TY - UNPB
T1 - The relationship between the global mean deep-sea and surface temperature during the Early Eocene
AU - Goudsmit-Harzevoort, Barbara
AU - Lansu, Angelique
AU - Baatsen, Michiel L.J.
AU - von der Heydt, Anna S.
AU - de Winter, Niels J.
AU - Zhang, Yurui
AU - Abe-Ouchi, Ayako
AU - de Boer, Agatha
AU - Chan, Wing-Le
AU - Donnadieu, Yannick
AU - Hutchinson, David K.
AU - Knorr, Gregor
AU - Ladant, Jean-Baptiste
AU - Morozova, Polina
AU - Niezgodzki, Igor
AU - Steinig, Sebastian
AU - Tripati, Aradhna
AU - Zhang, Zhongshi
AU - Zhu, Jiang
AU - Ziegler, Martin
N1 - to Bibl: This is a Pre-Print on Open Archive of Barbara Goudsmit etal. Barbara Goudsmit have published an OUNL MSc Thesis with the same title, but as OUNL Student's MSc Thesis Environmental Sciences, and as published Conference Abstract EGU22. This pre-print is a submitted, in peer-review, article in Journal.
The Journal has an Plain Language Summary:
Plain Language Summary
A widely used indicator of global climate change is the change in global mean(land and sea) surface air temperature (GMSAT). Our current understanding ofthe GMSAT evolution during the last 66 million years is largely based on deep-sea temperature proxies from fossilized micro-organisms and the assumptionthat changes in the global mean deep-sea temperature (GMDST) are similarto those in GMSAT. In short, GMDST and GMSAT are linked via the globalmean sea-surface temperature (GMSST) by assuming that they are both lesssensitive than the GMSST to atmospheric CO2changes by the same degree.The validity of this assumption is essential in our understanding of past climatestates such as the Early Eocene Climate Optimum (EECO, 56–48 million yearsago), a hothouse period characterized by high atmospheric CO2levels. Weanalyzed the relationship between the three global temperature indicators inclimate model simulations of the EECO. Based on linear regression analysis,we find that changes in GMDST can indeed be used to estimate changes inGMSAT during the EECO (regression slope 0.99). Furthermore, paleo-proxies ofGMDST, GMSST, and GMSAT during EECO show the best fit with the modelsimulations having an atmospheric CO2level of 1,680 ppm, which matches paleo-proxies of atmospheric CO2during EECO. This indicates a good fit betweenmodels and proxy-data.
PY - 2022/8
Y1 - 2022/8
N2 - Our current understanding of global mean near-surface (land and sea) air temperature (GMSAT) during the Cenozoic era relies on paleo-proxy estimates of deep-sea temperature combined with assumed relationships between global mean deep-sea temperature (GMDST), global mean sea-surface temperature (GMSST), and GMSAT. The validity of these assumptions is essential in our understanding of past climate states such as the Early Eocene Climate Optimum hothouse climate (EECO, 56–48 Ma). The EECO remains relevant today, because EECO-like CO2 levels are possible in the 22ndcentury under continued high CO2 emissions. We analyze the relationship between the three global temperature indicators for the EECO using 25 different millennia-long model simulations with varying CO2 levels from the Deep-Time Model Intercomparison Project (DeepMIP). The model simulations show limited spatial variability in deep-sea temperature, indicating that local temperature estimates can be regarded representative of GMDST. Linear regression analysis indicates that compared to GMSST, both GMDST and GMSAT respond more strongly to changes in atmospheric CO2 by factors of 1.18 and 1.17, respectively. Consequently, this model-based analysis validates the assumption that changes in GMDST can be used to estimate changes in GMSAT during the EECO. Paleo-proxies of GMDST, GMSST, and GMSAT during EECO show the best fit with model simulations having an atmospheric CO2 level of 1,680 ppm, which matches paleo-proxies of atmospheric CO2 during EECO. Similar analyses of other past climate states are needed to examine whether these results are robust throughout the Cenozoic, providing insight into the long-term future warming under various shared socioeconomic pathways.
AB - Our current understanding of global mean near-surface (land and sea) air temperature (GMSAT) during the Cenozoic era relies on paleo-proxy estimates of deep-sea temperature combined with assumed relationships between global mean deep-sea temperature (GMDST), global mean sea-surface temperature (GMSST), and GMSAT. The validity of these assumptions is essential in our understanding of past climate states such as the Early Eocene Climate Optimum hothouse climate (EECO, 56–48 Ma). The EECO remains relevant today, because EECO-like CO2 levels are possible in the 22ndcentury under continued high CO2 emissions. We analyze the relationship between the three global temperature indicators for the EECO using 25 different millennia-long model simulations with varying CO2 levels from the Deep-Time Model Intercomparison Project (DeepMIP). The model simulations show limited spatial variability in deep-sea temperature, indicating that local temperature estimates can be regarded representative of GMDST. Linear regression analysis indicates that compared to GMSST, both GMDST and GMSAT respond more strongly to changes in atmospheric CO2 by factors of 1.18 and 1.17, respectively. Consequently, this model-based analysis validates the assumption that changes in GMDST can be used to estimate changes in GMSAT during the EECO. Paleo-proxies of GMDST, GMSST, and GMSAT during EECO show the best fit with model simulations having an atmospheric CO2 level of 1,680 ppm, which matches paleo-proxies of atmospheric CO2 during EECO. Similar analyses of other past climate states are needed to examine whether these results are robust throughout the Cenozoic, providing insight into the long-term future warming under various shared socioeconomic pathways.
KW - Climatology
KW - Global Change
KW - Paleoclimatology
KW - Oceanography
KW - Sea-Air Interactions
U2 - 10.1002/essoar.10512236.1
DO - 10.1002/essoar.10512236.1
M3 - Preprint
BT - The relationship between the global mean deep-sea and surface temperature during the Early Eocene
PB - Earth and Space Science Open Archive
ER -