[A-AS03] Extreme Events and Mesoscale Weather: Observations and Modeling

[AAS03-P01] Predictability of a line-shaped heavy precipitation event in early July 2023 revealed by an ensemble forecast

*Takumi Honda¹, Kozo OKAMOTO², Eigo Tochimoto² (1.Information Technology Center, The University of Tokyo, 2.Meteorological Research Institute)

Keywords:Predictability, Line-shaped precipitation system, Ensemble forecast

In Japan, quasi-stationary line-shaped precipitation systems often cause severe disasters. Accurate prediction of such systems requires understanding the underlying processes that affect predictability. In particular, analyzing ensembles of predictions would provide valuable insights into how small differences result in significant variations in predicted precipitation among ensemble members. This study aims to investigate predictability of a line-shaped heavy precipitation event in early July 2023 using an ensemble forecast. During this event, a cloud system developed west of Kyushu Island, moved eastward, and caused substantial precipitation in the northern Kyushu area. To better capture this cloud system in the initial conditions, this study assimilates all-sky brightness temperature observations from Himawari-9. The assimilation clearly improves the representation of cloud patterns and the accuracy of precipitation ensemble forecasts. We will analyze this improved ensemble forecast to identify key characteristics associated with the predictability of this heavy precipitation event.