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<p>The Subtropical Indian Ocean Dipole (SIOD) is an important climate mode influencing regional climate variability. Traditional analysis methods based on predefined spatial structures may overlook nonclassical sea surface temperature (SST) patterns. This study employs an autoencoder (AE) framework to extract dominant modes of SST anomalies in the southern Indian Ocean, identifying one typical SIOD (T-SIOD) and two nonclassical SIOD modes: zonal SIOD (Z-SIOD) and meridional SIOD (M-SIOD). These patterns exhibit distinct southwest–southeast, zonal, and meridional dipole structures, respectively. Surface heat flux analysis reveals that their formation is primarily driven by shortwave radiation, while decay is attributed to latent heat flux. The three SIOD types exert significantly different influences on climate over China through distinct atmospheric pathways. Z-SIOD triggers a north–south dipole circulation pattern, inducing corresponding temperature anomalies and excessive precipitation over South China. M-SIOD influences China through the Hadley circulation and wave activity flux propagation, enhancing precipitation in Guangxi and Guizhou. T-SIOD modulates the Hadley and Walker circulations, leading to higher temperature and reduced precipitation over North China and excessive precipitation over South China. These findings demonstrate the capability of the AE framework to reveal previously underexplored climate modes and highlight the importance of distinguishing different SIOD types in climate prediction.</p>

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Nonclassical modes of subtropical Indian Ocean dipole identified by autoencoder and their distinct climatic impacts

  • 期刊论文

  • 发表日期：

    2026年7月31日

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  • Bicheng Huang,
  • Lingfeng Zheng,
  • Zengping Zhang,
  • Tao Su,
  • Guolin Feng,
  • Zhonghua Qian,
  • Yongping Wu

摘要

The Subtropical Indian Ocean Dipole (SIOD) is an important climate mode influencing regional climate variability. Traditional analysis methods based on predefined spatial structures may overlook nonclassical sea surface temperature (SST) patterns. This study employs an autoencoder (AE) framework to extract dominant modes of SST anomalies in the southern Indian Ocean, identifying one typical SIOD (T-SIOD) and two nonclassical SIOD modes: zonal SIOD (Z-SIOD) and meridional SIOD (M-SIOD). These patterns exhibit distinct southwest–southeast, zonal, and meridional dipole structures, respectively. Surface heat flux analysis reveals that their formation is primarily driven by shortwave radiation, while decay is attributed to latent heat flux. The three SIOD types exert significantly different influences on climate over China through distinct atmospheric pathways. Z-SIOD triggers a north–south dipole circulation pattern, inducing corresponding temperature anomalies and excessive precipitation over South China. M-SIOD influences China through the Hadley circulation and wave activity flux propagation, enhancing precipitation in Guangxi and Guizhou. T-SIOD modulates the Hadley and Walker circulations, leading to higher temperature and reduced precipitation over North China and excessive precipitation over South China. These findings demonstrate the capability of the AE framework to reveal previously underexplored climate modes and highlight the importance of distinguishing different SIOD types in climate prediction.