Arctic sea ice and physical oceanography derived from CryoSat-2 Baseline-C Level 1b waveform observations, Oct-Apr 2010-2018

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 circula...

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Bibliographic Details
Main Authors: Landy, Jack, Stroeve, Julienne
Format: Dataset
Language:English
Published: UK Polar Data Centre, Natural Environment Research Council, UK Research & Innovation 2020
Subjects:
Online Access:https://dx.doi.org/10.5285/cbd2cf78-462a-4968-be20-05f9c125ad10
https://data.bas.ac.uk/full-record.php?id=GB/NERC/BAS/PDC/01257
Description
Summary: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. : The data is derived from CryoSat-2 Baseline-C Level 1b waveform observations over the Arctic, north of 50 degrees altitude, for 2010 to 2018. : European Space Agency's CryoSat-2. : NetCDF files were produced from the final gridded satellite observations and contain all associated metadata, or details about auxiliary datasets used in the processor. No smoothing or averaging was performed on the 25-km gridded sea ice and sea surface height parameters. A 300-km Gaussian convolution filter was used to smooth artefacts in the dynamic ocean topography grids, before deriving geostrophic currents. 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.