Climate Dynamics

, Volume 37, Issue 7, pp 1457-1468

First online:

Open Access This content is freely available online to anyone, anywhere at any time.

Investigating the possibility of a human component in various pacific decadal oscillation indices

  • Céline BonfilsAffiliated withLawrence Livermore National Laboratory Email author 
  • , Benjamin D. SanterAffiliated withLawrence Livermore National Laboratory


The pacific decadal oscillation (PDO) is a mode of natural decadal climate variability, typically defined as the principal component of North Pacific sea surface temperature (SST) anomalies. To remove any global warming signal present in the data, the traditional definition specifies that monthly-mean, global-average SST anomalies are subtracted from the local anomalies. Differences in the warming rates over the globe and the PDO region may therefore be aliased into the PDO index. Here, we examine the possibility of a human component in the PDO, considering three different definitions. The implications of these definitions are explored using SSTs from both observations and simulations of historical and future climate, all projected onto (definition-dependent) observed PDO patterns. In the twenty first century scenarios, a systematic anthropogenic component is found in all three PDO indices. Under the first definition—in which no warming signal is removed—this component is so large that it is also statistically detectable in the observed PDO. Using the second/traditional definition, this component is also large, and arises primarily from the differential warming rates predicted in the North Pacific and over global oceans. Removing the spatial average SST signal in the PDO region (in the third definition) partially solves this problem, but a human signal persists because the predicted pattern of SST response to human forcing projects strongly onto the PDO pattern. This illustrates the importance of separating internally-generated and externally-forced components in the PDO, and suggests that caution should be exercised in using PDO indices for statistical removal of “natural variability” effects from observational datasets.


Climate simulations Pacific decadal oscillation Mode of decadal variability Trend Sea surface temperatures Detection of regional climate change