Constraining clouds and convective parameterizations in a climate model from past climate

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Riovie Ramos, Allegra LeGrande, Michael Griffiths, Gregory Elsaesser, Daniel Litchmore, Jessica Tierney , Francesco Pausata, Jesse Nusbaumer


Cloud and convective parameterizations strongly influence uncertainties in equilibrium climate sensitivity (ECS). We provide a proof-of-concept study to constrain these parameterizations in a perturbed parameter ensemble of the atmosphere-only version of the Goddard Institute for Space Studies (GISS) Model E2.1 simulations by evaluating model biases in the present-day runs using multiple satellite climatologies and by comparing simulated δ18O of precipitation (δ18Op), known to be sensitive to parameterization schemes, with a global database of speleothem δ18O records covering the Last Glacial Maximum (LGM), mid-Holocene (MH) and pre-industrial (PI) periods. Relative to modern, paleoclimate simulations show greater sensitivity to parameter changes, allowing for an evaluation of model uncertainties over a broader range of climate forcing and the identification of parts of the world that are parameter sensitive. Certain simulations reproduced absolute δ18Op values across all time periods and LGM and MH δ18Op anomalies relative to the PI better than the default parameterization. Not a single set of parameterizations worked well in all climate states, likely due to the non-stationarity of cloud feedbacks under varying boundary conditions.



Atmospheric Sciences, Climate



Published: 2021-10-06 09:15

Last Updated: 2021-11-02 05:09

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CC BY Attribution 4.0 International

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