This study aims to investigate the impacts of 30-secondupdate and 100-m-resolution data assimilation (DA) on a prediction of sudden local torrential rains caused by an isolated convective system in Kobe city on 11 September 2014. We perform a Local Ensemble Transform Kalman filter (LETKF) experiment with the Japan Meteorological Agency non-hydrostatic model (JMA-NHM) at 1-km and 100-m resolution using every-30-second radar reflectivity observed by the phased array weather radar (PAWR) at Osaka University. The 1-km-mesh experiment shows that 30-second-update PAWR DA has positive impacts on the analyses and forecasts. Moreover, the 100-m-mesh experiment shows significant advantages in representing the rainfall intensity and fine structure of the convective system. The promising results suggest that 30-second-update, 100-m-mesh DA have a great potential for predicting sudden local rain events.(Citation: Maejima, Y., M. Kunii, and T. Miyoshi, 2017: 30-second-update 100-m-mesh data assimilation experiments: A sudden local rain case in Kobe on 11 September 2014. SOLA, 13, 174−180, doi:10.2151/sola.2017-032.)
IntroductionIn modern numerical weather prediction (NWP), improvement for predicting hazardous phenomena is one of the central issues. Among others, much attention has been paid to skillful NWP for severe weather (e.g., Kain et al. 2006, Hohenegger and Schär 2007a, b;Kawabata et al. 2007;Roberts and Lean 2008). Recently, the ensemble Kalman filter (EnKF;Evensen 1994Evensen , 2003 has become a major method in data assimilation (DA), and has contributed to investigate convection-permitting regional NWP (e.g., Zhang et al. 2007;Stensrud et al. 2009Stensrud et al. , 2013Clark et al. 2010;Schwartz et al. 2010; Baldauf et al. 2011;Melhauser and Zhang 2012; Yussolf et al. 2013, Kunii 2014a, Weng and Zhang 2016.Recently, Miyoshi et al. (2016aMiyoshi et al. ( , 2016b reported an innovation of the "Big Data Assimilation" (BDA) technology, implementing a 30-second-update, 100-m-mesh local ensemble transform Kalman filter (LETKF;Hunt et al. 2007) to assimilate data from a Phased Array Weather Radar (PAWR) at Osaka University (Ushio et al. 2014) into regional NWP models known as the Japan Meteorological Agency non-hydrostatic model (JMA-NHM, Saito et al. 2006Saito et al. , 2007 and the Scalable Computing for Advanced Library and Environment-Regional Model (SCALE-RM, Nishizawa et al. 2015). The PAWR captures the rapid development of convective activities every 30 seconds at approximately 100-m resolution. The 100-m-mesh NWP models can resolve the internal structures of convective cells. The BDA system combines these two to enable NWP resolving each cumulonimbus explicitly.This study provides details of a case study shown in the review paper by Miyoshi et al. (2016b) and aims to investigate the benefits of the BDA system for predicting an isolated convective system. We apply the BDA system described by Miyoshi et al. (2016aMiyoshi et al. ( , 2016b for a sudden local severe rainstorm that occurred in the morning of 1...