Origin of interannual variability in global mean sea level

dc.contributor.author Hamlington, Benjamin D.
dc.contributor.author Piecuch, Christopher G.
dc.contributor.author Reager, John T.
dc.contributor.author Chandanpurkar, Hrishikesh A.
dc.contributor.author Frederikse, Thomas
dc.contributor.author Nerem, R. Steven
dc.contributor.author Fasullo, John T.
dc.contributor.author Cheon, Se-Hyeon
dc.date.accessioned 2020-06-25T19:34:35Z
dc.date.available 2020-12-08T08:35:25Z
dc.date.issued 2020-06-08
dc.description Author Posting. © National Academy of Sciences, 2020. This article is posted here by permission of National Academy of Sciences for personal use, not for redistribution. The definitive version was published in Proceedings of the National Academy of Sciences of the United States of America 117(25), (2020): 13983-13990, doi: 10.1073/pnas.1922190117. en_US
dc.description.abstract The two dominant drivers of the global mean sea level (GMSL) variability at interannual timescales are steric changes due to changes in ocean heat content and barystatic changes due to the exchange of water mass between land and ocean. With Gravity Recovery and Climate Experiment (GRACE) satellites and Argo profiling floats, it has been possible to measure the relative steric and barystatic contributions to GMSL since 2004. While efforts to “close the GMSL budget” with satellite altimetry and other observing systems have been largely successful with regards to trends, the short time period covered by these records prohibits a full understanding of the drivers of interannual to decadal variability in GMSL. One particular area of focus is the link between variations in the El Niño−Southern Oscillation (ENSO) and GMSL. Recent literature disagrees on the relative importance of steric and barystatic contributions to interannual to decadal variability in GMSL. Here, we use a multivariate data analysis technique to estimate variability in barystatic and steric contributions to GMSL back to 1982. These independent estimates explain most of the observed interannual variability in satellite altimeter-measured GMSL. Both processes, which are highly correlated with ENSO variations, contribute about equally to observed interannual GMSL variability. A theoretical scaling analysis corroborates the observational results. The improved understanding of the origins of interannual variability in GMSL has important implications for our understanding of long-term trends in sea level, the hydrological cycle, and the planet’s radiation imbalance. en_US
dc.description.embargo 2020-12-08 en_US
dc.description.sponsorship The research was carried out at JPL, California Institute of Technology, under a contract with NASA. This study was funded by NASA Grants NNX17AH35G (Ocean Surface Topography Science Team), 80NSSC17K0564, and 80NSSC17K0565 (NASA Sea Level Change Team). The efforts of J.T.F. in this work were also supported by NSF Award AGS-1419571, and by the Regional and Global Model Analysis component of the Earth and Environmental System Modeling Program of the US Department of Energy's Office of Biological & Environmental Research via National Science Foundation Grant IA 1844590. C.G.P. was supported by the J. Lamar Worzel Assistant Scientist Fund and the Penzance Endowed Fund in Support of Assistant Scientists at the Woods Hole Oceanographic Institution. en_US
dc.identifier.citation Hamlington, B. D., Piecuch, C. G., Reager, J. T., Chandanpurkar, H., Frederikse, T., Nerem, R. S., Fasullo, J. T., & Cheon, S. H. (2020). Origin of interannual variability in global mean sea level. Proceedings of the National Academy of Sciences of the United States of America, 117(25), 13983-13990. en_US
dc.identifier.doi 10.1073/pnas.1922190117
dc.identifier.uri https://hdl.handle.net/1912/25895
dc.publisher National Academy of Sciences en_US
dc.relation.uri https://doi.org/10.1073/pnas.1922190117
dc.subject Sea level en_US
dc.subject Climate variability en_US
dc.subject Global mean sea level en_US
dc.subject Satellite altimetry en_US
dc.title Origin of interannual variability in global mean sea level en_US
dc.type Article en_US
dspace.entity.type Publication
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