Abstract

Abstract An important parameter often adjusted to achieve agreement between simulated and observed radiative fluxes in climate models is the rain formation efficiency. This adjustment has been justified as accounting for the effects of subgrid-scale variability in cloud properties, but this tuning approach is rather arbitrary. This study examines results from a regional climate model with precipitation formation schemes that have been conventionally tuned, and it compares them with simulations employing a recently developed scheme that uses satellite observations to explicitly account for the subgrid-scale variability of clouds (“integral constraint method”). Simulations with the International Pacific Research Center’s Regional Atmospheric Model (iRAM) show that the integral constraint method is capable of simulating cloud fields over the eastern Pacific that are in good agreement with observations, without requiring model tuning. A series of global warming simulations for late twenty-first-century conditions is performed to investigate the impact of the treatment of the precipitation formation efficiency on modeled cloud–climate feedbacks. The results with the integral constraint method show that the simulated cloud feedbacks have similar patterns at all the model resolutions considered (grid spacings of 50, 100, and 200 km), but there are some quantitative differences (with smaller feedbacks at finer resolution). The cloud responses to global warming in simulations with a conventionally tuned autoconversion scheme and with the integral constraint method were found to be quite consistent, although differences in individual regions of ~10%–30% are evident. No conclusions can be drawn from this study on the validity of model tuning for thick clouds and mixed phase or ice clouds, however.

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