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

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, th...

Full description

Bibliographic Details
Main Authors: Feng Xiao, Fei Li, Shengkai Zhang, Jiaxing Li, Tong Geng, Yue Xuan
Format: Article
Language:English
Published: MDPI AG 2020-12-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/20/24/7011
id doaj-c66b147fe49545bfa759d1ee7db74d9e
record_format Article
spelling doaj-c66b147fe49545bfa759d1ee7db74d9e2020-12-09T00:01:13ZengMDPI AGSensors1424-82202020-12-01207011701110.3390/s20247011Estimating Arctic Sea Ice Thickness with CryoSat-2 Altimetry Data Using the Least Squares Adjustment MethodFeng Xiao0Fei Li1Shengkai Zhang2Jiaxing Li3Tong Geng4Yue Xuan5Chinese Antarctic Center of Surveying and Mapping, Wuhan University, 129 Luoyu Road, Wuhan 430079, ChinaChinese Antarctic Center of Surveying and Mapping, Wuhan University, 129 Luoyu Road, Wuhan 430079, ChinaChinese Antarctic Center of Surveying and Mapping, Wuhan University, 129 Luoyu Road, Wuhan 430079, ChinaChinese Antarctic Center of Surveying and Mapping, Wuhan University, 129 Luoyu Road, Wuhan 430079, ChinaChinese Antarctic Center of Surveying and Mapping, Wuhan University, 129 Luoyu Road, Wuhan 430079, ChinaChinese Antarctic Center of Surveying and Mapping, Wuhan University, 129 Luoyu Road, Wuhan 430079, ChinaSatellite 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.https://www.mdpi.com/1424-8220/20/24/7011Arcticsea ice thicknessCryoSat-2seasonal and annual variationsleast squares adjustment
collection DOAJ
language English
format Article
sources DOAJ
author Feng Xiao
Fei Li
Shengkai Zhang
Jiaxing Li
Tong Geng
Yue Xuan
spellingShingle Feng Xiao
Fei Li
Shengkai Zhang
Jiaxing Li
Tong Geng
Yue Xuan
Estimating Arctic Sea Ice Thickness with CryoSat-2 Altimetry Data Using the Least Squares Adjustment Method
Sensors
Arctic
sea ice thickness
CryoSat-2
seasonal and annual variations
least squares adjustment
author_facet Feng Xiao
Fei Li
Shengkai Zhang
Jiaxing Li
Tong Geng
Yue Xuan
author_sort Feng Xiao
title Estimating Arctic Sea Ice Thickness with CryoSat-2 Altimetry Data Using the Least Squares Adjustment Method
title_short Estimating Arctic Sea Ice Thickness with CryoSat-2 Altimetry Data Using the Least Squares Adjustment Method
title_full Estimating Arctic Sea Ice Thickness with CryoSat-2 Altimetry Data Using the Least Squares Adjustment Method
title_fullStr Estimating Arctic Sea Ice Thickness with CryoSat-2 Altimetry Data Using the Least Squares Adjustment Method
title_full_unstemmed Estimating Arctic Sea Ice Thickness with CryoSat-2 Altimetry Data Using the Least Squares Adjustment Method
title_sort estimating arctic sea ice thickness with cryosat-2 altimetry data using the least squares adjustment method
publisher MDPI AG
series Sensors
issn 1424-8220
publishDate 2020-12-01
description 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.
topic Arctic
sea ice thickness
CryoSat-2
seasonal and annual variations
least squares adjustment
url https://www.mdpi.com/1424-8220/20/24/7011
work_keys_str_mv AT fengxiao estimatingarcticseaicethicknesswithcryosat2altimetrydatausingtheleastsquaresadjustmentmethod
AT feili estimatingarcticseaicethicknesswithcryosat2altimetrydatausingtheleastsquaresadjustmentmethod
AT shengkaizhang estimatingarcticseaicethicknesswithcryosat2altimetrydatausingtheleastsquaresadjustmentmethod
AT jiaxingli estimatingarcticseaicethicknesswithcryosat2altimetrydatausingtheleastsquaresadjustmentmethod
AT tonggeng estimatingarcticseaicethicknesswithcryosat2altimetrydatausingtheleastsquaresadjustmentmethod
AT yuexuan estimatingarcticseaicethicknesswithcryosat2altimetrydatausingtheleastsquaresadjustmentmethod
_version_ 1724388799081873408