Application of a Quality Control Algorithm to Removing False Alerts on Strike Based Hail Detectors

Understory has deployed a network of sensors, known as RTis, which are deployed every one to two miles in order to measure weather impact on a granular scale. Quality Control of these measurements is incredibly important because of the decisions that they drive. The most pioneering measurement an RTi can make is the direct detection of hail. Such measurements allow for real-time highly localized detection of hail deposited within a storm. Ideally, real-time detection and communication of a cell producing hail within a storm can benefit those interested in the presence of hail, like emergency managers and the CASA test bed in Dallas-Fort Worth. This information would enable emergency managers to respond rapidly to damaging hail and allow CASA could collect detailed radar information of the hail producing cell. Since the hail data is driving important decisions, there is zero tolerance for false positives or inaccurate data. There are over 150 RTis in Dallas-Fort Worth and it is impossible to achieve real-time human verification of hail strikes. This talk will discuss the results of the real-time quality control algorithm for detecting birds alighting on RTis which will lead to the removal humans from the decision chain of communicating alerts in real-time.