Quantifying spread in spatiotemporal changes of upper-ocean heat content estimates: an internationally coordinated comparison

dc.contributor.author Savita, Abhishek
dc.contributor.author Domingues, Catia M.
dc.contributor.author Boyer, Tim
dc.contributor.author Gouretski, Viktor
dc.contributor.author Ishii, Masayoshi
dc.contributor.author Johnson, Gregory C.
dc.contributor.author Lyman, John
dc.contributor.author Willis, Joshua K.
dc.contributor.author Marsland, Simon
dc.contributor.author Hobbs, William
dc.contributor.author Church, John A.
dc.contributor.author Monselesan, Didier Paolo
dc.contributor.author Dobrohotoff, Peter
dc.contributor.author Cowley, Rebecca
dc.contributor.author Wijffels, Susan E.
dc.date.accessioned 2022-09-14T15:15:33Z
dc.date.available 2022-09-14T15:15:33Z
dc.date.issued 2022-01-15
dc.description Author Posting. © American Meteorological Society, 2022. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Climate 35(2), (2022): 851–875, https://doi.org/10.1175/JCLI-D-20-0603.1. en_US
dc.description.abstract 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. en_US
dc.description.sponsorship AS is supported by a Tasmanian Graduate Research Scholarship, a CSIRO-UTAS Quantitative Marine Science top-up, and by the Australian Research Council (ARC) (CE170100023; DP160103130). CMD was partially supported by ARC (FT130101532) and the Natural Environmental Research Council (NE/P019293/1). RC was supported through funding from the Earth Systems and Climate Change Hub of the Australian Government’s National Environmental Science Program. TB is supported by the Climate Observation and Monitoring Program, National Oceanic and Atmosphere Administration, U.S. Department of commerce. GCJ and JML are supported by NOAA Research and the NOAA Ocean Climate Observation Program. This is PMEL contribution number 5065. JAC is supported by the Centre for Southern Hemisphere Oceans Research (CSHOR), jointly funded by the Qingdao National Laboratory for Marine Science and Technology (QNLM, China) and the Commonwealth Scientific and Industrial Research Organization (CSIRO, Australia) and Australian Research Council’s Discovery Project funding scheme (project DP190101173). The research was carried out in part at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (80NM0018D0004). Data used in this study are available on request. en_US
dc.identifier.citation Savita, A., Domingues, C. M., Boyer, T., Gouretski, V., Ishii, M., Johnson, G. C., Lyman, J. M., Willis, J. K., Marsland, S. J., Hobbs, W., Church, J. A., Monselesan, D. P., Dobrohotoff, P., Cowley, R., & Wijffels, S. E. (2022). Quantifying spread in spatiotemporal changes of upper-ocean heat content estimates: an internationally coordinated comparison. Journal of Climate, 35(2), 851–875. en_US
dc.identifier.doi 10.1175/JCLI-D-20-0603.1
dc.identifier.uri https://hdl.handle.net/1912/29346
dc.publisher American Meteorological Society en_US
dc.relation.uri https://doi.org/10.1175/JCLI-D-20-0603.1
dc.subject Bias en_US
dc.subject Interpolation schemes en_US
dc.subject In situ oceanic observations en_US
dc.subject Uncertainty en_US
dc.subject Oceanic variability en_US
dc.subject Trends en_US
dc.title Quantifying spread in spatiotemporal changes of upper-ocean heat content estimates: an internationally coordinated comparison en_US
dc.type Article en_US
dspace.entity.type Publication
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