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Keywords:

  • human-automation interaction;
  • forecaster judgement;
  • weather radar;
  • severe weather;
  • warning decision;
  • confidence

Abstract

Experimental weather radars are being developed that could enhance the severe weather warning process by providing higher resolution data sensed closer to the ground and with faster update rates. Because wind speed is an important criterion in the issuance of severe thunderstorm warnings, this research investigates the impact of adding these new data to the forecaster decision-making process. In a static case review setting, 30 National Weather Service (NWS) forecasters evaluated six convective weather cases under two conditions: (1) using (conventional) WSR-88D weather radar data, and, (2) using both WSR-88D and additional data from an experimental four-radar network. Forecasters' predictions of ground level wind gusts, 2–5 min into the future, were compared to measurements from ground-based wind sensors. When provided with the additional radar data participants significantly improved the accuracy of their wind speed assessments (absolute error reduced from 5.9 m s−1 to 4.0 m s−1; p < 0.001), increased their assessment confidence ratings (p < 0.001), forecasted significantly greater wind speeds (20.4 m s−1 as opposed to 17.1 m s−1; p < 0.001), and increased the number of affirmative decisions to warn from 15 to 35 (p = 0.001). While the addition of high resolution, low altitude, rapidly updating radar data is shown to have both qualitative and quantitative benefits, training and warning policy implications for the incorporation of new technology must also be carefully considered as increased accuracy, confidence and higher wind speed estimates may lead to more warnings. Copyright © 2011 Royal Meteorological Society