4.6 Article

Origin of Indian Ocean multidecadal climate variability: role of the North Atlantic Oscillation

Journal

CLIMATE DYNAMICS
Volume 56, Issue 9-10, Pages 3277-3294

Publisher

SPRINGER
DOI: 10.1007/s00382-021-05643-w

Keywords

Indian Ocean sea surface temperature; North Atlantic Oscillation; Atlantic Multidecadal Oscillation; Pacific Decadal Oscillation

Funding

  1. National Key R&D Program of China [2016YFA0601801]
  2. National Natural Science Foundation of China (NSFC) Project [41790474]
  3. Shandong Natural Science Foundation Project [ZR2019ZD12]
  4. Fundamental Research Funds for the Central Universities [201962009]

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The study shows that the North Atlantic Oscillation (NAO) leads the multidecadal variability of Indian Ocean sea surface temperature (IOSST) through its leading effect on the Atlantic Multidecadal Oscillation (AMO). This ultimately affects the net longwave radiation in the Indian Ocean region and drives the annual IOSST multidecadal variability. Additionally, models incorporating the NAO signal better simulate the annual IOSST, indicating the combined influences of NAO and PDO on the variability.
The multidecadal variability of Indian Ocean sea surface temperature (IOSST) has an important impact on both the regional Indian Ocean climate and the global climate. Here, we explore multidecadal variability in the annual IOSST. Observational analysis shows that the annual IOSST multidecadal variability is not only related to the Pacific Decadal Oscillation (PDO), but also to the North Atlantic Oscillation (NAO). The NAO leads by 15-20 years the detrended annual IOSST in which the PDO signal of the same period has been removed. Further analysis reveals that the NAO leads the annual IOSST multidecadal variability through its leading effect on the Atlantic Multidecadal Oscillation (AMO). The AMO affects the vertical wind anomaly in the Indian Ocean region through the Atlantic-Indian Ocean multidecadal teleconnection (AIMT), which in turn affects the net longwave radiation in the Indian Ocean region, thus driving the annual IOSST multidecadal variability. A Hasselmann model based on NAO and PDO further verify the joint influence of the NAO and PDO on the multidecadal variability of the IOSST. A PDO-based linear model and a climate model that incorporates the NAO signal are also constructed for the annual IOSST. Results show that the climate model with the NAO signal can better simulate the annual IOSST. This again verifies that the NAO is part of the annual IOSST multidecadal variability source, indicating that the annual IOSST variability may be due to the combined influences of the NAO and PDO.

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