| | --- |
| | language: en |
| | license: mit |
| | library_name: pytorch |
| | --- |
| | |
| |
|
| | # Cloudcasting |
| |
|
| | ## Model Description |
| |
|
| | <!-- Provide a longer summary of what this model is/does. --> |
| | This model is trained to predict future frames of satellite data from past frames. It takes 3 hours |
| | of recent satellkite imagery at 15 minute intervals and predicts 3 hours into the future also at |
| | 15 minute intervals. The satellite inputs and predictions are multispectral with 11 channels. |
| |
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| |
|
| | See [1] for the repo used to train the model. |
| |
|
| | - **Developed by:** Open Climate Fix and the Alan Turing Institute |
| | - **License:** mit |
| |
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| |
|
| | # Training Details |
| |
|
| | ## Data |
| |
|
| | <!-- This should link to a Data Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> |
| | This was trained on EUMETSAT satellite imagery derived from the data stored in [this google public |
| | dataset](https://console.cloud.google.com/marketplace/product/bigquery-public-data/eumetsat-seviri-rss?hl=en-GB&inv=1&invt=AbniZA&project=solar-pv-nowcasting&pli=1). |
| |
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| | The data was processed using the protocol in [2] |
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| |
|
| | ### Software |
| |
|
| | - [1] https://github.com/alan-turing-institute/ocf-iam4vp |
| | - [2] https://github.com/alan-turing-institute/cloudcasting |
