Simulation and projection of Arctic snow ice by the EC-Earth3 climate model

Yang Xinrui; Zhao Jiechen; Wang Shizhu; Xu Minghuan; Zhang Zixuan; Chen Yuhan; Wang Jingjing; Jiang Chen

doi:10.12284/hyxb2025003

Volume 47 Issue 2

Feb. 2025

Turn off MathJax

Article Contents

Article Navigation > Haiyang Xuebao > 2025 > 47(2): 41-55

Yang Xinrui，Zhao Jiechen，Wang Shizhu, et al. Simulation and projection of Arctic snow ice by the EC-Earth3 climate model[J]. Haiyang Xuebao，2025, 47(2)：41–55 doi: 10.12284/hyxb2025003

Citation:

Yang Xinrui，Zhao Jiechen，Wang Shizhu, et al. Simulation and projection of Arctic snow ice by the EC-Earth3 climate model[J]. Haiyang Xuebao，2025, 47(2)：41–55 doi: 10.12284/hyxb2025003

Citation:

Yang Xinrui，Zhao Jiechen，Wang Shizhu, et al. Simulation and projection of Arctic snow ice by the EC-Earth3 climate model[J]. Haiyang Xuebao，2025, 47(2)：41–55 doi: 10.12284/hyxb2025003

PDF( 9649 KB)

Simulation and projection of Arctic snow ice by the EC-Earth3 climate model

doi: 10.12284/hyxb2025003

Yang Xinrui^{1, 2
,},
Zhao Jiechen^{2, 3, 4
,
,},
Wang Shizhu⁴,
Xu Minghuan^{1, 2},
Zhang Zixuan^{1, 2},
Chen Yuhan^{1, 2},
Wang Jingjing^{1, 2},
Jiang Chen^{1, 2}

1.
Qingdao Innovation and Development Base of Harbin Engineering University, Qingdao 266000, China
2.
Laboratory for Regional Oceanography and Numerical Modeling, Qingdao Marine Science and Technology Center, Qingdao 266000, China
3.
UN Decade Collaborative Centre on Ocean-Climate Nexus and Coordination Amongst Decade Implementing Partners in P.R.China, Qingdao 266000, China
4.
First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, China

Received Date: 2024-09-10
Rev Recd Date: 2024-12-02
Publish Date: 2025-02-28

Abstract

Abstract

Snow ice is the product of the transformation from snow into sea ice, which plays an important role in the change of sea ice structure. Studying the spatial and temporal variations of snow ice can provide deep insights into the “snow-ice” transformation process and help understand the evolution of sea ice and polar climate changes. This paper utilizes the EC-Earth3 model to analyze snow ice and its influencing factors in both historical simulations (1990−2014) and Shared Socioeconomic Pathways SSP245 projections (2015−2100). The spatiotemporal evolution of snow ice growth in historical and future periods was investigated by statistical methods such as ensemble averaging, regression analysis, and Mann-Kendall trend test. Compared with the satellite observation sea ice density data of the National Ice and Snow Data Center, the results indicate that the EC-Earth3 model performs well in reconstructing the observed sea ice, and hence provides confidence in projecting the future ice variation. Snow ice primarily forms in winter and spring, with distribution in the Davis Strait, the Nordic Seas, and the northern Barents Sea. The average decrease trend of snow ice growth is 7.4 × 10⁸ kg/a; the change of the average sea ice outer edge line is about 1 kg/m² in spring and winter; the highest proportion of snow ice is in the southeast of Greenland with an average of about 2%. Increased snowfall, rainfall and rising temperatures are important factors affecting snow ice formation. Future projections suggest that the generation of snow ice is still mainly concentrated in spring and winter, and the total amount of snow ice growth will decrease by 2.6 × 10⁸ kg/a on average; due to the increase of precipitation and temperature increase, the maximum increase trend of snow ice annual in March in the study area is 0.7 kg/m², and the proportion of snow ice in ice thickness increases year by year. The analysis of future scenario experiment results has important scientific reference value for the development and utilization of Arctic waterway and the design of icebreaker capacity.
- Arctic sea ice,
- snow ice evolution,
- EC-Earth3 model,
- historical period,
- future scenario

FullText(HTML)

References(27)

References

[1]	Rantanen M, Karpechko A Y, Lipponen A, et al. The Arctic has warmed nearly four times faster than the globe since 1979[J]. Communications Earth & Environment, 2022, 3(1): 168
[2]	Webster M A, Rigor I G, Nghiem S V, et al. Interdecadal changes in snow depth on Arctic sea ice[J]. Journal of Geophysical Research: Oceans, 2014, 119(8): 5395−5406. doi: 10.1002/2014JC009985
[3]	Leppäranta M. Freezing of Lakes and the Evolution of Their Ice Cover[M]. Berlin/Heidelberg, Germany: Springer, 2015.
[4]	Moslet P O. Field testing of uniaxial compression strength of columnar sea ice[J]. Cold Regions Science and Technology, 2007, 48(1): 1−14. doi: 10.1016/j.coldregions.2006.08.025
[5]	Fernández-Méndez M, Olsen L M, Kauko H M, et al. Algal hot spots in a changing Arctic Ocean: sea-ice ridges and the snow-ice interface[J]. Frontiers in Marine Science, 2018, 5: 75. doi: 10.3389/fmars.2018.00075
[6]	Haas C, Thomas D N, Bareiss J. Surface properties and processes of perennial Antarctic sea ice in summer[J]. Journal of Glaciology, 2001, 47(159): 613−625. doi: 10.3189/172756501781831864
[7]	Vavrus S J, Wynne R H, Foley J A. Measuring the sensitivity of southern Wisconsin lake ice to climate variations and lake depth using a numerical model[J]. Limnology and Oceanography, 1996, 41(5): 822−831. doi: 10.4319/lo.1996.41.5.0822
[8]	Fichefet T, Maqueda M A M. Modelling the influence of snow accumulation and snow-ice formation on the seasonal cycle of the Antarctic sea-ice cover[J]. Climate Dynamics, 1999, 15(4): 251−268. doi: 10.1007/s003820050280
[9]	Wang Caixin, Cheng Bin, Wang Keguang, et al. Modelling snow ice and superimposed ice on landfast sea ice in Kongsfjorden, Svalbard[J]. Polar Research, 2015, 34(1): 20828. doi: 10.3402/polar.v34.20828
[10]	Ohata Y, Toyota T, Shiraiwa T. Lake ice formation processes and thickness evolution at Lake Abashiri, Hokkaido, Japan[J]. Journal of Glaciology, 2016, 62(233): 563−578. doi: 10.1017/jog.2016.57
[11]	Merkouriadi I, Cheng Bin, Graham R M, et al. Critical role of snow on sea ice growth in the Atlantic sector of the Arctic Ocean[J]. Geophysical Research Letters, 2017, 44(20): 10,479−10,485.
[12]	Perovich D K, Roesler C S, Pegau W S. Variability in Arctic sea ice optical properties[J]. Journal of Geophysical Research: Oceans, 1998, 103(C1): 1193−1208. doi: 10.1029/97JC01614
[13]	Merkouriadi I, Liston G E, Graham R M, et al. Quantifying the potential for snow-ice formation in the Arctic Ocean[J]. Geophysical Research Letters, 2020, 47(4): e2019GL085020. doi: 10.1029/2019GL085020
[14]	Shu Q, Song Z, Qiao F. Assessment of sea ice simulations in the CMIP5 models[J]. The Cryosphere, 2015, 9(1): 399−409. doi: 10.5194/tc-9-399-2015
[15]	Cheng Bin, Launiainen J, Vihma T. Modelling of superimposed ice formation and subsurface melting in the Baltic Sea[J]. Geophysica, 2003, 39(1/2): 31−50.
[16]	Cheng Bin, Zhang Zhanhai, Vihma T, et al. Model experiments on snow and ice thermodynamics in the Arctic Ocean with CHINARE 2003 data[J]. Journal of Geophysical Research: Oceans, 2008, 113(C9): C09020.
[17]	杨清华, 程斌, 雷瑞波, 等. 北极夏季海冰反照率的观测和数值模拟试验[J]. 海洋学报, 2011, 33(2): 42−47. Yang Qinghua, Cheng Bin, Lei Ruibo, et al. Arctic sea ice albedo in summer: observation and modelling experiments[J]. Haiyang Xuebao, 2011, 33(2): 42−47.
[18]	Zhao Jiechen, Cheng Bin, Vihma T, et al. Observation and thermodynamic modeling of the influence of snow cover on landfast sea ice thickness in Prydz Bay, East Antarctica[J]. Cold Regions Science and Technology, 2019, 168: 102869. doi: 10.1016/j.coldregions.2019.102869
[19]	Döscher R, Acosta M, Alessandri A, et al. The EC-Earth3 Earth system model for the Coupled Model Intercomparison Project 6[J]. Geoscientific Model Development, 2022, 15(7): 2973−3020. doi: 10.5194/gmd-15-2973-2022
[20]	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
[21]	Vancoppenolle M, Bouillon S, Fichefet T, et al. The Louvain-la-Neuve sea ice model[J]. Notes du pole de modélisation, Institut Pierre-Simon Laplace (IPSL), Paris, France, 2012, 31.
[22]	Rousset C, Vancoppenolle M, Madec G, et al. The Louvain-La-Neuve sea ice model LIM3.6: global and regional capabilities[J]. Geoscientific Model Development, 2015, 8(10): 2991−3005. doi: 10.5194/gmd-8-2991-2015
[23]	Cheng Bin, Vihma T, Pirazzini R, et al. Modelling of superimposed ice formation during the spring snowmelt period in the Baltic Sea[J]. Annals of Glaciology, 2006, 44: 139−146. doi: 10.3189/172756406781811277
[24]	Gocic M, Trajkovic S. Analysis of changes in meteorological variables using Mann-Kendall and Sen’s slope estimator statistical tests in Serbia[J]. Global and Planetary Change, 2013, 100: 172−182. doi: 10.1016/j.gloplacha.2012.10.014
[25]	李瑜洁, 高晓清, 张录军, 等. 近30年北极海冰运动特征分析[J]. 高原气象, 2019, 38(1): 114−123. doi: 10.7522/j.issn.1000-0534.2018.00115 Li Yujie, Gao Xiaoqing, Zhang Lujun, et al. Analysis on the characteristics of arctic sea ice movement in recent 30 years[J]. Plateau Meteorology, 2019, 38(1): 114−123 doi: 10.7522/j.issn.1000-0534.2018.00115
[26]	何琰, 赵进平. 北欧海的锋面分布特征及其季节变化[J]. 地球科学进展, 2011, 26(10): 1079−1091. He Yan, Zhao Jinping. Distributions and seasonal variations of fronts in GIN seas[J]. Advances in Earth Science, 2011, 26(10): 1079−1091.
[27]	牟龙江, 赵进平. 格陵兰海海冰外缘线变化特征分析[J]. 地球科学进展, 2013, 28(6): 709−717. doi: 10.11867/j.issn.1001-8166.2013.06.0709 Mou Longjiang, Zhao Jinping. Variability of the Greenland Sea ice edge[J]. Advances in Earth Science, 2013, 28(6): 709−717. doi: 10.11867/j.issn.1001-8166.2013.06.0709