Assimilating high-resolution winds from a Doppler lidar using an ensemble Kalman filter with lateral boundary adjustment

作者：Sawada Masahiro^*; Sakai Tsuyoshi; Iwasaki Toshiki; Seko Hiromu; Saito Kazuo; Miyoshi Takemasa

来源：Tellus Series A-dynamic Meteorology and Oceanography, 2015, 67(1): 1-13.

DOI：10.3402/tellusa.v67.23473

• lateral boundary
• data assimilation
• ensemble kalman filter
• doppler lidar
• nowcast and very-short-range forecast
• mesoscale model

Monitoring severe weather, including wind shear and clear air turbulence, is important for aviation safety. To provide accurate information for nowcasts and very short-range forecasts up to an hour, a rapid-update prediction system has been developed, with a particular focus on lateral boundary adjustment (LBA) using the local ensemble transform Kalman filter (LETKF). Due to the small forecast domain, limited-area forecasts are dominated by the lateral boundary conditions from coarse-resolution global forecasts. To effectively extend the forecast lead time for the small domain, a new LBA scheme using the LETKF has been developed and assessed with three sea-breeze front cases. Observing system simulation experiments for high-resolution winds from a simulated Doppler lidar were performed with the Japan Meteorological Agency Nonhydrostatic Mesoscale Model at a horizontal resolution of 400 m and 15-minute update cycle. The results indicate that the LBA improved the forecast significantly. In particular, the 1-hour wind-speed forecast with the LBA is as accurate as the 15-minute forecast without the LBA. The assimilation of Doppler lidar high-resolution wind data with the LBA is a promising approach for very short-range forecasts up to an hour with a small domain, such as for aviation weather.

• 出版日期2015
• 单位中国气象科学研究院; RIKEN