Statistical Analysis of Radar-based Quantitative Precipitation Estimation over Complex terrain in Korea and Development of User-oriented Services for Mountainous Regions

Complex terrain is often characterized by mechanical sources, which force the initiation of convection in unstable atmospheric conditions, resulting in severe weather such as thunderstorms and hail, etc. With respect to the synoptic prevailing wind, the terrain can also cause heavy precipitation by converging flow and stationary rain bands. Rain gauges can provide a direct measure of accurate precipitation at a point station. However, low accessibility and high maintenance costs limit the ability to install high-resolution rain gauge networks in mountainous regions. Thus, quantitative precipitation estimation (QPE) through remote sensing using weather radar plays an important role in securing observation information on rainfall amounts in mountainous areas. 
In this study, we first analyzed the statistics of hazardous weather events retrieved from radar-based rainfall estimates over the Korean Peninsula according to complex topography. In order to analyze the frequency of occurrence of each type of hazardous weather such as torrential rain, hail, and snowfall according to orographic conditions, we used radar-based QPE. We investigated the correlation between topographic characteristics such as terrain altitude, wind direction, and downwind side and the frequency of occurrence and development of hazardous weather phenomena. 
We also examined the accuracy of QPE relating to rainfall mechanisms including radar echo top height for each warm and cold season. We analyzed the accuracy of QPEs according to various methods using radar reflectivity, dual-polarization parameters, and radar attenuation. We analyzed precipitation estimation error factors that may be caused by terrain shielding and high radar beam height in mountainous areas. We explored QPE errors based on radar beam height and echo intensity to improve the accuracy of QPE. 
Furthermore, in order to provide hazardous weather information specialized for the mountainous region, we have planned to develop an algorithm to estimate the probability of severe weather due to topographic characteristics by merging terrain altitude, atmospheric instability, and radar echo intensity by calculating Froude number using radar-based three-dimensional wind (Wind Synthesis System using Doppler Measurements, WISSDOM). In conjunction with the technology for calculating stationary precipitation information using radar echo image processing techniques, we aim to strengthen the ability to respond to dangerous weather by providing information on possible areas of heavy rain, snowfall, and extreme wind due to complex terrain.