Reducing the Spring Barrier in Predicting Summer Arctic Sea Ice Concentration

被引:5
作者
Zeng, Jingwen [1 ]
Yang, Qinghua [1 ]
Li, Xuewei [1 ]
Yuan, Xiaojun [2 ]
Bushuk, Mitchell [3 ]
Chen, Dake [1 ]
机构
[1] Sun Yat sen Univ, Sch Atmospher Sci, Southern Marine Sci & Engn Guangdong Lab Zhuhai, Zhuhai, Peoples R China
[2] Columbia Univ, Lamont Doherty Earth Observ, Palisades, NY USA
[3] Geophys Fluid Dynam Lab, Princeton, NJ USA
基金
国家重点研发计划; 中国国家自然科学基金;
关键词
sea ice; Arctic; prediction; SEASONAL PREDICTION; FORECAST; SKILL; PREDICTABILITY; REANALYSIS; ENSEMBLE; EXTENT;
D O I
10.1029/2022GL102115
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
The predictive skill of summer sea ice concentration (SIC) in the Arctic presents a steep decline when initialized before June, which is the so-called spring predictability barrier for Arctic sea ice. This study explores the potential influence of surface heat flux, cloud and water vapor anomalies on monthly to seasonal predictions of Arctic SIC anomalies. The results show an enhancement in skill predicting Arctic September SIC in the models that use surface fluxes, clouds, or water vapor in combination with SIC and surface sea temperature as predictors when initialized in boreal spring. This result shows the potential to reduce the spring barrier for Arctic SIC predictions by including the surface heat budget. The enhanced predictive skill can be very likely linked to the improved representation of the thermodynamics associated with water vapor and cloudiness anomalies in spring.
引用
收藏
页数:10
相关论文
共 48 条
  • [41] Predicting September sea ice: Ensemble skill of the SEARCH Sea Ice Outlook 2008-2013
    Stroeve, Julienne
    Hamilton, Lawrence C.
    Bitz, Cecilia M.
    Blanchard-Wrigglesworth, Edward
    [J]. GEOPHYSICAL RESEARCH LETTERS, 2014, 41 (07) : 2411 - 2418
  • [42] Benchmark seasonal prediction skill estimates based on regional indices
    Walsh, John E.
    Stewart, J. Scott
    Fetterer, Florence
    [J]. CRYOSPHERE, 2019, 13 (04) : 1073 - 1088
  • [43] Subseasonal forecast of Arctic sea ice concentration via statistical approaches
    Wang, Lei
    Yuan, Xiaojun
    Li, Cuihua
    [J]. CLIMATE DYNAMICS, 2019, 52 (7-8) : 4953 - 4971
  • [44] Predicting Summer Arctic Sea Ice Concentration Intraseasonal Variability Using a Vector Autoregressive Model
    Wang, Lei
    Yuan, Xiaojun
    Ting, Mingfang
    Li, Cuihua
    [J]. JOURNAL OF CLIMATE, 2016, 29 (04) : 1529 - 1543
  • [45] Coupled mode of cloud, atmospheric circulation, and sea ice controlled by wave-3 pattern in Antarctic winter
    Wang, Yunhe
    Yuan, Xiaojun
    Cane, Mark A.
    [J]. ENVIRONMENTAL RESEARCH LETTERS, 2022, 17 (04)
  • [46] Reassessing seasonal sea ice predictability of the Pacific-Arctic sector using a Markov model
    Wang, Yunhe
    Yuan, Xiaojun
    Bi, Haibo
    Bushuk, Mitchell
    Liang, Yu
    Li, Cuihua
    Huang, Haijun
    [J]. CRYOSPHERE, 2022, 16 (03) : 1141 - 1156
  • [47] Dynamic Preconditioning of the Minimum September Sea-Ice Extent
    Williams, James
    Tremblay, Bruno
    Newton, Robert
    Allard, Richard
    [J]. JOURNAL OF CLIMATE, 2016, 29 (16) : 5879 - 5891
  • [48] Arctic Sea Ice Seasonal Prediction by a Linear Markov Model
    Yuan, Xiaojun
    Chen, Dake
    Li, Cuihua
    Wang, Lei
    Wang, Wanqiu
    [J]. JOURNAL OF CLIMATE, 2016, 29 (22) : 8151 - 8173