Bulletin of Glaciological Research
Online ISSN : 1884-8044
Print ISSN : 1345-3807
ISSN-L : 1345-3807
An improved snowfall monitoring system developed in central Niigata Prefecture, Japan(新潟県中越地域に展開した改良型の降雪監視システム)
Katsuya YAMASHITA(山下克也)Sento NAKAI(中井専人)Hiroki MOTOYOSHI(本吉弘岐)Masaaki ISHIZAKA(石坂雅昭)
ジャーナル フリー

2019 年 37S 巻 p. 21-30


Meteorological radars are important for quantitative precipitation estimation (QPE) as they can determine precipitation distribution with high spatiotemporal resolution. However, accurate QPE of solid precipitation remains challenging despite its importance. A precise QPE algorithm requires an appropriate radar reflectivity-precipitation rate (Ze-R) relationship corresponding to the precipitation type, assessment of the change in size and fall velocity of snow particles falling below the radar beam, and validation using accurate precipitation amounts at the surface. In order to address these requirements, the study established an improved snowfall monitoring system, named the Concentrated Snowfall Monitoring System (CSMS) in central Niigata Prefecture. The CSMS was composed of an X-band radar and six ground observation sites. Optical disdrometers were installed at all sites to classify the precipitation type and select the appropriate Ze-R relationship. Vertical profiles of the precipitation particles and thermodynamic environment below the radar beam were assessed using micro rain radars and microwave radiometers. Presently, the precipitation amounts measured using tipping-bucket gauges are underestimated due to wind induced and wetting losses. Therefore, high accuracy weighing gauges were installed at three sites to quantify the underestimation. The CSMS data was used to conduct a preliminary analysis of the heavy snowfall that occurred on January 24 and 25, 2016, in central Niigata Prefecture. The designed CSMS estimated the precipitation distribution and precipitation type successfully. The results indicate that the CSMS can potentially determine an appropriate Ze-R relationship, which can improve the estimation of precipitation rates and contribute to the improved QPE of solid precipitation.

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