cff-version: 1.2.0 abstract: "
The dataset provided in this repository corresponds to the original data used in the publication by De Roda Husman et al. (2023) titled "A High-Resolution Record of Surface Melt on Antarctic Ice Shelves using Multi-Source Remote Sensing Data and Deep Learning" (DOI to be announced!).
The dataset, named UMelt, contains a comprehensive surface melt record for all Antarctic ice shelves. It offers a high spatial resolution of 500 meters and a high temporal resolution of 12 hours, covering the period from 2016 to 2021. Our methodology relies on the utilization of a deep learning model known as U-Net, which integrates microwave remote sensing observations from three sources: Sentinel-1, Special Sensor Microwave Imager/Sounder (SSMIS), and Advanced Scatterometer (ASCAT).
The data is available for download in two formats:
1. "Timeseries": This format provides the data at a twice-daily resolution, allowing for detailed analysis over time.
2. "MeltFraction": This format offers a yearly, summed product, providing a consolidated representation of the melt fraction.
Feel free to access and explore the dataset to gain valuable insights into surface melt dynamics on Antarctic ice shelves.
" authors: - family-names: de Roda Husman given-names: Sophie orcid: "https://orcid.org/0000-0001-8830-9894" - family-names: Lhermitte given-names: Stef orcid: "https://orcid.org/0000-0002-1622-0177" - family-names: Bolibar given-names: Jordi orcid: "https://orcid.org/0000-0002-0791-0731" - family-names: Hu given-names: Zhongyang orcid: "https://orcid.org/0000-0002-1793-3806" - family-names: Shukla given-names: Shashwat - family-names: Izeboud given-names: Maaike orcid: "https://orcid.org/0000-0002-8915-7252" - family-names: van der Meer given-names: Marijn - family-names: Long given-names: David - family-names: Wouters given-names: Bert orcid: "https://orcid.org/0000-0002-1086-2435" title: "A High-Resolution Record of Surface Melt on Antarctic Ice Shelves using Multi-Source Remote Sensing Data and Deep Learning" keywords: version: 1 identifiers: - type: doi value: 10.4121/8a8934ef-9407-406f-8bfb-573eb182ec54.v1 license: CC0 date-released: 2023-07-05