Inter-Model Spread of North Tropical Atlantic Trans-Basin Effect Substantially Biases Tropical Pacific Sea Surface Temperature Multiyear Prediction

被引:3
作者
Yang, Jun-Chao [1 ,2 ,3 ]
Lv, Zhen [1 ,2 ,3 ]
Richter, Ingo [4 ]
Zhang, Yu [1 ,2 ,3 ]
Lin, Xiaopei [1 ,2 ,3 ]
机构
[1] Ocean Univ China, Frontier Sci Ctr Deep Ocean Multispheres & Earth, Qingdao, Peoples R China
[2] Ocean Univ China, Phys Oceanog Lab, Qingdao, Peoples R China
[3] Qingdao Natl Lab Marine Sci & Technol Qingdao, Qingdao, Peoples R China
[4] Japan Agcy Marin Earth Sci & Technol JAMSTEC, Res Inst Value Added Informat Generat, Applicat Lab, Yokohama, Kanagawa, Japan
基金
日本学术振兴会; 中国国家自然科学基金; 中国博士后科学基金;
关键词
tropical Pacific; multiyear prediction; sea surface temperature; model bias; trans-basin variability; ENSO; SST; PREDICTABILITY; CIRCULATION; VARIABILITY; IMPACT; CMIP5;
D O I
10.1029/2022GL098620
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Sea surface temperature (SST) variability in the tropical Pacific (TP) has world-wide climate and economic influences; hence, improving its prediction is of great interest. Recent modeling studies suggested that north tropical Atlantic variability can influence TP SST variability and prediction. However, models are subject to biases in both the tropical Atlantic and Pacific, and it remains an open question whether these biases affect the trans-basin linkages and the prediction of TP SST. To investigate this issue, we apply linear inverse modeling to observations and climate models. We find that removing north tropical Atlantic forcing indeed strongly lowers TP SST multiyear prediction skills in observations and models. Models show a large spread of the Atlantic trans-basin effect, which leads to markedly different TP SST multiyear prediction skills. Our study highlights the necessity to narrow the inter-model spread for more reliable TP SST multiyear prediction.
引用
收藏
页数:10
相关论文
共 65 条
  • [1] Optimal filtering in singular spectrum analysis
    Allen, MR
    Smith, LA
    [J]. PHYSICS LETTERS A, 1997, 234 (06) : 419 - 428
  • [2] Improved Simulation of ENSO Variability Through Feedback From the Equatorial Atlantic in a Pacemaker Experiment
    Bi, Daohua
    Wang, Guojian
    Cai, Wenju
    Santoso, Agus
    Sullivan, Arnold
    Ng, Benjamin
    Jia, Fan
    [J]. GEOPHYSICAL RESEARCH LETTERS, 2022, 49 (02)
  • [3] BJERKNES J, 1969, MON WEATHER REV, V97, P163, DOI 10.1175/1520-0493(1969)097<0163:ATFTEP>2.3.CO
  • [4] 2
  • [5] Understanding ENSO Diversity
    Capotondi, Antonietta
    Wittenberg, Andrew T.
    Newman, Matthew
    Di Lorenzo, Emanuele
    Yu, Jin-Yi
    Braconnot, Pascale
    Cole, Julia
    Dewitte, Boris
    Giese, Benjamin
    Guilyardi, Eric
    Jin, Fei-Fei
    Karnauskas, Kristopher
    Kirtman, Benjamin
    Lee, Tong
    Schneider, Niklas
    Xue, Yan
    Yeh, Sang-Wook
    [J]. BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY, 2015, 96 (06) : 921 - 938
  • [6] Decadal Climate Variability and Predictability: Challenges and Opportunities
    Cassou, Christophe
    Kushnir, Yochanan
    Hawkins, Ed
    Pirani, Anna
    Kucharski, Fred
    Kang, In-Sik
    Caltabiano, Nico
    [J]. BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY, 2018, 99 (03) : 479 - 490
  • [7] El Nino-Southern Oscillation Evolution Modulated by Atlantic Forcing
    Chikamoto, Y.
    Johnson, Z. F.
    Wang, S. -Y. Simon
    McPhaden, M. J.
    Mochizuki, T.
    [J]. JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS, 2020, 125 (08)
  • [8] Skilful multi-year predictions of tropical trans-basin climate variability
    Chikamoto, Yoshimitsu
    Timmermann, Axel
    Luo, Jing-Jia
    Mochizuki, Takashi
    Kimoto, Masahide
    Watanabe, Masahiro
    Ishii, Masayoshi
    Xie, Shang-Ping
    Jin, Fei-Fei
    [J]. NATURE COMMUNICATIONS, 2015, 6
  • [9] Global patterns of ENSO-induced precipitation
    Dai, A
    Wigley, TML
    [J]. GEOPHYSICAL RESEARCH LETTERS, 2000, 27 (09) : 1283 - 1286
  • [10] Remote and local influences in forecasting Pacific SST: a linear inverse model and a multimodel ensemble study
    Dias, Daniela Faggiani
    Subramanian, Aneesh
    Zanna, Laure
    Miller, Arthur J.
    [J]. CLIMATE DYNAMICS, 2019, 52 (5-6) : 3183 - 3201