Literature DB >> 33302393

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

Feng Xiao1, Fei Li1, Shengkai Zhang1, Jiaxing Li1, Tong Geng1, Yue Xuan1.   

Abstract

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.

Entities:  

Keywords:  Arctic; CryoSat-2; least squares adjustment; sea ice thickness; seasonal and annual variations

Year:  2020        PMID: 33302393      PMCID: PMC7762569          DOI: 10.3390/s20247011

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  4 in total

1.  High interannual variability of sea ice thickness in the Arctic region.

Authors:  Seymour Laxon; Neil Peacock; Doug Smith
Journal:  Nature       Date:  2003-10-30       Impact factor: 49.962

2.  The central role of diminishing sea ice in recent Arctic temperature amplification.

Authors:  James A Screen; Ian Simmonds
Journal:  Nature       Date:  2010-04-29       Impact factor: 49.962

3.  Variability of Arctic sea ice thickness and volume from CryoSat-2.

Authors:  R Kwok; G F Cunningham
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2015-07-13       Impact factor: 4.226

4.  Oceanography: All change in the Arctic.

Authors:  Bob Dickson
Journal:  Nature       Date:  1999-02-04       Impact factor: 49.962

  4 in total

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