12:15 PM - 12:30 PM
[AAS02-02] Assimilation of rainwater estimated by a polarimetric radar for tornado outbreaks on 6 May 2012
Keywords:tornado, data assimilation, ensemble Kalman filter, polarimetric radar, surface observation
In LETKF-1 (horizontal grid interval: 15000 m), hourly operational observation data used in the Japan Meteorological Agency (JMA) operational meso-scale analysis were assimilated with 6 hours intervals. In LETKF-2 (horizontal grid interval: 1875 m), Doppler velocity observed by 4 radars and dense surface data (horizontal wind, temperature and relative humidity) observed by Automated Meteorological Data Acquisition System (AMeDAS) and Environmental Sensor Network (ESN) obtained every 10 minutes were assimilated with 1 hour intervals. In LETKF-3 (horizontal grid interval: 350 m), rainwater estimated from reflectivity and specific differential phase observed by MACS-POL radar as well as Doppler wind and surface data were assimilated with 10 minutes intervals. Using this LETKF-3 analysis at 12:30 JST as the initial condition, the extended forecast with the horizontal resolution of 50 m was performed. As a result, the simulated precipitation relating to the parent clouds of the tornadoes was stronger than that in the experiment without rainwater assimilation. In this case, assimilation of strong rain contributed to increase low-level water vapor in the LETKF-3 analysis through a positive correlation between amounts of low-level water vapor and rainwater. These results imply that the predictability of extreme weather may be improved by assimilating rainwater observations.
This work was supported in part by the research project "HPCI Strategic Program for Innovation Research Field 3" (ID: hp120282, hp130012, hp140220) and "Tokyo Metropolitan Area Convection Study for Extreme Weather Resilient Cities (TOMACS)". ESN data were from NTT DOCOMO INC. The extended forecast was performed by K-computer.