Published May 20, 2020
| Version 1.0.0
Dataset
Open
Data archive for "Stochastic Super-Resolution for Downscaling Time-Evolving Atmospheric Fields with a Generative Adversarial Network"
- 1. École polytechnique fédérale de Lausanne
- 2. Swiss Federal Office for Meteorology and Climatology MeteoSwiss
Description
This datasets supports the paper "Stochastic Super-Resolution for Downscaling Time-Evolving Atmospheric Fields with a Generative Adversarial Network" submitted to IEEE Transactions in Geoscience and Remote Sensing. A preprint of the paper can be found here: https://arxiv.org/abs/2005.10374. The code that uses these data is available at https://github.com/jleinonen/downscaling-rnn-gan.
The file "goes-samples-2019-128x128.nc" contains the training dataset called "GOES-COT" in the paper, consisting of cloud optical depth measurements from the GOES-16 satellite. The files "gen_weights*.nc" contain the generator weights saved at different time steps during training for the two different datasets described in the paper.
Files
Files
(31.7 GB)
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54.5 MB | Download |
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54.5 MB | Download |
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54.5 MB | Download |
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54.5 MB | Download |
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54.5 MB | Download |
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54.5 MB | Download |
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54.5 MB | Download |
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54.5 MB | Download |
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54.5 MB | Download |
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54.5 MB | Download |
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54.5 MB | Download |
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54.5 MB | Download |
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54.5 MB | Download |
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54.5 MB | Download |
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54.5 MB | Download |
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md5:6043aee51b68e4530dcdbe3aa31a846f
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54.5 MB | Download |
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54.5 MB | Download |
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54.5 MB | Download |
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md5:cfba9c3f68ed34207db86675cfa930a9
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54.5 MB | Download |
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54.5 MB | Download |
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54.5 MB | Download |
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54.5 MB | Download |
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54.5 MB | Download |
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54.5 MB | Download |
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54.5 MB | Download |
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54.5 MB | Download |
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54.5 MB | Download |
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54.5 MB | Download |
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54.5 MB | Download |
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54.5 MB | Download |
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54.5 MB | Download |
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54.5 MB | Download |
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54.5 MB | Download |
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54.5 MB | Download |
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54.5 MB | Download |
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54.5 MB | Download |
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54.5 MB | Download |
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54.5 MB | Download |
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54.5 MB | Download |
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54.5 MB | Download |
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54.5 MB | Download |
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md5:281563b475fa56647f99584d95ed8686
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54.5 MB | Download |
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md5:1d014234d519b6abfccc38d2618c74b2
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54.5 MB | Download |
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md5:95a0076dc60b15dc03c767c4c4ca806a
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54.5 MB | Download |
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md5:8a592611188ae74f4154b90967cf882f
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54.5 MB | Download |
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md5:764e1d05632693af3833da35c1d0c34d
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54.5 MB | Download |
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md5:9c48fd1a7db3d52bc6648bad01027a28
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54.5 MB | Download |
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md5:ce423df51c2067a42f124105308a629d
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18.1 GB | Download |
Additional details
Related works
- Is supplement to
- Preprint: arXiv:2005.10374 (arXiv)
Funding
- Riming in mountainous and Antarctic snowfall 200020_175700
- Swiss National Science Foundation