Investigating the possibility of a human component in various Pacific Decadal Oscillation indices Page: 4 of 38
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Abstract: 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
also specifies that monthly-mean, global-average SST anomalies are subtracted from the local
anomalies. Because of this, any differences in the warming rates over the globe and the PDO
region may be aliased into the PDO index itself. We examine the possibility of a human
component in the PDO using three definitions. The implications of these definitions are explored
using SSTs from both observations and model simulations of historical and future climate change,
all projected onto definition-dependent observed PDO patterns. A systematic anthropogenic
contamination is found in all PDO indices over the 21St century. Using the first definition-in
which no warming signal is removed-the contamination is so large that it is statistically
detectable in the observed PDO. Using the second (or traditional) definition, the contamination is
large, arising mainly from the differential warming rates predicted in the North Pacific and
globally. Removing the regional-mean signal (using 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 mode. In consequence, statistically removing "natural
variability" effects from a variety of observational datasets using PDO indices should be
exercised with great caution. This illustrates the importance of separating internally-generated
and externally-forced components in the PDO.
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Bonfils, C & Santer, B. Investigating the possibility of a human component in various Pacific Decadal Oscillation indices, article, December 22, 2009; Livermore, California. (digital.library.unt.edu/ark:/67531/metadc863447/m1/4/: accessed October 15, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.