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Free keywords:
MODIS SATELLITE DATA; AUTOCONVERSION PROCESS; SPECTRAL DISPERSION; CLOUD MICROPHYSICS; CONVECTIVE CLOUDS; SNOWFALL RATE; PARAMETERIZATION; SENSITIVITY; GCM; ALBEDO
Abstract:
Assessments of the influence of aerosol emissions from human activities on the radiation budget, in particular via the modification of cloud properties, have been a challenge. In light of the variability to both aerosol properties and environmental properties affected by aerosols, observational evidence alone cannot provide accurate and global answers, because detailed observations are locally limited and/or lack statistical significance. Thus, current understanding is predominantly derived from simulations with global models. General discrepancies to envelope (backward) modeling, however, suggest that many aerosol processes in global (forward) modeling are not properly considered. Using analytically derived parameterizations is recommended wherever possible. If an analytical method does not exist or is too demanding computationally, laboratory results augmented by field data are the second-best approach. For the constraint of so-derived parameterizations at the GCM scale, evaluating individual parameterizations using statistical relationships of satellite-retrieved quantities relevant to the process is recommended. The set of parameterizations may also be evaluated and improved using the data assimilation technique. To improve the quality of data references to modeling, there is a need to link available atmospheric data from all scales, and establish and support validation networks and experiments, and a commitment to fine-tune and improve satellite retrievals in an iterative process even beyond the anticipated period of the mission. Only then can more reliable estimates of the indirect aerosol effect be expected.
