Simulated and observed variability in ocean temperature and heat content

doi:10.1073/pnas.0611375104

Simulated and observed variability in ocean temperature and heat content

*Program for Climate Model Diagnosis and Intercomparison, Lawrence Livermore National Laboratory, Livermore, CA 94550;
^‡Frontier Research Center for Global Change, Japan Agency for Marine–Earth Science and Technology, Yokohama 236-0001, Japan;
^§Climate Research Division, Scripps Institution of Oceanography, La Jolla, CA 92037;
^¶National Oceanic and Atmospheric Administration/Geophysical Fluid Dynamics Laboratory, Princeton, NJ 08542; and
^‖National Center for Atmospheric Research, Boulder, CO 80307

Edited by Carl Wunsch, Massachusetts Institute of Technology, Cambridge, MA, and approved May 16, 2007 (received for review December 20, 2006)

Abstract

Observations show both a pronounced increase in ocean heat content (OHC) over the second half of the 20th century and substantial OHC variability on interannual-to-decadal time scales. Although climate models are able to simulate overall changes in OHC, they are generally thought to underestimate the amplitude of OHC variability. Using simulations of 20th century climate performed with 13 numerical models, we demonstrate that the apparent discrepancy between modeled and observed variability is largely explained by accounting for changes in observational coverage and instrumentation and by including the effects of volcanic eruptions. Our work does not support the recent claim that the 0- to 700-m layer of the global ocean experienced a substantial OHC decrease over the 2003 to 2005 time period. We show that the 2003–2005 cooling is largely an artifact of a systematic change in the observing system, with the deployment of Argo floats reducing a warm bias in the original observing system.

Footnotes

^†To whom correspondence should be addressed. E-mail: achutarao1{at}llnl.gov
Author contributions: K.M.A., B.D.S., K.E.T., T.P.B., R.J.S., and T.M.L.W. designed research; K.M.A., B.D.S., P.J.G., K.E.T., and D.W.P. performed research; M.I. contributed new reagents/analytic tools; K.M.A., M.I., P.J.G., and D.W.P. analyzed data; and K.M.A., B.D.S., P.J.G., K.E.T., T.P.B., D.W.P., R.J.S., and T.M.L.W. wrote the paper.
The authors declare no conflict of interest.
This article is a PNAS Direct Submission.
This article contains supporting information online at www.pnas.org/cgi/content/full/0611375104/DC1.
↵ ** Although all 13 modeling groups used very similar changes in well mixed greenhouse gases, the changes in other forcings were not prescribed as part of the experimental design. In practice, each group employed different combinations of 20th century forcings and often used different data sets for specifying individual forcings. End-dates for the experiments varied between groups and ranged from 1999 to 2003. Some modeling centers performed ensembles of the historical forcing simulation (see SI Text and SI Table 1). An ensemble contains multiple realizations of the same experiment, each starting from slightly different initial conditions but with identical changes in external forcings.
↵ †† We define T̄ as the arithmetic mean of the ensemble means, i.e., T̄=1/N Σ_j=1 ^N T̄_j, where N is the total number of models in the group (V or No-V) under consideration and T _j is the ensemble mean signal of the jth model. This weighting avoids placing undue emphasis on results from a single model with a large number of realizations. The intermodel SD is similarly defined based on the ensemble means (if available) from each model.
↵ ‡‡ The analysis of Gouretski and Koltermann (25) ended in 2001. In assessing profiler biases, therefore, it primarily focused on the pre-Argo generation of profilers used in the World Ocean Circulation Experiment.
↵ §§ We note, however, that there are also time-varying biases between the collocated XBT and CTD+Bottle data (25).
Abbreviations:

CTD,

conductivity–temperature–depth;

MBT,

mechanical bathythermograph;

OHC,

ocean heat content;

XBT,

expendable bathythermograph.