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Estimation of Arctic Winter Snow Depth, Sea Ice Thickness and Bulk Density, and Ice Freeboard by Combining CryoSat-2, AVHRR, and AMSR Measurements : Estimation of snow depth, sea ice thickness and bulk density, and ice freeboard in the Arctic winter by combining CryoSat-2, AVHRR, and AMSR measurements

Cited 2 time in Web of Science Cited 2 time in Scopus
Authors

Shi, Hoyeon; Lee, Sang-Moo; Sohn, Byung-Ju; Gasiewski, Albin J.; Meier, Walter N.; Dybkjaer, Gorm; Kim, Sang-Woo

Issue Date
2023-04
Publisher
Institute of Electrical and Electronics Engineers
Citation
IEEE Transactions on Geoscience and Remote Sensing, Vol.61, p. 4300718
Abstract
Information on snow depth on sea ice and bulk sea ice density is required to convert CryoSat-2 radar freeboard (hf) into sea ice thickness (SIT). It is difficult to obtain their information on an Arctic basin scale; therefore, most CryoSat-2 SIT products largely rely on the distributions of snow depth and bulk sea ice density derived from parameterizations, which are based on sea ice type and climatological values. Several observational studies have found that the distributions of parameterized variables are inaccurate compared to the actual distributions. This study aims to develop a new type of retrieval algorithm for snow depth, SIT and bulk density, and ice freeboard in the Arctic winter by synergizing active CryoSat-2 with passive microwave and infrared measurements. Two parameterizations for the snow-ice thickness ratio and bulk sea ice density were combined with the hydrostatic balance and radar wave speed correction equations. Consequently, solutions for the four target variables were obtained and applied to different CryoSat-2 hf, derived from empirical and waveform-fitting retracker algorithms. The retrieved thickness-related parameters based on hf from the lognormal waveform-fitting retracker algorithm showed good agreement with the airborne snow depth, total freeboard, and mooring ice draft measurements. The retrieved multiyear sea ice bulk density was significantly higher than the value of 882 kg m-3, which was used in the previous density parameterization, showing a higher agreement with values from in-situ measurements. The spatial and interannual variabilities of SIT increased when the results from this study were compared with those based on previous parameterizations.
ISSN
0196-2892
URI
https://hdl.handle.net/10371/201036
DOI
https://doi.org/10.1109/TGRS.2023.3265274
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  • College of Natural Sciences
  • Department of Earth and Environmental Sciences
Research Area Data Assimilation for Numerical Weather Prediction, Radiative Transfer Modeling, Satellite Remote Sensing

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