Daily gridded Arctic snow depth dataset over sea ice from AMSR2 using an adaptive seasonal algorithm (2012–2023), Version 1

Overview This dataset provides daily snow depth estimates over pan-Arctic sea ice for the freezing seasons from 2012 to 2023, derived from Advanced Microwave Scanning Radiometer-2 (AMSR2) data, utilizing a newly proposed adaptive seasonal algorithm (AdaSA-SD). To derive the algorithmic coefficients in AdaSA-SD, a novel airborne-calibrated altimetric snow depth dataset, derived from CryoSat-2 and Ice Cloud land Elevation Satellite-2 (ICESat-2) freeboard measurements, was used as the truth reference for algorithm training. Filename: YYYY-MM-dd [Year-Month-Day] Parameter(s): Snow_Depth: Daily mean snow depth field derived using the AdaSA-SD method (unit: cm) Snow_Depth_Movmean: Seven-day moving average of the daily snow depth (unit: cm) Uncertainty: Uncertainty in daily snow depth retrieval based on Monte Carlo-based simulations (unit: cm) Uncertainty_Movmean: Seven-day moving average of the daily snow depth uncertainty (unit: cm) Platform(s): GCOM-W, CryoSat-2, and ICESat-2 Sensor(s): Advanced Microwave Scanning Radiometer 2 (AMSR2), Synthetic Aperture Interferometric Radar Altimeter (SIRAL), and Advanced Topographic Laser Altimeter System (ATLAS) Data Format(s): NetCDF Temporal Coverage: 1 October 2012 to 30 April 2023 Temporal Resolution: 1 day Spatial Resolution: 25 km × 25 km Spatial Reference System(s): NSIDC Sea Ice Polar Stereographic North (EPSG:3411) Spatial Coverage: N:90 S:0 E:180 W:-180 The dataset consists of files for each day of the study period, along with the corresponding snow depth maps and uncertainty maps. Note: Snow depths were only retained for results with sea ice concentration above 50% to ensure data quality. The seven-day moving average results help mitigate the effects of melt-refreeze-thaw events, but they reduce the temporal resolution of the data If you have any questions please contact: [e-mail], thanks! Yi zhou, Xianwei Wang, and Chentong Zhang are with School of Oceanography, Shanghai Jiao Tong University, Shanghai 200030, China, and also with Key Laboratory of Polar Ecosystem and Climate Change (Shanghai Jiao Tong University), Ministry of Education, Shanghai, China. Ruibo Lei is with Key Laboratory for Polar Science, Ministry of Natural Resources, Polar Research Institute of China, Shanghai, China. Yu Zhang is with College of Oceanography and Ecological Science, Shanghai Ocean University, Shanghai 201306, China, and also with Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China.