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Publication Date
23 February 2018

Linear and Nonlinear Winter Atmospheric Responses to Extreme Phases of Low Frequency Pacific Sea Surface Temperature Variability

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Science

This study examines Northern Hemisphere winter (DJFM) atmospheric responses to opposite strong phases of interdecadal (low frequency, LF) Pacific sea surface temperature (SST) forcing, which resembles El Niño-Southern Oscillation (ENSO) on a longer time scale, in observations and GFDL and CAM4 model simulations.

Impact

In addition to significant extratropical PNA-like linear components of Z500 anomalies reported before, in the observations from winters 1949–2014 we also find a Southern Annular-like linear Z500 response in the SH, a significant NAO-like Z500 response in the North Atlantic–Europe sector, and a dipole-like response with a positive Z500 anomaly over East Asia centered near Lake Baikal and a negative Z500 anomaly over Eurasia high latitudes and the adjacent Arctic Ocean. Through AGCM simulations using the CAM4 and GFDL models, we demonstrate that almost all aspects of observed linear and nonlinear responses are reproducible in the Pacific–North American sector, including the PNA-like circulation responses, and the associated significant warming temperature anomaly over northeast North America and wet precipitation anomaly over southern North America. This indicates that AGCM simulations, even without a coupled ocean model, are potentially adequate to examine decadal predictability of climate changes over North America and southern lands associated with PDO/IPO-like interdecadal Pacific SST variability.

Summary

The observed winter surface temperature and precipitation anomalies are highly related to the low-frequency variability in the Pacific, through linear and nonlinear teleconnections. Climate models forced by SST anomalies associated with Pacific low-frequency variability are capable to reproduce the observed surface temperature and precipitation responses. This implies that if we could predict the Pacific low-frequency variability, we could be able to predict the surface temperature and precipitation on land.

Point of Contact
Aixue Hu
Institution(s)
National Center for Atmospheric Research (NCAR)
Funding Program Area(s)