Microphysical Characteristics of Winter Precipitation in Eastern China from 2014 to 2019

被引:8
|
作者
Pu, Kang [1 ]
Liu, Xichuan [1 ]
He, Hongbing [1 ]
Sun, Yu [2 ]
Hu, Shuai [1 ]
Wu, Yi [3 ]
机构
[1] Natl Univ Def Technol, Coll Meteorol & Oceanog, Nanjing 211101, Peoples R China
[2] Beijing Aerosp Control Ctr, Beijing 100094, Peoples R China
[3] China Meteorol Adm, Nanjing Meteorol Bur, Nanjing 210019, Peoples R China
基金
中国国家自然科学基金;
关键词
winter precipitation; particle size distribution; log(10)N(w)-D-m; mu-Lambda; Z(e)-S; RAINDROP SIZE DISTRIBUTION; RADAR REFLECTIVITY; STATISTICAL CHARACTERISTICS; RAINFALL EROSIVITY; FALL VELOCITY; RIMING DEGREE; SNOW; DISTRIBUTIONS; DISDROMETER; PHOTOGRAPHY;
D O I
10.3390/w12030920
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
To improve solid precipitation monitoring in the hydrology and meteorology field, 1-min precipitation data observed by the PARticle SIze VELocity (PARSIVEL) disdrometer in Nanjing, eastern China, from February 2014 to February 2019 for all days with solid precipitation, were used to study the microphysical characteristics of winter precipitation. In this study, the empirical V-D (velocity-diameter) relationships and observed surface temperature are used for matching precipitation types, and the precipitation data are divided into rain, graupel, wet snow and dry snow. The results show that dry snow and wet snow have maximum D-m (mass-weighted mean diameter) and minimum log(10)N(w) (normalized intercept parameter), while rain shows the opposite. Additionally, the mu-Lambda (shape parameter-slope parameter) curve of dry snow and wet snow is very close, and the mu value of dry snow and wet snow is higher than that of graupel and higher than that of rain for the same Lambda value. Furthermore, the Z(e)-S (equivalent reflectivity factor-precipitation intensity) relationships among different types of precipitation are significantly different. If only the Z(e)-S relationship of rain is used for quantitative precipitation estimation (QPE), then, for small precipitation intensity, solid precipitation will be overestimated, while, for large precipitation intensity, it will be underestimated.
引用
收藏
页数:16
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