This dataset presents monthly gridded sea ice and ocean parameters for the Arctic derived from the European Space Agency's satellite CryoSat-2. Parameters include sea ice freeboard, sea ice thickness, sea ice surface roughness, mean sea surface height, sea level anomaly, and geostrophic circulation. Data are provided as monthly grids with a resolution of 25 km, mapped onto the NSIDC EASE2-Grid, covering the Arctic region north of 50 degrees latitude, for all winter months (Oct-Apr) between 2010 and 2018. CryoSat-2 Level 1b Baseline C observed waveforms have been retracked using a numerical model for the SAR altimeter backscattered echo from snow-covered sea ice presented in Landy et al. (2019), which offers a sophisticated physically-based treatment of the effect of ice surface roughness on retracked ice and ocean elevations. Methods for optimizing echo model fits to observed CryoSat-2 waveforms, retracking waveforms, classifying returns, deriving sea ice freeboard, and converting to thickness are detailed in Landy et al. (In Review). This dataset contains derived sea ice thicknesses from two processing chains, the first using the conventional snow depth and density climatology from Warren et al. (1999) and the second using reanalysis and model-based snow data from SnowModel (Stroeve et al., In Review). Sea surface height and ocean topography grids were derived from only those CryoSat-2 samples classified as leads. Both the random and systematic uncertainties relevant for each parameter have been carefully estimated and are provided in the data files. NetCDF files contain detailed descriptions of each derived parameter. Funding was provided by ESA Living Planet Fellowship Arctic-SummIT grant ESA/4000125582/18/I-NS and NERC Project PRE-MELT grant NE/T000546/1.

This dataset presents biweekly gridded sea ice thickness and uncertainty for the Arctic derived from the European Space Agency's satellite CryoSat-2. An associated 'developer's product' also includes intermediate parameters used or output in the sea ice thickness processing chain. Data are provided as biweekly grids with a resolution of 80 km, mapped onto a Northern Polar Stereographic Grid, covering the Arctic region north of 50 degrees latitude, for all months of the year between October 2010 and July 2020. CryoSat-2 Level 1b Baseline-D observed radar waveforms have been retracked using two different approaches, one for the 'cold season' months of October-April and the second for 'melting season' months of May-September. The cold season retracking algorithm uses a numerical model for the SAR altimeter backscattered echo from snow-covered sea ice presented in Landy et al. (2019), which offers a physical treatment of the effect of ice surface roughness on retracked ice and ocean elevations. The method for optimizing echo model fits to observed CryoSat-2 waveforms, retracking waveforms, classifying returns, and deriving sea ice radar freeboard are detailed in Landy et al. (2020). The melting season retracking algorithm uses the SAMOSA+ analytical echo model with optimization to observed CryoSat-2 waveforms through the SARvatore (SAR Versatile Altimetric Toolkit for Ocean Research and Exploitation) service available through ESA Grid Processing on Demand (GPOD). The method for classifying radar returns and deriving sea ice radar freeboard in the melting season are detailed in Dawson et al. (2022). The melting season sea ice radar freeboards require a correction for an electromagnetic range bias, as described in Landy et al. (2022). After applying the correction, year-round freeboards are converted to sea ice thickness using auxiliary satellite observations of the sea ice concentration and type, as well as snow depth and density estimates from a Lagrangian snow evolution scheme: SnowModel-LG (Stroeve et al., 2020; Liston et al., 2020). The sea ice thickness uncertainties have been estimated based on methods described in Landy et al. (2022). NetCDF files contain detailed descriptions of each parameter. Funding was provided by the NERC PRE-MELT grant NE/T000546/1 and the ESA Living Planet Fellowship Arctic-SummIT grant ESA/4000125582/18/I-NS.

Prior and posterior uncertainties of sea ice volume (SIV, columns 4-6) and snow volume (SNV, columns 7-9) respectively for three regions in km3. Column 1 indicates observation, column 2 indicates uncertainty range ("product" refers to uncertainty specification provided with product), column 3 indicates uncertainty range of additional hypothetical snow product ("-" means no snow product is used). In each of columns 4-9 the lowest uncertainty range is highlighted in bold face font. The two bottom rows give estimates for the uncertainty due to model error, i.e. the residual uncertainty with optimal control vector.

Estimates of these four freshwater fluxes: discharge from rivers; inflow through ice and melt run off; outflow of freshwater in sea ice; and in/outflow of freshwater through ocean currents.