Improvement of Passive Microwave Rainfall Retrieval Algorithm over Mountainous Terrain

Abstract:

The microwave radiometer (MWR) algorithms underestimate heavy rainfall associated with shallow orographic rainfall systems owing to weak ice scattering signatures. Underestimation of the Global Satellite Mapping of Precipitation (GSMaP) MWR has been mitigated by an orographic/nonorographic rainfall classification scheme (Shige et al. 2013, 2015; Taniguchi et al. 2013; Yamamoto and Shige 2015). The orographic/nonorographic rainfall classification scheme is developed on the basis of orographically forced upward vertical motion and the convergence of surface moisture flux estimated from ancillary data. Lookup tables derived from orographic precipitation profiles are used to estimate rainfall for an orographic rainfall pixel, whereas those derived from original precipitation profiles are used to estimate rainfall for a nonorographic rainfall pixel.

The orographic/nonorographic rainfall classification scheme has been used by the version of GSMaP products, which are available in near real time (about 4 h after observation) via the Internet (http://sharaku.eorc.jaxa.jp/GSMaP/index.htm). The current version of GSMaP MWR algorithm with the orographic/nonorographic rainfall classification scheme improves rainfall estimation over the entire tropical region, but there is still room for improvement. In this talk, further improvement of orographic rainfall retrievals will be shown.