Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting
- intro: NIPS (2015)
- paper: https://arxiv.org/abs/1506.04214
Rainfall Prediction: A Deep Learning Approach
- intro: International Conference on Hybrid Artificial Intelligence Systems (2016)
- paper: https://link.springer.com/chapter/10.1007/978-3-319-32034-2_13
Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model
- intro: NIPS (2017)
- paper: https://arxiv.org/abs/1706.03458
- github: https://github.com/sxjscience/HKO-7
A short-term rainfall prediction model using multi-task convolutional neural networks
- intro: IEEE international conference on data mining (2017)
- paper: https://ieeexplore.ieee.org/abstract/document/8215512
All convolutional neural networks for radar-based precipitation nowcasting
- intro: Procedia Computer Science (2019)
- paper: https://www.sciencedirect.com/science/article/pii/S1877050919303801
Optical flow models as an open benchmark for radar-based precipitation nowcasting (rainymotion v0.1)
- intro: Geoscientific Model Development (2019)
- paper: https://gmd.copernicus.org/articles/12/1387/2019/
- github: https://github.com/hydrogo/rainymotion
Pysteps: an open-source Python library for probabilistic precipitation nowcasting (v1.0)
- intro: Geoscientific Model Development (2019)
- paper: https://gmd.copernicus.org/articles/12/4185/2019/
- github: https://github.com/pySTEPS/pysteps
Machine Learning for Precipitation Nowcasting from Radar Images
- intro: arXiv (2019)
- paper: https://arxiv.org/abs/1912.12132
- blog: https://ai.googleblog.com/2020/01/using-machine-learning-to-nowcast.html
A review of radar-based nowcasting of precipitation and applicable machine learning techniques
- intro: arXiv (2020)
- paper: https://arxiv.org/abs/2005.04988
RainNet v1.0: a convolutional neural network for radar-based precipitation nowcasting
- intro: Geoscientific Model Development (2020)
- paper: https://gmd.copernicus.org/articles/13/2631/2020/gmd-13-2631-2020-discussion.html
- github: https://github.com/hydrogo/rainnet
MetNet: A Neural Weather Model for Precipitation Forecasting
- intro: arXiv (2020)
- paper: https://arxiv.org/abs/2003.12140
- github: https://github.com/openclimatefix/metnet
Skilful precipitation nowcasting using deep generative models of radar
- intro: nature (2021)
- paper: https://www.nature.com/articles/s41586-021-03854-z
- github: https://github.com/deepmind/deepmind-research/tree/master/nowcasting, https://github.com/openclimatefix/skillful_nowcasting
Skillful Twelve Hour Precipitation Forecasts using Large Context Neural Networks, Deep learning for twelve hour precipitation forecasts
- intro: arXiv (2021), Nature communications (2022)
- paper: https://arxiv.org/abs/2111.07470, https://www.nature.com/articles/s41467-022-32483-x
- blog: https://ai.googleblog.com/2021/11/metnet-2-deep-learning-for-12-hour.html
Effective Training Strategies for Deep-learning-based Precipitation Nowcasting and Estimation
- intro: Computers & Geosciences (2022)
- paper: https://www.sciencedirect.com/science/article/pii/S009830042200036X
- github: https://github.com/jihoonko/DeepRaNE
Deep-Learning-Based Precipitation Nowcasting with Ground Weather Station Data and Radar Data
- intro: arXiv (2022)
- paper: https://arxiv.org/abs/2210.12853
Earthformer: Exploring Space-Time Transformers for Earth System Forecasting
- intro: NIPS (2022)
- paper: https://proceedings.neurips.cc/paper_files/paper/2022/hash/a2affd71d15e8fedffe18d0219f4837a-Abstract-Conference.html
Precipitation nowcasting using ground radar data and simpler yet better video prediction deep learning
- intro: GIScience & Remote Sensing (2023)
- paper: https://www.tandfonline.com/doi/pdf/10.1080/15481603.2023.2203363
MM-RNN: A Multimodal RNN for Precipitation Nowcasting
- intro: IEEE Transactions on Geoscience and Remote Sensing (2023)
- paper: https://ieeexplore.ieee.org/abstract/document/10092888
ClimaX: A foundation model for weather and climate
- intro: arXiv (2023)
- paper: https://arxiv.org/abs/2301.10343
- github: https://github.com/microsoft/ClimaX
- blog: https://www.microsoft.com/en-us/research/group/autonomous-systems-group-robotics/articles/introducing-climax-the-first-foundation-model-for-weather-and-climate/
- intro: NIPS 2022
- link: https://www.climatechange.ai/events/neurips2022
The Python-ARM Radar Toolkit. A data model driven interactive toolkit for working with weather radar data.
wradlib: An Open Source Library for Weather Radar Data Processing
Cartopy is a Python package designed to make drawing maps for data analysis and visualisation easy.
Satellite Optical Flow with machine learning models
Python and JavaScript bindings for calling the Earth Engine API.
EarthNet2021: A large-scale dataset and challenge for Earth surface forecasting as a guided video prediction task.
- intro: CVPR Workshop EarthVision (2021)
- paper: https://openaccess.thecvf.com/content/CVPR2021W/EarthVision/html/Requena-Mesa_EarthNet2021_A_Large-Scale_Dataset_and_Challenge_for_Earth_Surface_Forecasting_CVPRW_2021_paper.html
- doc: https://www.earthnet.tech/
- github: https://github.com/earthnet2021/earthnet-model-intercomparison-suite
RainBench: Towards Global Precipitation Forecasting from Satellite Imagery
- intro: AAAI (2021)
- paper: https://ojs.aaai.org/index.php/AAAI/article/view/17749
- github: https://github.com/FrontierDevelopmentLab/PyRain
Benchmark Dataset for Precipitation Forecasting by Post-Processing the Numerical Weather Prediction.
- intro: arXiv (2022)
- paper: https://arxiv.org/abs/2206.15241
- github: https://github.com/osilab-kaist/KoMet-Benchmark-Dataset
- intro: EarthArXiv publishes articles from all subdomains of Earth Science and related domains of planetary science.
- link: https://eartharxiv.org/repository/about/