[MTT46-P10] Study of the Mechanisms of Severe Thunderstorm in Tokyo Metropolitan Area using High Frequent Assimilation of GNSS and Other Ground-based Observations
Keywords:Water vapor, Data assimilation, Localized heavy rainfall
Highly urbanized Tokyo metropolitan area is vulnerable to severe storms such as local torrential rainfall, thunder lightning and tornado. Recently, the number of days with thunderstorms has been increasing in Tokyo. Elucidation of the mechanism of extreme weather in Tokyo is urgent matter (Nakatani et al. 2013). To study the rolls of water vapor and wind for the rapid life-cycle (initiation, development and dissipation) of hazardous cumulus convection, we installed a mobile Raman-lidar (Sakai et al. 2018), a wind profiler, and five GNSS stations in and around Tokyo.
Using 3DVAR capability of WRF data assimilation system (WRFDA)(Barker et al. 2012) , three-dimensional atmospheric fields with 1 km horizontal resolution were produced at every 10min throughout the August 2017 and 2018. Background fields were produced by JMA nonhydrostatic model (NHM)(Saito et al. 2007). In addition to the observed data at these campaign observation instruments, Japan Meteorological Agency’s operational surface meteorological stations, wind-profiler stations and GNSS PWV derived at dense GNSS network of Geospatial Information Authority of Japan are assimilated. We confirmed that the reproduced atmospheric fields (Temperature, humidity, and wind) showed better agreement with observations of radiosonde, lidar derived water vapor mixing ratio, and wind-profiler than background fields at altitudes lower than 2 km. Assimilation of surface meteorological observations (atmospheric pressure, temperature, humidity and wind) introduced better agreement mainly at altitude lower than 0.5 km. Inclusion of GNSS derived PWV resulted better agreement of humidity at altitude higher than 0.5 km and inclusion of wind field from wind-profiler led better agreement of wind field.
We have investigated roles of water vapor for several local heavy rainfall events occurred in Tokyo in August 2017 and 2018 and found that convergence of water vapor flux at 0.5 km altitude had intensified prior to the occurrence of torrential precipitation. Statistical and quantitative results will be discussed at the symposium.
This study is supported by JSPS KAKENHI Grants 17H00852.
Using 3DVAR capability of WRF data assimilation system (WRFDA)(Barker et al. 2012) , three-dimensional atmospheric fields with 1 km horizontal resolution were produced at every 10min throughout the August 2017 and 2018. Background fields were produced by JMA nonhydrostatic model (NHM)(Saito et al. 2007). In addition to the observed data at these campaign observation instruments, Japan Meteorological Agency’s operational surface meteorological stations, wind-profiler stations and GNSS PWV derived at dense GNSS network of Geospatial Information Authority of Japan are assimilated. We confirmed that the reproduced atmospheric fields (Temperature, humidity, and wind) showed better agreement with observations of radiosonde, lidar derived water vapor mixing ratio, and wind-profiler than background fields at altitudes lower than 2 km. Assimilation of surface meteorological observations (atmospheric pressure, temperature, humidity and wind) introduced better agreement mainly at altitude lower than 0.5 km. Inclusion of GNSS derived PWV resulted better agreement of humidity at altitude higher than 0.5 km and inclusion of wind field from wind-profiler led better agreement of wind field.
We have investigated roles of water vapor for several local heavy rainfall events occurred in Tokyo in August 2017 and 2018 and found that convergence of water vapor flux at 0.5 km altitude had intensified prior to the occurrence of torrential precipitation. Statistical and quantitative results will be discussed at the symposium.
This study is supported by JSPS KAKENHI Grants 17H00852.