To address this limitation, the use of eye-tracking technology to learn about the forecaster warning decision process was explored for the first time in the spring of 2015. This study was motivated by successful applications of eye-tracking methods in a variety of research domains including healthcare, air traffic control, and education. During the spring eye-tracking study, a forecaster's eye gaze data were collected as he worked a severe hail and wind event. Base velocity and reflectivity PAR data were displayed using the Warning Decision Support System-Integrated Information, which enabled the creation of three fixed areas of interest (AOIs): reflectivity, velocity, and controls. Analysis of the forecaster's eye fixations revealed interesting results. We found that while the forecaster fixated most frequently in the reflectivity AOI, his longest mean fixation duration was in the velocity AOI. Additionally, the forecaster provided a retrospective report following the simulation using the previously applied PARISE cognitive task analysis techniques. These qualitative data provided contextual support for trends observed in fixation count and mean fixation duration, and confirmed that the eye fixation data were a true representation of the forecaster's cognitive activity as the case evolved.
Given that results from the spring eye-tracking study demonstrated usefulness in applying this novel tool to objectively analyze a forecaster's cognitive process, we decided to apply our method during the 2015 PARISE. In this eye-tracking experiment, 30 NWS forecasters worked a 1-hour weather event in simulated real time. This event was comprised of a severe hail and wind producing storm and a null storm. Forecasters were randomly assigned to either a control group (5-min PAR updates) or an experimental group (1-min PAR updates). Preliminary findings shared during this presentation will look at whether PAR update time resulted in statistically significant differences between control and experimental participants' eye fixation measures.