Southern United States Winter Storm of 28 January 2014-v1. High Impact Snow on Edge of Forecast Precipitation Shield
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1 Southern United States Winter Storm of 28 January 2014-v1 High Impact Snow on Edge of Forecast Precipitation Shield by Richard H. Grumm National Weather Service State College, PA and 1. Introduction A highly amplified flow pattern (Fig. 1) brought unseasonably cold air and a relatively rare snow and ice event to the southern United States on 28 January The low-level cold air (Fig. 2) forced southward by the strong northerly flow ((Fig. 1) brought arctic air into the Gulf States with -1 to -2σ below normal 850 hpa temperatures. The precipitation (Fig. 3) which fell over the southern United States fell as rain along the immediate coast with freezing rain, sleet, and snow on the cold side of the system. The wintry precipitation wreaked havoc in portions of the south including the City of Atlanta. (CNN 2014; NPR 2014). Despite being relatively prepared for the storm, the lack of sufficient snow and ice removal resources combined with ill equipped drivers on icy roads contributed to massive traffic problems. Areas on the northern edge of the forecast precipitation shield such as the central and northern municipalities of Alabama (NPR 2014), including the city of Birmingham, staged snow removal equipment to the south to aid in clean up. The snow fell farther north than anticipated, resulting in serious problems in the city of Birmingham. This combination of issues produced hours long traffic tie ups, massive traffic accidents, and many traffic-related deaths and injuries. In some municipalities, school children were forced to overnight in schools. Forecasts of the intrusion of arctic air and the potential for ice and snow in the Deep South were relatively successful. The critical issues were the lead-time and uncertainty as to where the snow and ice would occur. Like many winter storms, ensemble forecasts showed tight gradients between where rain, freezing rain, and snow would fall. Along the northern edge of the precipitation shield, the ensembles showed a sharp gradient between areas to receive snow and areas to receive no snow. Studies on the use of ensembles in forecasting both rain and snow events have shown that forecasting along the edge of precipitation events is often difficult and fraught with uncertainty. The uncertainty associated with the precipitation shield proved to be a critical issue in this event. With that in mind, the focus of this paper is on the forecasts of the precipitation. Though areas where the probabilities of a rare winter precipitation event were high were generally prepared for the storm, areas on the edges, where the uncertainty was perceived to be a lower threat, were not
2 as prepared. And in Alabama, limited snow and ice removal resources were staged in the higher threat regions. This case demonstrated why probabilistic forecasting is essential, some limits to ensemble forecast systems, and critical issues in close proximity to tight gradients. It is critical to identify high impact events even if the probability of the event is low due to the potential losses should the low probability outcome occur. 2. Methods and Data The large scale pattern was reconstructed using 00-hour forecasts from the NCEP Global Forecast System (GFS). Standardized anomalies were computed as in Hart and Grumm (2001) using the re-analysis (Climate Forecast System; CFS) climate (R-Climate). The climatology spans a 30 year period. All data were displayed using GrADS (Doty and Kinter 1995). Ensemble forecasts were derived from the NCEP Global Ensemble Forecast System (GEFS) and the Short Range Ensemble Forecast System (SREF). Snowfall data was retrieved from the National Snow site in text format, decoded in Python, and plotted using GrADS. The QPE data was retrieved from the Stage-IV 6-hour data. These data too were plotted using GrADS. 3. Pattern The large scale pattern over North America (Fig.1) showed a deep trough over eastern North America and a sharp ridge over western North America and the eastern Pacific. This produced strong northerly flow from central Canada into the central and eastern United States. This pattern is a relatively well-known pattern favoring the intrusion of cold air and arctic masses into the central and eastern United States. The 850 hpa temperature pattern (Fig.2) showed the intrusion of cold air into the central and southern United States. The more significant 850 hpa temperature anomalies were over the Southern Plains where -3σ temperature anomalies were observed. A massive region of the Ohio Valley was covered by -2σ 850 hpa temperature anomalies. The 0C contour at 850 hpa was near Birmingham by 0000 UTC 28 January, had pushed to the south and east by 1800 UTC 28 January, and was through Atlanta shortly thereafter. The surface temperature and dew point plots (Fig.4) at both Atlanta and Birmingham show that temperatures were well above freezing before the arctic air pushed into the region. The observations show the temperature peaked in Birmingham at 953 AM (CDT) at 53F and then rapidly fell to 33F by 653 PM on 27 January (Fig. 5). The snow began at 953 AM on 28 January with a surface temperature of 21F. Atlanta reached a high of 61F on 27 January and fell to freezing around midnight with snow arriving around 11 AM on 28 January. The rapid intrusion of the sub-freezing air after a period of above freezing temperatures likely contributed to icy roads.
3 The surface pattern showed a strong anticyclone over the Midwest (Fig. 6) and a weak trough over the Gulf of Mexico. Like many overrunning events in and near strong 250 hpa jets (Fig. 7), there was not a significant cyclone or storm associated with this winter weather event. The 850 hpa winds (not shown) indicated modest warm advection over the southeastern United States. 4. Ensemble Forecasts of the Cyclone and Precipitation Shield The critical forecast elements associated with this event included the rapid intrusion of cold air into the Deep South and the onset time and type of precipitation. In a spatial context, where it would snow proved to be a critical element, and both the GEFS and SREF forecasted a sharp northern edge to the precipitation shield. In this event, the precipitation, in the form of snow, fell farther north than these two systems indicated. The area shown includes North Carolina and Virginia where both systems were relatively successful predicting both the snow and heavy snow.. For those states, this was a relatively wellforecasted event, and the regions were not as dramatically impacted as the Deep South. i. NCEP Global Ensemble Forecast System Forecasts from 6 GEFS forecast cycles are presented showing the probability of 6.25 mm or more of QPF and the ensemble mean QPF with each member s 6.25 mm contour. The location of Birmingham, AL is indicated; reflecting the issues of being on the edge of precipitation shield. These data (Figs. 8 & 9) show that the higher threat of over 6.25 mm (0.25 inches) was displaced well south of Birmingham. Initially, the threat was in the 4-10 percent range (Fig. 8a) but dropped to 0 percent at different times. The 6.25 mm contour generally stayed south of Birmingham or barely reached the region in most of the GEFS cycles presented. ii. NCEP Short Range Ensemble Forecast System The SREF QPF and probability of 6.25 mm (Fig. 10) showed a similar pattern to that predicted by the GEFS (Fig. 8). The focus for higher QPF amounts with higher probabilities was east of Birmingham. The mean QPF and the spaghetti plots (Fig. 11) showed a similar issue, with Birmingham, AL on the northwest edge of the precipitation shield. Due to the potential impact of snow in the Deep South, the SREF 2mm probabilities are shown in Figure 12. These data also show that Birmingham, AL was on the edge of the 2 mm or greater precipitation shield. But the probability was never lower than 20% and ranged as high as 60-80%. Thus, accumulating light snow was predicted by the SREF (Fig. 12) and the GEFS (not shown) when examining low end amounts. For contrast, the GEFS forecasts of snow and the probability of snow is shown in Figure 13. These data show the ensemble mean forecasts of 1-2 inches of snow and the probability of any snow extends well north of Birmingham. Ice and freezing rain forecasts (not shown) indicated a narrow band of ice and sleet south of this snow
4 band. Additionally, GEFS and SREF forecasts showed 6-10 inches of snow in eastern North Carolina and southeastern Virginia. 5. Summary An arctic front pushed into the southern United States on 28 January Ahead of the front, many locations were in the 50 and 60s within 24 hours of the onset of snow. The rapid temperature falls and onset of snow likely contributed to treacherous driving conditions in a region not accustomed to dealing with icy roads and snow. The rapid temperature changes may have contributed to icy road conditions. In addition to the rapid temperature falls, there were issues related to the onset time and area to be affected by snow and ice. The city of Birmingham, AL was perceived to be a location which might escape the snow as it was on the northern edge of the precipitation shield. Despite low probabilities of 6.25 mm or more QPF, snow fell in and around the city leading to serious disruptions to human activities. This storm demonstrates that even within areas where the threat of wintry weather was well predicted, many municipalities in the Deep South are ill prepared to deal with snow and ice. From climatological and fiscal perspectives, it is probably unfeasible to prepare for these rare events. The costs of plows and salt spreaders, which could go unused for years, is likely prohibitive. This combined with drivers not used to driving in snow and ice implies that with a high probability outcome of snow and ice, the best strategy may be to keep key roads open and restrict driving activities until the roads are cleared or the ice and snow have melted. A serious issue arises in the lower probability zones, such as Birmingham, AL where several forecast cycles showed a 0 to 10% chance of 6.25 mm or more QPF, which would fall as snow. In areas where the low probability event could be an extremely high impact event, precautions may be required. The impact of the forecast low probability event in Birmingham was clearly evident with massive traffic accidents, 5 traffic-related deaths, and stranded students. In climates where snow and ice are more frequent, a few inches of snow would likely have been a nuisance; snow and ice removal equipment could be easily deployed, drivers are more accustomed to driving in snow, and a percentage of drivers likely have tires specially designed to drive in snow. In areas where any snow is an issue, extreme low end probabilities need to be examined. In this event, the areal extent of the 2mm contour (Fig. 12 & Fig. 13) showed that some measureable snow was possible at the 40 to 80% confidence level within 24 hours of the onset of precipitation. Shorter range forecasts showed slightly improved probabilities. In areas where any snow is a high impact event, it may be advantageous to examine extremely low QPF and snow thresholds. 6. Science Issues This case study reveals a number of science issues the must be addressed before more accurate forecasts of these types of events are possible.
5 What were the predictability horizon issues o the frontal system was well predicted 4-7 days in advance o the precipitation event over the general region had 3-4 days of predictability o the areas where measureable snow would fall with high confidence on the northern edge of the system may have had hours of predictability How do forecasters deal with forecasts of snow on the edge of high probability o low probability where high impact event is a consideration o what thresholds are used matters and in the Deep South any accumulating snow is a high impact event How we use and examine data should be tied directly to I M P A C T S 7. Acknowledgements The Albany map for observations and discussions on the storm, storm potential, and snow to liquid issues related to the storm Thanks to Elyse Colbert for graphs, hourly observations, editing, and links to impacts. 8. References Doty, B. E., and J. L. Kinter III, 1995: Geophysical data and visualization using GrADS. Visualization Techniques Space and Atmospheric Sciences, E. P. Szuszczewicz and Bredekamp, Eds., NASA, Grumm, R.H. and R. Hart. 2001: Standardized Anomalies Applied to Significant Cold Season Weather Events: Preliminary Findings. Wea. and Fore., 16, Hamil, T.M, 2003: Evaluating Forecaster s Rule of Thumb: A study of d(prog)/dt. Wea. Forecasting,18, Hart, R. E., and R. H. Grumm, 2001: Using normalized climatological anomalies to rank synoptic scale events objectively. Mon. Wea. Rev., 129, Kocin, P. J., and L. W. Uccellini, 2004: Northeast Snowstorms, Volume I: Overview. Meteor. Monogr., Vol. 32, No. 54, Amer. Meteor. Soc., Kocin, P. J., and L. W. Uccellini, 1990: Snowstorms along the northeastern Coast of the United States: 1955 to Meteor. Monogr., No. 44, Amer. Meteor. Soc., 280p.
6 Stuart,N.A and R.H. Grumm 2006: Using Wind Anomalies to Forecast East Coast Winter Storms. Wea. and Forecasting, 21,
7 Figure 1. GFS 00-hour forecasts of 500 hpa heights (m) and 500 hpa height anomalies in 24 hour increments from a) January 2014 through f) 1200 UTC 29 January Contours are every 120 m and the black dot is the approximate location of Birmingham, AL. Return to text.
8 Figure 1. As in Figure 1 except for 850 hpa temperatures and temperature anomalies every 6 hours from a) 0000 UTC 28 January through f) 0600 UTC 29 January Return to text.
9 Figure 3. Total observed liquid equivalent precipitation for the period of 0000 UTC 28 through 1200 UTC 29 January Data from Stage-IV precipitation data (mm). Return to text.
10 Figure 4. Plots of surface temperature and dew points at the METAR sites in Atlanta and Birmingham. Return to text.
11 Figure 5. Image of the METAR data from Birmingham, AL. Return to text.
12 Figure 6. As in Figure 2 except for mean sea level pressure (hpa) and pressure anomalies. Contours every 4 hpa. Return to text.
13 Figure 7. As in Figure 6 except for 250 hpa winds and u-wind anomalies. Return to text.
14 Figure 8. NCEP 21-member GEFS forecasts showing the probability of 6.25mm or more QPF and the mean position of the 6.25mm contour from GEFS initialized at a) 0000 UTC 25 January, b) 0000 UTC 26 January, c) 0000 UTC 27 January, d) 0600 UTC 27 January, e) 1200 UTC 27 January, and 1800 UTC 27 January Shading is percentage and thick contour is ensemble mean. Return to text.
15 Figure 9. As in Figure 8 except for the GEFS mean QPF and each member s 6.25 mm contour with the ensemble mean in thick black. Return to text.
16 Figure 10. As in Figure 8 except for NCEP SREF forecasts initialized at a) 0300 UTC 26 January, b) 2100 UTC 6 January, c) 0300 UTC 26 January, d) 0900 UTC 27 January, f) 1500 UTC 27 January, and e) 2100 UTC 27 January Return to text.
17 Figure 11. As in Figure 10 except for SREF mean QPF (shaded) and each member s 6.25mm contour. Return to text.
18 Figure 12. As in Figure 10 except for SREF probabilities of 2 mm or more of QPF. Image is zoomed into the eastern Gulf States. Return to text.
19 Figure 2. As in Figure 8 except for NCEP GEFS forecasts of snow (inches) and the probability of snow valid from 1200 UTDC 28 through 0000 UTC 29 January Return to text.
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