Microscale and Mesoscale Structures in Convective Marine Boundary Layers

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9419927 Agee This grant will address the dynamic and thermodynamic properties and characteristics of convective marine boundary layers, through both observational study of special field data and theoretical model simulations. These cloud-topped boundary layers form in response to cold continental air masses that advect out over relatively warmer water, resulting in convective mixing and the formation of large polygonal arrays of mesoscale cellular convection that reside within the first one of two kilometers of the atmosphere. This convective pattern may exist as two- dimensional bands or streets, but often (downstream) resolves itself into three dimensional cells. During the past three decades a wealth of observational data for atmospheric convection studies has been accumulated from measurements by various means, including radar, aircraft, and satellites in special field observation programs. From the data, statistical parameters were obtained describing the structure and dynamics of the planetary boundary layers (PBL). These parameters are commonly computed in the form of temporal or spatial averages from a few (often from one) records of limited length, while theoretical studies operate with ensemble averages which assume averaging over an infinite number of realizations of random functions. Ensemble averages can be approximated by the averages taken over sufficiently large time or space segments only if the underlying random function is stationary (homogeneous). Current meteorological studies often result in statistically unreliable inference because of nonstationarity or inhomogeneity of data and inadequate averaging distances. For these reasons, under this project, data sets collected during several field programs will be revisited by employing a recently developed comprehensive statistical method that provides estimates of both statistical parameters and their statistical reliability. Large eddy simulation (LES) modeling is anoth er powerful tool that helps provide a theoretical understanding of the intricate fluid mechanics of atmospheric convection. Once again there is a problem of obtaining statistically reliable results, which will be addressed in this project by extending the above statistical method from random processes to random fields, and by approximating ensemble averages using Monte Carlo techniques. New LES model development of mesoscale convection in PBLs and proper statistical analysis of the LES model data will also be performed. The focus will be on the physical properties of convective PBLs with ice particles and snow precipitation. Model results will be compared with statistically reliable findings from field programs.