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Estimating Arctic Sea Ice Thickness with CryoSat-2 Altimetry Data Using the Least Squares Adjustment Method

Chinese Antarctic Center of Surveying and Mapping, Wuhan University, 129 Luoyu Road, Wuhan 430079, China
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Sensors 2020, 20(24), 7011; https://doi.org/10.3390/s20247011
Received: 15 October 2020 / Revised: 5 December 2020 / Accepted: 6 December 2020 / Published: 8 December 2020
(This article belongs to the Section Remote Sensors)
Satellite altimeters can be used to derive long-term and large-scale sea ice thickness changes. Sea ice thickness retrieval is based on measurements of freeboard, and the conversion of freeboard to thickness requires knowledge of the snow depth and snow, sea ice, and sea water densities. However, these parameters are difficult to be observed concurrently with altimeter measurements. The uncertainties in these parameters inevitably cause uncertainties in sea ice thickness estimations. This paper introduces a new method based on least squares adjustment (LSA) to estimate Arctic sea ice thickness with CryoSat-2 measurements. A model between the sea ice freeboard and thickness is established within a 5 km × 5 km grid, and the model coefficients and sea ice thickness are calculated using the LSA method. Based on the newly developed method, we are able to derive estimates of the Arctic sea ice thickness for 2010 through 2019 using CryoSat-2 altimetry data. Spatial and temporal variations of the Arctic sea ice thickness are analyzed, and comparisons between sea ice thickness estimates using the LSA method and three CryoSat-2 sea ice thickness products (Alfred Wegener Institute (AWI), Centre for Polar Observation and Modelling (CPOM), and NASA Goddard Space Flight Centre (GSFC)) are performed for the 2018–2019 Arctic sea ice growth season. The overall differences of sea ice thickness estimated in this study between AWI, CPOM, and GSFC are 0.025 ± 0.640 m, 0.143 ± 0.640 m, and −0.274 ± 0.628 m, respectively. Large differences between the LSA and three products tend to appear in areas covered with thin ice due to the limited accuracy of CryoSat-2 over thin ice. Spatiotemporally coincident Operation IceBridge (OIB) thickness values are also used for validation. Good agreement with a difference of 0.065 ± 0.187 m is found between our estimates and the OIB results. View Full-Text
Keywords: Arctic; sea ice thickness; CryoSat-2; seasonal and annual variations; least squares adjustment Arctic; sea ice thickness; CryoSat-2; seasonal and annual variations; least squares adjustment
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MDPI and ACS Style

Xiao, F.; Li, F.; Zhang, S.; Li, J.; Geng, T.; Xuan, Y. Estimating Arctic Sea Ice Thickness with CryoSat-2 Altimetry Data Using the Least Squares Adjustment Method. Sensors 2020, 20, 7011. https://doi.org/10.3390/s20247011

AMA Style

Xiao F, Li F, Zhang S, Li J, Geng T, Xuan Y. Estimating Arctic Sea Ice Thickness with CryoSat-2 Altimetry Data Using the Least Squares Adjustment Method. Sensors. 2020; 20(24):7011. https://doi.org/10.3390/s20247011

Chicago/Turabian Style

Xiao, Feng, Fei Li, Shengkai Zhang, Jiaxing Li, Tong Geng, and Yue Xuan. 2020. "Estimating Arctic Sea Ice Thickness with CryoSat-2 Altimetry Data Using the Least Squares Adjustment Method" Sensors 20, no. 24: 7011. https://doi.org/10.3390/s20247011

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