19 November 2014

Quantifying Underestimates of Long-Term Upper-ocean Warming


Quantifying Underestimates of Long-term Upper-Ocean Warming

Current literature has acknowledged that Southern Hemisphere ocean warming estimates are likely biased low due to poor observational data coverage. Although this is an established conclusion in the oceanography community, the implications of this bias on estimates of global ocean heat content changes have not been explored to date.

To investigate the impact of the Southern Hemisphere sampling biases on global ocean heat content, we utilize reliable satellite measurements of sea surface height in conjunction with a large suite of climate model simulations. We assess the Northern and Southern hemispheric partitioning of ocean heat content changes from 1970-present. As satellite observations only begin in 1992, we are unable to directly validate 35-year (1970-2004) changes between sea surface height and steric changes in models; however, we are able to evaluate the shorter overlapping time period.

We find that reliable sea surface height observations and model simulations of steric sea level changes agree well, and show that approximately half of the global ocean steric change is occurring in the Southern Hemisphere (where 60% of the global ocean volume is found). Conversely, we find that in-situ estimates of observed ocean heat content changes are inconsistent with model simulations, with most estimates suggesting just 30-40% (rather than the 60% suggested by models) of ocean heat content change is found in the Southern Hemisphere.

The agreement between highly accurate satellite observations and model simulations motivates the adjustment of the poorly constrained Southern Hemisphere estimates to be consistent with the broad range of simulated results. This yields substantial increases (24-58%) across all current observed ocean heat content change estimates.

This research provides evidence that long-term global ocean warming has been substantially underestimated. With more than 90% of the global warming attributed excess heat residing in the ocean, these new results have important implications for energy budget, sea level and climate sensitivity assessments.

Reference: Durack, P. J., P. J. Gleckler, F. W. Landerer and K. E. Taylor (2014) Quantifying Underestimates of Long-term Upper-Ocean Warming. Nature Climate Change, 4 (11), pp 999-1005. doi: 10.1038/nclimate2389

Paul J. Durack
Lawrence Livermore National Laboratory (LLNL)
Durack, PJ, PJ Gleckler, FW Landerer, and KE Taylor.  2014.  "Quantifying Underestimates of Long-Term Upper-Ocean Warming."  Nature Climate Change 4(11): 999-1005, doi:10.1038/nclimate2389.

The work of P.J.D., P.J.G. and K.E.T. from Lawrence Livermore National Laboratory is a contribution to the US Department of Energy, Office of Science, Climate and Environmental Sciences Division, Regional and Global Climate Modeling Program under contract DE-AC52-07NA27344. The work of F.W.L. was performed at the Jet Propulsion Laboratory, California Institute of Technology and is supported by NASA ROSES Physical Oceanography grant NNN13D462T and the NASA Sea Level Change Team (NSLCT). We thank numerous colleagues from the Program for Climate Model Diagnosis and Intercomparison (PCMDI) for valuable feedback and input into this project. We also thank J. Durack of the University of California, San Francisco (USA), M. V. Durack of educAID (Australia), T. P. Boyer from the National Oceanographic Data Center, Silver Spring (USA), C. M. Domingues from the Antarctic Climate and Ecosystems CRC, Hobart (Australia) and J. A. Church from the Centre for Australian Weather and Climate Research, Hobart (Australia). We acknowledge the sources of observed data used in this study: D. Smith and J. Murphy (Smi07), C. M. Domingues (Dom08), M. Ishii and M. Kimoto (Ish09), S. Levitus and T. Boyer (Lev12) and the International Argo Program and the national programs that contribute to it. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modelling groups (listed in Supplementary Tables 1 and 2) for producing and making available their model output. For CMIP the US Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. The DW10 data presented in this study can be downloaded from the CSIRO Ocean Change website at www.cmar.csiro.au/oceanchange. LLNL Release #: LLNL-JRNL-651841.