ICESat-2 Arctic sea ice thickness retrieved using multi-source snow depth data during freezing seasons (October to April)

This dataset provides Arctic sea ice thickness (SIT) estimates retrieved using multi-source snow depth data during the Arctic freezing seasons from November 2018 to December 2020. The dataset includes six cases of sea ice thickness, which were derived from various snow depth schemes, including: passive microwave algorithms (FY3/MWRI, ASD_MR), reanalysis (TOPAZ4b), modified climatology (MW99/AMSR2), a Lagrangian snow model (SMLG), and dual-satellite altimetry (KuLa). The data format is MATLAB (.mat), which can be opened and analyzed using MATLAB. This dataset serves as a valuable resource for improving the accuracy of ICESat-2 Arctic SIT retrievals, particularly by addressing biases introduced by snowpack interpretation, and offers insights into the seasonal and spatial variations of Arctic sea ice thickness. Li, L., Chen, H., Guan, L., 2021. Retrieval of Snow Depth on Arctic Sea Ice from the FY3B/MWRI. Remote Sensing 13, 1457. https://doi.org/10.3390/rs13081457. Copernicus Marine Service (CMEMS), 2022. “Product User Manual for Arctic Ocean Physical and BGC Analysis and Forecasting Products.” Hendricks, S., Paul, S., 2023. Product User Guide & Algorithm Specification - AWI CryoSat-2 Sea Ice Thickness (version 2.6) Issued by. He, L., Xue, B., Hui, F., Xu, S., Chen, Z., Cheng, X., 2024. Toward Daily Snow Depth Estimation on Arctic Sea Ice During the Whole Winter Season From Passive Microwave Radiometer Data. IEEE Transactions on Geoscience and Remote Sensing 62, 1–15. https://doi.org/10.1109/TGRS.2024.3358340. Liston, G.E., Polashenski, C., Rösel, A., Itkin, P., King, J., Merkouriadi, I., Haapala, J., 2018. A Distributed Snow-Evolution Model for Sea-Ice Applications (SnowModel). Journal of Geophysical Research: Oceans 123, 3786–3810. https://doi.org/10.1002/2017JC013706. Landy, J.C., de Rijke-Thomas, C., Nab, C., Lawrence, I., Glissenaar, I.A., Mallett, R.D.C., Fredensborg Hansen, R.M., Petty, A., Tsamados, M., Macfarlane, A.R., Braakmann-Folgmann, A., 2024. Anticipating CRISTAL: An exploration of multi-frequency satellite altimeter snow depth estimates over Arctic sea ice, 2018-2023. EGUsphere 1–41. https://doi.org/10.5194/egusphere-2024-2904. Product Temporal resolution Grid resolution Estimation Method Reference FY3/MWRI Daily 12.5 km passive microwave algorithm (Li et al., 2021) TOPAZ4b Daily 12.5 km reanalysis (CMEMS et al., 2022) MW99/AMSR2 Monthly 25 km modified climatology (Hendricks and Paul, 2023) ASD_MR Daily 25 km passive microwave algorithm (He et al., 2024) SMLG Daily 25 km Lagrangian snow evolution model (Liston et al., 2018) KuLa Monthly 25 km dual-satellite altimetry (Landy et al., 2024)