The forecasts and observation datasets are used in the paper "Convolutional neural network-based statistical post-processing of ensemble precipitation forecasts". https://doi.org/10.1016/j.jhydrol.2021.127301 The forecast data is a subset of the "ensemble for machine learning dataset (ENS4ML)" from ECMWF. The Python codes are stored in Github: https://github.com/wentao-bnu/LeNet_CSG_Preci
The most radical change to numerical weather prediction (NWP) during the last decade has been the op...
International audienceMeteorological ensemble members are a collection of scenarios for future weath...
Data and Python code for training and evaluating machine learning models for predicting thunderstorm...
The postprocessing method of ensemble forecasts is usually used to find a more precise estimate of f...
Code for the paper "Ensemble methods for neural network-based weather forecasts" by Sebastian Scher ...
Dataset created for machine learning and deep learning training and teaching purposes. Can for insta...
SummaryThis paper evaluates how post-processing can enhance raw precipitation forecasts made by diff...
International audienceAbstract. Statistical post-processing of ensemble forecasts, from simple linea...
Dataset for paper "Long Lead ENSO Forecast Using an Adaptive Graph Convolutional Recurrent Neural Ne...
The jupyter notebooks and datasets associated with the EEM20 forecasts are available here. More deta...
This is the data for the paper "Improve dynamical climate prediction with machine learning"
This page includes spatiotemporal datasets used in the paper STConvS2S: Spatiotemporal Convolutional...
Code for "Postprocessing of Ensemble Weather Forecasts Using Permutation-invariant Neural Networks" ...
SciAdv2022 Supplementary Dataset for paper: Skillful forecasts of springtime CONUS tornado activity...
As adotpion of machine learning in weather and climate research increases, we want to move to turnin...
The most radical change to numerical weather prediction (NWP) during the last decade has been the op...
International audienceMeteorological ensemble members are a collection of scenarios for future weath...
Data and Python code for training and evaluating machine learning models for predicting thunderstorm...
The postprocessing method of ensemble forecasts is usually used to find a more precise estimate of f...
Code for the paper "Ensemble methods for neural network-based weather forecasts" by Sebastian Scher ...
Dataset created for machine learning and deep learning training and teaching purposes. Can for insta...
SummaryThis paper evaluates how post-processing can enhance raw precipitation forecasts made by diff...
International audienceAbstract. Statistical post-processing of ensemble forecasts, from simple linea...
Dataset for paper "Long Lead ENSO Forecast Using an Adaptive Graph Convolutional Recurrent Neural Ne...
The jupyter notebooks and datasets associated with the EEM20 forecasts are available here. More deta...
This is the data for the paper "Improve dynamical climate prediction with machine learning"
This page includes spatiotemporal datasets used in the paper STConvS2S: Spatiotemporal Convolutional...
Code for "Postprocessing of Ensemble Weather Forecasts Using Permutation-invariant Neural Networks" ...
SciAdv2022 Supplementary Dataset for paper: Skillful forecasts of springtime CONUS tornado activity...
As adotpion of machine learning in weather and climate research increases, we want to move to turnin...
The most radical change to numerical weather prediction (NWP) during the last decade has been the op...
International audienceMeteorological ensemble members are a collection of scenarios for future weath...
Data and Python code for training and evaluating machine learning models for predicting thunderstorm...