Showing papers by "Guifu Zhang published in 2007"

A Statistical and Physical Description of Hydrometeor Distributions in Colorado Snowstorms Using a Video Disdrometer

Abstract: Winter-storm hydrometeor distributions along the Front Range in eastern Colorado are studied with a ground-based two-dimensional video disdrometer. The instrument provides shape, size, and terminal velocity information for particles that are larger than about 0.4 mm. The dataset is used to determine the form of particle size distributions (PSDs) and to search for useful interrelationships among the governing parameters of assumed distribution forms and environmental factors. Snowfalls are dominated by almost spherical aggregates having near-exponential or superexponential size distributions. Raindrop size distributions are more peaked than those for snow. A relation between bulk snow density and particle median volume diameter is derived. The data suggest that some adjustment may be needed in relationships found previously between temperature and the concentration and slope parameters of assumed exponential PSDs. A potentially useful relationship is found between the slope and shape terms of the ...

Spaced-Antenna Interferometry to Measure Crossbeam Wind, Shear, and Turbulence: Theory and Formulation

Abstract: The theory of measuring crossbeam wind, shear, and turbulence within the radar’s resolution volume V6 is described. Spaced-antenna weather radar interferometry is formulated for such measurements using phased-array weather radar. The formulation for a spaced-antenna interferometer (SAI) includes shear of the mean wind, allows turbulence to be anisotropic, and allows receiving beams to have elliptical cross sections. Auto- and cross-correlation functions are derived based on wave scattering by randomly distributed particles. Antenna separation, mean wind, shear, and turbulence all contribute to signal decorrelation. Crossbeam wind cannot be separated from shear, and thus crossbeam wind measurements are biased by shear. It is shown that SAI measures an apparent crossbeam wind (i.e., the angular shear of the radial wind component). Whereas the apparent crossbeam wind and turbulence within V6 cannot be separated using monostatic Doppler techniques, angular shear and turbulence can be separated using ...

Error modeling of simulated reflectivity observations for ensemble Kalman filter assimilation of convective storms

Abstract: [1] The impact of two different ways of modeling errors in simulated radar reflectivity data for observing system simulation experiments (OSSEs) with an ensemble Kalman filter is investigated. An error model different from the one used in earlier studies is introduced, and it specifies relative Gaussian-distributed errors in the linear domain of the equivalent radar reflectivity factor. This model is consistent with the processes of error propagation in real radar data. When the error variances specified in the filter and in the data are consistently smaller or larger, the analysis is more accurate, but when these values do not match, poorer analyses result. Such behaviors agree with expectation but are not observed when errors are directly added to the reflectivity in the log domain. These results point to the importance of properly modeling observation errors in OSSEs when the observation operator is nonlinear. Citation: Xue, M., Y. Jung, and G. Zhang (2007), Error modeling of simulated reflectivity observations for ensemble Kalman filter assimilation of convective storms, Geophys. Res. Lett., 34, L10802, doi:10.1029/2007GL029945.