1. A Process-Oriented Observational Study of Snowfall Potential in the Central United States Chad M Gravelle Saint Louis University Charles E Graves Saint Louis University Scott M Rochette State University of New York College at Brockport Annual Missouri Academy of Science Meeting Missouri Western State University, 21 April 2007

2. Outline Introduction Description of Dataset Methodology/Case Selection Summary of Results Conclusions

3. Introduction Even with advances in numerical and ensemble model guidance, forecasting the axis and spatial extent of heavy snowfall still contains a large amount of uncertainty. Gouree and Younkin 1966 Browne and Younkin 1970 Probabilistic forecasts are used by SPC and HPC to show the uncertainty with an event.

4. Dataset Daily 24-h snowfall amounts were obtained from the National Climate Data Center (NCDC) Cooperative Summary of the Day (COOP) collection for the period of November 1998 and March 2003. North American Regional Reanalysis (NARR) –3-h dataset with 32-km resolution on 29 pressure levels NCDC publications of the Daily Weather Maps. COOP and NARR datasets were displayed using the General Meteorological Package (GEMPAK) software.

5. Methodology

6. 15 Jan 200316 Jan 2003 17 Jan 200372-h Event

7. Methodology

8. COOP event data for each station was objectively analyzed using a Barnes objective analysis. –271 x 171 grid ~ 10 km grid spacing Parameters for the objective analysis were chosen such that stations within 35 km had the most influence on each grid point. Finally, a 9-pt smoother was applied to all fields before generating graphics.

9. Methodology

10. Case Categories Total events, n = 82 Banded (upper left), n = 42 Widespread (upper right), n = 15 Other/Multi-banded/Undefinable (lower left), n = 25

11. Banded Categories Total events, n = 42 NW/SE (upper left), n = 11 W/E within 30° of major axis (upper right), n = 17 SW/NE (lower left), n = 14

12. Length/Width Example

13. Banded Length Statistics

14. Banded Width Statistics

15. A Look Ahead... X

16. X X

17. X X X

18. X X X X

19. Conclusions Lengths at lower snowfall thresholds often exceed the domain. SW/NE bands are the widest, followed by E/W and NW/SE. Early indications suggest that the differences in width of the three orientations are not the results of sampling, but the physical processes associated with snowfall generation.

20. Future Research Using percentiles to provide forecasters with probabilistic guidance on the width of snowfall bands. Examine the orientation and strength of processes to snowfall potential. Expanding the period of record to include more years. Use the identified events as analogs of future events.

21. Find this, and other presentations online at: www.eas.slu.edu/CIPS/ Questions or Comments? gravelle@eas.slu.edu