Articles | Volume 17, issue 1
https://doi.org/10.5194/tc-17-279-2023
https://doi.org/10.5194/tc-17-279-2023
Research article
 | 
20 Jan 2023
Research article |  | 20 Jan 2023

Inter-comparison and evaluation of Arctic sea ice type products

Yufang Ye, Yanbing Luo, Yan Sun, Mohammed Shokr, Signe Aaboe, Fanny Girard-Ardhuin, Fengming Hui, Xiao Cheng, and Zhuoqi Chen

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Cited articles

Aaboe, S., Sørensen, A., Eastwood, S., and Lavergne, T.: Sea ice edge and type daily gridded data from 1978 to present derived from satellite observations, Climate Data Store [data set], https://doi.org/10.24381/cds.29c46d83, 2020. 
Aaboe, S., Down, E., and Eastwood, S.: Global Sea Ice Edge (OSI-402-d) and Type (OSI-403-d) Validation Report, v3.1, in: SAF/OSI/CDOP3/MET-Norway/SCI/RP/224, EUMETSAT OSISAF – Ocean and Sea Ice Satellite Application Facility, 2021a. 
Aaboe, S., Down, E., and Eastwood, S.: Algorithm Theoretical Basis Document for the Global Sea-Ice Edge and Type, v3.4, in: SAF/OSI/CDOP3/MET-Norway/TEC/MA/379, EUMETSAT OSISAF: Ocean and Sea Ice Satellite Application Facility, 2021b. 
Aaboe, S., Sørensen, A., Lavergne, T., and Eastwood, S.: Sea Ice Edge and Sea Ice Type Climate Data Records Algorithm Theoretical Basis Document, v3.1, EU C3S-Copernicus Climate Change Service, Copernicus Climate Change Service, https://datastore.copernicus-climate.eu/documents/satellite-sea-ice-edge-type/v2.0/D1.SIETy.2-v2.0_ATBD-of-v2.0-SeaIceEdgeType-products_v3.1_APPROVED_Ver1.pdf (last access: 1 April 2022), 2021c. 
Aldenhoff, W., Heuzé, C., and Eriksson, L. E. B.: Comparison of ice/water classification in Fram Strait from C- and L-band SAR imagery, Ann. Glaciol., 59, 112–123, https://doi.org/10.1017/aog.2018.7, 2018. 
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Short summary
Arctic sea ice type (SITY) variation is a sensitive indicator of climate change. This study gives a systematic inter-comparison and evaluation of eight SITY products. Main results include differences in SITY products being significant, with average Arctic multiyear ice extent up to 1.8×106 km2; Ku-band scatterometer SITY products generally performing better; and factors such as satellite inputs, classification methods, training datasets and post-processing highly impacting their performance.