The use of co-polar correlation coefficient to separate regions of rain, melting layer and snow regions for applying corrections to vertical profiles of reflectivity

This presentation will describe polarimetric radar-based quantitative precipitation estimations (QPE) for low freezing levels when, even at the lowest possible elevation angles, radar resolution volumes at longer ranges are in melting layer or snow regions while it rains at the ground. An adjusted vertical profile of reflectivity (VPR) approach is introduced for a QPE routine. The mean VPR is constructed based on the range-height indicator (RHI) scans, and the effects of smoothing of radar bright band (BB) features with range are accounted for. A principal feature of the suggested QPE approach is the determination of slant beam boundaries of BB on a beam-by-beam basis using the co-polar correlation coefficient which is routinely available from most polarimetric radars. It is shown that this coefficient provides a robust discrimination among the regions of rain, melting hydrometeors and snow. While reflectivity and differential reflectivity measurements can potentially also be used for such discrimination, they do not exhibit such robustness as the co-polar correlation coefficient. Reflectivity measurements can vary significantly along the radar beam reflecting the varying precipitation intensity which impedes applications of automatic procedures for a BB boundary detection. Differential reflectivity measurements can provide multiple BB-like features due to hydrometeor habit changes. The transitions from snow to the melting layer and from the melting layer to rain correspond to decrease/increase in the co-polar correlation coefficient when it stably crosses certain values that do not depend on precipitation intensity. The suggested VPR approach with polarimetric determination of BB boundaries was used for QPE during the winter deployment of the X-band polarimetric radar as part of the 2006 Hydrometeorlogical Testbed field experiment in the Sierra Nevada foothills. It is shown that this approach noticeably improves rainfall accumulation estimates compared to traditional radar methods.