The 28 January 2014 “Snowmageddon” in the Southeastern U.S.

A rare combination of anomalously cold air and rapidly-falling snow produced a massive travel disruption in parts of the southeastern U.S. on 28 January 2014. Storm-total snowfalls were generally only around 5 cm in the Birmingham and Atlanta areas, but most people were at work or school when the snow began. Due to rapid and widespread icing on roadways, thousands of people were forced to sleep in offices and children slept in schools. Many others’ vehicles were abandoned on freeways and surface streets, forcing them to walk miles to shelter in bitterly cold temperatures.

This event was a unique forecasting challenge in many aspects, especially for the southeastern U.S. In the 24 hours leading up to the event, computer model QPF was focused to the south of the main population centers, where the main disruptions eventually occurred. A layer of extremely dry air was present up to 800 hPa. A descending snow level with time in radar data reflectivity data a few hours before the event provided evidence that snow may occur. However, forecasters did not anticipate the rapid saturation of the low levels given low RH and large dewpoint depressions. However, the saturation deficit was only ~3 g kg^-1. Also, the very high snow-to-liquid ratios at very cold temperatures were not anticipated (25 was observed in this case, 3 times the climatological average for the Southeast). Hourly climatology of surface snowfall observations at Birmingham since 1948 showed the median temperature for snow was 1 °C, whereas on 28 January 2014, it was -7 °C. Finally, soil and road temperatures were already very cold due to abnormally low temperatures in the weeks leading up to the event, and the extreme cold on the day of the event was the primary factor in causing road deterioration with such a small amount of snow.

In this paper, we will examine the event in detail, including the synoptic setup, vertical profiles of temperature and moisture, soil temperatures, numerical models, radar data, and forecasting. The goal is to show how snow in anomalously cold air masses, specifically in the Southern U.S., presents a variety of forecast challenges, and how to mitigate those problems.