Investigating the quality of radar composites in a mountainous region in northeastern Thailand

Composite radar products are made by combining radar scans of multiple radar stations into a single product to improve the quality of the radar product in overlapping region and to visualize the distribution and movement of precipitation over a large area. The reliability of radar composites depends on radar data quality, as each radar measurement is influenced by, among others, atmospheric conditions, interference with other sources, and the radar specifications. The quality of rain radar composites is critical as these products will be used for near real-time forecasting of hydrometeorological hazards. This research aims to investigate the controlling factors influencing the quality of radar composites over a hazard-prone mountainous region in northeastern Thailand. In this study we evaluate and quantify the rain radar composites by looking at four quality indexes among the distance to the radar station (DTR), the height of the beam above the ground (HTG), the radar beam blockage fraction (BBF), and the radar reflectivity fraction between the composited radar stations (RRF). For our overarching research to build a near real-time forecasting system for landslide and flashflood warnings in the Khao Yai National Park, Lamtakong basin and surroundings. Hereto, local cells of high intensity precipitation should be derived with highest accuracy. Two rain radar stations were selected: Sattahip, 220 kilometer southwest and Phimai, 140 kilometer North of the Lamtakong basin. Automatic rain gauges in the overlapping area were used to evaluate the radar composite product during storm events in 2020. The results indicated that specific quality indexes could be used to identify areas with inaccurate or unreliable raw data. This was a particular advantage in areas where the radar beam was (partly) blocked by an obstacle and underestimated the intensity of the storm. The BBF was the most important quality index in the study area. Moreover, combining the BBF with the RRF could increase the accuracy and reliability of radar rainfall estimates. Overall, using radar composites with raw radar data quality control can play an essential role in improving near real-time nowcasting for further natural hazard mitigation in the mountainous area.