Weather Radar

Weather radar is a crucial tool for observing and predicting atmospheric phenomena, with current research focusing on improving its capabilities through advanced data processing and machine learning. This involves developing sophisticated algorithms, including deep learning models like convolutional neural networks and recurrent graph convolutional networks, to analyze radar data for applications such as precipitation nowcasting, tornado detection, and animal movement tracking. These advancements enhance the accuracy and resolution of weather predictions, leading to improved forecasting and more effective hazard mitigation strategies across various sectors, from aviation to environmental management. The integration of data from multiple sources, including satellite imagery and other sensors, further refines predictive models.

Papers

August 11, 2024

Personalized Federated Learning for improving radar based precipitation nowcasting on heterogeneous areas
Judith Sáinz-Pardo Díaz, María Castrillo, Juraj Bartok, Ignacio Heredia Cachá, Irina Malkin Ondík, Ivan Martynovskyi, Khadijeh Alibabaei, Lisana Berberi, Valentin Kozlov, Álvaro López García
Personalized Federated Learning Wave Over the Horizon Radar Radar Field Spatial Heterogeneity Precipitation Associated Weather Radar Radar Echo

August 8, 2024

Detection of Animal Movement from Weather Radar using Self-Supervised Learning
Mubin Ul Haque, Joel Janek Dabrowski, Rebecca M. Rogers, Hazel Parry
Self Supervised Learning Data Detection Radar Data Weather Radar

January 26, 2024

A Benchmark Dataset for Tornado Detection and Prediction using Full-Resolution Polarimetric Weather Radar Data
Mark S. Veillette, James M. Kurdzo, Phillip M. Stepanian, John Y. N. Cho, Siddharth Samsi, Joseph McDonald
Human Prediction MAESTRO Dataset Benchmark Dataset Polarimetric Synthetic Aperture Radar Weather Radar Tornado Prediction

June 22, 2023

Prediction of Annual Snow Accumulation Using a Recurrent Graph Convolutional Approach
Benjamin Zalatan, Maryam Rahnemoonfar
Convolutional Neural Network Graph Neural Network Human Prediction Graph Attention Weather Radar Snow Accumulation

February 2, 2023

Recurrent Graph Convolutional Networks for Spatiotemporal Prediction of Snow Accumulation Using Airborne Radar
Benjamin Zalatan, Maryam Rahnemoonfar
Graph Neural Network Radar Data Spatiotemporal Prediction Weather Radar Snow Accumulation

November 30, 2022

WeatherFusionNet: Predicting Precipitation from Satellite Data
Jiří Pihrt, Rudolf Raevskiy, Petr Šimánek, Matej Choma
Satellite Data Precipitation Associated Weather Radar Radar Reflectivity Weather4cast Challenge

November 2, 2022

Thunderstorm nowcasting with deep learning: a multi-hazard data fusion model
Jussi Leinonen, Ulrich Hamann, Ioannis V. Sideris, Urs Germann
Deep Learning Deep Learning Model Numerical Weather Prediction Data Fusion Weather Radar Lightning Fast Thunderstorm Warning Upward Lightning

July 15, 2022

Rain regime segmentation of Sentinel-1 observation learning from NEXRAD collocations with Convolution Neural Networks
Aurélien Colin, Pierre Tandeo, Charles Peureux, Romain Husson, Nicolas Longépé, Ronan Fablet
Convolutional Neural Network Sentinel 1 Precipitation Estimation Collocation Point Weather Radar Precipitation Map

Weather Radar

Papers

Personalized Federated Learning for improving radar based precipitation nowcasting on heterogeneous areas

Detection of Animal Movement from Weather Radar using Self-Supervised Learning

A Benchmark Dataset for Tornado Detection and Prediction using Full-Resolution Polarimetric Weather Radar Data

Prediction of Annual Snow Accumulation Using a Recurrent Graph Convolutional Approach

Recurrent Graph Convolutional Networks for Spatiotemporal Prediction of Snow Accumulation Using Airborne Radar

WeatherFusionNet: Predicting Precipitation from Satellite Data

Thunderstorm nowcasting with deep learning: a multi-hazard data fusion model

Rain regime segmentation of Sentinel-1 observation learning from NEXRAD collocations with Convolution Neural Networks