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Published on: June 13, 2020
Possible shift in controls of the tropical Pacific surface warming pattern
Masahiro Watanabe1, Sarah M Kang2, Matthew Collins3
1Atmosphere and Ocean Research Institute, University of Tokyo, Kashiwa, Japan. hiro@aori.u-tokyo.ac.jp.
Understanding tropical Pacific sea surface temperature (SST) patterns is crucial for global warming projections. Past SST changes were driven by strengthening mechanisms, but future changes will likely be driven by weakening mechanisms.
Area of Science:
- Climate Science
- Oceanography
- Atmospheric Science
Background:
- Sea surface temperature (SST) patterns in the tropical Pacific significantly influence global warming and regional climate.
- Observed recent decades' changes, including enhanced zonal SST contrast and strengthened Walker circulation, remain a subject of scientific debate.
- Accurate projections of future climate depend on understanding the drivers of these SST pattern changes.
Purpose of the Study:
- To investigate the drivers of tropical Pacific sea surface temperature pattern changes.
- To review and reconcile energy and dynamical perspectives on external forcing's role.
- To project future shifts in the mechanisms governing SST pattern evolution.
Main Methods:
- Review of existing mechanisms for forced response, categorized by energy and dynamical perspectives.
- Analysis of collective and relative contributions of these perspectives to past and future SST changes.
- Synthesis of findings to propose a narrative reconciling different viewpoints.
Main Results:
- The study suggests that strengthening mechanisms have historically dominated tropical Pacific SST pattern changes.
- Future projections indicate a shift, with weakening mechanisms expected to dominate.
- A reconciliation of energy and dynamical perspectives on external forcing is proposed.
Conclusions:
- External forcing plays a critical role in modulating tropical Pacific SST patterns.
- The balance of strengthening versus weakening mechanisms is projected to shift in the future.
- Resolving model-observation discrepancies is key to improving climate projections.
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