National Oceanic and
Atmospheric Administration
United States Department of Commerce


FY 2022

Quantifying spread in spatio-temporal changes of upper-ocean heat content estimates: An internationally coordinated comparison

Savita, A., C.M. Domingues, T. Boyer, V. Gouretski, M. Ishii, G.C. Johnson, J.M. Lyman, J.K. Willis, S.J. Marsland, W. Hobbs, J.A. Church, D.P. Monselesan, P. Dobrohotoff, R. Cowley, and S.E. Wijffels

J. Climate, 35(2), 851–875, doi: 10.1175/JCLI-D-20-0603.1, View online (open access) (2022)

The Earth system is accumulating energy due to human-induced activities. More than 90% of this energy has been stored in the ocean as heat since 1970, with ∼60% of that in the upper 700 m. Differences in upper-ocean heat content anomaly (OHCA) estimates, however, exist. Here, we use a dataset protocol for 1970–2008—with six instrumental bias adjustments applied to expendable bathythermograph (XBT) data, and mapped by six research groups—to evaluate the spatiotemporal spread in upper OHCA estimates arising from two choices: 1) those arising from instrumental bias adjustments and 2) those arising from mathematical (i.e., mapping) techniques to interpolate and extrapolate data in space and time. We also examined the effect of a common ocean mask, which reveals that exclusion of shallow seas can reduce global OHCA estimates up to 13%. Spread due to mapping method is largest in the Indian Ocean and in the eddy-rich and frontal regions of all basins. Spread due to XBT bias adjustment is largest in the Pacific Ocean within 30°N–30°S. In both mapping and XBT cases, spread is higher for 1990–2004. Statistically different trends among mapping methods are found not only in the poorly observed Southern Ocean but also in the well-observed northwest Atlantic. Our results cannot determine the best mapping or bias adjustment schemes, but they identify where important sensitivities exist, and thus where further understanding will help to refine OHCA estimates. These results highlight the need for further coordinated OHCA studies to evaluate the performance of existing mapping methods along with comprehensive assessment of uncertainty estimates.

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