[ TRACK // GARAGE LAB & HOBBY ]ID: hailcast-ml-radar-nowcasting
HailCast-ML — Radar Nowcasting & Hail Detection
A meteorological nowcasting and radar processing platform. Ingests dual-polarization radar reflectivity matrices, applies cell tracking and optical flow motion vectors, and uses ML models to predict hail probability and severe storm trajectories in real time.
PythonMachine LearningComputer VisionMeteorologyNumPy
FIG: HailCast-ML
Convective Storm Nowcasting
Severe convective storms and hailstorms cause millions in damage within minutes. HailCast-ML is an end-to-end radar nowcasting platform that analyzes open-source meteorological radar data in real time to detect severe convective cells and predict hail trajectories.
[ WARNING ]Standard numerical weather models have update cycles of 3-6 hours. HailCast-ML operates on 5-minute radar scan loops to compute instantaneous storm cell kinematics.
Processing Pipeline
- Data Ingestion: Dual-polarization radar matrices (Z, ZDR, KDP) from open radar networks.
- Computer Vision Tracking: Gunnar Farneback optical flow and TITAN (Thunderstorm Identification, Tracking, Analysis and Nowcasting) centroid clustering.
- Machine Learning Inference: Random Forest / Gradient Boosted ensemble predicting Maximum Expected Size of Hail (MESH) and severe gust probabilities.