[A-CG37] Satellite Earth Environment Observation

[ACG37-09] Evaluation of cloud microphysics scheme using ground-based micro-rain radar in senjo-kousuitai event

*Yasutaka Ikuta¹ (1.Meteorological Research Institute)

Keywords:Radar, Cloud microphysics scheme, Senjo-kousuitai

In Japan, the precipitation from ‘senjo-kousuitai’ has caused enormous meteorological disasters such as floods and landslides. To mitigate the damage caused by these disasters, improving the forecast accuracy of the senjo-kosuitai is necessary. The accuracy of precipitation forecasts depends on the performance of cloud microphysics schemes in the numerical weather prediction model. In order to confirm the performance of the cloud microphysics scheme, we tried to evaluate the cloud microphysics scheme using a vertical pointing micro-rain radar (24.2 GHz) and a disdrometer. The micro-rain radar and the disdrometer are operated by JAXA's GPM ground validation. The numerical weather prediction model under evaluation is the JMA non-hydrostatic model ASUCA, and the cloud microphysics scheme of ASUCA is the single-moment bulk scheme. In order to compare observed and simulated reflectivity, the micro-rain radar reflectivity is simulated based on the assumptions of the cloud microphysics scheme. The scattering coefficients in the reflectivity simulation are calculated by the T-matrix method. For comparison with the disdrometer observations, the particle size distribution of raindrops in the model was also calculated based on the assumptions of the cloud microphysics scheme. In this study, sensitivity experiments of the cloud microphysics scheme were conducted for a senjo-kosuitai case study and validated using the micro-rain radar and the disdrometer. We compared schemes with inverse exponential raindrop size distributions with those with bimodal raindrop size distributions. For the inverse-exponential type, the simulated reflectivities were larger than the observed values, while for the bimodal type, the overestimation was reduced. Thus, micro-rain radar provides important information, but because it is a fixed-point observation, even a slight deviation of the precipitation forecast location from the actual precipitation location lead to apparently large errors. In my presentation, I would like to introduce the results and issues of the evaluation using micro-rain radar and a disdrometer.