Testing and Comparing Precipitation Algorithms

An algorithm (Alg. 2) was created to calculate precipitation rates and to predict weather events using raw data from a weather event simulator for the duration of two months. The Alg. 2’s results from the simulation were compared to the results of the algorithm that currently produces the data for the Marshall Field Site Webplots (Alg. 1) using a Pierce Skill Score(PSS) as a performance comparison. The two algorithms were also compared using the precipitation accumulation data, acquired from the Tall Double Fence Intercomparison Reference(DFIR) shielded GEONOR gauge in the Marshall field site, 1 April – 30 April 2017. The precipitation rate results from the two algorithms were then compared visually for this data set. The data acquired from these two comparisons showed that the adjusted algorithm had a Pierce Skill Score for predicting weather events that was 8.99% higher than the Alg. 1, it was quicker at identifying weather events, and had a reliable and accurate precipitation rate detection, but had a higher false alarm rate