Greenhouse warming intensifies north tropical Atlantic climate variability.


Journal

Science advances
ISSN: 2375-2548
Titre abrégé: Sci Adv
Pays: United States
ID NLM: 101653440

Informations de publication

Date de publication:
Aug 2021
Historique:
received: 08 02 2021
accepted: 06 07 2021
entrez: 26 8 2021
pubmed: 27 8 2021
medline: 27 8 2021
Statut: epublish

Résumé

Variability of North Tropical Atlantic (NTA) sea surface temperature (SST), characterized by a near-uniform warming at its positive phase, is a consequential mode of climate variability. Modulated by El Niño-Southern Oscillation (ENSO) and the North Atlantic Oscillation, NTA warm anomalies tend to induce La Niña events, droughts in Northeast Brazil, increased frequency of extreme hurricanes, and phytoplankton blooms in the Guinea Dome. Future changes of NTA variability could have profound socioeconomic impacts yet remain unknown. Here, we reveal a robust intensification of NTA variability under greenhouse warming. This intensification mainly arises from strengthening of ENSO-forced Pacific-North American pattern and tropospheric temperature anomalies, as a consequence of an eastward shift of ENSO-induced equatorial Pacific convection and of increased ENSO variability, which enhances ENSO influence by reinforcing the associated wind and moist convection anomalies. The intensification of NTA SST variability suggests increased occurrences of extreme NTA events, with far-reaching ramifications.

Identifiants

pubmed: 34433566
pii: 7/35/eabg9690
doi: 10.1126/sciadv.abg9690
pmc: PMC8386939
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).

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Auteurs

Yun Yang (Y)

College of Global Change and Earth System Science, Beijing Normal University, Beijing, China. yunyang@bnu.edu.cn.
State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China.

Lixin Wu (L)

Key Laboratory of Physical Oceanography/Institute for Advanced Ocean Studies, Ocean University of China and Qingdao National Laboratory for Marine Science and Technology, Qingdao, China.

Ying Guo (Y)

College of Global Change and Earth System Science, Beijing Normal University, Beijing, China.

Bolan Gan (B)

Key Laboratory of Physical Oceanography/Institute for Advanced Ocean Studies, Ocean University of China and Qingdao National Laboratory for Marine Science and Technology, Qingdao, China.

Wenju Cai (W)

Key Laboratory of Physical Oceanography/Institute for Advanced Ocean Studies, Ocean University of China and Qingdao National Laboratory for Marine Science and Technology, Qingdao, China.
Centre for Southern Hemisphere Oceans Research (CSHOR), CSIRO Oceans and Atmosphere, Hobart, Tasmania, Australia.

Gang Huang (G)

State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China.
Laboratory for Regional Oceanography and Numerical Modeling, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China.
University of Chinese Academy of Sciences, Beijing, China.

Xichen Li (X)

Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China.

Tao Geng (T)

Key Laboratory of Physical Oceanography/Institute for Advanced Ocean Studies, Ocean University of China and Qingdao National Laboratory for Marine Science and Technology, Qingdao, China.

Zhao Jing (Z)

Key Laboratory of Physical Oceanography/Institute for Advanced Ocean Studies, Ocean University of China and Qingdao National Laboratory for Marine Science and Technology, Qingdao, China.

Shujun Li (S)

Key Laboratory of Physical Oceanography/Institute for Advanced Ocean Studies, Ocean University of China and Qingdao National Laboratory for Marine Science and Technology, Qingdao, China.

Xi Liang (X)

Key Laboratory of Research on Marine Hazards Forecasting, National Marine Environmental Forecasting Center, Beijing, China.

Shang-Ping Xie (SP)

Scripps Institution of Oceanography, University of California, San Diego, La Jolla, CA 92037, USA.

Classifications MeSH