Two-year assessment of nowcasting performance in the CASA system

Nowcasting refers to short-term automated forecasting (0-6 hours or less) of high-impact weather events such as heavy rainfall that can produce severe flooding. Accurate and efficient nowcasting can be used to assist emergency managers in the decision-making process. This paper presents an evaluation of nowcasting performance within the Collaborative Adaptive Sensing of the Atmosphere (CASA) system from the 2009-2010 Integrative Project 1 (IP1) experiment. The nowcasting methodology consists of the Dynamic and Adaptive Radar Tracking of Storms (DARTS) method for motion estimation and a sine kernel-based advection method. Radar reflectivity fields were predicted up to 10 min into the future. Previous analysis is extended to include data over a two year period using Critical Success Index (CSI), False Alarm Ratio (FAR), Probability of Detection (POD), and Mean Absolute Error (MAE) scores for evaluation. Analysis of the categorical scores (i.e., CSI, POD, FAR) relative to scoring threshold and neighborhood is also presented.