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Gal-Chen, Tzvi

Publications and source records attributed to Gal-Chen, Tzvi.

Estimations of atmospheric boundary layer fluxes and other turbulence parameters from Doppler lidar data

Methods for extraction of boundary layer parameters from measurements of a short pulse CO2 Doppler lidar are presented. Assuming that the turbulence is horizontally homogeneous, the mean wind, its standard deviations, and the momentum fluxes are estimated. Regarding the analysis method, it is shown that for a horizontally homogeneous turbulence the mean wind, its variance and the vertical momentum fluxes can be determined from single Doppler lidar data.

Gal-Chen, Tzvi

Momentum and heat flux estimation in the planetary boundary layer (PBL) with a 10.6-micron Doppler lidar

The mean wind, its standard deviation, and the momentum fluxes in the PBL are estimated with a 10.6-micron Doppler lidar. Spectral analysis of the radial velocities was performed, from which, by examining the amplitude of the power spectrum at the inertial range, the kinetic energy dissipation was deduced. The statistical form of the Navier-Stokes equations was used to derive the surface heat flux as the residual balance between the vertical gradient of the third moment of the vertical velocity and the kinetic energy dissipation.

Gal-Chen, Tzvi

Retrieval of wind temperature and pressure from single Doppler radar and a numerical model

A 4D data assimilation algorithm to obtain 3D wind and thermodynamic fields from radial velocities and a numerical model is derived. It is a blend of the continuous updating technique of Charney et al. (1969) and a diagnostic pressure and temperature retrieval technique suggested by Gal-Chen (1978). This model is tested only against model-generated data which are viewed as 'data observed from a real atmosphere'. A thermal bubble developing in a dry, neutral environment is simulated. The thermal recovery technique is found to be a necessary procedure to obtain successful data assimilation results. The present assimilation method is found to be capable of reducing the 'observational error' and making the assimilation run converge toward the control run. Without data insertion, errors in the nonobserved wind component are large.

Liou, Yu-Chieng

Single Doppler radar and lidar studies of the dynamics of mixed layers and overlying stable regions

Some examples of profiles of PBL quantities retrieved from Doppler radar and lidar observations are shown, and the extent to which the deduced quantities agree with the traditional eddy viscosity concept is examined. It is found in one case that the concept of 'top down bottom up' diffusion introduced by Wyngaard (1983) is more pertinent than that of the eddy viscosity. In another case it is found that, in stable layers with sufficiently large Richardson number, the momentum fluxes could be counter-gradient. In this latter case the use of a negative turbulence diffusion coefficient would result in an ill-posed differential equation, thus confusing the 'diffusion problem'.

Xu, Mei

Convective dynamics - Panel report

Aspects of highly organized forms of deep convection at midlatitudes are reviewed. Past emphasis in field work and cloud modeling has been directed toward severe weather as evidenced by research on tornadoes, hail, and strong surface winds. A number of specific issues concerning future thrusts, tactics, and techniques in convective dynamics are presented. These subjects include; convective modes and parameterization, global structure and scale interaction, convective energetics, transport studies, anvils and scale interaction, and scale selection. Also discussed are analysis workshops, four-dimensional data assimilation, matching models with observations, network Doppler analyses, mesoscale variability, and high-resolution/high-performance Doppler. It is also noted, that, classical surface measurements and soundings, flight-level research aircraft data, passive satellite data, and traditional photogrammetric studies are examples of datasets that require assimilation and integration.

Carbone, Richard

Flux estimation of the FIFE planetary boundary layer (PBL) with 10.6 micron Doppler lidar

A method is devised for calculating wind, momentum, and other flux parameters that characterize the planetary boundary layer (PBL) and thereby facilitate the calibration of spaceborne vs. in situ flux estimates. Single Doppler lidar data are used to estimate the variance of the mean wind and the covariance related to the vertically pointing fluxes of horizontal momentum. The skewness of the vertical velocity and the range of kinetic energy dissipation are also estimated, and the surface heat flux is determined by means of a statistical Navier-Stokes equation. The conclusion shows that the PBL structure combines both 'bottom-up' and 'top-down' processes suggesting that the relevant parameters for the atmospheric boundary layer be revised. The conclusions are of significant interest to the modeling techniques used in General Circulation Models as well as to flux estimation.

Gal-Chen, Tzvi

Estimations of ABL fluxes and other turbulence parameters from Doppler lidar data

Techniques for extraction boundary layer parameters from measurements of a short-pulse CO2 Doppler lidar are described. The measurements are those collected during the First International Satellites Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE). By continuously operating the lidar for about an hour, stable statistics of the radial velocities can be extracted. Assuming that the turbulence is horizontally homogeneous, the mean wind, its standard deviations, and the momentum fluxes were estimated. Spectral analysis of the radial velocities is also performed from which, by examining the amplitude of the power spectrum at the inertial range, the kinetic energy dissipation was deduced. Finally, using the statistical form of the Navier-Stokes equations, the surface heat flux is derived as the residual balance between the vertical gradient of the third moment of the vertical velocity and the kinetic energy dissipation. Combining many measurements would normally reduce the error provided that, it is unbiased and uncorrelated. The nature of some of the algorithms however, is such that, biased and correlated errors may be generated even though the raw measurements are not. Data processing procedures were developed that eliminate bias and minimize error correlation. Once bias and error correlations are accounted for, the large sample size is shown to reduce the errors substantially. The principal features of the derived turbulence statistics for two case studied are presented.

Gal-Chen, Tzvi