Multidecadal variability and predictability of Antarctic sea ice in the GFDL SPEAR_LO model

Author:

Morioka YushiORCID,Zhang LipingORCID,Delworth Thomas L.,Yang Xiaosong,Zeng Fanrong,Nonaka MasamiORCID,Behera Swadhin K.

Abstract

Abstract. Using a state-of-the-art coupled general circulation model, physical processes underlying Antarctic sea ice multidecadal variability and predictability are investigated. Our model simulations constrained by atmospheric reanalysis and observed sea surface temperature broadly capture a multidecadal variability in the observed sea ice extent (SIE) with a low sea ice state (late 1970s–1990s) and a high sea ice state (2000s–early 2010s), although the model overestimates the SIE decrease in the Weddell Sea around the 1980s. The low sea ice state is largely due to the deepening of the mixed layer and the associated deep convection that brings subsurface warm water to the surface. During the high sea ice period (post-2000s), the deep convection substantially weakens, so surface wind variability plays a greater role in the SIE variability. Decadal retrospective forecasts started from the above model simulations demonstrate that the Antarctic sea ice multidecadal variability can be skillfully predicted 6–10 years in advance, showing a moderate correlation with the observation. Ensemble members with a deeper mixed layer and stronger deep convection tend to predict a larger sea ice decrease in the 1980s, whereas members with a larger surface wind variability tend to predict a larger sea ice increase after the 2000s. Therefore, skillful simulation and prediction of the Antarctic sea ice multidecadal variability require accurate simulation and prediction of the mixed layer, deep convection, and surface wind variability in the model.

Funder

Japan Society for the Promotion of Science

Publisher

Copernicus GmbH

Subject

Earth-Surface Processes,Water Science and Technology

Reference82 articles.

1. Adcroft, A., Anderson, W., Balaji, V., Blanton, C., Bushuk, M., Dufour, C. O., Dunne, J. P., Griffies, S. M., Hallberg, R., Harrison, M. J., Held, I. M., Jansen, M. F., John, J. G., Krasting, J. P., Langenhorst, A. R., Legg, S., Liang, Z., McHugh, C., Radhakrishnan, A., Reichl, B. G., Rosati, T., Samuels, B. L., Shao, A., Stouffer, R., Winton, M., Wittenberg, A. T., Xiang, B., Zadeh, N., and Zhang, R.: The GFDL global ocean and sea ice model OM4.0: Model description and simulation features, J. Adv. Mod. Ear. Sys., 11, 3167–3211, https://doi.org/10.1029/2019MS001726, 2019.

2. Akitomo, K., Awaji, T., and Imasato, N: Open-ocean deep convection in the Weddell Sea: Two-dimensional numerical experiments with a nonhydrostatic model, Deep-Sea Res. Pt. I, 42, 53–73, https://doi.org/10.1016/0967-0637(94)00035-Q, 1995.

3. Blanchard-Wrigglesworth, E., Roach, L. A., Donohoe, A., and Ding, Q.: Impact of winds and Southern Ocean SSTs on Antarctic sea ice trends and variability, J. Climate, 34, 949–965, https://doi.org/10.1175/JCLI-D-20-0386.1, 2021.

4. Bushuk, M., Msadek, R., Winton, M., Vecchi, G., Yang, X., Rosati, A., and Gudgel, R.: Regional Arctic sea–ice prediction: potential versus operational seasonal forecast skill, Clim. Dynam., 52, 2721–2743, https://doi.org/10.1007/s00382-018-4288-y, 2019.

5. Bushuk, M., Winton, M., Haumann, F. A., Delworth, T., Lu, F., Zhang, Y., Jia, L., Zhang, L., Cooke, W., Harrison, M., Hurlin, B., Johnson, N. C., Kapnick, S. B., McHugh, C., Murakami, H., Rosati, A., Tseng, K., Wittenberg, A. T., Yang, X., and Zeng, F.: Seasonal Prediction and Predictability of Regional Antarctic Sea Ice, J. Climate, 34, 6207–6233, https://doi.org/10.1175/JCLI-D-20-0965.1, 2021.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3