Spatial assessment of produced hailstorm maps in severely affected areas in Northern Thailand based on dual-polarimetric radar using the cloud computing platform Google Earth Engine

The objective of this study was to use dual-polarimetric radar data to create an hourly hail product, which would then be analyzed using Google Earth Engine (GEE), a cloud computing platform. We used ground-based weather radar from the Thailand Meteorological Department’s Chiang Rai station in the north of Thailand. Dual-polarimetric weather radar data were analyzed at 15-minute intervals with Python-based open-source radar libraries such as PyArt and Wradlib. Hydrometeor classification was conducted using simulated atmospheric sounding data obtained from ERA5 reanalysis data, which had been classified into ten classes between 17.00 and 20.00 Local Time. At a 2-kilometer altitude grid, similar hydrometeor types with comparable solid-state characteristics were collected and presented in CAPPI format. Furthermore, we used JavaScript programming to conduct a localized impact study of the hailstorm in GEE in order to prove the preliminary damage assessment concept by comprising sophisticated spatial overlays with land use data, urban regions, farmland, population data, and counts of roofed homes. The analysis results in GEE reveal the potential damaging area prone to hailstorm passage. This is the first attempt in Thailand to create an hourly hailstorm product and integrate it into the Geographic Information System (GIS) using GEE’s cloud-based platform. This invention can annually support local organizations in disaster monitoring, impact assessment, and adaptation to hail-related events.