The rain/no-rain threshold value of cloud liquid water (CLW) is important for the microwave precipitation retrieval
algorithms. In our previous study, we proposed a parameterization of rain/no-rain threshold value of CLW as a function
of storm height for Global Satellite Mapping of Precipitation (GSMaP) algorithm. In this study, we determine rain/norain
threshold value of CLW using CloudSat precipitation product and the cloud liquid water derived from Aqua/AMSRE.
The threshold values of CLW from CloudSat precipitation product are lower than 0.5 kg m-2 for GSMaP over all
regions. The threshold value of CLW is found at its peak in the Tropics and decreases poleward. The threshold value of
cloud liquid water contents computed from threshold value of CLW divided by the zonal mean storm height from
PR3A25 is employed on the parameterization of threshold value of CLW. The result shows that GSMaP with new
parameterization can detect the shallow rain observed by CloudSat.
An over-ocean precipitation retrieval algorithm is developed to retrieve precipitation for the Baiu period from brightness temperatures (TB's) supplied by the TRMM Microwave Imager (TMI). The basic idea of the algorithm is to find the optimal precipitation that gives radiative transfer model (RTM)-calculated, field-of-view (FOV)- averaged TB's that fit best with the TMI TB's at 10.7, 19.7, and 85.5 GHz with vertical polarization. For the RTM calculation, spatial precipitation inhomogeneity and freezing level height are estimated from TMI TB's. The optimal precipitation with 10 km resolution is obtained by solving the gradient equation of a cost function that is a weighted sum of squares of TB differences between the TMI observation and the RTM calculation. Precipitation retrieved by this algorithm was validated using TRMM Precipitation Radar (PR) data from the western part of Japan during June-July of 1998. The results indicate: 1) Meso- scale (approximately 100 km) structures of precipitation disturbances were retrieved successfully with the algorithm. However, there were discrepancies in position and strength of individual rain cells between the precipitation retrievals and PR data. 2) Precipitation retrieved by the algorithm agreed well with PR data within the precipitation range of 1-25 mm/hr, irrespective of precipitation type.
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