Published in

American Geophysical Union, Geophysical Research Letters, 13(40), p. 3450-3456, 2013

DOI: 10.1002/grl.50647

Links

Tools

Export citation

Search in Google Scholar

Characterizing decadal to centennial variability in the equatorial Pacific during the last millennium: TROPICAL PACIFIC DEC-CEN VARIABILITY

Journal article published in 2013 by T. R. Ault, C. Deser, M. Newman, J. Emile-Geay ORCID
This paper is available in a repository.
This paper is available in a repository.

Full text: Download

Green circle
Preprint: archiving allowed
Green circle
Postprint: archiving allowed
Orange circle
Published version: archiving restricted
Data provided by SHERPA/RoMEO

Abstract

[1] The magnitude of sea surface temperature variability in the NINO3.4 region of the equatorial Pacific on decadal and longer timescales is assessed in observational data, state-of-the-art (Coupled Model Intercomparison Project 5) climate model simulations, and a new ensemble of paleoclimate reconstructions. On decadal to multidecadal timescales, variability in these records is consistent with the null hypothesis that it arises from “multivariate red noise” (a multivariate Ornstein-Uhlenbeck process) generated from a linear inverse model of tropical ocean-atmosphere dynamics. On centennial and longer timescales, both a last millennium simulation performed using the Community Climate System Model 4 (CCSM4) and the paleoclimate reconstructions have variability that is significantly stronger than the null hypothesis. However, the time series of the model and the reconstruction do not agree with each other. In the model, variability primarily reflects a thermodynamic response to reconstructed solar and volcanic activity, whereas in the reconstruction, variability arises from either internal climate processes, forced responses that differ from those in CCSM4, or nonclimatic proxy processes that are not yet understood. These findings imply that the response of the tropical Pacific to future forcings may be even more uncertain than portrayed by state-of-the-art models because there are potentially important sources of century-scale variability that these models do not simulate.