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这个IUM RMAPS-ST,全称是“Rapid-refresh Multiscale Analysis and Prediction System - Short Term”,我理解这个东西的着力点在Rapid refresh上,核心就是WRF,开发的都是外围的一些壳子,比如怎么设计热启动来满足快速更新,怎么同化雷达等资料获得更实时的初始场等。具体的物理过程应该是没有开发的。
RMAPS-ST is short for the Rapid-refresh Multi-scale Analysis and Prediction System—Short-term, which is a km-scale regional NWP system developed based on the Weather Research and Forecasting model (WRF) and WRF data assimilation (WRFDA). The latest RMAPS-ST has been updated with the version 4.1.2 of WRF.
There are 51 sigma vertical levels in the RMAPS-ST system. The top pressure of the model has been updated to 10 hPa. A set of physics parameterizations is configured for both domains of the system, including Thompson double moment microphysics, radiation schemes of RRTMG, Kain-Fritsch deep convection, and the scheme of ACM2 PBL. The boundary and initial conditions of the RMAPS-ST system are taken from ECMWF forecast products with the resolution of 0.25°. One important aspect of the RMAPS-ST system is its multi-source data assimilation and analysis. Various observation data preprocessed have been successfully used in the system, including conventional grounded-based synoptic (SYNOP) and sounding data, radiosonde observations (RAOB), aircraft meteorological data relay (AMDAR), pilot balloon system (PILOT), global positioning system derived zenith total delay (GPSZTD), meteorological terminal aviation routine weather report (METAR), ship-based (SHIP) and oceanographic buoys (BUOY) observations, and radar data. Radar data mainly includes radial velocity and reflectivity, which has been used in both 9-km and 3-km domains. Rapidly refreshing is another import aspect of the system. All kinds of these rich observations are assimilated into the system in 3-h cycling runs to provide optimal analysis.
来自https://www.mdpi.com/2072-4292/14/2/275 |
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