1. Anticipating Structure in Lake-Effect Snow Events (Updated Results) Michael L. Jurewicz, Sr. NOAA/NWS, Binghamton, NY Justin Arnott NOAA/NWS, Gaylord, MI 2013 U.S./Canada Great Lakes Meteorology Workshop April 16, 2013

2. Outline Motivation Motivation Goals Goals Brief review of concepts / earlier research on the morphology of Lake-effect precipitation Brief review of concepts / earlier research on the morphology of Lake-effect precipitation Study Methodology Study Methodology Results Results Demonstration of potential utility in an operational forecast setting Demonstration of potential utility in an operational forecast setting

3. Motivation Anticipating how well organized a lake-effect snow event will become can be tricky business Anticipating how well organized a lake-effect snow event will become can be tricky business “Conventional thinking” dictates that changes in mode / organization tend to be impacted by the diurnal heating cycle “Conventional thinking” dictates that changes in mode / organization tend to be impacted by the diurnal heating cycle –More fractured cellular elements in the afternoon, with better defined banded structures from late at night into the morning However, this doesn’t always work However, this doesn’t always work –Well defined bands have occasionally been observed during peak heating (afternoon); with unexpected occurrences of disorganized, open-cellular snow showers late at night or in the morning Suggests these processes are more complex than simply being tied to diurnal heating / cooling, or time of year Suggests these processes are more complex than simply being tied to diurnal heating / cooling, or time of year

4. Goals To identify the atmospheric parameters most responsible for governing the organization / different modes of Lake- effect snow To identify the atmospheric parameters most responsible for governing the organization / different modes of Lake- effect snow Utilize this information to formulate a technique for predicting convective mode in Lake-effect snow situations Utilize this information to formulate a technique for predicting convective mode in Lake-effect snow situations

5. Brief Overview of Earlier Research It has been shown that well defined roll-type convection (banded structures) tends to prevail when: It has been shown that well defined roll-type convection (banded structures) tends to prevail when: –The low-level environment (1-2 km AGL) has moderate to strong speed shear; although little directional shear –Some low-level heat flux / instability is present However, there seems to be an upper-limit However, there seems to be an upper-limit –If too unstable, can detract from overall organization Weckwerth, et al. (1997); Stull (1988); and Miura (1986) Weckwerth, et al. (1997); Stull (1988); and Miura (1986) These findings also substantiated by the Lake-Ice Field Experiment over Lake Michigan (Kristovich, Laird, and Hjemfeldt (2003)) These findings also substantiated by the Lake-Ice Field Experiment over Lake Michigan (Kristovich, Laird, and Hjemfeldt (2003))

6. Satellite View of “Lake- Ice” Project Area

7. Formation of Bands Clouds are suppressed in between bands

8. A Plan Coming Together Given that we’ve established the importance of both vertical speed shear and at least some CBL instability to the existence of horizontal rolls / Lake-effect bands; these questions logically follow: Given that we’ve established the importance of both vertical speed shear and at least some CBL instability to the existence of horizontal rolls / Lake-effect bands; these questions logically follow: –Is there a preferred amount of either one; or an optimal balance between them? –How would one best quantify and then illustrate these parameters?

9. Initial Methodology Interrogated Central NY Lake-effect snow events archived from the winters of 2005-06 up through 2008-09 Interrogated Central NY Lake-effect snow events archived from the winters of 2005-06 up through 2008-09 –Originally, only looked at Feb., March, and April cases –Later filled in cases from Oct.-Jan. Utilized radar and sounding information Utilized radar and sounding information –Radar imagery was the basis for categorizing individual events (banded structures vs. open-cellular convection) –NAM BUFKIT soundings used to determine shear and stability parameters at 6-hourly time steps (0000, 0600, 1200, and 1800 UTC) Specific site was chosen based on proximity to greatest radar coverage Specific site was chosen based on proximity to greatest radar coverage

10. Updated Methodology Addition of LES cases from Northern MI; and also more recent Central NY events (2010 to Present) Addition of LES cases from Northern MI; and also more recent Central NY events (2010 to Present) –Still adding more events to database Slightly different radar/sounding strategy used for MI cases Slightly different radar/sounding strategy used for MI cases –Instead of using specific sites, an “areal average” methodology was employed Helps avoid potential pitfalls of choosing a single “contaminated site” (artificially high CAPE within a well organized LES band) Helps avoid potential pitfalls of choosing a single “contaminated site” (artificially high CAPE within a well organized LES band) “Background state” stability more representative “Background state” stability more representative Analogous to avoiding a sounding location affected by thunderstorms in the warm season Analogous to avoiding a sounding location affected by thunderstorms in the warm season –Currently in the process of tabulating “areal average” values for the NY events (not yet fully correlated)

11. Sampling of Originally Chosen Parameters –For Stability: Lapse Rates Lapse Rates CAPE (Terrestrial and Lake-Induced) CAPE (Terrestrial and Lake-Induced) –For Shear (including normalized values) Mixed Layer (ML) Speed Shear Mixed Layer (ML) Speed Shear 0-1 km Speed Shear 0-1 km Speed Shear

12. Better Correlations (NY Cases, So Far) For statistical purposes, we assigned Banded events a value of 0 and Disorganized / Cellular events a value of 1 For statistical purposes, we assigned Banded events a value of 0 and Disorganized / Cellular events a value of 1 –Diffuse (Broken / Discontinuous Bands) events were given a value of 0.5 Here’s how some of the numbers currently look [normalized values for Mixed Layer depths in brackets]: Here’s how some of the numbers currently look [normalized values for Mixed Layer depths in brackets]: –CAPE = 0.36 [0.34] –Lake-Induced CAPE = (-0.11) [-0.28] –Bulk Speed Shear = (-0.28) [-0.36] –0-1 km Speed Shear = (-0.30) There seemed to be sensitivity to the depths over which Bulk Speed Shear occurred There seemed to be sensitivity to the depths over which Bulk Speed Shear occurred

13. Scatter Plot for NY Cases Dark Blue = Well defined Bands Yellow = Diffuse Bands Purple = Open-cellular Snow Showers

14. Lines of Best Fit Open-Cellular Snow Showers Diffuse Bands Well defined Bands

15. Scatter Plot for MI Cases * Most Banded Cases had CAPE < 15 J/kg

16. LI CAPE vs. CAPE (NY) Banded = Dark Blue Diffuse Bands = Yellow Cellular Snow Showers = Purple * Most Well-defined Bands had Terrestrial CAPES < 20 J/kg

17. Is This Worth It? As mentioned earlier, the value of this technique will be measured by how much skill it can show over normal diurnal trends As mentioned earlier, the value of this technique will be measured by how much skill it can show over normal diurnal trends To that end, let’s look at some statistics, then a case study example To that end, let’s look at some statistics, then a case study example

18. Graphical Comparison

19. Example March Case Appeared to be a situation where consolidated LES bands typically develop / evolve in Central NY: Appeared to be a situation where consolidated LES bands typically develop / evolve in Central NY: –Steady-state and moist 290 to 300 degree flow in the CBL –Little directional shear –Late night / early morning time frame Despite these factors, LES remained disorganized / cellular in nature Despite these factors, LES remained disorganized / cellular in nature –Not enough vertical shear to balance lingering terrestrial instability?

20. Radar Images at 0600 UTC, 03/13/04

21. Sounding from Ithaca, NY at 0600 UTC, 03/13/04

22. Snowfall Totals

23. Where This Event Falls Open-Cellular Snow Showers Diffuse Bands Well defined Bands Early Morning, 3/13/04

24. Summary How well LES bands were able to remain consolidated inland, seemed to hinge on a preferred balance of CBL CAPE and Normalized Bulk Speed Shear How well LES bands were able to remain consolidated inland, seemed to hinge on a preferred balance of CBL CAPE and Normalized Bulk Speed Shear Better vertical shear and some instability were most conducive; while too much instability and/or too little shear were the primary detractors Better vertical shear and some instability were most conducive; while too much instability and/or too little shear were the primary detractors Fits conceptual model of Horizontal Rolls well and supports previous LES research Fits conceptual model of Horizontal Rolls well and supports previous LES research

25. Summary (continued) “Best fit” line was drawn on scatter plot of CAPE vs. Normalized Speed Shear “Best fit” line was drawn on scatter plot of CAPE vs. Normalized Speed Shear –Discriminated fairly well between Banded and Cellular LES events –New technique showed improvement over simply using diurnal trends “Odd ball” cases provided the best support (well developed LES bands near peak heating or disorganized cellular convection late at night / early in the morning) “Odd ball” cases provided the best support (well developed LES bands near peak heating or disorganized cellular convection late at night / early in the morning)

26. Future Work Finish tabulating parameters and correlations for the entire body of events (2005-Present); and over both areas (NY/MI) Finish tabulating parameters and correlations for the entire body of events (2005-Present); and over both areas (NY/MI) If necessary, refine Scatter Plots / Nomograms If necessary, refine Scatter Plots / Nomograms Modified BRN ? Modified BRN ? Publish Results Publish Results BUFKIT Application ? BUFKIT Application ?

27. A Model for Future Application?

28. Questions ?? Questions ??