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Snow Squalls: Forecasting and Hazard Mitigation P ETER B ANACOS 1, A NDREW LOCONTO 1, and G REG D E V OIR 2 1 WFO Burlington, VT 2 WFO State College, PA.

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Presentation on theme: "Snow Squalls: Forecasting and Hazard Mitigation P ETER B ANACOS 1, A NDREW LOCONTO 1, and G REG D E V OIR 2 1 WFO Burlington, VT 2 WFO State College, PA."— Presentation transcript:

1 Snow Squalls: Forecasting and Hazard Mitigation P ETER B ANACOS 1, A NDREW LOCONTO 1, and G REG D E V OIR 2 1 WFO Burlington, VT 2 WFO State College, PA Northeast Regional Operational Workshop XIV – 11 December 2013

2 2 Background information on squalls and societal impacts Synoptic and mesoscale snow squall environments Snow Squall Forecasting Parameter R20: Research  Operations Conveying the message (Special Wx Statements, Social Media, Interactive Highway signs, action plans, etc.) Outline

3 What is a Snow Squall? A mesoscale convective system producing gusty winds & heavy snow. 3 Time-Matched Imagery 30 November 2007 Elm St., Potsdam, NY TYX 0.5 o reflectivity loop Tend to be short-lived Don’t reach NWS snow advisory criteria Falling temperatures can produce a “flash freeze” situation Can have deadly road consequences (high-impact, sub-advisory, HISA)

4 4 Long history of deadly accidents with snow squalls (~ 1”)… …how do we mitigate this? NBC33 - Indianapolis Burlington Free Press

5 More certainty in forecast products, better lead times. Better communication. Road crews pre-treat surfaces PREVIOUS STUDIES OF SNOW SQUALLS (non-lake effect) Create a snow squall database and improve our meteorological understanding through compositing WHAT WE WANT TO DO: Improve forecaster situational awareness by developing a new snow squall parameter (these are low QPF events) Validate snow squall parameter against individual cases Continue to improve operational messaging, education, and state/local partnerships END RESULT: 5 A few case studies and one forecast technique (WINDEX, Lundstedt 1993). Cool-season MCS work may be relevant (e.g., Low-Dewpoint MCS/derechos, Corfidi et al. ‘06). Some focus on external partnerships (Devoir 2004, NWS – PENNDOT)

6 BTV MPV MSS New York Vermont METHODS Searched 10 years of ASOS data for moderate or heavy snow (VSBY ≤ ½ SM) with a west wind component. Each S or S+ observation was compared with 2-km radar mosaics to subjectively determine if the event was associated with a cold front or mobile upper trough (and not a stratiform/WAA case). Found 36 total snow squall events ( through ). Logged surface data characteristics for each case. 3 ASOS locations used 6 Creating a Snow Squall Database

7 Surface and Synoptic Features 7

8 8 Snow squalls are short-lived events… VSBY ≤ ¼ SM ASOS VSBY ≤ ½ SM

9 9 Modest Snow AmountsSmall Liquid EquivalentContinental SLRs

10 10 Dendrite growth zone (-12 to -18C) Wind speed max (38 kts)

11 BUFKIT Summary Time-height cross-sections: – A brief, intense zone of UVV in the lowest 2km AGL. Intersects Dendritic Growth Zone (-12 to -18C) in saturated (RH ≥ 90%) atmosphere Along/just ahead of cold front. – Examine θ e profile for vertically-oriented or folded isentropes (steep lapse rates, potential instability). – Well-defined wind shift with strongest wind speeds/ mixing just behind front. – Don’t get hung up on QPF. Likely only ~0.05”. 11

12 Parameters Examined using 3-hrly NARR data in GEMPAK (analysis times immediately before and after squall time) 12 SBCAPEMUCAPE (0-180mb) Sfc-2km Theta-e differenceSfc-2km RH Sfc-2km mean windSfc-2km wind shear 925mb frontogenesisSfc isallobars (3hrly) 850mb frontogenesisWBZ height Precipitable Water300mb Divergence 925mb theta-e Adv.850mb theta-e Adv. 850mb temperature advection0-2km lapse rate

13 13 NARR Variable Distribution for 36 Snow Squall Events Normalized between 25 th and 50 th percentile values… 9ms -1, 75%, 0K/2km

14 14 NARR SCATTERPLOT of 0-2km mean RH vs. THETA-E Difference (36 SNSQ CASES) Favored parameter space

15 15 Moisture low-level Instability Wind Calibration was done using NARR data, but can be tweaked for operational models. Snow Squall Parameter (SNSQ, non-dimensional) plot only for values > 0 and where T w ≤ 1 2m Cold enough for snow Necessary Ingredients for Squalls Moist convection, but cold enough for snow. (1) moisture, (2) lift, (3) instability, (4) wind, and (5) vertical temperature structure (to support snow) SNSQ approaches zero as any of these variables approaches zero. Lift (forcing) would be assessed independently (isallobaric rise/fall couplet, F-GEN).

16 3-hrly NARR SNSQ time series at BTV (5 months) SNSQ Parameter One # to highlight where kinematic and thermodynamic conditions are favorable for snow squalls Winter

17 Case Examples February 2003 (using the NARR) 17 January 2013 (using the NARR & BTV-12km WRF) BTV-12km WRF: Initialized with the GFS and no convective parameterization.

18 Testing the SNSQ Parameter Against Past Events: Feb CG Lightning (11/20z through 12/12z) EXAMPLE 1 “SNOW DERECHO” CASE

19 Feb /21 Z 12/00 Z WI 12/03 Z SNSQ Parameter Shaded, left panels 3-hr Isallobars A simple way to assess convergence (lift) /propagation Pres. couplets often the difference between convective snow showers and organized squalls 21z 00z 03z SNSQ RADAR

20 SBCAPE (J kg -1 ), 925mb Frontogenesis (K 100km -1 3hr -1 ) 0-2km  e Diff. 0-2km Mean RH (%) Isallobaric Convergence 3-hr Isallobars (mb) mb F-gen

21 January 2013 EXAMPLE 2 Intense snow squalls along sharp cold front SNSQ (03z, 9 h forecast) BTV-12km WRF 17 Jan 2013 Lake effect snow showers

22 22 SNOW SQUALL OBSERVATIONS: CYYU Z 33020KT 1/8SM +SN +BLSN VV001 M14/M35 A2944 RMK SN8 PRESRR SLP962 CYNM Z AUTO 33028G37KT 1/4SM +SN BLSN VV005 M17/M19 A2936 RMK MAX WND 33037KT AT 2300Z PRESRR SLP968 CYXR Z AUTO 32028G38KT 230V330 1/8SM +SN SCT014 BKN019 BKN027 OVC070 M08/M10 A2948 RMK MAX WND 27038KT AT 2345Z PRESRR SLP998 CYSB Z 35021G28KT 1/2SM R22/2800VP6000FT/D SHSN DRSN VV003 RMK SN8 CYVO Z 32020G28KT 1/2SM -SN BLSN VV007 M14/M15 A2951 RESN RMK BLSN8 PRESRR SLP022 17/0040Z January 2013 CaseEXAMPLE 2 Reflectivity – Landrienne, Quebec

23 NARR SNSQ parameter with PMSL and isallobars (03z 17 Jan 2013) 23 isallobaric wind Convergence maximized on leading edge of isallobaric gradient (usually near zero change line). SNSQ

24 24 Isallobaric convergence part of thermally direct frontogenetic circulation. 925mb F-gen Isallobaric Convergence

25 View from Burlington, VT of snow squall crossing Lake Champlain (17/13z) SNSQ Parameter (17/12z) (BTV-12km WRF 12-hr FCST) Mosaic Composite Reflectivity (17/1155z)

26 See the SNSQ Parameter in Real-Time 26 SPC is working on adding the SNSQ Parameter to Mesoanalysis page (full CONUS availabiliity) SNSQ On the Web (BTV 4 and 12km WRF runs) AWIPS 4-panel procedures (Volume browser changes sent to the SOO mail list) URLs:

27 27 QUESTIONS?


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