Radar data objective analysis

Abstract

The spherical geometry of weather radar scans results in a data distribution wherein datapoint separation in one coordinate direction and/or in one part of the analysis domain can differ widely from that in another. Objective analysis of the nonuniform radar data to a uniform Cartesian grid is desirable for many diagnostic purposes. For the benefit of the diagnostic data analyst as well as of users of these analyses, the authors evaluate properties of techniques typically used for such objective analysis. This is done partly through theoretical consideration of the properties of the schemes, but mostly by empirical testing. In terms of preservation of the phase and amplitude of the input data, predictability of the degree of smoothing and filtering, and relative insensitivity to input data unsteadiness or spatial characteristic, the isotropic Gaussian or Barnes-type weight function with constant smoothing parameter appears to be the most desirable of the schemes considered. Modification of this scheme so that the weight function varies spatially, with the datapoint spacing, results in an improved analysis, according to some commonly used measures of error. Interpretation of analyses based on such a modified scheme can be affected, however. For example, analyses of unsteady input fields suffer from a convolution of the temporal evolution of the data with spatial variations of the weight function. As a consequence, unambiguous assessment of physical evolution is precluded.