Quantitative precipitation nowcasting using specific differential phase

Radar-based quantitative precipitation forecasting has traditionally been done using reflectivity data; however, recent research indicates that using specific differential phase (Kdp) has several advantages over using reflectivity for estimating rainfall. Estimating Kdp is known to be a challenging process. A new method has been developed to estimate Kdp that has shown to be more accurate and robust than previous methods. Studies investigating the feasibility of quantitative precipitation forecasting based on such Kdp estimates have yet to be performed. This paper presents an evaluation of nowcasting rainfall fields based on Kdp estimates using the Collaborative Adaptive Sensing of the Atmosphere nowcasting methodology and radar data and rain gauge data from the USDA Little Washita River Experimental Watershed. The results compare the short-term predictability of reflectivity- and Kdp-based rainfall fields using both initial radar-based estimates and rain gauge data as ground truth.