Abstract
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 Dm (mass-weighted mean diameter) and minimum log10Nw (normalized intercept parameter), while rain shows the opposite. Additionally, the μ-Λ (shape parameter–slope parameter) curve of dry snow and wet snow is very close, and the μ value of dry snow and wet snow is higher than that of graupel and higher than that of rain for the same Λ value. Furthermore, the Ze-S (equivalent reflectivity factor–precipitation intensity) relationships among different types of precipitation are significantly different. If only the Ze-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.
Highlights
The accurate monitoring of solid precipitation is of great significance for aviation safety, transportation and freezing disaster prevention, especially in the middle and high latitudes [1,2,3].the study of the microphysical characteristics of solid precipitation contributes to the development of weather forecasts, remote sensing of precipitation, and hydrology [1,4,5,6]
The study of the microphysical characteristics of solid precipitation contributes to the development of weather forecasts, remote sensing of precipitation, and hydrology [1,4,5,6]
Ground-based or space-based electromagnetic propagation models are sensitive to the shape and density of solid precipitation particles, and a reasonable description of precipitation microphysical characteristics is essential to the inversion algorithm of precipitation intensity based on remote sensing [10,11,12]
Summary
The accurate monitoring of solid precipitation is of great significance for aviation safety, transportation and freezing disaster prevention, especially in the middle and high latitudes [1,2,3]. On the one hand, due to the great difference in the physical properties of different solid precipitation particles, it is still an urgent problem to invert solid precipitation by radar remote sensing [18,19,20], but on the other hand, the data collected by previous researchers were mostly limited by quantity; their statistical significance has yet be further verified, and experiments were rarely carried out in many regions of the world, such as East Asia. To improve the application level of remote sensing for solid precipitation in eastern China, this study analyzes the microphysical characteristics of rain, graupel, dry snow and wet snow by using 6 years of winter PARSIVEL (first generation) observation data in Nanjing.
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