Upper tropospheric warming intensifies sea surface warming

  • Baoqiang Xiang
  • , Bin Wang
  • , Axel Lauer
  • , June Yi Lee
  • , Qinghua Ding

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

One of the robust features in the future projections made by the state-of-the-art climate models is that the highest warming rate occurs in the upper-troposphere especially in the tropics. It has been suggested that more warming in the upper-troposphere than the lower-troposphere should exert a dampening effect on the sea surface warming associated with the negative lapse rate feedback. This study, however, demonstrates that the tropical upper-tropospheric warming (UTW) tends to trap more moisture in the lower troposphere and weaken the surface wind speed, both contributing to reduce the upward surface latent heat flux so as to trigger the initial sea surface warming. We refer to this as a 'top-down' warming mechanism. The rise of tropospheric moisture together with the positive water vapor feedback enhance the downward longwave radiation to the surface and facilitate strengthening the initial sea surface warming. Meanwhile, the rise of sea surface temperature (SST) can feed back to intensify the initial UTW through the moist adiabatic adjustment, completing a positive UTW-SST warming feedback. The proposed 'top-down' warming mechanism and the associated positive UTW-SST warming feedback together affect the surface global warming rate and also have important implications for understanding the past and future changes of precipitation, clouds and atmospheric circulations.

Original languageEnglish
Pages (from-to)259-270
Number of pages12
JournalClimate Dynamics
Volume43
Issue number1-2
DOIs
StatePublished - Jun 2014
Externally publishedYes

Funding

The authors thank Shang-Ping Xie, Qiang Fu, Tim Li and three anonymous reviewers for their valuable comments. This study is supported by the International Pacific Research Center which is funded jointly by JAMSTEC, NOAA, and NASA. B.X., B.W. and J.Y.L. acknowledge APEC Climate Center (APCC) and Global Research Laboratory (GRL) grant funded by the Ministry of Education, Science and Technology (MEST 2011-0021927). J.Y.L. is supported by the MEST Brain Pool program. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modeling, which is responsible for CMIP, and we thank the climate modeling groups for producing and making available their model output.

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