2018
DOI: 10.1175/jcli-d-17-0769.1
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A Global Glacial Ocean State Estimate Constrained by Upper-Ocean Temperature Proxies

Abstract: We use the method of least squares with Lagrange multipliers to fit an ocean general circulation model to the Multiproxy Approach for the Reconstruction of the Glacial Ocean Surface (MARGO) estimate of near sea surface temperature (NSST) at the Last Glacial Maximum (LGM; circa 23-19 thousand years ago). Compared to a modern simulation, the resulting global, last-glacial ocean state estimate, which fits the MARGO data within uncertainties in a free-running coupled ocean-sea ice simulation, has global-mean NSSTs… Show more

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Cited by 22 publications
(26 citation statements)
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“…This causes a cooling of the basin (Fig. i), and an increase in the salinity at depth (Figure f), since below 2,000 m the water column is mostly occupied by the AABW, which is saltier due to brine rejection around Antarctica (Amrhein et al, ). The vertical structure of the salinity differences (CAM‐UVic), with freshening at the surface and salinification underneath induces the increased northward freshwater transport across 34°S (Figure b).…”
Section: Resultsmentioning
confidence: 99%
“…This causes a cooling of the basin (Fig. i), and an increase in the salinity at depth (Figure f), since below 2,000 m the water column is mostly occupied by the AABW, which is saltier due to brine rejection around Antarctica (Amrhein et al, ). The vertical structure of the salinity differences (CAM‐UVic), with freshening at the surface and salinification underneath induces the increased northward freshwater transport across 34°S (Figure b).…”
Section: Resultsmentioning
confidence: 99%
“…Proxy modeling is one important step in this direction (Dee et al, 2015), as are simulated proxies (Stevenson et al, 2018). Until recently proxies for some ocean variables have been too uncertain or sparse to quantitatively constrain models (Stevenson et al, 2013;Amrhein et al, 2018;Bereiter et al, 2018), although sea level is an important exception (e.g., Miller et al, 2013). • Increasing use of artificial intelligence, neural networks, and deep learning as part of the development and improvement of parameterizations-particularly in their numerical optimization for efficiency (Schneider et al, 2017;Gentine et al, 2018;Bolton and Zanna, 2019).…”
Section: What To Expect By 2030mentioning
confidence: 99%
“…For instance, during the last glacial period from 115,000 to 11,700 years ago, Greenland Ice‐core records show repeated pronounced warming and cooling events (e.g., Dansgaard–Oeschger and Heinrich events; Heinrich, ; Dansgaard et al, ) that are superposed on the longer climate cycles from glacial cycles. Whereas the factors that caused these events are still unclear, analyses of multiple proxies have suggested a connection to the AMOC (e.g., Bond et al, ; Gebbie, 2014; Amrhein et al, ). A particularly interesting and important point raised in these studies is whether abrupt AMOC changes seen in the past may happen in the present or future climate.…”
Section: Introductionmentioning
confidence: 99%