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Processes Controlling Sea Surface Temperature Variability of Ningaloo Niño

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  • 1 CAS Key Laboratory of Ocean Circulation and Waves, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China
  • 2 University of Chinese Academy of Sciences, Beijing, China
  • 3 Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao, China
  • 4 Function Laboratory for Ocean Dynamics and Climate, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China
  • 5 CAS Center for Excellence in Quaternary Science and Global Change, Xi’an, China
  • 6 College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao, China
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Abstract

A high-resolution (3–8 km) regional oceanic general circulation model is utilized to understand the sea surface temperature (SST) variability of Ningaloo Niño in the southeast Indian Ocean (SEIO). The model reproduces eight Ningaloo Niño events with good fidelity and reveals complicated spatial structures. Mesoscale noises are seen in the warming signature and confirmed by satellite microwave SST data. Model experiments are carried out to quantitatively evaluate the effects of key processes. The results reveal that the surface turbulent heat flux (primarily latent heat flux) is the most important process (contribution > 68%) in driving and damping the SST warming for most events, while the roles of the Indonesian Throughflow (~15%) and local wind forcing are secondary. A suitable air temperature warming is essential to reproducing the reduced surface latent heat loss during the growth of SST warming (~66%), whereas the effect of the increased air humidity is negligibly small (1%). The established SST warming in the mature phase causes increased latent heat loss that initiates the decay of warming. A 20-member ensemble simulation is performed for the 2010/11 super Ningaloo Niño, which confirms the strong influence of ocean internal processes in the redistribution of SST warming signatures. Oceanic eddies can dramatically modulate the magnitudes of local SST warming, particularly in offshore areas where the “signal-to-noise” ratio is low, raising a caution for evaluating the predictability of Ningaloo Niño and its environmental consequences.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JCLI-D-19-0698.s1.

© 2020 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Yuanlong Li, liyuanlong@qdio.ac.cn

Abstract

A high-resolution (3–8 km) regional oceanic general circulation model is utilized to understand the sea surface temperature (SST) variability of Ningaloo Niño in the southeast Indian Ocean (SEIO). The model reproduces eight Ningaloo Niño events with good fidelity and reveals complicated spatial structures. Mesoscale noises are seen in the warming signature and confirmed by satellite microwave SST data. Model experiments are carried out to quantitatively evaluate the effects of key processes. The results reveal that the surface turbulent heat flux (primarily latent heat flux) is the most important process (contribution > 68%) in driving and damping the SST warming for most events, while the roles of the Indonesian Throughflow (~15%) and local wind forcing are secondary. A suitable air temperature warming is essential to reproducing the reduced surface latent heat loss during the growth of SST warming (~66%), whereas the effect of the increased air humidity is negligibly small (1%). The established SST warming in the mature phase causes increased latent heat loss that initiates the decay of warming. A 20-member ensemble simulation is performed for the 2010/11 super Ningaloo Niño, which confirms the strong influence of ocean internal processes in the redistribution of SST warming signatures. Oceanic eddies can dramatically modulate the magnitudes of local SST warming, particularly in offshore areas where the “signal-to-noise” ratio is low, raising a caution for evaluating the predictability of Ningaloo Niño and its environmental consequences.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JCLI-D-19-0698.s1.

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Corresponding author: Yuanlong Li, liyuanlong@qdio.ac.cn

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