U.S. Department of Energy Office of Biological and Environmental Research

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First Evidence of Long-Term Human Influence in Pacific Decadal Oscillation
Published: November 01, 2010
Posted: November 05, 2010

Both natural systems, from salmon productivity to fires to river flow to the onset of spring, etc., and atmospheric variables are affected by decadal-scale natural fluctuations in northern Pacific Ocean sea surface temperatures, known as the Pacific Decadal Oscillation (PDO). However, it turns out that this natural climate variability may not be entirely “natural” after all. Two BER-funded scientists present the first evidence of a long-term human component in the PDO. They considered three definitions of a PDO index, two of which attempt to remove a global warming signal that could be present in the sea surface temperature data. These definitions were analyzed using sea surface temperature data from two observational datasets and from two coupled ocean-atmosphere model simulations of historical and future climate. In the 21st century scenarios, an anthropogenic component is systematically found in all three PDO indices. For the definition in which no attempt was made to remove a global warming signal, the human component is so large that it is already statistically detectable in the observed PDO index. This study illustrates the importance of separating internally-generated and externally-forced components of the PDO, suggests that caution should be exercised in using PDO indices for statistical removal of ‘‘natural variability’’ effects from observational datasets, and suggests that we should carefully examine other “natural” climate change fluctuations to understand the sources of the variations.

Reference: Bonfils, C. and B.D. Santer. 2010. "Investigating the Possibility of a Human Component in Various Pacific Decadal Oscillation Indices," Climate Dynamics. Online First.

Contact: Renu Joseph, SC-23.1, (301) 903-9237, Dorothy Koch, SC-23.1, (301) 903-0105
Topic Areas:

  • Research Area: Earth and Environmental Systems Modeling

Division: SC-23.1 Climate and Environmental Sciences Division, BER

 

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