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A Method to Reliably Predict Convective Modes in Late Season Lake-Effect Snow Events

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. Motivation. Lake-effect snow forecasting can be quite challenging

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A Method to Reliably Predict Convective Modes in Late Season Lake-Effect Snow Events

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  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 • 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 • 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 • 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 Methodology • Central NY Lake-effect snow events have been archived since the winter of 2002-03 • Only looked at Feb., March, and April cases for this project • Utilized radar and sounding information from this database • Radar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 • 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 • Horizontal Roll concepts (Multiple Bands) • Similar transverse circulations / convergence on the edges of intense single bands • Overview of how technique was developed for predicting convective mode • Demonstration of potential utility in an operational forecast setting

  8. Horizontal Convective Rolls The COMET Program • 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

  9. Formation of Bands Clouds are suppressed in between bands

  10. Lake-ICE Experiment • 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 • 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 km2box 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: • 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 • 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 • Need sufficient vertical shear to balance CAPE • Will typically result in more organized multi-cell systems, squall lines, etc. • Weakly sheared environments • Will typically see shorter-lived and disorganized storms • 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: • 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: • 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: • For instability – Lapse Rates, CAPE, and depths of the Mixed Layer (for any normalization) • 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

  20. Spreadsheet Sample

  21. Correlations • 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: • 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 • 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: • 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 For Banded: POD=0.84 and FAR = 0.05 Line of Best Fit 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: • 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 • 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 • 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 February 12, 2003 at 1800Z Line of Best Fit

  38. Summary • 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 • Fits conceptual model of Horizontal Rolls well and supports previous LES research • 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 • 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)

  40. Future Work • 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 • Varying terrain, lake / land interfaces, upwind influences, etc. • Examine November to January cases • Strong single bands less sensitive to downstream changes in stability / shear ? • How much vertical shear is too much ? • Especially with shorter-fetch bands • Stability Differences between Land / Lake Surfaces

  41. A Model for Future Application?

  42. Thank You !! Questions ??

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