Gaoyuan qixiang (Aug 2024)
Impact of Satellite Microwave Hygrometer Data Assimilation on the Yarlung Zangbo Grand Canyon Area Heavy Rain Simulation
Abstract
This study uses the Weather Research Forecast Model （WRF） numerical forecast system and the Three-Dimensional Variational Data Assimilation （WRF-DA） system to investigate the impact of assimilating data from the Micro-Wave Humidity Sounder 2 （MWHS-2） onboard FY-3C and the Microwave Humidity Sounder （MHS） from NOAA-19 （National Oceanic and Atmospheric Administration-19） on the simulation and prediction of heavy rainfall events in the Yarlung Zangbo Grand Canyon.Three assimilation schemes are compared： the control （Con） scheme， the NOAA-19 scheme （MHS） and the FY-3C scheme （MWHS-2）.The results indicate that assimilation of MHS and MWHS-2 microwave radiance data using WRF-3DVAR （Three-Dimensional Variation） improves the simulation performance compared to the Con experiment.It improves the accuracy of the precipitation location， although the MWHS-2 experiment shows a northern bias in the precipitation area.Satellite data assimilation significantly improves the moisture field， but its effect on heavy rain intensity is less pronounced than its effect on precipitation area improvement.Data assimilation enhances the 700 hPa meridional wind component， leading to increased moisture transport within the study area.With respect to temperature， the assimilation of satellite microwave moisture data has a moderately positive effect， which forming an unstable vertical temperature structure in the 700~400 hPa layer， conducive to the generation and development of precipitation.Overall， the simulation results of the MHS experiment outperform those of MWHS-2， especially in the wind field， temperature and humidity fields.In addition， the root mean square error changes in the 24-hour forecast of the MWHS-2 experiment are relatively stable， indicating that MWHS-2 satellite data are more advantageous for medium to long-term simulation studies.
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