Rain retrieval algorithms from satellite-borne microwave radiometers (MWR) utilize lookup tables (LUTs) related
between MWR brightness temperatures (Tbs) and rain intensity and databases about precipitation characteristics. Since
LUT is generated to simulate Tbs from vertical rain profiles through a radiative transfer model, the accuracy of
estimation in precipitation amount depends on the input vertical rain profiles. Some previous studies reported that
underestimation of precipitation occurred for generated or reinforced rain systems by orography and over high elevation
area. In order to improve the underestimation, orographic precipitation identification was applied to the Global Satellite
Mapping of Precipitation (GSMaP) algorithm.
Upward wind by topography and moisture convergence at near the surface calculated by a re-analysis data and a digital
elevation map were utilized to identify areas in orographic precipitation, and a new LUT based on a warm rain case was
constructed and applied to the GSMaP algorithm. In addition to the case, we examined representative vertical profiles in
precipitation for above mentioned precipitation characteristics. Compared to the standard GSMaP product, clear
improvement can be found for a orographic precipitation case affected by a typhoon in Taiwan.