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  - climate
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  ---
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- # FourCastNet: a global data-driven high-resolution weather model
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- This is a global data-driven high-resolution weather model implemented, trained and open sourced by [High-Flyer AI](https://www.high-flyer.cn/en/). It is the first AI weather model, which can compare with the ECMWF Integrated Forecasting System (IFS).
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  See also: [Github repository](https://github.com/HFAiLab/FourCastNet) and [High-flyer AI's blog](https://www.high-flyer.cn/blog/fourcastnet/)
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- Typhoon track prediction:
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- ![](./wind_small.gif)
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- Water vapour prediction:
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- ![](./precipitation_small.gif)
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-
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- For more cases about FourCastNet prediction, please have a look at [HF-Earth](https://www.high-flyer.cn/hf-earth/), a daily updated demo released by [High-Flyer AI](https://www.high-flyer.cn/en/).
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  ## Inference
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  You can load the weights `backbone.pt` and `precipitation.pt` to generate weather predictions, as shown in the following pseudocode. The complete code is released at `./infer2img.py`.
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  ```python
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  FourCastNet can predict 7 surface variables, plus 5 atmospheric variables at each of 3 or 4 pressure levels, for 21 variables total. The details of these variables follow the [paper](https://arxiv.org/abs/2202.11214).
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-
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  ## Description of Files
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  `backbone.pt`
 
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  - climate
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+ # OpenCastKit: an open-source solutions of global data-driven high-resolution weather forecasting
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+ This is an open-source solutions of global data-driven high-resolution weather forecasting, implemented and improved by [High-Flyer AI](https://www.high-flyer.cn/). It can compare with the ECMWF Integrated Forecasting System (IFS).
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  See also: [Github repository](https://github.com/HFAiLab/FourCastNet) and [High-flyer AI's blog](https://www.high-flyer.cn/blog/fourcastnet/)
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+ Several cases:
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+ ![Typhoon track comparison](./wind_small.gif)
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+ ![Water vapour comparison](./precipitation_small.gif)
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+ For more cases about FourCastNet/GraphCast prediction, please have a look at [HF-Earth](https://www.high-flyer.cn/hf-earth/), a daily updated demo released by [High-Flyer AI](https://www.high-flyer.cn/en/).
 
 
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  ## Inference
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+ ### FourCastNet
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  You can load the weights `backbone.pt` and `precipitation.pt` to generate weather predictions, as shown in the following pseudocode. The complete code is released at `./infer2img.py`.
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  ```python
 
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  FourCastNet can predict 7 surface variables, plus 5 atmospheric variables at each of 3 or 4 pressure levels, for 21 variables total. The details of these variables follow the [paper](https://arxiv.org/abs/2202.11214).
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  ## Description of Files
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  `backbone.pt`