An Iterative Approach toward Development of Ensemble Visualization Techniques for High-Impact Winter Weather Hazards: Part II: Product Evaluation

Author:

Radford Jacob T.1,Lackmann Gary M.2,Goodwin Jean3,Correia James4,Harnos Kirstin5

Affiliation:

1. Department of Marine, Earth, and Atmospheric Sciences, North Carolina State University, Raleigh, North Carolina, and Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, Colorado;

2. Department of Marine, Earth, and Atmospheric Sciences, North Carolina State University, Raleigh, North Carolina;

3. Department of Communication, North Carolina State University, Raleigh, North Carolina;

4. National Oceanic and Atmospheric Administration/National Weather Service/National Center for Environmental Prediction/Weather Prediction Center, College Park, Maryland, and Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, Colorado;

5. National Oceanic and Atmospheric Administration/National Weather Service/National Center for Environmental Prediction/Weather Prediction Center, College Park, Maryland

Abstract

Abstract We developed five prototype convection-allowing model ensemble visualization products with the goal of improving depictions of the timing of winter weather hazards. These products are interactive, web-based plots visualizing probabilistic onset times and durations of intense snowfall rates, probabilities of heavy snow at rush hour, periods of heightened impacts, and mesoscale snowband probabilities. Prototypes were evaluated in three experimental groups coordinated by the Weather Prediction Center (WPC) Hydrometeorological Testbed (HMT), with a total of 53 National Weather Service (NWS) forecasters. Forecasters were asked to complete a simple forecast exercise for a snowfall event, with a control group using the Storm Prediction Center’s (SPC) High-Resolution Ensemble Forecast (HREF) system viewer, and an experimental group using both the HREF viewer and the five experimental graphics. Forecast accuracy was similar between the groups, but the experimental group exhibited smaller mean absolute error for snowfall duration forecasts. A series of Likert-scale questions saw participants respond favorably to all of the products and indicated that they would use them in operational forecasts and in communicating information to core partners. Forecasters also felt that the new products improved their comprehension of ensemble spread and reduced the time required to complete the forecasting exercise. Follow-up plenary discussions reiterated that there is a high demand for ensemble products of this type, though a number of potential improvements, such as greater customizability, were suggested. Ultimately, we demonstrated that social science methods can be effectively employed in the atmospheric sciences to yield improved visualization products.

Publisher

American Meteorological Society

Subject

Atmospheric Science

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