High-Resolution Rainfall Estimation from X-Band Polarimetric Radar Measurements

The paper presents a rainfall estimation technique based on algorithms that couple, along a radar ray, profiles of horizontal polarization reflectivity (Z H ), differential reflectivity (Z DR ), and differential propagation phase shift ( DP ) from X-band polarimetric radar measurements. Based on in situ raindrop size distribution (DSD) data and using a three-parameter ''normalized'' gamma DSD model, relationships are derived that correct X-band reflectivity profiles for specific and differential attenuation, while simultaneously retrieving variations of the normalized intercept DSD parameter (N w ). The algorithm employs an iterative scheme to intrinsically account for raindrop oblateness variations from equilibrium condition. The study is facilitated from a field experiment conducted in the period October-November 2001 in Iowa City, Iowa, where observations from X-band dualpolarization mobile radar (XPOL) were collected simultaneously with high-resolution in situ disdrometer and rain-gauge rainfall measurements. The observed rainfall events ranged in intensity from moderate stratiform precipitation to high-intensity (50 mm h 1 ) convective rain cells. The XPOL measurements were tested for calibration, noise, and physical consistency using corresponding radar parameters derived from coincidentally measured raindrop spectra. Retrievals of N w from the attenuation correction scheme are shown to be unbiased and consistent with N w values calculated from independent raindrop spectra. The attenuation correction based only on profiles of reflectivity measurements is shown to diverge significantly from the corresponding polarimetric-based corrections. Several rain retrieval algorithms were investigated using matched pairs of instantaneous high-resolution XPOL observations with rain rates from 3-min-averaged raindrop spectra at close range (5 km) and rain-gauge measurements from further ranges (10 km). It is shown that combining along-a-ray (corrected Z H , Z DR , and specific differential phase shift) values gets the best performance in rainfall estimation with about 40% (53%) relative standard deviation in the radar-disdrometer (radar-gauge) differences. The casetuned reflectivity-rainfall rate (Z-R) relationship gives about 65% (73%) relative standard deviation for the same differences. The systematic error is shown to be low (3% overestimation) and nearly independent of rainfall intensity for the multiparameter algorithm, while for the standard Z-R it varied from 10% underestimation to 3% overestimation.