1. A Method to Reliably Predict Convective Modes in Late Season Lake-Effect Snow Events Michael L. Jurewicz, Sr. NOAA/NWS Binghamton, NY November 1, 2006 NROW 8 Albany, NY

2. Motivation Lake-effect snow forecasting can be quite challenging Lake-effect snow forecasting can be quite challenging –Particularly late in the season (February through April) Due to the increased sun angle, changes in mode / organization tend to follow the diurnal heating cycle Due to the increased sun angle, changes in mode / organization tend to follow the diurnal heating cycle However, this doesn’t always work However, this doesn’t always work –For example, well defined bands during peak heating time (afternoon); or disorganized open-cellular snow showers late at night or in the morning

3. Goals To identify the atmospheric parameters primarily responsible for governing the organization / different modes of Lake- effect snow To identify the atmospheric parameters primarily 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 –In order for this method to have value, skill must be demonstrated over and above simply following diurnal trends

4. Methodology Central NY Lake-effect snow events have been archived since the winter of 2002-03 Central NY Lake-effect snow events have been archived since the winter of 2002-03 –Only looked at Feb., March, and April cases for this project Utilized radar and sounding information from this database Utilized radar and sounding information from this database –Radar imagery was the basis for categorizing individual events (banded structures vs. open-cellular convection) –NAM soundings used to determine shear and stability parameters at 6-hourly time steps (0000, 0600, 1200, and 1800 UTC) 111 different time periods evaluated for this study 111 different time periods evaluated for this study Specific site was chosen based on proximity to greatest radar coverage Specific site was chosen based on proximity to greatest radar coverage

5. Examples

6. Example of Data Cataloging

7. Outline Review of earlier research on the morphology of Lake-effect precipitation Review of earlier research on the morphology of Lake-effect precipitation –Horizontal Roll concepts (Multiple Bands) Similar transverse circulations / convergence on the edges of intense single bands Similar transverse circulations / convergence on the edges of intense single bands Overview of how technique was developed for predicting convective mode Overview of how technique was developed for predicting convective mode Demonstration of potential utility in an operational forecast setting Demonstration of potential utility in an operational forecast setting

8. Horizontal Convective Rolls Counter-rotating horizontal vortices in CBL Aligned along mean wind direction Due to combination of surface heat flux and wind Clouds often above updraft branches The COMET Program

9. Formation of Bands Clouds are suppressed in between bands

10. Lake-ICE Experiment Project conducted in January of 1998 Project conducted in January of 1998 Used mobile soundings, observation sites, and airborne Doppler radar to look at structure / behavior of Lake- effect bands / cells over Lake Michigan Used mobile soundings, observation sites, and airborne Doppler radar to look at structure / behavior of Lake- effect bands / cells over Lake Michigan –Kristovich, Laird, and Hjemfeldt (2003)

11. Satellite View of Project Area

12. Sounding Data

13. Airborne Radar Depiction

14. Brief Summary of Findings In 100 km 2 In 100 km 2 box over Lake Michigan: – –Snow showers displayed mainly disorganized / open cellular appearance Further south over Lake Michigan: – –Snow showers displayed a banded look to them; more consistent with organized horizontal rolls Stronger low-level shear and more boundary layer stability (lower air-lake temperature differentials) across this region

15. Consistency with Other Research It has been shown that roll-type convection tends to prevail when: It has been shown that roll-type convection tends to prevail when: –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, seems to be an upper-limit However, seems to be an upper-limit –If too unstable, can detract from overall organization –Weckwerth, et al. (1997); Stull (1988); and Miura (1986)

16. Warm Season Comparisons Can make an interesting analogy with Pulse vs. Organized thunderstorms Can make an interesting analogy with Pulse vs. Organized thunderstorms –Need sufficient vertical shear to balance CAPE Will typically result in more organized multi-cell systems, squall lines, etc. Will typically result in more organized multi-cell systems, squall lines, etc. –Weakly sheared environments Will typically see shorter-lived and disorganized storms Will typically see shorter-lived and disorganized storms One important difference is with directional shear One important difference is with directional shear –Favorable ingredient to strengthen updrafts and cold pool dynamics with upright convection / thunderstorms –Unfavorable for maintaining narrow updraft branches / corridors with horizontal roll type convection

17. 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?

18. BUFKIT Several advantages of using BUFKIT soundings as part of the study: Several advantages of using BUFKIT soundings as part of the study: –Good data availability (archived back to 2002) –Many shear / stability parameters already quantified within the program –Widely used forecast tool in Lake-effect situations

19. Trial and Error Initially unsure of what specific quantities to look at, we decided to try the following: Initially unsure of what specific quantities to look at, we decided to try the following: –For instability – Lapse Rates, CAPE, and depths of the Mixed Layer (for any normalization) LR and CAPE values from the surface to inversion base LR and CAPE values from the surface to inversion base –For shear – Bulk Speed Shear and the Mean Flow near the top of the CBL Bulk Speed Shear values also from the surface to inversion base Bulk Speed Shear values also from the surface to inversion base

20. Spreadsheet Sample

21. Correlations 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 After tabulating results for the entire database, here’s how some of the numbers fell out: After tabulating results for the entire database, here’s how some of the numbers fell out: –Bulk Speed Shear (-0.66) –CAPE (0.58) –Normalized Bulk Shear (-0.57) –Lapse Rate (0.43) –Wind Speed just below Inversion (-0.23) –CBL Depth (-0.05)

22. Scatter Plot Diagram Purple Markers = Open Cellular Events Dark Blue Markers = Banded Events

23. Scatter Plot Diagram Line of Best Fit

24. 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 case study examples To that end, let’s look at some statistics, then case study examples

25. Statistical Comparisons If one were to simply follow diurnal trends to forecast convective mode (in other words, 06z or 12z = Banded ; and 18z or 00z = Cellular), here’s how the numbers added up: If one were to simply follow diurnal trends to forecast convective mode (in other words, 06z or 12z = Banded ; and 18z or 00z = Cellular), here’s how the numbers added up: –For Banded Events : POD = 0.74 and FAR = 0.16 –For Cellular Events : POD = 0.82 and FAR = 0.29

26. Stats for New Method Line of Best Fit For Banded: POD=0.84 and FAR = 0.05 For Cellular: POD = 0.94 and FAR = 0.19

27. Graphical Comparison

28. March 13, 2004 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 instability?

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

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

31. Snowfall Totals

32. Specific Plots Line of Best Fit March 13, 2004 at 06z and 12z

33. February 12, 2003 It was approaching the right time of year for LES bands to break up near peak heating in the afternoon It was approaching the right time of year for LES bands to break up near peak heating in the afternoon Yet, in this case, a single LES band stayed well in tact Yet, in this case, a single LES band stayed well in tact –Not enough instability to disrupt “roll circulation,” that was kept well in tact by strong vertical shear

34. Radar Images at 1800 UTC, 02/12/03

35. Sounding from Syracuse, NY at 1800 UTC, 02/12/03

36. Snowfall Information

37. Specific Plot Line of Best FitFebruary 12, 2003 at 1800Z

38. Summary The following are preliminary results (from a database of 4 different winter seasons and 100+ time periods): The following are preliminary results (from a database of 4 different winter seasons and 100+ time periods): –How well LES bands were able to organize into banded structures, or remain consolidated, seemed to hinge on a preferred balance of CBL CAPE and 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 Analogous to some aspects of warm-season convection Analogous to some aspects of warm-season convection

39. Summary (continued) “Best fit” line was drawn on scatter plot of CAPE vs. Bulk Speed Shear “Best fit” line was drawn on scatter plot of CAPE vs. Bulk 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)

40. Future Work Continue to evaluate this technique over coming winter seasons to see if success continues with a larger database Continue to evaluate this technique over coming winter seasons to see if success continues with a larger database –If success continues, possibly include as a diagnostic tool within BUFKIT Also look at different parts of the Great Lakes region / Other times of year Also look at different parts of the Great Lakes region / Other times of year –Varying terrain, lake / land interfaces, upwind influences, etc. –Examine November to January cases Strong single bands less sensitive to downstream changes in stability / shear ? Strong single bands less sensitive to downstream changes in stability / shear ? How much vertical shear is too much ? How much vertical shear is too much ? –Especially with shorter-fetch bands Stability Differences between Land / Lake Surfaces Stability Differences between Land / Lake Surfaces

41. A Model for Future Application?

42. Thank You !! Questions ?? Questions ??