On the seasonal prediction of the western United States El Niño precipitation pattern during the 2015/16 winter

Xiaosong Yang, Liwei Jia, Sarah B. Kapnick, Thomas L. Delworth, Gabriel Andres Vecchi, Rich Gudgel, Seth Underwood, Fanrong Zeng

Research output: Contribution to journalArticle

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Abstract

A “typical” El Niño leads to wet (dry) wintertime anomalies over the southern (northern) half of the Western United States (WUS). However, during the strong El Niño of 2015/16, the WUS winter precipitation pattern was roughly opposite to this canonical (average of the record) anomaly pattern. To understand why this happened, and whether it was predictable, we use a suite of high-resolution seasonal prediction experiments with coupled climate models. We find that the unusual 2015/16 precipitation pattern was predictable at zero-lead time horizon when the ocean/atmosphere/land components were initialized with observations. However, when the ocean alone is initialized the coupled model fails to predict the 2015/16 pattern, although ocean initial conditions alone can reproduce the observed WUS precipitation during the 1997/98 strong El Niño. Further observational analysis shows that the amplitudes of the El Niño induced tropical circulation anomalies during 2015/16 were weakened by about 50% relative to those of 1997/98. This was caused by relative cold (warm) anomalies in the eastern (western) tropical Pacific suppressing (enhancing) deep convection anomalies in the eastern (western) tropical Pacific during 2015/16. The reduced El Niño teleconnection led to a weakening of the subtropical westerly jet over the southeast North Pacific and southern WUS, resulting in the unusual 2015/16 winter precipitation pattern over the WUS. This study highlights the importance of initial conditions not only in the ocean, but in the land and atmosphere as well, for predicting the unusual El Niño teleconnection and its influence on the winter WUS precipitation anomalies during 2015/16.

Original languageEnglish (US)
Pages (from-to)3765-3783
Number of pages19
JournalClimate Dynamics
Volume51
Issue number9-10
DOIs
StatePublished - Nov 1 2018

All Science Journal Classification (ASJC) codes

  • Atmospheric Science

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