Simulated and observed variability in ocean temperature and heat content
Edited by Carl Wunsch, Massachusetts Institute of Technology, Cambridge, MA, and approved May 16, 2007
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.
Acknowledgments
The authors of the original Lyman et al. paper (12) have now publicly acknowledged that their earlier finding of pronounced ocean cooling over 2003–2005 was spurious (30). Their unpublished analyses confirm that this “cooling” arose for reasons similar to those identified here.
We thank the modeling groups for providing their data for analysis; the Program for Climate Model Diagnosis and Intercomparison for collecting and archiving the model output; the WCRP Working Group on Coupled Modeling for organizing the model data analysis activity; the editor, three anonymous reviewers, and Jonathan Gregory (University of Reading/Hadley Centre, Reading, U.K.) for valuable comments; Viktor Gouretski (Alfred Wegener Institute for Polar and Marine Research, Bremerhaven, Germany), Josh Willis (Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA), and John Lyman (National Oceanic and Atmospheric Administration/Pacific Marine Environmental Laboratory, Seattle, WA) for providing data and insights; Gary Strand (National Center for Atmospheric Research) for supplying ocean temperature data from the CCSM3 model; and Detelina Ivanova for additional technical help. The multimodel data archive is supported by the Office of Science, U.S. Department of Energy. This work was performed under the auspices of the U. S. Department of Energy by the University of California, Lawrence Livermore National Laboratory, under Contract W-7405-Eng-48. T.M.L.W. was supported by National Oceanic and Atmospheric Administration Office of Climate Programs (“Climate Change Data and Detection”) Grant NA87GP0105.
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© 2007 by The National Academy of Sciences of the USA.
Submission history
Received: December 20, 2006
Published online: June 26, 2007
Published in issue: June 26, 2007
Keywords
Acknowledgments
The authors of the original Lyman et al. paper (12) have now publicly acknowledged that their earlier finding of pronounced ocean cooling over 2003–2005 was spurious (30). Their unpublished analyses confirm that this “cooling” arose for reasons similar to those identified here.
We thank the modeling groups for providing their data for analysis; the Program for Climate Model Diagnosis and Intercomparison for collecting and archiving the model output; the WCRP Working Group on Coupled Modeling for organizing the model data analysis activity; the editor, three anonymous reviewers, and Jonathan Gregory (University of Reading/Hadley Centre, Reading, U.K.) for valuable comments; Viktor Gouretski (Alfred Wegener Institute for Polar and Marine Research, Bremerhaven, Germany), Josh Willis (Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA), and John Lyman (National Oceanic and Atmospheric Administration/Pacific Marine Environmental Laboratory, Seattle, WA) for providing data and insights; Gary Strand (National Center for Atmospheric Research) for supplying ocean temperature data from the CCSM3 model; and Detelina Ivanova for additional technical help. The multimodel data archive is supported by the Office of Science, U.S. Department of Energy. This work was performed under the auspices of the U. S. Department of Energy by the University of California, Lawrence Livermore National Laboratory, under Contract W-7405-Eng-48. T.M.L.W. was supported by National Oceanic and Atmospheric Administration Office of Climate Programs (“Climate Change Data and Detection”) Grant NA87GP0105.
Notes
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 Σj=1N T̄j, where N is the total number of models in the group (V or No-V) under consideration and Tj 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).
Authors
Competing Interests
The authors declare no conflict of interest.
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