Spatiotemporal Analysis of Hail Events in the Philippines

Abstract

Hailstorms are relatively rare in the Philippines, and as such, they remain understudied despite their potential to cause significant damage to agriculture and property. This study investigates the spatiotemporal characteristics of hail events across the Philippines from 2006 to 2024, identifying key seasonal, regional, and meteorological patterns. Most hail events occurred during the pre-Southwest Monsoon season (March-May), when conditions are favorable for localized convection. While Luzon accounted for the majority of reported hail events, larger hailstones (≥ 3 cm) were more frequently reported in the Visayas and Mindanao, where weaker monsoonal influence allows localized convective activity to persist into the later months of the year. Hail occurrences were also predominantly observed during the afternoon hours, consistent with peak diurnal heating and convective cycles. To better understand the local dynamics of hail formation in the Philippine setting, a detailed analysis was conducted on a significant hail event on 08 May 2020 in Cabiao, Nueva Ecija (15.2289° N, 120.8729° E). This event produced hailstones exceeding 4 cm in diameter and is the largest documented in this study. Satellite and radar observations revealed deep convection with cloud tops exceeding 12 km over a ~ 40 km region. High reflectivity values (> 60 dBZ) and lightning flash densities confirmed the storm’s intensity. Numerical simulations using the Weather and Research Forecasting (WRF) model captured the spatiotemporal evolution of the hail event, with increasing instability, strong updrafts, and substantial surface moisture flux convergence. Microphysical analysis indicated dominant hail and graupel mixing ratios at mid-levels. Hydrometeor vertical profiles emphasized the critical role of mixed-phase processes in hail development. This work presents the first hailstorm simulation in the Philippines using the WRF model and offers new insights into hailstorm dynamics in tropical environments, supporting future improvements in local hail detection and forecasting.