The Global Precipitation Measurement (GPM) Core Observatory will carry a Dual-frequency Precipitation Radar (DPR) consisting of a Ku-band precipitation radar (KuPR) and a Ka-band precipitation radar (KaPR). In this study, "at-launch" codes of DPR precipitation algorithms, which will be used in GPM ground systems at launch, were evaluated using synthetic data based upon the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) data. Results from the codes (Version 4.20131010) of the KuPR-only, KaPR-only, and DPR algorithms were compared with "true values" calculated based upon drop size distributions assumed in the synthetic data and standard results from the TRMM algorithms at an altitude of 2 km over the ocean.The results indicate that the total precipitation amounts during April 2011 from the KuPR and DPR algorithms are similar to the true values, whereas the estimates from the KaPR data are underestimated. Moreover, the DPR estimates yielded smaller precipitation rates for rates less than about 10 mm/h and greater precipitation rates above 10 mm/h. Underestimation of the KaPR estimates was analyzed in terms of measured radar reflectivity ( ) of the KaPR at an altitude of 2 km. The underestimation of the KaPR data was most pronounced during strong precipitation events of < (high attenuation cases) over heavy precipitation areas in the Tropics, whereas the underestimation was less pronounced when the > 26 (moderate attenuation cases). The results suggest that the underestimation is caused by a problem in the attenuation correction method, which was verified by the improved codes.

To quantitatively evaluate how different methods for creating 5 km mesh Radar/Raingauge-Analyzed Precipitation (R/A) affected annual precipitation, we compared three kinds of 5 km mesh R/A during 1991-2009 by devoting attention to the modification of its spatial resolution. It was,

This study investigated the spatial distribution of heavy rainfall that enhanced the occurrence of potential landslide hazards throughout Japan during the period 2001-2008, using the Soil Water Index (SWI). We calculated SWI using a tank model, with Radar/Raingauge-Analyzed Precipitation for the period 1991-2008 as input data provided by the Japan Meteorological Agency. The SWI can represent and elucidate the conceptual soil water contents during a rainfall-event associated with the shallow landslide initiation. Comparing the SWI of the present rainfall event with the upper level record of SWI during the past decade, we can evaluate the occurrence of potential landslide hazards at a location during rainfall. For this research, by comparing the SWI for the past decade, we defined the top 3 heavy rainfall events that raised the SWI, enhancing the occurrence of potential landslide hazards. We then calculated the frequency of such rainfall events. The results showed regional differences of heavy rainfall frequency that raised the SWI during the last 8 years.

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