Abstract
In modeling the thermal structure of the atmosphere, the role of clouds is critically important. Clouds modify the solar flux distribution throughout the atmosphere, radiate significantly in the infrared, and provide large thermal reservoirs because of the large latent heat of water. In the best current radiative convective one-dimensional models the global atmosphere is modeled as the sum of clear and cloudy sky parts weighted by a fractional cloud cover. In considering the cloudy sky part, previous models have treated the clouds as input and characterized them simply in terms of their altitudes, thicknesses, and optical properties. This report compares the surface temperature sensitivities to variations in cloud cover for three cloud approximations: (1) a single effective fixed cloud with a mean water vapor profile, (2) a floating clouds approximation in which cloud altitudes and thicknesses are calculated and a mean water vapor profile is used and (3) a fully interactive formulation in which cloud altitudes and thicknesses are calculated and separate clear and cloudy water vapor profiles are used. In all three approximations the cloud cover amount, A c , is an input. The fully interactive approximation is shown to reduce the sensitivity of surface temperature to cloud cover variations from ?4.7 times 10 -2 K/(1% A c ) for the single effective approximation to ?3.6 times 10 -2 K/(1% A c ). This reveals that when the model allows the clouds and water vapor to interact, calculated surface temperature changes caused by changing the amount of clouds are less than previous studies indicate. DOI: 10.1111/j.2153-3490.1981.tb01769.x
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