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Kerry A. Emanuel and Marina Živković-Rothman

Abstract

Cumulus convection is a key process in controlling the water vapor content of the atmosphere, which is in turn the largest feedback mechanism for climate change in global climate models. Yet scant attention has been paid to designing convective representations that attempt to handle water vapor with fidelity, and even less to evaluating their performance. Here the authors attempt to address this deficiency by designing a representation of cumulus convection with close attention paid to convective water fluxes and by subjecting the scheme to rigorous tests using sounding array data. The authors maintain that such tests, in which a single-column model is forced by large-scale processes measured by or inferred from the sounding data, must be carried out over a period at least as long as the radiative-subsidence timescale—about 30 days—governing the water vapor adjustment time. The authors also argue that the observed forcing must be preconditioned to guarantee integral enthalpy conservation, else errors in the single-column prediction may be falsely attributed to convective schemes.

Optimization of the new scheme’s parameters is performed using one month of data from the intensive flux array operating during the Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment, with the aid of the adjoint of the linear tangent of the single-column model. Residual root-mean-square errors, after optimization, are about 15% in relative humidity and 1.8 K in temperature. It is difficult to reject the hypothesis that the residual errors are due to noise in the forcing. Evaluation of the convective scheme is performed using Global Atmospheric Researh Program Atlantic Tropical Experiment data. The performance of the scheme is compared to that of a few other schemes used in current climate models. It is also shown that a vertical resolution better than 50 mb in pressure is necessary for accurate prediction of atmospheric water vapor.

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