Statistical errors of rain rate estimators due to natural variations in raindrop size distribution (DSD) are studied for 3-cm wavelength polarimetric radar. Four types of estimators are examined: A classical estimator RðZ H Þ, and three types of polarimetric radar estimators RðK DP Þ, RðZ H ; Z DR Þ, and RðK DP ; Z DR Þ, where R is the rain rate, Z H is the reflectivity factor at horizontal polarization, K DP is the specific differential phase, and Z DR is the differential reflectivity. The T-matrix method is employed for the scattering calculations, and a total of 7,664 one-minute raindrop size spectra, measured with a Joss-Waldvogel type disdrometer are used.According to simulation results, the normalized errors (NEs) of RðZ H Þ, RðK DP Þ, RðK DP ; Z DR Þ, and RðZ H ; Z DR Þ for all DSD samples are 25%, 14%, 9%, and 10%, respectively. The NEs of all estimators, except RðZ H Þ, tend to decrease with increasing rain rate. For rain rates larger than 10 mmh À1 , e.g., the average NEs of RðZ H Þ, RðK DP Þ, RðK DP ; Z DR Þ, and RðZ H ; Z DR Þ are 25%, 9%, 5%, and 7%, respectively. The simulation results show that the classical estimator RðZ H Þ is the most sensitive to variations in DSD and the estimator RðK DP ; Z DR Þ is the least sensitive.The lowest sensitivity of the rain estimator RðK DP ; Z DR Þ to variations in DSD can be explained by the following facts. The difference in the forward-scattering amplitudes at horizontal and vertical polarizations, which contributes K DP , is proportional to the 4.78th power of the drop diameter. On the other hand, the exponent of the backscatter cross section, which contributes to Z H , is proportional to the 6.38th power of the drop diameter. Because the rain rate R is proportional to the 3.67th power of the drop diameter, K DP is less sensitive to DSD variations than Z H . However, DSD spectra with unusually large median volume diameter D 0 can increase the estimation error of RðK DP Þ. The differential reflectivity Z DR reduces the effect of unusual D 0 and is useful for further improvement of the estimator RðK DP Þ. This is due to the fact that Z DR itself is a good measure of D 0 .

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.