Mesoscale Structure of Mesoscale Structure of Precipitation Regions in Precipitation Regions in Northeast Winter Storms Northeast Winter Storms Matthew D. Greenstein, Lance F. Bosart, and Matthew D. Greenstein, Lance F. Bosart, and Daniel Keyser Daniel Keyser Department of Earth and Atmospheric Sciences Department of Earth and Atmospheric Sciences University at Albany, Albany, NY 12222 University at Albany, Albany, NY 12222 David J. Nicosia David J. Nicosia National Weather Service National Weather Service Binghamton Weather Forecast Office, Johnson City, Binghamton Weather Forecast Office, Johnson City, NY 13790 NY 13790 7 April 2006 7 April 2006 CSTAR-II support provided by NOAA Grant NA04NWS4680005 CSTAR-II support provided by NOAA Grant NA04NWS4680005
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Mesoscale Structure of Precipitation Regions in Northeast Winter Storms
Mesoscale Structure of Precipitation Regions in Northeast Winter Storms. Matthew D. Greenstein, Lance F. Bosart, and Daniel Keyser Department of Earth and Atmospheric Sciences University at Albany, Albany, NY 12222 - PowerPoint PPT Presentation
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Mesoscale Structure ofMesoscale Structure ofPrecipitation Regions inPrecipitation Regions inNortheast Winter StormsNortheast Winter Storms
Matthew D. Greenstein, Lance F. Bosart, and Daniel KeyserMatthew D. Greenstein, Lance F. Bosart, and Daniel KeyserDepartment of Earth and Atmospheric SciencesDepartment of Earth and Atmospheric Sciences
University at Albany, Albany, NY 12222University at Albany, Albany, NY 12222David J. NicosiaDavid J. Nicosia
National Weather ServiceNational Weather ServiceBinghamton Weather Forecast Office, Johnson City, NY Binghamton Weather Forecast Office, Johnson City, NY
1379013790
7 April 20067 April 2006CSTAR-II support provided by NOAA Grant NA04NWS4680005CSTAR-II support provided by NOAA Grant NA04NWS4680005
OutlineOutline
• IntroductionIntroduction• Case selectionCase selection• Radar classificationRadar classification• Cross section analysisCross section analysis• Summary of results Summary of results • Future workFuture work
IntroductionIntroduction• Forecasters Forecasters cancan predict likely areas of precipitation predict likely areas of precipitation• Forecasters Forecasters cannotcannot always skillfully predict always skillfully predict mesoscale features mesoscale features• Forecasting mesoscale details adds value to a Forecasting mesoscale details adds value to a forecast:forecast:
• Prediction of snowfall amount and variabilityPrediction of snowfall amount and variability• Differentiating between high-impact andDifferentiating between high-impact and low-impact snows low-impact snows
IntroductionIntroduction• Precipitation regions have multiple modes Precipitation regions have multiple modes (patterns)(patterns)• Goal is to examine ingredients …Goal is to examine ingredients … * Lift* Lift * Instability * Instability * Moisture * Moisture * Microphysics * Microphysics … … to find ways of distinguishing the to find ways of distinguishing the modesmodes
Introduction: Introduction: Previous banded Previous banded studiesstudies• Matejka, Houze, and Hobbs (1980)Matejka, Houze, and Hobbs (1980)
Warm frontalWarm frontal
SurgSurgee
PostfrontaPostfrontall
Cold frontalCold frontal
Warm Warm sectorsector
Introduction: Introduction: Previous banded Previous banded studiesstudies• Nicosia and Grumm (1999)Nicosia and Grumm (1999)
Introduction: Introduction: Previous banded Previous banded studiesstudies• Novak et al. (2004)Novak et al. (2004)
Banded Nonbanded
Introduction: Introduction: Previous banded Previous banded studiesstudies• Novak et al. (2004)Novak et al. (2004)
Banded Nonbanded
Case SelectionCase Selection• Cases occur in area bounded by Cases occur in area bounded by 36.5°N, 50°N, 65°W, and 85°W36.5°N, 50°N, 65°W, and 85°W• Within U.S. radar coverage Within U.S. radar coverage • 1 October – 30 April 1 October – 30 April • No warm sector precipitationNo warm sector precipitation• P–type predominantly snow P–type predominantly snow • “ “Heavy snow” = 15+ cm in 12 h over area the Heavy snow” = 15+ cm in 12 h over area the size of CTsize of CT• No lake effect snows and enhancementsNo lake effect snows and enhancements• Past three winters (2002–3, 2003–4, 2004–5)Past three winters (2002–3, 2003–4, 2004–5)
Case SelectionCase Selection• Data usedData used
• NCDC national hourly mosaic reflectivity NCDC national hourly mosaic reflectivity imagesimages• Public Information Statements (PNS)Public Information Statements (PNS)• Northeast River Forecast Center snowfall mapsNortheast River Forecast Center snowfall maps• NCDC’s U.S. Storm Events DatabaseNCDC’s U.S. Storm Events Database• ASOS reportsASOS reports
20 Cases20 Cases• 26–27 Nov 26–27 Nov 20022002• 4–6 Dec 20024–6 Dec 2002• 25–26 Dec 25–26 Dec 20022002• 2–5 Jan 20032–5 Jan 2003• 6–7 Feb 20036–7 Feb 2003• 15–18 Feb 15–18 Feb 20032003• 6 Mar 20036 Mar 2003
• 5–8 Dec 20035–8 Dec 2003• 13–15 Dec 13–15 Dec 20032003• 14–15 Jan 14–15 Jan 20042004• 27–28 Jan 27–28 Jan 20042004• 16–17 Mar 16–17 Mar 20042004• 18–19 Mar 18–19 Mar 20042004
• 19–20 Jan 200519–20 Jan 2005• 22–23 Jan 200522–23 Jan 2005• 24–25 Feb 200524–25 Feb 2005• 28 Feb–2 Mar 28 Feb–2 Mar 20052005• 8–9 Mar 20058–9 Mar 2005• 11–13 Mar 200511–13 Mar 2005• 23–24 Mar 200523–24 Mar 2005
Radar ClassificationRadar Classification• 2km WSI NOW2km WSI NOWradrad mosaics mosaics
* 15-min resolution* 15-min resolution* 3 levels of quality control* 3 levels of quality control* Composite reflectivity* Composite reflectivity
Cross Section AnalysisCross Section Analysis• Previous research:Previous research: frontogenesis in the presence of weak frontogenesis in the presence of weak moist symmetric stability yields bands moist symmetric stability yields bands
Summary of Results: Summary of Results: Distinguishing Distinguishing featuresfeatures Frontogenesis Other
Uniform weak and/or flator none
no CI
ClassicBand
strong and steep; surface-based
ascent indicates frontal circulation dominates
Transient
Band
decoupled ω not well rooted in B.L.;CI alters precip pattern
Bandlets thin, weak, or none; surface-based
CI / escalator–elevator;deep CI = messier pattern
Fractured
fragmented;decoupled
CI or frontogenesis enhances precip; lower RH ‡ ‡ = some look like a band= some look like a band CI enhances updrafts & CI enhances updrafts &
downdraftsdowndrafts
‡‡
‡‡
Summary of Results: Summary of Results: Nondistinguishing featuresNondistinguishing features• Ascent strengthAscent strength
* * Uniform: −4 to −24 μb s-1
** Classic band: ≤ −20 μb s-1
• Intersection of max ascent with DGZ• Depth of DGZ (~50–100 hPa in most cases)–100 hPa in most cases)• Intersection of max ascent with CI regionIntersection of max ascent with CI region• RH patternsRH patterns• Reduced EPV*Reduced EPV*
* All cases contain EPV* 0–0.25 PVU (WMSS) * All cases contain EPV* 0–0.25 PVU (WMSS) and CSIand CSI
* Shape and location of reduced EPV* regions* Shape and location of reduced EPV* regions
Summary of Results: Summary of Results: Nondistinguishing featuresNondistinguishing features• From plan-view analyses…From plan-view analyses…
• QG–forcing ratio: DCVA / (DCVA + WAA)• Depths of reduced EPV* satisfying various criteria
• EPV* ≤ 0, ≤ 0.25, 0–0.25, or –0.25, or ≤ −0.25 + RH ≥ 70% + Ascent
Summary of Results: Summary of Results: EPV* vs. EPVEPV* vs. EPV
• Reasons for EPVReasons for EPV• Symmetric instability theory: thermal wind Symmetric instability theory: thermal wind balancebalance• MMgg more accurately captures growing instability more accurately captures growing instability
• Reasons for EPV*• Better representation of curved flow• Assumption that time scale of convection << time scale for large-scale environmental changes not valid? Potential for slantwise convection better found by using an evolving and unbalanced environment?
**gg**gg
EPVEPV
EPV*EPV*
**gg
0600 UTC 23 Jan 0600 UTC 23 Jan 20052005
Summary of Results: Summary of Results: EPV* vs. EPV EPV* vs. EPV
• EPV produces a messier pattern with more EPV produces a messier pattern with more negative negative values, especially in dry areas values, especially in dry areas• EPV “bull’s-eyes” line up with band positions EPV “bull’s-eyes” line up with band positions
**gg**gg
**gg
• Because… Because… 1) Value does not seem to matter1) Value does not seem to matter2) WMSS is a necessary but not distinguishing 2) WMSS is a necessary but not distinguishing
factorfactor3) CI plays an important role3) CI plays an important role
• Use EPV* because it produces a cleaner imageUse EPV* because it produces a cleaner image• If classic band is indicated, use EPV for positionIf classic band is indicated, use EPV for position
**g g
Summary of Results: Summary of Results: Conceptual Conceptual ModelsModels
Summary of Results: Summary of Results: Conceptual Conceptual ModelsModels
Summary of Results: Summary of Results: Conceptual Conceptual ModelsModels
Summary of Results: Summary of Results: Conceptual Conceptual ModelsModels
Summary of Results: Summary of Results: Conceptual Conceptual ModelsModels
Summary of Results: Summary of Results: FlowchartFlowchart
Frontogenesis?
YES NO
CI?
YES NO
Decoupled frontogenesis?
NO YES
Strong, steep frontogenesis?
Fragmented frontogenesis?
YES NO
Classic Band
Bandlets
Transient Band
YES NO
CI?
YES NO
Bandlets
Uniform
Fractured
Uniform
Future WorkFuture Work• Is the “fractured” mode really just a hybrid of Is the “fractured” mode really just a hybrid of “bandlets” & “transient bands” but with drier “bandlets” & “transient bands” but with drier spaces?spaces?
• Examine the Examine the EPV “bull’s-eyes”EPV “bull’s-eyes” **gg
Special ThanksSpecial Thanks• Lance and DanLance and Dan
• David Ahijevych (NCAR)David Ahijevych (NCAR)• Kevin TyleKevin Tyle• Alan SrockAlan Srock• Anantha AiyyerAnantha Aiyyer• Keith WagnerKeith Wagner• Celeste, Sharon, and LynnCeleste, Sharon, and Lynn• My parentsMy parents