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Volume 24 Issue 3

May  2007

Article Contents
Article >  ADVANCES IN ATMOSPHERIC SCIENCES  > 2007 >  24(3): 343-359

Time-Frequency Characteristics of the Relationships Between Tropical Indo-Pacific SSTs

  • 1.

    NOAA's Climate Prediction Center, 5200 Auth Road, Camp Springs, MD 20746, USA,Department of Land Surveying and Geo-Informatics, Hong Kong Polytechnic University,Center for Astrogeodynamics Research, Shanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai 200030,RSIS/Climate Prediction Center, 5200 Auth Road, Camp Springs, MD 20746, USA


doi: 10.1007/s00376-007-0343-z

  • In this study, several advanced analysis methods are applied to understand the relationships between the Nino-3.4 sea surface temperatures (SST) and the SSTs related to the tropical Indian Ocean Dipole (IOD). By analyzing a long data record, the authors focus on the time-frequency characteristics of these relationships, and of the structure of IOD. They also focus on the seasonal dependence of those characteristics in both time and frequency domains. Among the Nino-3.4 SST, IOD, and SSTs over the tropical western Indian Ocean (WIO) and eastern Indian Ocean (EIO), the WIO SST has the strongest annual and semiannual oscillations. While the Nino-3.4 SST has large inter-annual variability that is only second to its annual variability, the IOD is characterized by the largest semiannual oscillation, which is even stronger than its annual oscillation. The IOD is strongly and stably related to the EIO SST in a wide range of frequency bands and in all seasons. However, it is less significantly related to the WIO SST in the boreal winter and spring. There exists a generally weak and unstable relationship between the WIO and EIO SSTs, especially in the biennial and higher frequency bands. The relationship is especially weak in summer and fall, when IOD is apparent, but appears highly positive in winter and spring, when the IOD is unimportantly weak and even disappears. This feature reflects a caution in the definition and application of IOD. The Nino-3.4 SST has a strong positive relationship with the WIO SST in all seasons, mainly in the biennial and longer frequency bands. However, it shows no significant relationship with the EIO SST in summer and fall, and with IOD in winter and spring.
  • [1] YUAN Yuan, C. L. Johnny CHAN, ZHOU Wen, LI Chongyin, 2008: Decadal and Interannual Variability of the Indian Ocean Dipole, ADVANCES IN ATMOSPHERIC SCIENCES, 25, 856-866.  doi: 10.1007/s00376-008-0856-0
    [2] Yuanhai FU, Zhongda LIN, Tao WANG, 2021: Simulated Relationship between Wintertime ENSO and East Asian Summer Rainfall: From CMIP3 to CMIP6, ADVANCES IN ATMOSPHERIC SCIENCES, 38, 221-236.  doi: 10.1007/s00376-020-0147-y
    [3] Yun YANG, Jianping LI, Lixin WU, Yu KOSAKA, Yan DU, Cheng SUN, Fei XIE, Juan FENG, 2017: Decadal Indian Ocean Dipolar Variability and Its Relationship with the Tropical Pacific, ADVANCES IN ATMOSPHERIC SCIENCES, 34, 1282-1289.  doi: 10.1007/s00376-017-7009-2
    [4] XU Tengfei, YUAN Dongliang, YU Yongqiang, and ZHAO Xia, 2013: An assessment of Indo-Pacific oceanic channel dynamics in the FGOALS-g2 coupled climate system model, ADVANCES IN ATMOSPHERIC SCIENCES, 30, 997-1016.  doi: 10.1007/s00376-013-2131-2
    [5] Paxson K. Y. CHEUNG, Wen ZHOU, Dongxiao WANG, Marco Y. T. LEUNG, 2022: Dissimilarity among Ocean Reanalyses in Equatorial Pacific Upper-Ocean Heat Content and Its Relationship with ENSO, ADVANCES IN ATMOSPHERIC SCIENCES, 39, 67-79.  doi: 10.1007/s00376-021-1109-8
    [6] Xiaoxuan ZHAO, Riyu LU, 2020: Vertical Structure of Interannual Variability in Cross-Equatorial Flows over the Maritime Continent and Indian Ocean in Boreal Summer, ADVANCES IN ATMOSPHERIC SCIENCES, 37, 173-186.  doi: 10.1007/s00376-019-9103-0
    [7] Yang AI, Ning JIANG, Weihong QIAN, Jeremy Cheuk-Hin LEUNG, Yanying CHEN, 2022: Strengthened Regulation of the Onset of the South China Sea Summer Monsoon by the Northwest Indian Ocean Warming in the Past Decade, ADVANCES IN ATMOSPHERIC SCIENCES, 39, 943-952.  doi: 10.1007/s00376-021-1364-8
    [8] ZHENG Fei, ZHANG Rong-Hua, ZHU Jiang, , 2014: Effects of Interannual Salinity Variability on the Barrier Layer in the Western-Central Equatorial Pacific: A Diagnostic Analysis from Argo, ADVANCES IN ATMOSPHERIC SCIENCES, 31, 532-542.  doi: 10.1007/s00376-013-3061-8
    [9] Li Chongyin, Mu Mingquan, 2001: The Influence of the Indian Ocean Dipole on Atmospheric Circulation and Climate, ADVANCES IN ATMOSPHERIC SCIENCES, 18, 831-843.
    [10] Yiyong LUO, Jian LU, Fukai LIU, Xiuquan WAN, 2016: The Positive Indian Ocean Dipole-like Response in the Tropical Indian Ocean to Global Warming, ADVANCES IN ATMOSPHERIC SCIENCES, 33, 476-488.  doi: 10.1007/s00376-015-5027-5
    [11] Rong FENG, Wansuo DUAN, 2019: Indian Ocean Dipole-related Predictability Barriers Induced by Initial Errors in the Tropical Indian Ocean in a CGCM, ADVANCES IN ATMOSPHERIC SCIENCES, 36, 658-668.  doi: 10.1007/s00376-019-8224-9
    [12] WANG Zhiren, WU Dexing, CHEN Xue'en, QIAO Ran, 2013: ENSO Indices and Analyses, ADVANCES IN ATMOSPHERIC SCIENCES, 30, 1491-1506.  doi: 10.1007/s00376-012-2238-x
    [13] Rong FENG, Wansuo DUAN, 2018: Investigating the Initial Errors that Cause Predictability Barriers for Indian Ocean Dipole Events Using CMIP5 Model Outputs, ADVANCES IN ATMOSPHERIC SCIENCES, 35, 1305-1320.  doi: 10.1007/s00376-018-7214-7
    [14] Xinyi XING, Xianghui FANG, Da PANG, Chaopeng JI, 2024: Seasonal Variation of the Sea Surface Temperature Growth Rate of ENSO, ADVANCES IN ATMOSPHERIC SCIENCES, 41, 465-477.  doi: 10.1007/s00376-023-3005-x
    [15] Siyu Zhou, Bo Sun, Huijun Wang, Yi Zheng, Jiarui Cai, Huixin Li, Botao Zhou, 2024: Distinct interannual variability and physical mechanisms of snowfall frequency over the Eurasian continent during autumn and winter, ADVANCES IN ATMOSPHERIC SCIENCES.  doi: 10.1007/s00376-024-3327-3
    [16] LI Gang*, LI Chongyin, TAN Yanke, and BAI Tao, 2014: The Interdecadal Changes of South Pacific Sea Surface Temperature in the Mid-1990s and Their Connections with ENSO, ADVANCES IN ATMOSPHERIC SCIENCES, 31, 66-84.  doi: 10.1007/s00376-013-2280-3
    [17] Xiaofei WU, Jiangyu MAO, 2019: Decadal Changes in Interannual Dependence of the Bay of Bengal Summer Monsoon Onset on ENSO Modulated by the Pacific Decadal Oscillation, ADVANCES IN ATMOSPHERIC SCIENCES, 36, 1404-1416.  doi: 10.1007/s00376-019-9043-8
    [18] Yadi LI, Xichen LI, Juan FENG, Yi ZHOU, Wenzhu WANG, Yurong HOU, 2024: Uncertainties of ENSO-related Regional Hadley Circulation Anomalies within Eight Reanalysis Datasets, ADVANCES IN ATMOSPHERIC SCIENCES, 41, 115-140.  doi: 10.1007/s00376-023-3047-0
    [19] MENG Xiangfeng, WU Dexing, LIN Xiaopei, LAN Jian, 2006: A Further Investigation of the Decadal Variation of ENSO Characteristics with Instability Analysis, ADVANCES IN ATMOSPHERIC SCIENCES, 23, 156-164.  doi: 10.1007/s00376-006-0016-3
    [20] ZHOU Qian, DUAN Wansuo, MU Mu, FENG Rong, 2015: Influence of Positive and Negative Indian Ocean Dipoles on ENSO via the Indonesian Throughflow: Results from Sensitivity Experiments, ADVANCES IN ATMOSPHERIC SCIENCES, 32, 783-793.  doi: 10.1007/s00376-014-4141-0
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    • Manuscript History

    Manuscript received: 10 May 2007
    Manuscript revised: 10 May 2007
    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

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    Time-Frequency Characteristics of the Relationships Between Tropical Indo-Pacific SSTs

    • 1. NOAA's Climate Prediction Center, 5200 Auth Road, Camp Springs, MD 20746, USA,Department of Land Surveying and Geo-Informatics, Hong Kong Polytechnic University,Center for Astrogeodynamics Research, Shanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai 200030,RSIS/Climate Prediction Center, 5200 Auth Road, Camp Springs, MD 20746, USA
    • Manuscript received: 2007-05-10
    • Manuscript revised: 2007-05-10

    Abstract: In this study, several advanced analysis methods are applied to understand the relationships between the Nino-3.4 sea surface temperatures (SST) and the SSTs related to the tropical Indian Ocean Dipole (IOD). By analyzing a long data record, the authors focus on the time-frequency characteristics of these relationships, and of the structure of IOD. They also focus on the seasonal dependence of those characteristics in both time and frequency domains. Among the Nino-3.4 SST, IOD, and SSTs over the tropical western Indian Ocean (WIO) and eastern Indian Ocean (EIO), the WIO SST has the strongest annual and semiannual oscillations. While the Nino-3.4 SST has large inter-annual variability that is only second to its annual variability, the IOD is characterized by the largest semiannual oscillation, which is even stronger than its annual oscillation. The IOD is strongly and stably related to the EIO SST in a wide range of frequency bands and in all seasons. However, it is less significantly related to the WIO SST in the boreal winter and spring. There exists a generally weak and unstable relationship between the WIO and EIO SSTs, especially in the biennial and higher frequency bands. The relationship is especially weak in summer and fall, when IOD is apparent, but appears highly positive in winter and spring, when the IOD is unimportantly weak and even disappears. This feature reflects a caution in the definition and application of IOD. The Nino-3.4 SST has a strong positive relationship with the WIO SST in all seasons, mainly in the biennial and longer frequency bands. However, it shows no significant relationship with the EIO SST in summer and fall, and with IOD in winter and spring.

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