Abstract

<div> <div> <div>We present results from an ensemble of eight climate models, each of which has carried out simulations of theearly Eocene climate optimum (EECO, ∼50 million years ago). These simulations have been carried out in the framework of DeepMIP (www.deepmip.org), and as such all models have been configured with the same paleogeographic and vegetation boundary conditions. The results indicate that these non-CO<sub>2</sub> boundary conditions contribute between 3 and 5<sup>o</sup>C to Eocene warmth. Compared to results from previous studies, the DeepMIP simulations show in general reduced spread of global mean surface temperature response across the ensemble for a given atmospheric CO<sub>2</sub> concentration, and an increased climate sensitivity on average. An energy balance analysis of the model ensemble indicates that global mean warming in the Eocene compared with preindustrial arises mostly from decreases in emissivity due to the elevated CO<sub>2</sub> (and associated water vapour and long-wave cloud feedbacks), whereas in terms of the meridional temperature gradient, the reduction in the Eocene is primarily due to emissivity and albedo changes due to the non-CO<sub>2</sub> boundary conditions (i.e. removal of the Antarctic ice sheet and changes in vegetation). Three of the models (CESM, GFDL, and NorESM) show results that are consistent with the proxies in terms of global mean temperature, meridional SST gradient, and CO<sub>2</sub>, without prescribing changes to model parameters. In addition, many of the models agree well with the first-order spatial patterns in the SST proxies. However, at a more regional scale the models lack skill. In particular, in the southwest Pacific, the modelled anomalies are substantially less than indicated by the proxies; here, modelled continental surface air temperature anomalies are more consistent with surface air temperature proxies, implying a possible inconsistency between marine and terrestrial temperatures in either the proxiesor models in this region. Our aim is that the documentation of the large scale features and model-data comparison presented herein will pave the way to further studies that explore aspects of the model simulations in more detail, for example the ocean circulation, hydrological cycle, and modes of variability; and encourage sensitivity studies to aspects such as paleogeography, orbital configuration, and aerosols</div> </div> </div>

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