The Inland Extent of Lake Effect Snow (LES) Bands Joseph P. Villani NOAA/NWS Albany, NY Michael L....
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Transcript of The Inland Extent of Lake Effect Snow (LES) Bands Joseph P. Villani NOAA/NWS Albany, NY Michael L....
The Inland Extent of Lake Effect Snow (LES) Bands
Joseph P. VillaniNOAA/NWS Albany, NY
Michael L. Jurewicz, Sr.NOAA/NWS Binghamton, NY
Jason KrekelerNOAA/NWS State College, PA/State University
of NY at Albany
Outline
• Goals• Methodology• Results• A few case
studies/examples• Summary
Goals
• Identify atmospheric parameters which commonly have the greatest influence on a LES band’s inland extent
• Infuse research findings into operations
• Improve forecasts to support NWS Watch/Warning/Advisory program
Satellite depiction of developing LES band
Well developed band from Lake Ontario to the Hudson Valley
Upstream moisture sources
Methodology/Data Sources
• Examined around 25 LES events across the Eastern Great Lakes (Erie/Ontario) during the 2006-2009 time frame
– For each event, parameters evaluated at 6-hour intervals (00, 06, 12, and 18 UTC), using mainly 0-hr NAM12 model soundings
– Event duration varied from 6 hours to multiple days
Methodology/Data Sources
• Wind regimes stratified by mean flows:–250-290° for single bands (WSW-ENE
oriented)–300-320° for multi bands (NW-SE oriented)
• LES bands’ inland extent (miles) calculated from radar mosaics, distance measuring tool
• Data points:– Locations inside and north/south band• Data stratified by location relative to band
Example of Data Points
Points in and near LES band
BUF soundingALY sounding
Parameters1) Mixed layer (ML) wind Avg. direction/speed (deg/kt)
2) Ambient low level moisture
Surface dewpoint (°C); Max ML dewpoint depression (TdD) (°C)
3) Snow band width/length
>= 15 dBZ contour (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 sheara. bulk shear (0-1, 0-3 km)
Vector difference between wind at top and bottom of layer (kt)
6) Vertical wind shearb. directional/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/radar data
Strategy to Determine Best Parameters
• Used statistical correlations in Excel spreadsheet to determine most influential factors driving inland extent
– Overall, locations relative to bands made little difference in the correlations (within the bands vs. north or south)• A few exceptions
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)
Statistical Correlations
• Also notable correlators in locations outside of the bands: – Points south of the band:• Mixed-layer wind speed (0.33)• Mixed-layer directional shear (-0.18)
– Points north of the band:• Surface convergence (0.34)• 925 hPa convergence (0.12)
Results from Correlations
• Environments that promote greater inland extent:
–Multi-Lake Connection– Conditional instability class– Strong 0-1 km shear, weaker shear in1-3
km layer– High capping inversion height
Event Types from Results
• Event types favorable for inland extent based on strongest correlations– Instability and Multi-Lake Connection (MLC)
• Niziol Instability Class: – Conditional Instability• Lake-850 hPa difference: 12°C to18°C• Lake-700 hPa difference: 17°C to 24°C
–Moderate-Extreme Instability• Lake-850 hPa difference: >18°C• Lake-700 hPa difference: >24°C
• Use these parameters to classify events:
– Type A – MLC & Conditional Instability (most favorable type for inland extent)
– Type B – MLC & Moderate/Extreme Instability
– Type C – No MLC & Moderate/Extreme Instability
– Type D – No MLC & Conditional Instability
Classifying Event Types
0 20 40 60 80 100 120
Inland Extent (mi)
Lake–850 TD (°C)
Lake-700 TD (°C)
Inversion Height (km x 10)
Type C
Type B
Type A
Results by Event Type
Vertical Wind Profiles of Mixed Layer
• Type A – greater 0-1 km shear, less above 1 km
• Other Types – less 0-1 km shear, greater above
0-3 km
0-1 km
Z
X
Type A – Surface – 29Oct2006 18Z
Type A Sounding - 29Oct2006 18Z
• Strong 0-1 km speed shear, weaker 1-3 km
• Little directional shear in mixed layer
• High (if any) capping inversion
• Conditional Instability– Lake temp: 10°C– 850 temp : - 4°C– 700 temp: - 15°C
0°C
• Broad cyclonic flow associated with Low pressure in Quebec
• Multi-Lake Connection indicated by visible satellite
Type A – Satellite – 29Oct2006 18Z
850 hPa wind
Upstream Bands
• LES band inland extent around 169 mi
Type A – Radar – 29Oct2006 18Z
0-1 km bulk shear
Type C – Surface – 07Feb2007 18Z
Type C Sounding – 07Feb2007 18Z
• Less 0-1 km speed shear, greater shear in 1-3 km layer
• More directional shear in mixed layer
• Extreme Instability– Lake temp:
4°C– 850 temp : -
18°C– 700 temp: -
28°C
0°C
• NO Multi-Lake Connection indicated by visible satellite• Well-developed single band, but with little inland extent
Type C – Satellite – 07Feb2007 18Z
850 hPa wind
No connection with upstream bands
• LES band inland extent only 34 mi
Type C – Radar – 07Feb2007 18Z
0-1 km bulk shear
• Type A events result in greatest inland extent, often over 100 miles
• Key factors are: Instability, MLC, Shear– Ideal conditions: • Conditional instability• MLC• Strong mixed layer flow with minimal
speed shear between 1-3 km • Nearly unidirectional flow through mixed
layer
Summary
• Refer to event types when forecasting inland extent– Forecast the event type, which will yield good
first guess for inland extent potential
• Use pattern recognition of favorable surface, 850/700 hPa low tracks in forecasting MLC
• Use AWIPS forecast application (based on equation derived from correlated parameters), which provides estimate of inland extent
Application
850 mb Low center tracks
Example of Real-time Application
Example of Real-time Application
Ongoing/Future Work
• Infuse forecast applications into operations
• Develop graphical interface for output from equation
• Evaluate output from AWIPS forecast application
Acknowledgements
• Jason Krekeler– NOAA/NWS State College, PA/State
University of NY at Albany
• Hannah Attard– State University of NY at Albany
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.
Questions?
[email protected]@[email protected]
www.weather.gov/alywww.weather.gov/bgmwww.weather.gov/ctp