1. The Inland Extent of Lake- Effect Snow (LES) Bands Joe Villani NOAA/NWS Albany, NY Michael L. Jurewicz, Sr. NOAA/NWS Binghamton, NY Jason Krekeler State Univ. of NY, Albany, NY 18 th GLOMW, Toronto, Ontario March 22-24, 2010

2. Outline Motivation Motivation Goals Goals Methodology Methodology Results Results Case Studies Case Studies Ongoing / Future Work Ongoing / Future Work

3. Motivation Considerable research has been devoted to LES processes and forecast issues over the last 2-3 decades Considerable research has been devoted to LES processes and forecast issues over the last 2-3 decades –However, among these, comparatively little attention has been given to inland extent

4. Goals To identify atmospheric parameters that commonly have the most influence on a LES band’s inland penetration To identify atmospheric parameters that commonly have the most influence on a LES band’s inland penetration –Use these results in the forecast process to improve: The quality/detail of information given to the public (nowcasting) The quality/detail of information given to the public (nowcasting) The NWS Watch/Warning/Advisory program The NWS Watch/Warning/Advisory program

5. Satellite Depiction of an Intense Band all the way to Albany, NY Well developed single band from Lake Ontario to the Hudson Valley Upstream moisture sources

6. Methodology/Data Sources Examined 20 LES events across the Eastern Great Lakes (Erie/Ontario) during the 2007-2010 time frame Examined 20 LES events across the Eastern Great Lakes (Erie/Ontario) during the 2007-2010 time frame –For each event, parameters were evaluated at 6-hour intervals (00, 06, 12, and 18 UTC), using the NAM12 and RUC models, as well as BUF/ALY soundings –Events averaged 24-30 hours in length Wind regimes varied from a mean flow of 250-260 (WSW-ENE oriented bands) to 300-320 (NW-SE oriented bands) Wind regimes varied from a mean flow of 250-260 (WSW-ENE oriented bands) to 300-320 (NW-SE oriented bands)

7. Methodology (Continued) LES bands’ inland penetrations (miles) calculated from radar mosaics, and a distance measuring application LES bands’ inland penetrations (miles) calculated from radar mosaics, and a distance measuring application Data points Data points –Locations both inside bands and on their peripheries were used (north, south, and just downstream of the band) Data stratified based on location relative to band Data stratified based on location relative to band

8. Example of Data Points Points in and near the LES band BUF sounding ALY sounding

9. Parameters 1) Mixed layer (ML) wind Avg. 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 (n mi) 4) Niziol instability class Lake–air  T( ° C) at 700/850 hPa 5) Capping inversion Inversion height: top of ML (m) 6) Vertical wind shear a. magnitude (0-1, 0-3 km) Vector difference between wind at top and bottom of layer (kt) (from Storm Prediction Center) 6) Vertical wind shear b. direction/speed Estimated values between surface and top of ML (deg/kt) 7) Low-level convergence From 0-hour 12km NAM 8) Multi-lake connection? Satellite data

10. Strategy to Determine “Best” Parameters Used statistical correlations to determine the most influential factors for inland extent Used statistical correlations to determine the most influential factors for inland extent –Overall, locations relative to bands made little difference in the correlations (within the bands vs. north or south) A few notable exceptions A few notable exceptions

11. Statistics Best correlators to inland extent (all points together): Best correlators to inland extent (all points together): –Multi-lake connection (0.75) –850/700 mb Lake-air differentials (-0.65) –Mixed-layer speed shear (0.27) –Mixed-layer directional shear (-0.23)

12. Results (Continued) Also a few healthy correlators in locations outside of the bands: Also a few healthy correlators in locations outside of the bands: –Points south of the band: Height of capping inversion (-0.4) Height of capping inversion (-0.4) Mixed-layer speed shear (0.35) Mixed-layer speed shear (0.35) –Points north of the band: Mixed-layer directional shear (-0.4) Mixed-layer directional shear (-0.4) Surface winds (0.3) Surface winds (0.3)

13. Brief Case Study Examples Both events featured 260-270 mean flow single bands Both events featured 260-270 mean flow single bands –8 January 2009 Only small inland penetration Only small inland penetration –16 January 2009 Much greater inland extent Much greater inland extent

14. 8 January – Radar + 1 km Shear Strong mixed-layer flow - 30 to 40 kt

15. 8 January – BUF Sounding - Lake to 850 mb Delta T of 13C - Lake to 700 mb Delta T of 22C - Only conditionally unstable LR’s

16. 16 January – Radar + 1 km Shear Strong mixed-layer flow – 30 to 40 kt Weaker mixed-layer flow - 10-20 kt

17. 16 January – BUF Sounding - Lake to 850 mb Delta T of 26C - Lake to 700 mb Delta T of 37C - Much steeper LR’s

18. Take-Home Points Environments that promoted greater inland extent of LES bands seemed to feature these characteristics: Environments that promoted greater inland extent of LES bands seemed to feature these characteristics: –Strong, well aligned flow in the mixed layer (especially north of the band) –Only conditional terrestrial instability Moderately to extremely unstable cases tended to produce disorganized/cellular structures, confined closer to the shoreline Moderately to extremely unstable cases tended to produce disorganized/cellular structures, confined closer to the shoreline

19. More Summary Points South of the band: South of the band: –Stable, sheared environments seemed favorable for inland extent Cold low-level inflow into the band Cold low-level inflow into the band Lower cap/EL Lower cap/EL Multi-Lake connection (MLC) is another factor that strongly related to inland extent Multi-Lake connection (MLC) is another factor that strongly related to inland extent

20. Ongoing / Future Work Further develop an algorithm/equation that provides an estimate of inland extent, based on favorably correlated parameters Further develop an algorithm/equation that provides an estimate of inland extent, based on favorably correlated parameters –To be used in cases where LES band development seems likely –Has already been tested on some of our cases, with favorable results Individual/composite plots for MLC patterns Individual/composite plots for MLC patterns –MSLP/850/700 low tracks –Based on flow regimes

21. Present/Future Work (Continued) Perhaps better delineate significant thresholds for strongly correlated parameters Perhaps better delineate significant thresholds for strongly correlated parameters Single banded vs. Multi-banded cases Single banded vs. Multi-banded cases

22. The End Questions ??