Effect of sea ice deformation on winter ice thickness in Arctic based on CICE model simulation results

Li Hao; Su Jie

doi:10.12284/hyxb2023092

Volume 45 Issue 8

Aug. 2023

Turn off MathJax

Article Contents

Article Navigation > Haiyang Xuebao > 2023 > 45(8): 46-61

Li Hao，Su Jie. Effect of sea ice deformation on winter ice thickness in Arctic based on CICE model simulation results[J]. Haiyang Xuebao，2023, 45(8)：46–61 doi: 10.12284/hyxb2023092

Citation:

Li Hao，Su Jie. Effect of sea ice deformation on winter ice thickness in Arctic based on CICE model simulation results[J]. Haiyang Xuebao，2023, 45(8)：46–61 doi: 10.12284/hyxb2023092

Citation:

Li Hao，Su Jie. Effect of sea ice deformation on winter ice thickness in Arctic based on CICE model simulation results[J]. Haiyang Xuebao，2023, 45(8)：46–61 doi: 10.12284/hyxb2023092

PDF( 5194 KB)

Effect of sea ice deformation on winter ice thickness in Arctic based on CICE model simulation results

doi: 10.12284/hyxb2023092

Li Hao^{1, 2, 3
,},
Su Jie^{1, 2, 3
,
,}

1.
College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao 266100, China
2.
Key Laboratory of Physical Oceanography, Ministry of Education, Ocean University of China, Qingdao 266100, China
3.
University Corporation for Polar Research, Beijing 100875, China

Received Date: 2022-12-13
Rev Recd Date: 2023-03-23

Available Online: 2023-08-18

Publish Date: 2023-08-31

Abstract

Abstract

Sea ice numerical model is an effective way to study the dynamical and thermal state parameters of sea ice and the connections between them. The current assessment of the results of numerical ice thickness simulation is much less than the sea ice extent/area and concentration, and the study of the influence of ice velocity and sea ice deformation on ice thickness distribution is still lacking. We simulated the Arctic sea ice variability from 1980 to 2018 using the Los Alamos sea ice model (CICE), and validated and comparison the CICE simulation results using remote sensing and assimilated ice thickness data. We further analyzed the effects of simulated ice velocity and sea ice deformation on ice thickness, and calculated the contributions of ice velocity divergence and shear bias to ice thickness bias. The results show that the interannual variability of the mean ice thickness and ice speed in the Arctic north of 70°N is reasonable, but the multi-year trends of the simulated mean ice thickness and ice speed are smaller than the variability of the assimilated data; the differences in the spatial distribution of the simulated and observed ice thickness are closely related to the deviations of the ice speed and deformation rate, mainly in the positive deviation in the Beaufort Sea and the negative deviation in the Arctic central zone to Fram Strait. The contribution of divergence and shear deviation to ice thickness deviation in the pan-Arctic region fluctuates between 13% and 16% before March, and jumps from 16% to 27% in March-April. The divergence bias dominates the positive bias of ice thickness in the Beaufort Sea region in November and December, while the shear bias dominates the negative ice thickness bias in the winter in the ocean north of the Canadian archipelago and in the region of the Arctic transpolar drift.
- Arctic,
- ice thickness,
- ice velocity,
- deformation,
- simulation results

FullText(HTML)

References(43)

References

[1]	Walsh J E. The role of sea ice in climatic variability: theories and evidence[J]. Atmosphere-Ocean, 1983, 21(3): 229−242. doi: 10.1080/07055900.1983.9649166
[2]	Stroeve J, Holland M M, Meier W, et al. Arctic sea ice decline: faster than forecast[J]. Geophysical Research Letters, 2007, 34(9): L09501.
[3]	Ding Qinghua, Schweiger A, L’Heureux M, et al. Influence of high-latitude atmospheric circulation changes on summertime Arctic sea ice[J]. Nature Climate Change, 2017, 7(4): 289−295. doi: 10.1038/nclimate3241
[4]	Renner A H H, Gerland S, Haas C, et al. Evidence of Arctic sea ice thinning from direct observations[J]. Geophysical Research Letters, 2014, 41(14): 5029−5036. doi: 10.1002/2014GL060369
[5]	Kacimi S, Kwok R. Arctic snow depth, ice thickness, and volume from ICESat-2 and CryoSat-2: 2018–2021[J]. Geophysical Research Letters, 2022, 49(5): e2021GL097448.
[6]	Rampal P, Weiss J, Marsan D. Positive trend in the mean speed and deformation rate of Arctic sea ice, 1979–2007[J]. Journal of Geophysical Research: Oceans, 2009, 114(C5): C05013.
[7]	Kwok R, Spreen G, Pang S. Arctic sea ice circulation and drift speed: Decadal trends and ocean currents[J]. Journal of Geophysical Research: Oceans, 2013, 118(5): 2408−2425. doi: 10.1002/jgrc.20191
[8]	Rothrock D A, Zhang J, Yu Youran. The Arctic ice thickness anomaly of the 1990s: a consistent view from observations and models[J]. Journal of Geophysical Research: Oceans, 2003, 108(C3): 3083. doi: 10.1029/2001JC001208
[9]	Kwok R. Arctic sea ice thickness, volume, and multiyear ice coverage: losses and coupled variability (1958–2018)[J]. Environmental Research Letters, 2018, 13(10): 105005. doi: 10.1088/1748-9326/aae3ec
[10]	Spreen G, Kwok R, Menemenlis D. Trends in Arctic sea ice drift and role of wind forcing: 1992−2009[J]. Geophysical Research Letters, 2011, 38(19): L19501.
[11]	Zhang Fanyi, Pang Xiaoping, Lei Ruibo, et al. Arctic sea ice motion change and response to atmospheric forcing between 1979 and 2019[J]. International Journal of Climatology, 2022, 42(3): 1854−1876. doi: 10.1002/joc.7340
[12]	Docquier D, Massonnet F, Barthélemy A, et al. Relationships between Arctic sea ice drift and strength modelled by NEMO-LIM3.6[J]. The Cryosphere, 2017, 11(6): 2829−2846. doi: 10.5194/tc-11-2829-2017
[13]	Chikhar K, Lemieux J F, Dupont F, et al. Sensitivity of ice drift to form drag and ice strength parameterization in a coupled ice–ocean model[J]. Atmosphere-Ocean, 2019, 57(5): 329−349. doi: 10.1080/07055900.2019.1694859
[14]	Itkin P, Spreen G, Hvidegaard S M, et al. Contribution of deformation to sea ice mass balance: a case study from an N-ICE2015 storm[J]. Geophysical Research Letters, 2018, 45(2): 789−796. doi: 10.1002/2017GL076056
[15]	Kwok R, Cunningham G F. Contributions of growth and deformation to monthly variability in sea ice thickness north of the coasts of Greenland and the Canadian Arctic archipelago[J]. Geophysical Research Letters, 2016, 43(15): 8097−8105. doi: 10.1002/2016GL069333
[16]	von Albedyll L, Haas C, Dierking W. Linking sea ice deformation to ice thickness redistribution using high-resolution satellite and airborne observations[J]. The Cryosphere, 2021, 15(5): 2167−2186. doi: 10.5194/tc-15-2167-2021
[17]	von Albedyll L, Hendricks S, Grodofzig R, et al. Thermodynamic and dynamic contributions to seasonal Arctic sea ice thickness distributions from airborne observations[J]. Elementa: Science of the Anthropocene, 2022, 10(1): 00074. doi: 10.1525/elementa.2021.00074
[18]	Krumpen T, von Albedyll L, Goessling H F, et al. MOSAiC drift expedition from October 2019 to July 2020: sea ice conditions from space and comparison with previous years[J]. The Cryosphere, 2021, 15(8): 3897−3920. doi: 10.5194/tc-15-3897-2021
[19]	Barnhart K R, Miller C R, Overeem I, et al. Mapping the future expansion of Arctic open water[J]. Nature Climate Change, 2016, 6(3): 280−285. doi: 10.1038/nclimate2848
[20]	DuVivier A K, Holland M M, Kay J E, et al. Arctic and Antarctic sea ice mean state in the community earth system model version 2 and the influence of atmospheric chemistry[J]. Journal of Geophysical Research: Oceans, 2020, 125(8): e2019JC015934.
[21]	Shu Qi, Wang Qiang, Song Zhenya, et al. Assessment of sea ice extent in CMIP6 with comparison to observations and CMIP5[J]. Geophysical Research Letters, 2020, 47(9): e2020GL087965.
[22]	Wang Huazhao, Zhang Lijun, Chu Min, et al. Advantages of the latest Los Alamos sea-ice model (CICE): evaluation of the simulated spatiotemporal variation of Arctic sea ice[J]. Atmospheric and Oceanic Science Letters, 2020, 13(2): 113−120. doi: 10.1080/16742834.2020.1712186
[23]	王松, 苏洁, 储敏, 等. BCC_CSM对北极海冰的模拟: CMIP5和CMIP6历史试验比较[J]. 海洋学报, 2020, 42(5): 49−64. Wang Song, Su Jie, Chu Min, et al. Comparison of simulation results of the Arctic sea ice by BCC_CSM: CMIP5 and CMIP6 historical experiments[J]. Haiyang Xuebao, 2020, 42(5): 49−64.
[24]	Yu Xiaoyong, Rinke A, Dorn W, et al. Evaluation of Arctic sea ice drift and its dependency on near-surface wind and sea ice conditions in the coupled regional climate model HIRHAM–NAOSIM[J]. The Cryosphere, 2020, 14(5): 1727−1746. doi: 10.5194/tc-14-1727-2020
[25]	房永杰, 储敏, 吴统文, 等. CICE5.0与BCC_CSM2.0模式的耦合及对北极海冰的模拟评估[J]. 海洋学报, 2017, 39(5): 33−43. Fang Yongjie, Chu Min, Wu Tongwen, et al. Couping of CICE5.0 with BCC_CSM2.0 model and its performance evaluation on Arctic sea ice simulation[J]. Haiyang Xuebao, 2017, 39(5): 33−43.
[26]	Ricker R, Hendricks S, Kaleschke L, et al. A weekly Arctic sea-ice thickness data record from merged CryoSat-2 and SMOS satellite data[J]. The Cryosphere, 2017, 11(4): 1607−1623. doi: 10.5194/tc-11-1607-2017
[27]	Zhang Jinlun, Rothrock D A. Modeling global sea ice with a thickness and enthalpy distribution model in generalized curvilinear coordinates[J]. Monthly Weather Review, 2003, 131(5): 845−861. doi: 10.1175/1520-0493(2003)131<0845:MGSIWA>2.0.CO;2
[28]	Tschudi M A, Meier W N, Stewart J S. An enhancement to sea ice motion and age products at the National Snow and Ice Data Center (NSIDC)[J]. The Cryosphere, 2020, 14(5): 1519−1536. doi: 10.5194/tc-14-1519-2020
[29]	Lavergne T, Eastwood S, Teffah Z, et al. Sea ice motion from low-resolution satellite sensors: an alternative method and its validation in the Arctic[J]. Journal of Geophysical Research: Oceans, 2010, 115(C10): C10032.
[30]	Cavalieri D J, Parkinson C L, Gloersen P, et al. Deriving long-term time series of sea ice cover from satellite passive-microwave multisensor data sets[J]. Journal of Geophysical Research: Oceans, 1999, 104(C7): 15803−15814. doi: 10.1029/1999JC900081
[31]	Wu Shuqiang, Zeng Qingcun, Bi Xunqiang. Modeling of Arctic sea ice variability during 1948–2009: validation of two versions of the Los Alamos sea ice model (CICE)[J]. Atmospheric and Oceanic Science Letters, 2015, 8(4): 215−219. doi: 10.1080/16742834.2015.11447262
[32]	Hersbach H, Bell B, Berrisford P, et al. The ERA5 global reanalysis[J]. Quarterly Journal of the Royal Meteorological Society, 2020, 146(730): 1999−2049. doi: 10.1002/qj.3803
[33]	Kerbyson D J, Jones P W. A performance model of the parallel ocean program[J]. The International Journal of High Performance Computing Applications, 2005, 19(3): 261−276. doi: 10.1177/1094342005056114
[34]	Steele M, Morley R, Ermold W. PHC: a global ocean hydrography with a high-quality Arctic Ocean[J]. Journal of Climate, 2001, 14(9): 2079−2087. doi: 10.1175/1520-0442(2001)014<2079:PAGOHW>2.0.CO;2
[35]	Kwok R, Hunke E C, Maslowski W, et al. Variability of sea ice simulations assessed with RGPS kinematics[J]. Journal of Geophysical Research: Oceans, 2008, 113(C11): C11012. doi: 10.1029/2008JC004783
[36]	Kumar R, Li Junde, Hedstrom K, et al. Intercomparison of Arctic sea ice simulation in ROMS-CICE and ROMS-Budgell[J]. Polar Science, 2021, 29: 100716. doi: 10.1016/j.polar.2021.100716
[37]	Sumata H, Lavergne T, Girard-Ardhuin F, et al. An intercomparison of Arctic ice drift products to deduce uncertainty estimates[J]. Journal of Geophysical Research: Oceans, 2014, 119(8): 4887−4921. doi: 10.1002/2013JC009724
[38]	施骞, 苏洁. 三种国际主流的北极卫星遥感冰速产品评估和分析[J]. 遥感学报, 2020, 24(7): 867−882. Shi Qian, Su Jie. Assessment of Arctic remote sensing ice motion products based on ice drift buoys[J]. Journal of Remote Sensing, 2020, 24(7): 867−882.
[39]	Hansen E, Gerland S, Granskog M A, et al. Thinning of Arctic sea ice observed in Fram Strait: 1990–2011[J]. Journal of Geophysical Research Oceans, 2013, 118: 5202−5221.
[40]	Rothrock D A. The energetics of the plastic deformation of pack ice by ridging[J]. Journal of Geophysical Research, 1975, 80(33): 4514−4519. doi: 10.1029/JC080i033p04514
[41]	Thorndike A S, Rothrock D A, Maykut G A, et al. The thickness distribution of sea ice[J]. Journal of Geophysical Research, 1975, 80(33): 4501−4513. doi: 10.1029/JC080i033p04501
[42]	Martin T, Tsamados M, Schroeder D, et al. The impact of variable sea ice roughness on changes in Arctic Ocean surface stress: a model study[J]. Journal of Geophysical Research: Oceans, 2016, 121(3): 1931−1952. doi: 10.1002/2015JC011186
[43]	Hoffman J P, Ackerman S A, Liu Yinghui, et al. A 20-year climatology of sea ice leads detected in infrared satellite imagery using a convolutional neural network[J]. Remote Sensing, 2022, 14(22): 5763. doi: 10.3390/rs14225763