[p1] Multi-scale and multi-component treatments


[p1-19]

Impacts of the surface observations on predicting torrential rainfalls on September 9, 2015 around Tochigi and Ibaraki prefectures

Y. Maejima (RIKEN), and T. Miyoshi (RIKEN)

 
Abstract

To investigate the impact of the surface observations on a severe rainfall event occurred on September 9, 2015 around Tochigi and Ibaraki prefectures, we perform a series of data assimilation (DA) experiments using the Local Ensemble Transform Kalman Filter (LETKF) with the SCALE regional NWP model (Nishizawa et al. 2015). In this event, an active rainband was maintained for an extended period and caused torrential rainfalls over 500 mm/day with catastrophic flooding.
Two DA experiments were performed: the control experiment (CTRL) at 4-km resolution with only conventional observations (NCEP PREPBUFR), and the other with additional surface observation data with every minute (TEST). CTRL showed generally similar rainfall patterns, although the intensity was smaller, and rainfall area was shifted westward compared to the JMA analyzed precipitation based on the radar and gauge networks. By contrast, TEST showed stronger rainfall intensity, better matching with the JMA analyzed precipitation. Surface DA contributed to improve the moisture field in the lower layer, leading to intensified rainfall amount. The results suggest that the surface DA have a potential to improve the forecast accuracy for severe rainfall events.