Raindrop size distributions (DSDs) are the microphysical characteristics of raindrop spectra. Rainfall characterization is important to: (1) provide information on extreme rate, thus, it has an impact on rainfall related hazard; (2) provide data for indirect observation, model and forecast; (3) calibrate and validate the parameters in radar reflectivity-rainfall intensity (Z-R) relationships (quantitative estimate precipitation, QPE) and the mechanism of precipitation erosivity. In this study, the one-year datasets of raindrop spectra were measured by an OTT Parsivel-2 Disdrometer placed in Yulin, Shaanxi Province, China. At the same time, four TE525MM Gauges were also used in the same location to check the disdrometer-measured rainfall data. The theoretical formula of raindrop kinetic energy-rainfall intensity (KE-R) relationships was derived based on the DSDs to characterize the impact of precipitation characteristics and environmental conditions on KE-R relationships in semi-arid areas. In addition, seasonal rainfall intensity curves observed by the disdrometer of the area with application to erosion were characterized and estimated. The results showed that after quality control (QC), the frequencies of raindrop spectra data in different seasons varied, and rainfalls with R within 0.5-5 mm/h accounted for the largest proportion of rainfalls in each season. The parameters in Z-R relationships (Z = aRb) were different for rainfall events of different seasons (a varies from 78.3-119.0, and b from 1.8-2.1), and the calculated KE-R relationships satisfied the form of power function KE = ARm, in which A and m are parameters derived from rainfall shape factor μ. The sensitivity analysis of parameter A with μ demonstrated the applicability of the KE-R formula to different precipitation processes in the Yulin area.
CITATION STYLE
Xie, Z., Yang, H., Lv, H., & Hu, Q. (2020). Seasonal characteristics of disdrometer-observed raindrop size distributions and their applications on radar calibration and erosion mechanism in a semi-arid area of China. Remote Sensing, 12(2). https://doi.org/10.3390/rs12020262
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