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• 标题：Simulation of early Eocene water isotopes using an Earth system model and its implication for past climate reconstruction
• 关键词：early Eocene,Paleocene–Eocene Thermal Maximum,oxygen isotopes,isotope-enabled simulation,hydrological cycle,ocean circulation
• 作者：Jiang Zhu, Christopher J. Poulsen, Bette L. Otto-Bliesner, Zhengyu Liu, Esther C. Brady, David C. Noone

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Our understanding of past climate conditions largely comes from paleoclimate proxies, such as oxygen isotope ratios (δ18Oc) in marine fossils. The marine δ18Oc signal primarily reflflects a mixture of seawater temperature and oxygen isotopic composition of seawater (δ18Ow) at the time of calcifification. Knowledge of δ18Ow is critical for the interpretation of marine δ18Oc records but remains poor for past hothouse climates. Here, we conduct water isotope-enabled simulations of the early Eocene using CO2 levels of 1×, 3×, 6×, and 9× the preindustrial value. We calculate model δ18Oc using simulated δ18Ow and ocean temperature, and make direct comparison with proxy records. Model δ18Oc matches the proxy values well for the early Eocene and Paleocene–Eocene Thermal Maximum with root-mean-squared errors approaching the standard error in individual records. Eocene δ18Ow in the model exhibits strong variation depending on states of the hydrological cycle and ocean circulation. Differences in the mean δ18Ow between regions of net evaporation and precipitation increase monotonically with the magnitude of the net atmospheric moisture transport that connects them; however, this relationship breaks at the regional scale due to ocean circulation changes. In particular, an increase in ocean ventilation brings more 18O-enriched deep water into the mixed layer, increasing sea-surface δ18Ow near the ventilation site and in certain remote regions through fast upper ocean currents. δ18Ow variations and the linkage to both hydrological cycle and ocean circulation bring challenges for an accurate interpretation of marine δ18Oc records. Our study illustrates the value of using water isotope-enabled simulations and model-data comparison for learning past climate changes. © 2020 Elsevier B.V. All rights reserved.