506 citations · 998 across the 6 of their papers we have counts for
6 papers
Improving medium-range ensemble weather forecasts with hierarchical ensemble transformers
Zied Ben-Bouallegue, Jonathan A Weyn, Mariana C A Clare +3
Statistical post-processing of global ensemble weather forecasts is revisited by leveraging recent developments in machine learning. Verification of past forecasts is exploited to…
Super-resolution Probabilistic Rain Prediction from Satellite Data Using 3D U-Nets and EarthFormers
Yang Li, Haiyu Dong, Zuliang Fang +2
Accurate and timely rain prediction is crucial for decision making and is also a challenging task. This paper presents a solution which won the 2 nd prize in the Weather4cast 2022…
MS-nowcasting: Operational Precipitation Nowcasting with Convolutional LSTMs at Microsoft Weather
Sylwester Klocek, Haiyu Dong, Matthew Dixon +7
We present the encoder-forecaster convolutional long short-term memory (LSTM) deep-learning model that powers Microsoft Weather's operational precipitation nowcasting product. This…
Sub-seasonal forecasting with a large ensemble of deep-learning weather prediction models
Jonathan A. Weyn, Dale R. Durran, Rich Caruana +1
We present an ensemble prediction system using a Deep Learning Weather Prediction (DLWP) model that recursively predicts key atmospheric variables with six-hour time resolution. Th…
Improving data-driven global weather prediction using deep convolutional neural networks on a cubed sphere
Jonathan A. Weyn, Dale R. Durran, Rich Caruana
We present a significantly-improved data-driven global weather forecasting framework using a deep convolutional neural network (CNN) to forecast several basic atmospheric variables…
WeatherBench: A benchmark dataset for data-driven weather forecasting
Stephan Rasp, Peter D. Dueben, Sebastian Scher +3
Data-driven approaches, most prominently deep learning, have become powerful tools for prediction in many domains. A natural question to ask is whether data-driven methods could al…