Computer Science
Scientific paper
Jan 1996
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1996phdt........13l&link_type=abstract
Thesis (PH.D.)--THE UNIVERSITY OF OKLAHOMA, 1996.Source: Dissertation Abstracts International, Volume: 56-12, Section: B, page:
Computer Science
Doppler Lidar, Large Eddy Simulation, Remote Sensing, Fife, Gravity Waves
Scientific paper
A planetary boundary layer (PBL) developed on 11 July, 1987 during the First International Satellites Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) is investigated numerically by a two dimensional and a three dimensional large eddy simulation (LES) model. Most of the simulated mean and statistical properties are utilized to compare or verify against the observational results extracted from single Doppler lidar scans conducted by Gal-Chen et al. (1992) on the same day. Through the methods of field measurements and numerical simulations, it is found that this PBL, in contrast to the well-known convective boundary layer (CBL), is driven by not only buoyancy but also wind shear. Large eddies produced by the surface heating, as well as internal gravity waves excited by the convection, are both present in the boundary layer. The most unique feature is that in the stable layer, the momentum flux ({overlinerm u^' w^'}), transported by the gravity waves, is counter-gradient. The occurrence of this phenomenon is interpreted by Gal-Chen et al. (1992) using the theory of critical layer singularity, and is confirmed by the numerical simulations in this study. Qualitative agreements are achieved between the model-generated and lidar-derived results. However, quantitative comparisons are less satisfactory. The most serious discrepancy is that in the stable layer the magnitudes of the observed momentum flux ({overlinerm u^ ' w^'}) and vertical velocity variance ({overlinerm w^'^2}) are much larger than their simulated counterparts. Nevertheless, through the technique of numerical simulation, evidence is collected to show inconsistencies among the observations. Thus, the lidar measurements of {overline rm u^' w^'} and {overlinerm w^ '^2} seem to be doubtful. A Four Dimensional Data Assimilation (FDDA) experiment is performed in order to connect the evolution of the model integration with the observations. The results indicate that the dynamical relaxation (nudging) scheme appears to be an appropriate method by which the observed mean quantities such as mean wind ({overline u}) and potential temperature ({ overlinetheta}) can be assimilated into the model without causing data rejection.
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