Quantitative precipitation estimates from dual-polarization weather radar in lazio region

Many phenomena (such as attenuation and range degradation) can influence the accuracy of rainfall radar estimates. They introduce errors that increase as the distance from the radar increases, thereby decreasing the reliability of radar estimates for applications that require quantitative precipitation estimation. The aim of the present work is to develop a range dependent error model called adjustment factor, that can be used as a range error pattern for allowing to correct the mean error which affects long-term quantitative precipitation estimates. A range dependent gauge adjustment technique was applied in combination with other processing of radar data in order to correct the range dependent error affecting radar measurements. Issues like beam blocking, path attenuation, vertical structure of precipitation related error, bright band, and incorrect Z-R relationship are implicitly treated with this type of method. In order to develop the adjustment factor, radar error was determined with respect to rain gauges measurements through a comparison between the two devices, based on the assumption that gauge rain was real. Therefore, the G/R ratio between the yearly rainfall amount measured in each rain gauge position during 2008 and the corresponding radar rainfall amount was calculated against the distance from radar. Trend of the G/R ratio shows two behaviors: a concave part due to the melting layer effect close to the radar location, and an almost linear increasing trend at greater distance. Then, a linear best fitting was used to find an adjustment factor, which estimates the radar error at a given range. The effectiveness of the methodology was verified by comparing pairs of rainfall time series that were observed simultaneously by collocated rain gauges and radar. Furthermore, the variability of the adjustment factor was investigated at the scale of event, both for convective and stratiform events. The main result is that there is not an univocal range error pattern, as it is also a function of the event characteristics. On the other hand, the adjustment factor tends to stabilize over long periods of observation as in the case of a whole year of measures.