🔥 Deep learning has been widely explored almost in all research filed. Here is a curated list of papers about deep learning methods in Earth System, especially relating to weather prediction. It also contains frameworks for data-driven Numerical Weather Prediciton (NWP) training, tools to deploy weather prediction, courses and tutorials about Ai4earth and all publicly available weather prediction checkpoints and APIs.

• Awesome-ai4earth

  • Updates

  • Table of Content

  • Milestone Papers

  • Preprocessing

    • Data Assimilation

  • Forcasting

    • Numerical Weather Prediciton
    • Precipitation Nowcasting

  • Postprocessing

    • Downscaling
    • Bias Correction

  • Applications

    • Extreme Weather and Prediction

      tropical cyclones, heat wave etc.

    • Climate phenomena analysis

  • Weather&Climate Related Application

    • global-wildfire-prediction

  • Other Papers

  • Ai4earth Benchmark

  • Dataset

• [2023-11-07] Creat this project, add some big model for atmospherical modeling!

• Add more paper, datasets, research directions for ai4earth ✨Contributions Wanted

Also check out the project that I am currently working on: EarthVision - A deep learniong framwork for Numerical Weather Prediction, Earth System Data cmpression, Precipitation Prediction)

Date	keywords	Institute	Paper	Publication
2022-02	FourCastNet	Nvidia	FourCastNet: Accelerating Global High-Resolution Weather Forecasting Using Adaptive Fourier Neural Operators [paper1][paper2]	PASC
2022-11	PanguWeather	HuaWei	Accurate medium-range global weather forecasting with 3D neural networks [paper1][paper2]	Nature
2022-12	GraphCast	DeepMind	GraphCast: Learning skillful medium-range global weather forecasting	Science
2023-04	FengWu	Shanghai AILab	FengWu: Pushing the Skillful Global Medium-range Weather Forecast beyond 10 Days Lead	arxiv
2023-06	FuXi	Fudan University	FuXi: A cascade machine learning forecasting system for 15-day global weather forecast	npj

• FengWu-Adas Towards an End-to-End Artificial Intelligence Driven Global Weather Forecasting System. (arxiv, 12/2023)
• FengWu-4DVar FengWu-4DVar: Coupling the Data-driven Weather Forecasting Model with 4D Variational Assimilation (arxiv, 12/2023)

• NeuralGCM Neural General Circulation Models. (arxiv, 11/2023)
• GenCast Diffusion-based ensemble forecasting for medium-range weather. (arxiv. 12/2023)
• MetNet-3 Deep Learning for Day Forecasts from Sparse Observations. (arxiv, 06/2023)
• ClimaX A foundation model for weather and climate, (ICML, 2023) [project]

• NowcastNet Skilful nowcasting of extreme precipitation with NowcastNet. (nature, 07/2023)
• PostRainBench - A comprehensive benchmark and a new model for precipitation forecasting. (arxiv, 10/2023)
• Anthropogenic fingerprints in daily precipitation revealed by deep learning. (nature, 08/2023)

• CorrDiff Generative residual diffusion modeling for km-scale atmospheric downscaling, (arxiv, 09/2023)

• Two deep learning-based bias-correction pathways improve summer precipitation prediction over China, (Environmental Research Letters, 12/2022) paper

• FuXi-Extreme: Improving extreme rainfall and wind forecasts with diffusion mode. (arxiv, 10/2023)

• The Potential Predictability of Fire Danger Provided by Numerical Weather Prediction (JAMC, 11/2016)
• Machine learning–based observation-constrained projections reveal elevated global socioeconomic risks from wildfire. (nature communication, 22/03/2023)

WeatherBench 2: A benchmark for the next generation of data-driven global weather models [project] [LeaderBoard] (08/2023)

If you're interested in the field of LLM, you may find the above list of milestone papers helpful to explore its history and state-of-the-art. However, each direction of LLM offers a unique set of insights and contributions, which are essential to understanding the field as a whole. For a detailed list of papers in various subfields, please refer to the following link (it is possible that there are overlaps between different subfields):

(:exclamation: We would greatly appreciate and welcome your contribution to the following list. ❗)

• ML-weather-Survey

• Ai4earth-NWP-Analysis

  Analyse different NWP models in different fields with respect to different abilities

• Ai4earth-Wildfire

  some deeplearning methods in wildfire forecast.

• Ai4earth-Application

The following list makes sure that all LLMs are compared apples to apples.

You may also find these leaderboards helpful:

• WeatherBench2 Leaderboard - evaluating and comparing various weather forecasting models. displays up-to-date scores of many of the state-of-the-art ML and physics-based models.

• DeepSpeed - DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
• Megatron-DeepSpeed - DeepSpeed version of NVIDIA's Megatron-LM that adds additional support for several features such as MoE model training, Curriculum Learning, 3D Parallelism, and others.
• FairScale - FairScale is a PyTorch extension library for high performance and large scale training.
• Megatron-LM - Ongoing research training transformer models at scale.
• Colossal-AI - Making large AI models cheaper, faster, and more accessible.
• BMTrain - Efficient Training for Big Models.
• Mesh Tensorflow - Mesh TensorFlow: Model Parallelism Made Easier.
• maxtext - A simple, performant and scalable Jax LLM!
• Alpa - Alpa is a system for training and serving large-scale neural networks.
• GPT-NeoX - An implementation of model parallel autoregressive transformers on GPUs, based on the DeepSpeed library.

• xx - A distributed multi-model LLM serving system with web UI and OpenAI-compatible RESTful APIs.

• xx - A curated (still actively updated) list of practical guide resources of earth-related research.

This is an active repository and your contributions are always welcome!

I will keep some pull requests open if I'm not sure if they are awesome for ai4earth, you could vote for them by adding 👍 to them.

If you have any question about this opinionated list, do not hesitate to contact me hantao10200@gmail.com.