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EarthNet2021: A novel large-scale dataset and challenge for forecasting localized climate impacts
[article]
2020
arXiv
pre-print
Preserved Fulltext
For model intercomparison we frame EarthNet2021 as a challenge with four tracks based on different test sets. ...
Hence, we define the EarthNetScore, a novel ranking criterion for models forecasting Earth surface reflectance. ...
We are thankful for invaluable help, comments and discussions to the DLR Climate Informatics and the MPI-BGC EIES group members, especially to Andreas Gerhardus, Christopher Käding, Miguel Mahecha, Christian ...
arXiv:2012.06246v1
fatcat:m7a32p22zbht5mpfxjdo46t3eu
EarthNet2021: A large-scale dataset and challenge for Earth surface forecasting as a guided video prediction task
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
EarthNet2021 is a large dataset suitable for training deep neural networks on the task. ...
Additionally we frame EarthNet2021 as a challenge allowing for model intercomparison. Resulting forecasts will greatly improve (>x50) over the spatial resolution found in numerical models. ...
Acknowledgements We thank three anonymous reviewers and the area chair for their constructive reviews. ...
arXiv:2104.10066v1
fatcat:w6fg5gzhmvdr5ank4jfhbustg4