This paper documents the production and validation of retrieved rainfall data obtained from satellite-borne microwave radiometers by the Global Satellite Mapping of Precipitation (GSMaP) Project. Using various attributes of precipitation derived from Tropical Rainfall Measuring Mission (TRMM) satellite data, the GSMaP has implemented hydrometeor profiles derived from Precipitation Radar (PR), statistical rain/no-rain classification, and scattering algorithms using polarization-corrected temperatures (PCTs) at 85.5 and 37 GHz. Combined scattering-based surface rainfalls are computed depending on rainfall intensities. PCT85 is not used for stronger rainfalls, because strong depressions of PCT85 are related to tall precipitation-top heights. Therefore, for stronger rainfalls, PCT37 is used, with PCT85 used for weaker rainfalls. With the suspiciously strong rainfalls retrieved from PCT85 deleted, the combined rainfalls correspond well to the PR rain rates over land. The GSMaP algorithm for the TRMM Microwave Imager (TMI) is validated using the TRMM PR, ground radar [Kwajalein (KWAJ) radar and COBRA], and Radar Automated Meteorological Data Acquisition System (AMeDAS) precipitation analysis (RA). Monthly surface rainfalls retrieved from six microwave radiometers (GSMaP_MWR) are compared with the gauge-based dataset. Rain rates retrieved from the TMI (GSMaP_TMI) are in better agreement with the PR estimates over land everywhere except over tropical Africa in the boreal summer. Validation results of the KWAJ radar and COBRA show a good linear relationship for instantaneous rainfall rates, while validation around Japan using the RA shows a good relationship in the warm season. Poor results, connected to weakprecipitation cases, are found in the cold season around Japan.

In this paper, the attenuation-correction methodology presented in Part I is applied to radar measurements observed by the multiparameter radar at the X-band wavelength (MP-X) of the National Research Institute for Earth Science and Disaster Prevention (NIED), and is evaluated by comparison with scattering simulations using ground-based disdrometer data. Further, effects of attenuation on the estimation of rainfall amounts and drop size distribution parameters are also investigated. The joint variability of the corrected reflectivity and differential reflectivity show good agreement with scattering simulations. In addition, specific attenuation and differential attenuation, which are derived in the correction procedure, show good agreement with scattering simulations. In addition, a composite rainfall-rate algorithm is proposed and evaluated by comparison with eight gauges. The radar-rainfall estimates from the uncorrected (or observed) Z H produce severe underestimation, even at short ranges from the radar and for stratiform rain events. On the contrary, the reflectivity-based rainfall estimates from the attenuation-corrected Z H does not show such severe underestimation and does show better agreement with rain gauge measurements. More accurate rainfall amounts can be obtained from a simple composite algorithm based on specific differential phase K DP , with the R(Z H _cor) estimates being used for low rainfall rates (K DP Յ 0.3°km Ϫ1 or Z H _cor Յ 35 dBZ ). This improvement in accuracy of rainfall estimation based on K DP is a result of the insensitivity of the rainfall algorithm to natural variations of drop size distributions (DSDs). The Z H , Z DR , and K DP data are also used to infer the parameters (median volume diameter D 0 and normalized intercept parameter N w ) of a normalized gamma DSD. The retrieval of D 0 and N w from the corrected radar data show good agreement with those from disdrometer data in terms of the respective relative frequency histograms. The results of this study demonstrate that high-quality hydrometeorological information on rain events such as rainfall amounts and DSDs can be derived from X-band polarimetric radars.

In this paper, the attenuation-correction methodology presented in Part I is applied to radar measurements observed by the multiparameter radar at the X-band wavelength (MP-X) of the National Research Institute for Earth Science and Disaster Prevention (NIED), and is evaluated by comparison with scattering simulations using ground-based disdrometer data. Further, effects of attenuation on the estimation of rainfall amounts and drop size distribution parameters are also investigated. The joint variability of the corrected reflectivity and differential reflectivity show good agreement with scattering simulations. In addition, specific attenuation and differential attenuation, which are derived in the correction procedure, show good agreement with scattering simulations. In addition, a composite rainfall-rate algorithm is proposed and evaluated by comparison with eight gauges. The radar-rainfall estimates from the uncorrected (or observed) ZH produce severe underestimation, even at short ranges from the radar and for stratiform rain events. On the contrary, the reflectivity-based rainfall estimates from the attenuation-corrected ZH does not show such severe underestimation and does show better agreement with rain gauge measurements. More accurate rainfall amounts can be obtained from a simple composite algorithm based on specific differential phase KDP, with the R(ZH_cor) estimates being used for low rainfall rates (KDP ≤ 0.3° km−1 or ZH_cor ≤ 35 dBZ). This improvement in accuracy of rainfall estimation based on KDP is a result of the insensitivity of the rainfall algorithm to natural variations of drop size distributions (DSDs). The ZH, ZDR, and KDP data are also used to infer the parameters (median volume diameter D0 and normalized intercept parameter Nw) of a normalized gamma DSD. The retrieval of D0 and Nw from the corrected radar data show good agreement with those from disdrometer data in terms of the respective relative frequency histograms. The results of this study demonstrate that high-quality hydrometeorological information on rain events such as rainfall amounts and DSDs can be derived from X-band polarimetric radars.

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A classification of snow clouds, called the "snowfall mode," is proposed based on Doppler radar observations at 10-minute intervals at Nagaoka in 1999/2000 winter season. Using 795 hours of data at an altitude of 1.6 km, six snowfall modes were defined: longitudinal line (Lmode), transversal line (T-mode), spreading precipitation (S-mode), meso-scale vortex (V-mode), mountainslope precipitation (M-mode), and local-frontal (discontinuity) band (D-mode). In migrating snow clouds, a subclass, referred to as snowfall with coastal intensification (xI-mode, where x is L, T, S and V) was defined. A sample snapshot and the mean Ze are shown for each snowfall mode. The frequency of occurrence of the snowfall modes indicated that both of the longitudinal cloud streets and the mesoscale disturbances occupied about 1/3 of the analysis period. About 18% of the precipitation in the analysis period was considered to be under orographic effects. The prevailing wind direction differed between the snowfall modes although a west-northwesterly wind dominated. IntroductionSnow clouds developing over the Sea of Japan generate a wide variety of radar echo patterns, which suggests that there are a number of mechanisms involved in the development of snow clouds. In the 1970s, some classifications of snow clouds were made using conventional radars (e.g., Nanasawa 1975). However, their time resolution was low that the motion and duration of the specific patterns were not analyzed. Since then, many theoretical and observational case studies have been conducted. There are several wellknown structures of snow clouds. Longitudinal (Lmode) snowbands often correspond to "cloud streets" that appear during cold outbreaks. The structure of the transversal (T-mode) snowbands was recently elucidated (Murakami et al. 2002). Vortex disturbances often appear around the Japan Sea Polar-Airmass Convergence Zone (JPCZ) (Asai 1988; Tsuboki and Asai 2004). They were also observed as radar echoes (e.g., Asai and Miura 1981). Moreover, land breezes contribute to the formation of snowbands and significantly affect the snowfall (e.g., Ishihara et al. 1989;Ohigashi and Tsuboki 2005).Thus, various structure and development processes of the snow clouds have been analyzed. However, systematic morphological terminology has not been established, and the frequency of occurrence has not been thoroughly analyzed.The Nagaoka Institute of Snow and Ice Studies (NISIS) locates in the central part of the Niigata Prefecture (Fig. 1). The NISIS makes it possible to observe snow clouds throughout the winter season. In this paper, we propose a classification of snow clouds or "snowfall modes" based on Doppler radar winter observations. ObservationAn X-band Doppler radar, X-POL (Iwanami et al. 1996), was set up on the roof of the NISIS. The observation area was a northwestern-side semicircle with a radius of 64 km. The radar operation consisted of 15 steps of a PPI scan, repeated at about 10-minute intervals. Three-dimensional distributions of the equivalent radar reflect...

Three-year semi-operational observations of rainfall distributions with NIED X-band multiparameter (or polarimetric) radar started in the Kanto area of Japan from July 2003. The purposes and outlines of the radar observations with networks of rain gauges and disdrometers for ground validations are described. Preliminary results of validation analysis of polarimetric rain rate estimators show the usefulness of X-band multi-parameter radar for hydrological and meteorological applications in a small area.

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