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Clouds play a critical role in the Earth's hydrologic cycle and in the energy balance of the climate system. They have a strong effect on solar heating by reflecting part of the incident solar radiation back to space. An increase in the average albedo of the Earth-atmosphere system by only 10 percent could decrease the surface temperature to that of the last ice age. Clouds affect the thermal cooling by intercepting part of the infrared radiation emitted by the Earth and atmosphere below the cloud, and re-emitting part of this radiation back to the surface. Global change in surface temperature is highly sensitive to cloud amount and type. Increasing low-level and middle-level clouds has a net cooling effect because they reflect more solar radiation and have a relatively small effect on infrared radiation. On the other hand, increased high clouds will have a warming effect by virtue of their low temperature and reduced cooling to space. High cirrus also act as a natural cloud seeder and strongly modulate the radiatively-important upper tropospheric water vapor budget. Given the sensitivity of the global climate to clouds, it is not surprising that the largest uncertainty in model estimates of global warming is due to clouds.
Climate models and remote sensing depend on plane-parallel models. These employ "effective" cloud parameters, such as cloud liquid water content, which depend on the macrophysical and microphysical properties of clouds. Inhomogeneous fractal cloud models are used to study the dependence of effective cloud parameters on macrostructural parameters such as the variance and wavenumber spectra of cloud liquid water. Determination of both macrophysical and microphysical cloud properties on horizontal scales from a few tens of meters to hundreds of kilometers, based on measurements taken from surface, aircraft and satellite platforms, allow plane-parallel and fractal cloud models to be tested and tuned for various meteorological conditions. Fractal cascades designed for various cloud types generate cloud layers having a range of inhomogeneities, and Monte Carlo methods then determine the radiative properties of such clouds. Fractal clouds are generally less reflective than plane-parallel clouds that have the same total cloud liquid water, and equivalently fractal clouds contain more liquid water than plane-parallel clouds which have the same reflectivity. When tuned to have realistic inhomogeneities, fractal clouds provide a connection between local measurements made in real clouds and idealized plane-parallel clouds employed by large-scale models. Computations of cloud reflection, absorption and transmission for highly inhomogeneous clouds rely on various 3-dimensional radiative transfer techniques, such as Monte Carlo, spherical-harmonic discrete ordinates, or diffusion. An Intercomparison of 3D Radiation Codes (I3RC) is now underway to determine the efficiency and relative accuracy of the various methods. Measurements of cloud radiative properties are conducted using airborne scanning radiometers and imaging spectrometers. For example, the Cloud Absorption Radiometer (CAR) is a multi-wavelength scanning radiometer that measures the angular distribution of scattered radiation. The retrieved cloud properties from these measurements are compared with simultaneous in situ measurements of cloud microphysics. The methods have been used to develop remote sensing capability from spaceborne platforms, to study cloud properties in regional areas, and to study the interaction of clouds with aerosol particles and their combined climatic impact. An extensive series of field observations since 1990 have been made with the MODIS Airborne Simulator (MAS). Recent activity involves measuring and studying the impact of ship effluents on cloud properties. Existing on a small scale, ship tracks provide a useful laboratory for the study of cloud microphysical changes as well as tests of instrumentation and remote sensing and retrieval algorithms. The extrapolation of ship track measurements to the global-scale climate is a difficult problem which is still being studied. Contact: Alexander Marshak
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