A model–model and data–model comparison for the early Eocene hydrological cycle
- 1BRIDGE, School of Geographical Sciences and Cabot Institute, University of Bristol, Bristol, UK
- 2Organic Geochemistry Unit, School of Chemistry and Cabot Institute, University of Bristol, Bristol, UK
- 3Climate Dynamics Prediction Laboratory, Department of Earth Sciences, The University of New Hampshire, Durham, NH, USA
- 4Institute of Geosciences, Kiel University, Kiel, Germany
- 5Climate and Global Dynamics Laboratory, UCAR/NCAR, Boulder, CO, USA
- 6NASA Goddard Institute for Space Studies, New York, NY, USA
- 7The Met Office, Exeter, UK
- 8Climate Research Group, Department of Earth and Environmental Sciences, University of Texas Arlington, Arlington, TX, USA
- anow at: Department of Geology and Geophysics, Yale University, New Haven, CT, USA
Abstract. A range of proxy observations have recently provided constraints on how Earth's hydrological cycle responded to early Eocene climatic changes. However, comparisons of proxy data to general circulation model (GCM) simulated hydrology are limited and inter-model variability remains poorly characterised. In this work, we undertake an intercomparison of GCM-derived precipitation and P − E distributions within the extended EoMIP ensemble (Eocene Modelling Intercomparison Project; Lunt et al., 2012), which includes previously published early Eocene simulations performed using five GCMs differing in boundary conditions, model structure, and precipitation-relevant parameterisation schemes.
We show that an intensified hydrological cycle, manifested in enhanced global precipitation and evaporation rates, is simulated for all Eocene simulations relative to the preindustrial conditions. This is primarily due to elevated atmospheric paleo-CO2, resulting in elevated temperatures, although the effects of differences in paleogeography and ice sheets are also important in some models. For a given CO2 level, globally averaged precipitation rates vary widely between models, largely arising from different simulated surface air temperatures. Models with a similar global sensitivity of precipitation rate to temperature (dP∕dT) display different regional precipitation responses for a given temperature change. Regions that are particularly sensitive to model choice include the South Pacific, tropical Africa, and the Peri-Tethys, which may represent targets for future proxy acquisition.
A comparison of early and middle Eocene leaf-fossil-derived precipitation estimates with the GCM output illustrates that GCMs generally underestimate precipitation rates at high latitudes, although a possible seasonal bias of the proxies cannot be excluded. Models which warm these regions, either via elevated CO2 or by varying poorly constrained model parameter values, are most successful in simulating a match with geologic data. Further data from low-latitude regions and better constraints on early Eocene CO2 are now required to discriminate between these model simulations given the large error bars on paleoprecipitation estimates. Given the clear differences between simulated precipitation distributions within the ensemble, our results suggest that paleohydrological data offer an independent means by which to evaluate model skill for warm climates.