On January 6-7th, 2017, a high impact winter event crossed north and central Georgia. Ahead of this system, NWS Atlanta supplied three experimental probabilistic snowfall graphics across the forecast area in an effort to illustrate the wide range of potential outcomes from this system; the minimum, most likely and maximum snowfall scenarios. Advertising the various snowfall solutions aided in effective communication of the large scale potential for model variability and forecaster uncertainty. This method proved effective as mid-level warming drastically reduced snowfall totals across metro Atlanta during the event. In addition, with forecast precipitation type changing to freezing rain and ice as the system unfolded, quick communication of these hazards to our core partners through webinars was essential.
While this winter event was a success in many regards with best practices gained, a bigger challenge surfaced. How do we effectively communicate a quickly changing forecast to our core partners and the public, especially when extreme conditions forecasted may rapidly change? This is not an easy task, especially in relation to winter weather across a large metropolitan area. A similar situation occurred in March 2017 when a large snowstorm was set to cripple some of the largest cities in the Northeast. As the event neared, weather models started to lessen the storm totals that were already forecasted and well communicated. The NWS chose not to reduce snowfall totals despite the wavering model solutions in an effort to maintain a consistent message and not to cause confusion. In the end, this decision did cause backlash amongst media and politicians as the observed amounts were less than the forecast.
Through a thorough analysis of these winter events we will highlight the challenges of expressing uncertainty to our core partners while also reviewing the importance of open communication amongst a rapidly evolving system.
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