Abstract:
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.
Keywords:
Arctic, CryoSat-2, sea ice, sea ice freeboard, sea ice thickness
Landy, J., & Dawson, G. (2022). Year-round Arctic sea ice thickness from CryoSat-2 Baseline-D Level 1b observations 2010-2020 (Version 1.0) [Data set]. NERC EDS UK Polar Data Centre. https://doi.org/10.5285/d8c66670-57ad-44fc-8fef-942a46734ecb
| Access Constraints: | No restrictions apply. |
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| Use Constraints: | Data supplied under Open Government Licence v3.0 http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/. Please cite the indicated publications if using this dataset. |
| Creation Date: | 2022-02-28 |
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| Dataset Progress: | Complete |
| Dataset Language: | English |
| ISO Topic Categories: |
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| Parameters: |
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| Personnel: | |
| Name | UK Polar Data Centre |
| Role(s) | Metadata Author |
| Organisation | British Antarctic Survey |
| Name | Jack Landy |
| Role(s) | Investigator, Technical Contact |
| Organisation | University of Bristol |
| Name | Geoffrey Dawson |
| Role(s) | Investigator |
| Organisation | University of Bristol |
| Parent Dataset: | N/A |
| Reference: | Please cite the following publications if using this dataset: Landy, J.C., Dawson, G.J., Tsamados, M. et al. A year-round satellite sea-ice thickness record from CryoSat-2. Nature (2022) Volume 609 Issue 7927. https://doi.org/10.1038/s41586-022-05058-5 Dawson, G., Landy, J., Tsamados, M., Komarov, A.S., Howell, S., Heorton, H. and Krumpen, T., 2022. A 10-year record of Arctic summer sea ice freeboard from CryoSat-2. Remote Sensing of Environment, 268, p.112744. https://doi.org/10.1016/j.rse.2021.112744. Other relevant publications: Landy, J.C., Tsamados, M. and Scharien, R.K., 2019. A facet-based numerical model for simulating SAR altimeter echoes from heterogeneous sea ice surfaces. IEEE Transactions on Geoscience and Remote Sensing, 57(7), 4164 - 4180. https://doi.org/10.1109/TGRS.2018.2889763. Landy, J.C., Petty, A.A., Tsamados, M. and Stroeve, J.C., 2020. Sea ice roughness overlooked as a key source of uncertainty in CryoSat-2 ice freeboard retrievals. Journal of Geophysical Research: Oceans, 125(5), p.e2019JC015820. https://doi.org/10.1029/2019JC015820. Liston, G.E., Itkin, P., Stroeve, J., Tschudi, M., Stewart, J.S., Pedersen, S.H., Reinking, A.K. and Elder, K., 2020. A Lagrangian snow-evolution system for sea-ice applications (SnowModel-LG): Part I-Model description. Journal of Geophysical Research: Oceans, 125(10), p.e2019JC015913. https://doi.org/10.1029/2019jc015913. Stroeve, J., Liston, G.E., Buzzard, S., Zhou, L., Mallett, R., Barrett, A., Tschudi, M., Tsamados, M., Itkin, P. and Stewart, J.S., 2020. A Lagrangian snow evolution system for sea ice applications (SnowModel-LG): Part II-Analyses. Journal of Geophysical Research: Oceans, 125(10), p.e2019JC015900. https://doi.org/10.1029/2019jc015900. |
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| Quality: | 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 80-km gridded sea ice thickness data. NetCDF files contain detailed descriptions of each derived parameter, both in the main sea ice thickness and developer's products. | |
| Lineage: | The data is derived from CryoSat-2 Baseline-D Level 1b waveform observations over the Arctic, north of 50 degrees latitude, for 2010 to 2020. | |
| Temporal Coverage: | |
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| Start Date | 2010-10-01 |
| End Date | 2020-07-31 |
| Spatial Coverage: | |
| Latitude | |
| Southernmost | 50 |
| Northernmost | 90 |
| Longitude | |
| Westernmost | -180 |
| Easternmost | 180 |
| Altitude | |
| Min Altitude | N/A |
| Max Altitude | N/A |
| Depth | |
| Min Depth | N/A |
| Max Depth | N/A |
| Data Resolution: | |
| Latitude Resolution | N/A |
| Longitude Resolution | N/A |
| Horizontal Resolution Range | 50 km - < 100 km or approximately .5 degree - < 1 degree |
| Vertical Resolution | N/A |
| Vertical Resolution Range | N/A |
| Temporal Resolution | Biweekly |
| Temporal Resolution Range | Weekly - < Monthly |
| Location: | |
| Location | Arctic |
| Detailed Location | Arctic Ocean |
| Sensor(s): |
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| Data Collection: | European Space Agency's CryoSat-2. |
| Distribution: | |
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| Distribution Media | Online Internet (HTTP) |
| Distribution Size | 282 MB |
| Distribution Format | netCDF |
| Fees | N/A |
| Distribution Media | Online Internet (HTTP) |
| Distribution Size | 37 MB |
| Distribution Format | TIFF |
| Fees | N/A |
| Data Storage: | PRODUCT #1: "SEA ICE THICKNESS" The dataset contains a single NetCDF .nc file, including gridded sea ice thickness derived from CryoSat-2, sea ice thickness uncertainty derived from CryoSat-2, sea ice concentration from OSI-SAF, and sea ice type from NSIDC. Quicklook .tif images for the sea ice thickness and sea ice thickness uncertainty in each year of the record, from 2011 to 2020, are also provided. PRODUCT #2: "DEVELOPERS PRODUCT" The dataset contains ten NetCDF .nc files, each including all gridded biweekly sea ice and auxiliary parameters for a single summer season (May-September) of the record, 2011-2020. |