Abstract

The observed global-mean surface temperature (GST) has been warming in the presence of increasing atmospheric concentration of greenhouse gases, but its rise has not been monotonic. Attention has increasingly been focused on the prominent variations about the linear trend in GST, especially on interdecadal and multidecadal time scales. When the sea-surface temperature (SST) and the land- plus-ocean surface temperature (ST) are averaged globally to yield the global-mean SST (GSST) and the GST, respectively, spatial information is lost. Information on both space and time is needed to properly identify the modes of variability on interannual, decadal, interdecadal and multidecadal time scales contributing to the GSST and GST variability. Empirical Orthogonal Function (EOF) analysis is usually employed to extract the space–time modes of climate variability. Here we use the method of pair-wise rotation of the principal components (PCs) to extract the modes in these time-scale bands and obtain global spatial EOFs that correspond closely with regionally defined climate modes. Global averaging these clearly identified global modes allows us to reconstruct GSST and GST, and in the process identify their components. The results are: Pacific contributes to the global mean variation mostly on the interannual time scale through El Nino-Southern Oscillation (ENSO) and its teleconnections, while the Atlantic contributes strongly to the global mean on the multidecadal time scale through the interhemispheric mode called the Atlantic Multidecadal Oscillation (AMO). The Pacific Decadal Oscillation (PDO) has twice as large a variance as the AMO, but its contribution to GST is only 1/10 that of the AMO because of its compensating patterns of cold and warm SST in northwest and northeast Pacific. Its teleconnection pattern, the Pacific/North America (PNA) pattern over land, is also found to be self-cancelling when globally averaged because of its alternating warm and cold centers. The Interdecadal Pacific Oscillation (IPO) is not a separate mode of variability but contains AMO and PDO. It contributes little to the global mean, and what it contributes is mainly through its AMO component. A better definition of a Pacific low-frequency variability is through the IPO Tripole Index (TPI), using difference of averaged SST in different regions of the Pacific. It also has no contribution to the GSST and GST due to the PDO being its main component.

Highlights

  • It has often been noted that the observed global-mean surface temperature (GST) has prominent variations about the positive trend of global warming

  • It was thought that the Atlantic Multidecadal Oscillation (AMO) is largely responsible for the global-mean surface temperature variation in the 60–70 year time scale (Wu et al 2011), recently it has been proposed that it is the Interdecadal Pacific Oscillation (IPO) that is responsible for such a multidecadal variation in the global mean (Meehl et al 2016)

  • Models have the ability to separate the forced from the unforced variability, with the former given by the ensemble mean

Read more

Summary

Introduction

It has often been noted that the observed global-mean surface temperature (GST) has prominent variations about the positive trend of global warming. Two-dimensional surface temperature was projected onto this time component to yield the spatial structure of the mode that is responsible for the multidecadal variation of the global mean. The same procedure was previously used by Wu et al (2011) to find the spatial SST pattern of the multidecadal mode with an average period of 65 years, except that here we broaden the frequency range to include the decadal and interdecadal in addition to multidecadal variability. Wu et al (2011) showed that the 65-year mode’s center of action is in the Atlantic, with only a weak extension in the Pacific; our result agrees with that and shows that variability in all time scales longer than decadal, and not just the 65-year mode, has no center of action in the Pacific This result concerns only the source that causes the variability in the global-mean surface temperature. Mode mixing provides the crucial information in answering the question: what is the IPO?

EOF decomposition of SST
Components of global‐mean SST
Components of GST
The IPO
The TPI
Conclusion and discussion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call