1. Forecasting the Inland Extent of Lake-Effect Snow (LES) Bands: Application and Verification for Winter 2010-2011 Joseph P. Villani NOAA/NWS Albany, NY Michael L. Jurewicz, Sr. NOAA/NWS Binghamton, NY Jason Krekeler NOAA/NWS State College, PA

2. Outline Introduction Forecast Application Verification of App. A few case studies Composite Plots Future Work

3. Introduction Determine atmospheric parameters which commonly have the greatest influence on a LES band’s inland extent Examined over 20 LES events across the Eastern Great Lakes (Erie/Ontario) during 2006-2009 winter seasons – For each event, parameters evaluated at 6-hour intervals (00, 06, 12, and 18 UTC), using mainly 0-hr NAM12 model soundings

4. Introduction Wind regimes stratified by mean flows: – 250-290° for single bands – 300-320° for multi bands LES bands’ inland extent (miles) calculated from radar mosaics, distance measuring tool Data points: – Locations inside and north/south band

5. Parameters 1) Mixed layer (ML) windAvg. direction/speed (deg/kt) 2) Ambient low level moisture Surface dewpoint ( ° C); Max ML dewpoint depression (T dD ) ( ° C) 3) Snow band width/length>= 15 dBZ contour (mi) 4) Niziol instability class Lake–air  T( ° C) at 700/850 hPa 5) Capping inversionInversion height: top of ML (m) 6) Vertical wind shear a. bulk shear (0-1, 0-3 km) Vector difference between wind at top and bottom of layer (kt) 6) Vertical wind shear b. directional/speed Estimated values between surface and top of ML (deg/kt) 7) Low-level convergenceFrom 0-hour 12km NAM 8) Multi-lake connection?Satellite/radar data

6. Strategy to Determine Best Parameters Used statistical correlations in Excel spreadsheet to determine most influential factors driving inland extent of LES bands Values for the best correlated parameters statistically significant to the 99.95% level with N > 500

7. Statistical Correlations Best correlators to inland extent (all points together): ALY events – 850 hPa Lake-air ∆T (-0.63) – Multi-lake connection present (0.59) – Capping inversion height (0.53) – 0-1 km bulk shear (0.44)

8. Results from Correlations Environments that promote greater inland extent (IE): – Multi-Lake Connection (from upstream lakes) – Conditional instability class – Strong 0-1 km shear, weaker shear in1-3 km layer – High capping inversion height

9. Favorable Environment far-reaching IE MLC present (not shown) Strong 0-1 km shear; little shear in 1-3 km layer High capping inversion height over 3 km 0-1 km 1-3 km 0°C Inversion

10. AWIPS Forecast Application Equation developed to determine inland extent of lake effect snow bands based on most strongly correlated parameters Forecast application based on equation created for use in NWS AWIPS software Application integrated on experimental basis at Albany and Binghamton NWS offices

11. Example of Forecast Application

12. Multi-Lake Connection (MLC) Use pattern recognition for favorable surface, 850/700 hPa low center tracks in forecasting MLC 850 hPa low center tracks

13. Verification of Application 10 event times verified via radar with >15 dBZ – Avg error = 10 miles – Excluding two narrow/multi-band/NW flow events Avg error = 4 miles – Avg bias = (-7) miles (under-forecasting IE) – Avg bias = (1) miles (excluding the two outliers) – Avg bias = (-35) miles (for 2 outliers)  Need more events to support verification

14. Example of single-band event 27 November 2010 – Single band event – extensive IE – MLC Present – IE forecast from application: 1100 UTC = 94 miles – Verification = 92 miles 1600 UTC = 90 miles – Verification = 100 miles

15. 27 November 2010 – 1600 UTC MLC present from Georgian Bay Well-developed single band depicted by satellite

16. 27 November 2010 – 1200 UTC MLC present Strong 0-1 km shear; little shear in 1-3 km layer High capping inversion height over 3 km 0-1 km 1-3 km 0°C Inversion

17. 27 November 2010 – 1100 UTC IE Forecast from application = 94 miles Actual IE = 92 miles Good performance of app.

18. Example of single-band event 02 December 2010 – Single band event – IE not extensive – No MLC Present – IE forecast from application: 1400 UTC = 46 miles – Verification = 45 miles 1500 UTC = 43 miles – Verification = 37 miles

19. 02 December 2010 – 1400 UTC No MLC present (not shown) Modest 0-1 km shear; greater shear in 1-3 km layer Lower capping inversion height 0-1 km 1-3 km 0°C Inversion

20. 02 December 2010 – 1400 UTC IE Forecast from application = 46 miles Actual IE = 45 miles Good performance of app.

21. Example of multi band event 08 December 2010 – Multi band event – IE extensive – MLC Present – IE forecast from application: 2100 UTC = 67 miles – Verification = 120 miles

22. 08 December 2010 – 2100 UTC IE Forecast from application = 67 miles Actual IE = 120 miles Poor performance of app.

23. Example of single-band event 16 January 2011 – Single band event – IE extensive – MLC Present – IE forecast from application: 0200 UTC = 92 miles – Verification = 87 miles 0600 UTC = 103 miles – Verification = 104 miles

24. 16 January 2011 – 0200 UTC IE Forecast from application = 92 miles Actual IE = 87 miles Good performance of app.

25. Composite Plots using NARR Composite maps of surface pressure and 500/700/850 hPa mean geopotential height plotted for far-reaching IE of LES bands Plus favorable environments with: – Multi-Lake Connection (from upstream lakes) – Conditional instability class – Strong 0-1 km shear, weaker shear in1-3 km layer – High capping inversion height

26. 850 hPa Mean Height Composite Mean Sea-Level Pressure Composite

27. 500 hPa Mean Height Composite 700 hPa Mean Height Composite

28. Composite Plots using NARR Plots obtained from NOAA’s Earth System Research Laboratory (ESRL) using North American Regional Reanalysis (NARR) Favorable positions for low centers generally in South-Central Quebec for far-reaching IE of LES bands into Albany forecast area

29. Conclusions In general, application represented IE well for well-developed single bands in W to WSW flow. Application under-forecasted IE (significantly at times) for narrow multi-bands in NW flow Additional changes may be needed for multi- band events

30. Ongoing/Future Work Solidify operational functionality of application through additional real-time events Develop graphical representation of the inland extent of snow bands, compare to models

31. Acknowledgements Jason Krekeler – NOAA/NWS State College, PA/State University of NY at Albany Vasil Koleci – NOAA/NWS Albany, NY Hannah Attard – State University of NY at Albany

32. References Niziol, Thomas, 1987: Operational Forecasting of Lake Effect Snowfall in Western and Central New York. Weather and Forecasting. Niziol, et al., 1995: Winter Weather Forecasting throughout the Eastern United States – Part IV: Lake Effect Snow. Weather and Forecasting.

33. Questions? Joe.Villani@noaa.gov Michael.Jurewicz@noaa.gov Jason.Krekeler@noaa.gov www.weather.gov/aly www.weather.gov/bgm www.weather.gov/ctp