: 詳細を見る

In this talk, we review our achievement in regional-scale data assimilation with Himawari-8 satellite radiances. In July 2015, the Japan Meteorological Agency (JMA) started full operations of their new geostationary satellite “Himawari-8”, the first of a series of the third-generation geostationary meteorological satellites. Himawari-8 can produce high-resolution observations with 16 frequency bands every 10 minutes for full disk. To assimilate Himawari-8 radiances, we implemented a radiative transfer model into a regional-scale data assimilation system known as SCALE-LETKF, consists of the Scalable Computing for Advanced Library and Environment-Regional Model (SCALE-RM) and the Local Ensemble Transform Kalman Filter (LETKF). We assimilated all-sky every-10-minute infrared (IR) radiances from Himawari-8. The results showed that assimilating the every-10-minute Himawari-8 IR radiances improves the analyzed tropical cyclone (TC) structure and intensity forecasts. In another case in September 2015, the heavy precipitation forecasts are greatly improved by assimilating the Himawari-8 IR observations. We ran a rainfall-runoff model using the improved precipitation forecasts and found that assimilating the Himawari-8 observations frequently may give longer lead times in terms of the flood risk. We also show other case studies on a different TC case and the extremely-heavy precipitation event in July 2018.