Share Cite as Shangshang Yang, Huiling Yuan. (2023). A customized multi-scale deep learning framework for storm nowcasting. Zenodo. (submitted to Geophysical Research Letters). https://doi.org/10.5281/zenodo.800184
StormCast is a distributed artificial intelligence application which aims at predicting severe storm...
To cater to the imminent threats of changing weather pattern and increase urbanisation, Singapore’s ...
Abstract Strong convection nowcasting has been gaining importance in operational weather forecasting...
This dataset contains the pretrained model weights and precomputed results for the paper "Thundersto...
Predictions of thunderstorm-related hazards are needed in several sectors, including first responder...
A deep learning model is presented to nowcast the occurrence of lightning at a five-minute time reso...
Nowcasting (very short-term forecasting) in meteorology is a very important topic for agriculture, h...
In this repository you can find the weights of the models used in the paper "Deep Learning Approach ...
Input and targets for Deep Learning augmented Weather Prediction based on Cubic Sphere for global pr...
This repository contains the code and dataset for the paper: Nowcasting thunderstorm hazards using ...
QuakeFlow: A Scalable Deep-learning-based Earthquake Monitoring Workflow with Cloud Computin
This repository contains the dataset for the paper: Nowcasting thunderstorm hazards using machine l...
2020 Summer.Includes bibliographical references.Weather nowcasting is heavily dependent on the obser...
Abstract In this report, we propose a deep learning technique for high-accuracy estimation of the in...
In this report, we propose a deep learning technique for high-accuracy estimation of the intensity c...
StormCast is a distributed artificial intelligence application which aims at predicting severe storm...
To cater to the imminent threats of changing weather pattern and increase urbanisation, Singapore’s ...
Abstract Strong convection nowcasting has been gaining importance in operational weather forecasting...
This dataset contains the pretrained model weights and precomputed results for the paper "Thundersto...
Predictions of thunderstorm-related hazards are needed in several sectors, including first responder...
A deep learning model is presented to nowcast the occurrence of lightning at a five-minute time reso...
Nowcasting (very short-term forecasting) in meteorology is a very important topic for agriculture, h...
In this repository you can find the weights of the models used in the paper "Deep Learning Approach ...
Input and targets for Deep Learning augmented Weather Prediction based on Cubic Sphere for global pr...
This repository contains the code and dataset for the paper: Nowcasting thunderstorm hazards using ...
QuakeFlow: A Scalable Deep-learning-based Earthquake Monitoring Workflow with Cloud Computin
This repository contains the dataset for the paper: Nowcasting thunderstorm hazards using machine l...
2020 Summer.Includes bibliographical references.Weather nowcasting is heavily dependent on the obser...
Abstract In this report, we propose a deep learning technique for high-accuracy estimation of the in...
In this report, we propose a deep learning technique for high-accuracy estimation of the intensity c...
StormCast is a distributed artificial intelligence application which aims at predicting severe storm...
To cater to the imminent threats of changing weather pattern and increase urbanisation, Singapore’s ...
Abstract Strong convection nowcasting has been gaining importance in operational weather forecasting...
DOI
Add to ORKG