ESA StormSurgeCastNet Dataset

<blockquote> <p>This is the dataset for the storm surge forecasting work of Ebel et al (2024), featuring the curation of a global and multi-decadal dataset of extreme weather induced storm surges as well as the implementation of neural networks for addressing the associated forecasting task. The provided dataset is multi-modal and features preprocessed in-situ tide gauge records as well as atmospheric reanalysis products and ocean state simulations. The models applied in this work learn to fuse the sparse yet accurate in-situ measurements with the global ocean and atmosphere state products. This way, more accurate storm surge forecasts are achieved, with predictions broadcasted to sites missing well-maintained tidal gauge infrastructure.</p> </blockquote> <p>&nbsp;</p> <ul> <li>The publication is available in the proceedings <a href="https://openaccess.thecvf.com/content/CVPR2024W/EarthVision/html/Ebel_Implicit_Assimilation_of_Sparse_In_Situ_Data_for_Dense__CVPRW_2024_paper.html" rel="nofollow">https://openaccess.thecvf.com/content/CVPR2024W/EarthVision/html/Ebel_Implicit_Assimilation_of_Sparse_In_Situ_Data_for_Dense__CVPRW_2024_paper.html</a></li> <li>For the associated code, please see <a href="https://github.com/PatrickESA/StormSurgeCastNet">https://github.com/PatrickESA/StormSurgeCastNet</a></li> <li>For any further questions, please reach out to me here or via the credentials on my <a href="https://pwjebel.com" rel="nofollow">website</a>.</li> </ul> <p><br><strong>Reference:</strong></p> <p><br><em>P. Ebel, B. Victor, P. Naylor, G. Meoni, F. Serva, R. Schneider Implicit Assimilation of Sparse In Situ Data for Dense &amp; Global Storm Surge Forecasting. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2024.</em></p>