The Challenge of Arctic Sea Ice Thickness Prediction by ECMWF on Subseasonal Time Scales

被引:6
|
作者
Xiu, Yongwu [1 ]
Luo, Hao [1 ]
Yang, Qinghua [1 ]
Tietsche, Steffen [2 ]
Day, Jonathan [2 ]
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] European Ctr Medium Range Weather Forecasts, Reading, Berks, England
基金
中国国家自然科学基金;
关键词
DATA ASSIMILATION; OCEAN MODEL; SATELLITE; CRYOSAT-2; SYSTEM; VOLUME;
D O I
10.1029/2021GL097476
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
A recent study has provided the first thorough assessment of subseasonal Arctic sea ice edge prediction in operational forecast systems. However, the corresponding assessment of the Arctic sea ice thickness (SIT) is still lacking. Here, the Arctic SIT reforecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) on subseasonal time scales are evaluated for the first time using a well-developed SIT reanalysis data set. The results show that ECMWF forecasts of Arctic SIT are more skillful than persistence forecast (PFs) during the transition seasons for lead times longer than 30 days, indicating the advantages of dynamical prediction. However, ECMWF suffers from large initial SIT errors and has lower skill than a PF, especially from March to June. Thus, subseasonal Arctic SIT predictions still face many challenges, and improving the mean SIT in the model and assimilating satellite-estimated SIT in the ocean analysis would significantly improve SIT forecasts.
引用
收藏
页数:9
相关论文
共 50 条
  • [1] Bright Prospects for Arctic Sea Ice Prediction on Subseasonal Time Scales
    Zampieri, Lorenzo
    Goessling, Helge F.
    Jung, Thomas
    [J]. GEOPHYSICAL RESEARCH LETTERS, 2018, 45 (18) : 9731 - 9738
  • [2] Subseasonal to seasonal Arctic sea-ice prediction:A grand challenge of climate science
    Ke Wei
    Jiping Liu
    Qing Bao
    Bian He
    Jiao Ma
    Ming Li
    Mirong Song
    Zhu Zhu
    [J]. Atmospheric and Oceanic Science Letters, 2021, 14 (04) : 21 - 23
  • [3] Subseasonal to seasonal Arctic sea-ice prediction: A grand challenge of climate science
    Wei, Ke
    Liu, Jiping
    Bao, Qing
    He, Bian
    Ma, Jiao
    Li, Ming
    Song, Mirong
    Zhu, Zhu
    [J]. ATMOSPHERIC AND OCEANIC SCIENCE LETTERS, 2021, 14 (04)
  • [4] Understanding the Forecast Skill of Rapid Arctic Sea Ice Loss on Subseasonal Time Scales
    McGraw, Marie C.
    Blanchard-Wrigglesworth, Eduardo
    Clancy, Robin P.
    Bitz, Cecilia M.
    [J]. JOURNAL OF CLIMATE, 2022, 35 (04) : 1179 - 1196
  • [5] Predictability of Antarctic Sea Ice Edge on Subseasonal Time Scales
    Zampieri, Lorenzo
    Goessling, Helge F.
    Jung, Thomas
    [J]. GEOPHYSICAL RESEARCH LETTERS, 2019, 46 (16) : 9719 - 9727
  • [6] A Spatiotemporal Multiscale Deep Learning Model for Subseasonal Prediction of Arctic Sea Ice
    Zheng, Qingyu
    Wang, Ru
    Han, Guijun
    Li, Wei
    Wang, Xuan
    Shao, Qi
    Wu, Xiaobo
    Cao, Lige
    Zhou, Gongfu
    Hu, Song
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2024, 62 : 1 - 22
  • [7] Predictability of Arctic sea ice on weather time scales
    M. Mohammadi-Aragh
    H. F. Goessling
    M. Losch
    N. Hutter
    T. Jung
    [J]. Scientific Reports, 8
  • [8] Predictability of Arctic sea ice on weather time scales
    Mohammadi-Aragh, M.
    Goessling, H. F.
    Losch, M.
    Hutter, N.
    Jung, T.
    [J]. SCIENTIFIC REPORTS, 2018, 8
  • [9] The role of bias correction on subseasonal prediction of Arctic sea ice during summer 2018
    Jiechen Zhao
    Qi Shu
    Chunhua Li
    Xingren Wu
    Zhenya Song
    Fangli Qiao
    [J]. Acta Oceanologica Sinica, 2020, 39 : 50 - 59
  • [10] The role of bias correction on subseasonal prediction of Arctic sea ice during summer 2018
    Zhao, Jiechen
    Shu, Qi
    Li, Chunhua
    Wu, Xingren
    Song, Zhenya
    Qiao, Fangli
    [J]. ACTA OCEANOLOGICA SINICA, 2020, 39 (09) : 50 - 59