Comparing Forecaster Eye Movements during the Warning Decision Process
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Comparing Forecaster Eye Movements during the Warning Decision Process

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  • Journal Title:
    Weather and Forecasting
  • Personal Author:
  • NOAA Program & Office:
  • Description:
    An eye-tracking experiment was conducted to examine whether differences in forecasters’ eye movements provide further insight into how radar update speed impacts their warning decision process. In doing so, this study also demonstrates the applications of a new research method for observing how National Weather Service forecasters distribute their attention across a radar display and warning interface. In addition to observing forecasters’ eye movements during this experiment, video data and retrospective recalls were collected. These qualitative data were used to provide an explanation for differences observed in forecasters’ eye movements. Eye movement differences were analyzed with respect to fixation measures (i.e., count and duration) and scanpath dimensions (i.e., vector, direction, length, position, and duration). These analyses were completed for four stages of the warning decision process: the first 5 min of the case, 2 min prior to warning decisions, the warning issuance process, and warning updates. While radar update speed did not impact forecasters’ fixation measures during these four stages, comparisons of scanpath dimensions revealed differences in their eye movements. Video footage and retrospective recall data illustrated how forecasters’ interactions with the radar display and warning interface, encounters with technological challenges, and varying approaches to similar tasks resulted in statistically significantly (p value < 0.05) lower scanpath similarity scores. The findings of this study support the combined use of eye-tracking and qualitative research methods for detecting and understanding individual differences in forecasters’ eye movements. Future applications of these methods in operational meteorology research have potential to aid usability studies and improve human–computer interactions for forecasters.
  • Source:
    Weather and Forecasting, 33(2), 501-521
  • DOI:
  • Document Type:
    Journal Article
  • Funding:
    Grant no. NA11OAR4320072
  • Rights Information:
    Other
  • Compliance:
    CHORUS
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