Climate & Radiation Branch Seminar Series, Matthew D. Lebsock

Dept. of Atmospheric Science, Colorado State University

Marine boundary layer clouds demonstrate a particular fragility with respect to perturbations in both their thermodynamic and microphysical environments. This fragility leads to large uncertainties in quantifying the forcing exerted on the climate system through aerosol indirect effects and the radiative cloud feedbacks associated with changes in cloud morphology in a perturbed climate. A particularly important aspect of these clouds is their ability to modify boundary layer structure and cloud morphology through drizzle and light precipitation. Furthermore, an inconsistency in global observations of precipitation and the atmospheric radiative budget exists, which may be partially explained by the insensitivity of current precipitation sensors to light precipitation falling from shallow clouds. With this knowledge as a motivation, several examples of A-Train sensor synergy are presented that have the potential to improve our understanding of precipitation processes in these climatically critical cloud regimes.

First, coincident CloudSat and MODIS data are used to examine the relationship of MODIS cloud microphysical retrievals to the occurrence of precipitation. The data show a gradual transition from non-precipitating cloud to precipitating cloud as opposed to hard thresholds at which precipitation begins. The analysis demonstrates that using the MODIS products to identify precipitation requires at least three parameters. In order of importance, these parameters are the cloud optical depth, the effective radius, and the effective radius difference between the retrievals using the 2.1 and 3.7 micron channels. These observations are grounded in theoretical models of the interaction of radiation with cloud and precipitation microphysics. The analysis suggests that simple precipitation thresholds based on the cloud effective radius or water path alone neglect important information contained within the MODIS observations.

Second, two different approaches are presented to simultaneously derive the cloud water path and the precipitation water path. The separation of the cloud and precipitation signals relies heavily on the relative insensitivity of the optical observations to the presence of precipitation in conjunction with the strong sensitivity of the microwave (both passive and active) observations to precipitation water. Results of the retrieval methodologies presented are consistent with the idea described above that information regarding the occurrence of precipitation is coded in the MODIS microphysical retrievals. Initial results highlight both microphysical and macrophysical controls on the production of precipitation, which suggests potential implications for quantifying aerosol indirect effects and cloud radiative feedbacks.

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