This paper deals with the central argument that skeptics bring up about claims of global warming: How do you separate the temperature signal from the base components like natural variation, human land-use influence, micro-site bias, measurement errors and biases, and other factors to get the “true” global warming signal?

The answer is that you can’t, at least not easily.

With the surface temperature record, it’s somewhat easier since  you can observe some of those elements directly and separate them (such as we’ve done in our surfacestations project for land-use microsite biases), but in the ocean, everything is homogenized by the ocean itself. All you can look for is patterns, and try to disentangle based on pattern recognition. That’s what they are trying to do here.

Disentangling Global Warming, Multidecadal Variability, and El Niño in Pacific Temperatures
Authors
Robert C. Wills, Tapio Schneider, John M. Wallace, David S. Battisti, Dennis L. Hartmann

Abstract

A key challenge in climate science is to separate observed temperature changes into components due to internal variability and responses to external forcing. Extended integrations of forced and unforced climate models are often used for this purpose. Here we demonstrate a novel method to separate modes of internal variability from global warming based on differences in time scale and spatial pattern, without relying on climate models. We identify uncorrelated components of Pacific sea surface temperature variability due to global warming, the Pacific Decadal Oscillation (PDO), and the El Niño–Southern Oscillation (ENSO). Our results give statistical representations of PDO and ENSO that are consistent with their being separate processes, operating on different time scales, but are otherwise consistent with canonical definitions. We isolate the multidecadal variability of the PDO and find that it is confined to midlatitudes; tropical sea surface temperatures and their teleconnections mix in higher-frequency variability. This implies that midlatitude PDO anomalies are more persistent than previously thought.

http://onlinelibrary.wiley.com/wol1/doi/10.1002/2017GL076327/full

Unfortunately, the article is paywalled, even though it is publicly funded by the National Science Foundation. Grant Number: AGS-1549579. The author’s webpage at UW doesn’t have a draft copy, so I can’t comment further. If anyone has access they can provide me, I’ll be happy to update the article.

It is unfortunate (and wrong) that publicly funded science gets put under lock and key from the public examination of it.