Objective method for hailstorm forecasting over Dehradun, Uttarakhand, India

Abstract Hailstorms are severe mesoscale weather phenomena that cause extensive damage to life, livelihood and property. Its timely forecast is immensely important to reduce the damage to aviation, agriculture and allied sectors. This study investigates the synoptic, dynamic, and thermodynamic conditions responsible for hail in Dehradun, Uttarakhand, India during the winter & pre-monsoon seasons. Analysis of 16 hailstorm events during winter & pre-monsoon seasons of 2016 & 2017 revealed that strong vertical wind shear (≥ 10 knots/km between 925-500 hPa or 925–200 hPa) and Total Totals Index (TTI ≥ 46) are reliable predictors, accounting for 63% of the events. The remaining 37% of events occurred under weaker wind shear but with elevated TTI (≥ 50) and Severe Weather Threat (SWEAT) Index (≥ 184). The study also highlights that warm, moist south-easterly winds at low levels, coupled with cold, dry westerly winds aloft, create conditions conducive to deep convection. The forecast of these quantitative thresholds and favourable synoptic conditions from Numerical Weather Prediction (NWP) models provide a qualitative basis for forecasting hailstorms 24 to 72 h in advance. Our findings contribute to improving localized hailstorm forecasting in mountainous regions.