Diagnostic analysis of turbulent boundary layer data by trivariate Lagrangian partitioning methods.

摘要

A method is developed for thermodynamic and kinematic analysis by partitioning boundary layer data by parcel vertical velocity and the conservative forms of temperature and moisture using a Lagrangian parcel approach. Large Eddy Simulation (LES) derived data fields were used to develop the partitioning method. The LES model provides sufficiently dense and thermodynamically consistent data, which are not yet available from observational datasets. LES Model data fields are three velocity components, potential temperature, total water mixing ratio, cloud liquid water, turbulent kinetic energy (TKE), and buoyancy. The procedure calculates vertical mixing, vertical transports, and the joint frequency histograms of the turbulent data fields with respect to potential temperature and total water mixing ratio, with a Lagrangian partitioning into strong rising, strong sinking, and weakly moving subsets.;An analysis of boundary layer thermodynamics using datasets from the large eddy simulation (LES) model is used to test the partitioning and analysis method. Observed datasets from the Frontal Air Sea Interaction Experiment (FASINEX) are used for comparative analysis of marine boundary layers and LES results. Results indicate the method is useful in further understanding the diurnal boundary layer entrainment hysteresis cycle, vertical transport, and similar features which develop from the non-Gaussian properties of turbulent boundary layer data. Potential applications of these results in boundary layer modeling are discussed.