Performance assessment of drone-based photogrammetry coupled with machine-learning for the estimation of hail size distributions on the ground

Hail-producing thunderstorm are extreme weather phenomena that can have devastating impacts on the environment, agriculture and infrastructure, leading to large financial losses. Remote sensing techniques such as dual-polarimetric weather radar are the state-of-the-art for observing hail over large areas, but don’t necessarily represent conditions on the ground.To verify weather radar-based products, current ground-based observations provide valuable information but exhibit various limitations: Crowd-sourced reports provide information over widespread areas, but only indicate the size of the largest hail stones and are biased towards populated areas, while automatic hail sensors and hailpads provide hail size distribution (HSD), based only on small observational areas of