license: cc-by-4.0
task_categories:
- image-to-image
- image-segmentation
tags:
- climate
pretty_name: hrmelt
size_categories:
- 10K<n<100K
This is the official dataset for MeltwaterBench: Deep learning for spatiotemporal downscaling of surface meltwater.
This dataset sets up a benchmark for spatiotemporal downscaling. Downscaling is similar to superresolution across space and time. The task is to create high-resolution surface meltwater maps from low-resolution (LR) data streams. The LR data contains passive microwave (PMW), a regional climate model (MARv3.14), a temporal interpolation of the targets from dates excluding the target date (time_interpolate_sar), and a static digital elevation map (DEM).
The generated 100m daily surface meltwater product can be found at interim/runs/unet_smp/data_v1_4/deploy/. You can download individual files by clicking the 'download' button. For downloading the full dataset and training models use git clone [email protected]:datasets/blutjens/meltwaterbench --branch main --single-branch and see full instructions at https://github.com/blutjens/meltwaterbench
Reference
If this data is useful for your analysis please consider citing:
@misc{lutjens25meltwaterbench,
title={MeltwaterBench: Deep learning for spatiotemporal downscaling of surface meltwater},
author={Bj\"orn L\"utjens and Patrick Alexander and Raf Antwerpen and Til Widmann and Guido Cervone and Marco Tedesco},
year={2025},
journal = {arXiv},
}