Relative contributions of external SST forcing and internal atmospheric variability to July–August heat waves over the Yangtze River valley

Article

Abstract

The Yangtze River valley (YRV), located in central-eastern China, has witnessed increased numbers of heat waves in the summer since 1951. Knowing what factors control and affect the interannual variability of heat waves, especially distinguishing the contributions of anomalous sea surface temperature (SST) forcings and those of internal modes of variability, is important to improving heat wave prediction. After evaluating 70 members of the atmospheric model intercomparison project (AMIP) experiments from the 25 models that participated in the coupled model intercomparison project phase 5 (CMIP5), 13 high-skill members (HSMs) are selected to estimate the SST-forced variability. The results show that approximately 2/3 of the total variability of the July–August heat waves in the YRV during 1979–2008 can be attributed to anomalous SST forcings, whereas the other 1/3 are due to internal variability. Within the SST-forced component, one-half of the influence is from the impact of the El Niño–Southern Oscillation (ENSO) and the other half is from non-ENSO related SST forcings, specifically, the SST anomalies in the North Pacific and the North Atlantic. Both the decaying El Niño and developing La Niña accompanied by a warm Indian Ocean and cold central Pacific, respectively, are favorable to hotter summers in the YRV because these patterns strengthen and extend the western North Pacific Subtropical High (WNPSH) westwards, for which the decaying ENSO plays a dominant role. The internal variability shows a circumglobal teleconnection in which Rossby waves propagate southeastwards over the Eurasian Continent and strengthen the WNPSH. Atmospheric model sensitivity experiments confirm that non-ENSO SST forcings can modulate the WNPSH and heat wave variability by projecting their influences onto the internal mode.

Keywords

Heat wave Yangtze River valley ENSO Internal variability AMIP 

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Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.LASG, Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina
  2. 2.University of Chinese Academy of SciencesBeijingChina

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