If I missed any of your work or if there's a need for an update in this review, please email me or just pull a request here. Thank you!
:paperclip: Papers&Codes ==
Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting
Rainfall Prediction: A Deep Learning Approach
Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model
A short-term rainfall prediction model using multi-task convolutional neural networks
All convolutional neural networks for radar-based precipitation nowcasting
Optical flow models as an open benchmark for radar-based precipitation nowcasting (rainymotion v0.1)
Pysteps: an open-source Python library for probabilistic precipitation nowcasting (v1.0)
Machine Learning for Precipitation Nowcasting from Radar Images
A review of radar-based nowcasting of precipitation and applicable machine learning techniques
RainNet v1.0: a convolutional neural network for radar-based precipitation nowcasting
MetNet: A Neural Weather Model for Precipitation Forecasting
Skilful precipitation nowcasting using deep generative models of radar
(1) Skillful Twelve Hour Precipitation Forecasts using Large Context Neural Networks
(2) Deep learning for twelve hour precipitation forecasts
Effective Training Strategies for Deep-learning-based Precipitation Nowcasting and Estimation
Deep-Learning-Based Precipitation Nowcasting with Ground Weather Station Data and Radar Data
Earthformer: Exploring Space-Time Transformers for Earth System Forecasting
Precipitation nowcasting using ground radar data and simpler yet better video prediction deep learning
MM-RNN: A Multimodal RNN for Precipitation Nowcasting
ClimaX: A foundation model for weather and climate
Skilful nowcasting of extreme precipitation with NowcastNet
Deep Learning Model based on Multi-scale Feature Fusion for Precipitation Nowcasting
Latent diffusion models for generative precipitation nowcasting with accurate uncertainty quantification
PreDiff: Precipitation Nowcasting with Latent Diffusion Models
Physical-Dynamic-Driven AI-Synthetic Precipitation Nowcasting Using Task-Segmented Generative Model
Learning skillful medium-range global weather forecasting
PAUNet: Precipitation Attention-based U-Net for rain prediction from satellite radiance data
RainAI - Precipitation Nowcasting from Satellite Data
DiffCast: A Unified Framework via Residual Diffusion for Precipitation Nowcasting
Improving Precipitation Nowcasting for High-Intensity Events Using Deep Generative Models with Balanced Loss and Temperature Data: A Case Study in the Netherlands
CasCast: Skillful High-resolution Precipitation Nowcasting via Cascaded Modelling
DB-RNN: A RNN for Precipitation Nowcasting Deblurring
PP-Loss: An imbalanced regression loss based on plotting position for improved precipitation nowcasting
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.
OpenSTL: A Comprehensive Benchmark of Spatio-Temporal Predictive Learning
EarthNet2021: A large-scale dataset and challenge for Earth surface forecasting as a guided video prediction task.
RainBench: Towards Global Precipitation Forecasting from Satellite Imagery
Benchmark Dataset for Precipitation Forecasting by Post-Processing the Numerical Weather Prediction.
POSTRAINBENCH: A COMPREHENSIVE BENCHMARK AND A NEW MODEL FOR PRECIPITATION FORECASTING
A benchmark for the next generation of data-driven global weather models