A51D-0073
Detecting Coherent Structures in Large-Eddy Simulation of Shallow Convection

Friday, 18 December 2015
Poster Hall (Moscone South)
Seung-BU PARK1, Pierre Gentine1, Kai Schneider2 and Marie Farge3, (1)Columbia University of New York, Palisades, NY, United States, (2)Aix-Marseille Université, Marseille, France, (3)LMD-IPSL-CNRS, Paris, France
Abstract:
Coherent structures such as the vortical updrafts (and their shell) and subsidence are the main heat- and moisture-transporting flow structures in atmospheric convective layers. Although understanding their stochastic characteristics is essential in improving convection parameterization, even detecting them in well simulated numerical data is difficult because of their complex spatial and temporal distribution. A new method, classifying coherent structures in the boundary and cloud layers, is introduced. The new method first filters out noise from numerical simulation data and then it divides the denoised coherent flow into "updraft", "downdraft/shell", "subsidence" and other flow structures using an octant analysis. The method is used to detect the coherent structures in the shallow convection, simulated by large-eddy simulation model. The frequency and contribution to the vertical transport of heat and moisture of the coherent structures are analyzed. Updraft and environmental subsidence are the most frequent and dominant contributor to the vertical transport of heat and moisture in the boundary layer. The two flow structures with downdraft/shell illustrate the horizontal convective rolls in the boundary layer. Cloudy updrafts spread over the horizontal convective rolls and several updrafts with subsiding shells tend to form larger and complex convective structures. The role of downdraft/shell is distinct especially in the upper cloud layer and it acts against the updraft in transporting heat and moisture in the vertical direction. The newly developed method enables tracking individual or an ensemble of coherent structures from unsaturated boundary layer to less turbulent cloud layer. Thus, this method is expected to help understand en/detrainment around the complex but coherent structures.