17:15 〜 19:15
[AAS05-P11] Toward investigation of the potential impact of the single Phased Array Weather Radar observation on a forecast for the July 2020 rainfall event
キーワード：データ同化、メソ気象学、数値天気予報
On 4 July 2020, southern Kumamoto area encountered record-breaking rainfalls which brought over 400 mm precipitation in a day. To investigate a impact of dense and frequent Phased Array Weather Radar (PAWR; Yoshikawa et al. 2013, Ushio et al. 2015) observation on the forecast of the rainfall event, Maejima et al. (2022) performed a series of observing system simulation experiments (OSSEs) with a 17-PAWR network by the local ensemble transform Kalman filter (LETKF; Hunt et al, 2007) with a regional numerical weather prediction (NWP) model known as the Scalable Computing for Advanced Library and Environment-Regional Model (SCALE-RM; Nishizawa et al. 2015) at 1-km resolution. In the study, assimilating the PAWR data improves the heavy rainfall prediction mainly up to 1-hour lead time. Following Maejima et al. (2022), this study performs another OSSE which investigates a potential impact of a single phased array weather radar (PAWR) located in Meshima island in East China Sea. This island is located on the upstream side of the intense rainband from the catastrophic disaster area. The nature run and the general settings of the OSSE come from Maejima et al. (2022), and every 30-seond synthetic radar reflectivity and radial wind within 60-km range are generated by the Nature run. This study will evaluate the impact of the PAWR observation on the upstream side of the intense rainband on a rainfall forecast around disaster area.