An Empirical Method of Estimating Raingage and Radar Rainfall Measurement Bias and Resolution

Abstract

This paper presents new methods of estimating the bias and the resolution of radar and raingage area average rainfall measurements over a defined area when both devices are employed simultaneously. The bias of raingage measurements for various rainfall amount ranges is estimated from published data, and the bias for radar measurement is then determined through comparison with the raingage recordings. The resolution estimations are carried out using error variance analysis on corresponding sets of gage and radar observations. The assumptions underlying this technique demand a uniform terrain for rainfall measurements, a large sample of cases, and, for one of the analysis options, a high correlation between radar and gage rainfall measurements. The procedure is illustrated using the gage and radar rainfall data from the second phase of the Florida Area Cumulus Experiment (FACE-2). The gage sampling error variance estimations for various rainfall amount categories using an empirical radar-derived method are examined by comparison with those of published studies using alternate methods and are found to be in general agreement. The FACF,2 gage network is found to provide more highly resolved rainfall measurements than the WSR-57 radar in moderate or heavy rainfall, but the radar exhibits the superior resolution in light rainfall if the radar rainfall adjustment used in FACE is not carried out. The radar rainfall adjustment appears to reduce radar measurement bias quite effectively, but the resolution is generally not improved and is degraded in below-median rainfall amounts.