Dual-Polarization Radar-Based Quantitative Precipitation Estimation of Mountain Terrain Using Multi-Disdrometer Data

Abstract

The precipitation systems that pass over mountains develop rapidly due to the forcible ascent caused by the topography, and spatial rainfall distribution differences occur due to the local development of the system because of the topography. In order to reduce the damage caused by orographic rainfall, it is essential to provide rainfall field data with high spatial rainfall accuracy. In this study, the rainfall estimation relationship was calculated using drop size distribution data obtained from 10 Parsivel disdrometers that were installed along the long axis of Mt. Halla (oriented west–east; height: 1950 m; width: 78 km; length: 35 km) on Jeju Island, South Korea. An ensemble rainfall estimation relationship was obtained using the HSA (harmony search algorithm). Through the linear combination of the rainfall estimation relationships determined by the HSA, the weight values of each relationship for each rainfall intensity were optimized. The relationships considering KDP, such as R(KDP) and R(ZDR, KDP), had higher weight values at rain rates that were more than 10 mm h−1. Otherwise, the R(ZH) and R(ZH, ZDR) weights, not considering KDP, were predominant at rain rates weaker than 5 mm h−1. The ensemble rainfall estimation method was more accurate than the rainfall that was estimated through an independent relationship. To generate the rain field that reflected the differences in the rainfall distribution according to terrain altitude and location, the spatial correction value was calculated by comparing the rainfall obtained from the dual-polarization radar and AWS observations. The distribution of Mt. Halla’s rainfall correction values showed a sharp difference according to the changes in the topographical elevation. As a result, it was possible to calculate the optimal rain field for the orographic rainfall through the ensemble of rainfall relationships and the spatial rainfall correction process. Using the proposed methodology, it is possible to create a rain field that reflects the regional developmental characteristics of precipitation.

Keywords

• quantitative precipitation estimation
• dual-polarization radar
• disdrometer
• orographic precipitation
• spatial bias correction
• heuristic optimization algorithm