Pan-Arctic monthly maps of sea surface height anomaly and geostrophic velocity from the satellite altimetry Cryosat-2 mission, 2011-2020

• Main Authors: Doglioni, Francesca, Ricker, Robert, Rabe, Benjamin, Barth, Alexander, Troupin, Charles, Kanzow, Torsten
• Format: Dataset
• Language: English
• Published: PANGAEA 2021
• Subjects: Arctic; CryoSat-2; Current sea ice maps for Arctic and Antarctic; meereisportal.de; ocean circulation; RACE-II; radar altimetry; Regional Atlantic Circulation and global Change II; SAGA__SSHA_GEOVEL__60N_88N__2011_2020; SALT; Satellite altimetry; sea level; Antarctic; Arctic Ocean; Antarc*; Sea ice
• Online Access: https://doi.pangaea.de/10.1594/PANGAEA.931869; https://doi.org/10.1594/PANGAEA.931869

This data set was created with the aim of supporting observational studies of the sea level and surface ocean circulation variability in the Arctic Ocean. The data set was created in the frame of the Regional Atlantic Circulation and global changE (RACE) project. It consists of monthly maps of the Arctic sea surface height anomaly and absolute geostrophic velocity generated from sea surface height observations taken by the European Space Agency's satellite mission Cryosat-2. The dataset spans the period 2011-2020 and was generated by interpolation of satellite altimetry along-track observations onto a regular latitude-longitude grid of resolution 0.25°X0.75°. The sea surface height anomaly observations along the Cryosat-2 satellite tracks used in this work are, for the ice-covered ocean, data from the Alfred Wegner Institute (AWI version 2.4, ftp://ftp.awi.de/sea_ice/projects/cryoawi_ssh), and for the open ocean, data from the Radar Altimetry Database System (RADS, http://rads.tudelft.nl/rads/rads.shtml). The merged AWI+RADS along track data, processed as described in Doglioni et al., 2022 and used to generate the monthly maps, are included in the present file. The along track observations are interpolated on the output grid using the Data-Interpolating Variational Analysis tool (Troupin et al., 2012) with a decorrelation length of 50 km. Detailed methodology for the derivation and assessment of the dataset can be found in Doglioni et al., 2022 (under review). As auxiliary variables, the bin-average of along track sea surface height anomaly, the bin-standard deviation and the number of observations per bin are included.