309 citations · 663 across the 9 of their papers we have counts for
9 papers
WeatherNext 3: Increasing resolution and performance of global weather models with raw observations
Stephan Rasp, Boris Babenko, Dominic Masters +22
State-of-the-art AI weather models have shown impressive medium-range forecast skill and computational efficiency, but suffer two key shortcomings: their forecasts have lower spati…
An Operational Deep Learning System for Satellite-Based High-Resolution Global Nowcasting
Shreya Agrawal, Mohammed Alewi Hassen, Emmanuel Asiedu Brempong +16
Precipitation nowcasting, which predicts rainfall up to a few hours ahead, is a critical tool for vulnerable communities in the Global South frequently exposed to intense, rapidly…
WeatherBench 2: A benchmark for the next generation of data-driven global weather models
Stephan Rasp, Stephan Hoyer, Alexander Merose +15
WeatherBench 2 is an update to the global, medium-range (1-14 day) weather forecasting benchmark proposed by Rasp et al. (2020), designed with the aim to accelerate progress in dat…
Deep Learning for Day Forecasts from Sparse Observations
Marcin Andrychowicz, Lasse Espeholt, Di Li +5
Deep neural networks offer an alternative paradigm for modeling weather conditions. The ability of neural models to make a prediction in less than a second once the data is availab…
A Machine Learning Outlook: Post-processing of Global Medium-range Forecasts
Shreya Agrawal, Rob Carver, Cenk Gazen +7
Post-processing typically takes the outputs of a Numerical Weather Prediction (NWP) model and applies linear statistical techniques to produce improve localized forecasts, by inclu…
Global Extreme Heat Forecasting Using Neural Weather Models
Ignacio Lopez-Gomez, Amy McGovern, Shreya Agrawal +1
Heat waves are projected to increase in frequency and severity with global warming. Improved warning systems would help reduce the associated loss of lives, wildfires, power disrup…
Skillful Twelve Hour Precipitation Forecasts using Large Context Neural Networks
Lasse Espeholt, Shreya Agrawal, Casper Sønderby +7
The problem of forecasting weather has been scientifically studied for centuries due to its high impact on human lives, transportation, food production and energy management, among…
MetNet: A Neural Weather Model for Precipitation Forecasting
Casper Kaae Sønderby, Lasse Espeholt, Jonathan Heek +6
Weather forecasting is a long standing scientific challenge with direct social and economic impact. The task is suitable for deep neural networks due to vast amounts of continuousl…
Machine Learning for Precipitation Nowcasting from Radar Images
Shreya Agrawal, Luke Barrington, Carla Bromberg +3
High-resolution nowcasting is an essential tool needed for effective adaptation to climate change, particularly for extreme weather. As Deep Learning (DL) techniques have shown dra…