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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

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Mesoscale Structure of Precipitation Regions in Northeast Winter Storms

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Mesoscale Structure ofPrecipitation Regions inNortheast Winter Storms

Matthew D. Greenstein, Lance F. Bosart, and Daniel KeyserDepartment of Earth and Atmospheric SciencesUniversity at Albany, Albany, NY 12222

David J. NicosiaNational Weather ServiceBinghamton Weather Forecast Office, Johnson City, NY 13790

7 April 2006

CSTAR-II support provided by NOAA Grant NA04NWS4680005


Outline

  • Introduction

  • Case selection

  • Radar classification

  • Cross section analysis

  • Summary of results

  • Future work


Introduction

  • Forecasters can predict likely areas of precipitation

  • Forecasters cannot always skillfully predict mesoscale features

  • Forecasting mesoscale details adds value to a forecast:

    • Prediction of snowfall amount and variability

    • Differentiating between high-impact and low-impact snows


Introduction

  • Precipitation regions have multiple modes (patterns)

  • Goal is to examine ingredients …

  • * Lift * Instability * Moisture * Microphysics

  • … to find ways of distinguishing the modes


Introduction: Previous banded studies

  • Matejka, Houze, and Hobbs (1980)

Surge

Postfrontal

Warm frontal

Cold frontal

Warm sector


Introduction: Previous banded studies

  • Nicosia and Grumm (1999)


Introduction: Previous banded studies

  • Novak et al. (2004)

Banded

Nonbanded


Introduction: Previous banded studies

  • Novak et al. (2004)

Banded

Nonbanded


Case Selection

  • Cases occur in area bounded by 36.5°N, 50°N, 65°W, and 85°W

  • Within U.S. radar coverage

  • 1 October – 30 April

  • No warm sector precipitation

  • P–type predominantly snow

  • “Heavy snow” = 15+ cm in 12 h over area the size of CT

  • No lake effect snows and enhancements

  • Past three winters (2002–3, 2003–4, 2004–5)


Case Selection

  • Data used

    • NCDC national hourly mosaic reflectivity images

    • Public Information Statements (PNS)

    • Northeast River Forecast Center snowfall maps

    • NCDC’s U.S. Storm Events Database

    • ASOS reports


20 Cases

  • 26–27 Nov 2002

  • 4–6 Dec 2002

  • 25–26 Dec 2002

  • 2–5 Jan 2003

  • 6–7 Feb 2003

  • 15–18 Feb 2003

  • 6 Mar 2003

  • 5–8 Dec 2003

  • 13–15 Dec 2003

  • 14–15 Jan 2004

  • 27–28 Jan 2004

  • 16–17 Mar 2004

  • 18–19 Mar 2004

  • 19–20 Jan 2005

  • 22–23 Jan 2005

  • 24–25 Feb 2005

  • 28 Feb–2 Mar 2005

  • 8–9 Mar 2005

  • 11–13 Mar 2005

  • 23–24 Mar 2005


Radar Classification

  • 2km WSI NOWrad mosaics * 15-min resolution* 3 levels of quality control* Composite reflectivity

  • Uniform

  • Classic Band

  • Transient Band

  • Bandlets

  • Fractured

  • Unclassifiable

Multiple modes may exist in a storm’s lifecycle and at one time


Radar Classification: Uniform

1200 UTC 27 Nov 2002


Radar Classification: Classic Band

1900 UTC 7 Feb 2003


Radar Classification: Transient Band

1200–2100 UTC 16 Feb 2003

Evolving Band


Radar Classification: Transient Band

1600 UTC 6 Dec 2003

Broken Band


Radar Classification: Transient Band

2115 UTC 14 Dec 2003

Messy Band


Radar Classification: Bandlets

1500 UTC 17 Feb 2003


Radar Classification: Fractured

1500 UTC 16 Mar 2004


Cross Section Analysis

  • Previous research: frontogenesis in the presence of weak moist symmetric stability yields bands

  • Negative saturation equivalent potential vorticity (EPV*) indicates conditional slantwise instability (CSI) and/or conditional upright instability (CI)

  • CI dominates CSI

*

  • EPV* = – g (ζ · θe), where ζ is the absolute vorticity vector


Cross Section Analysis

  • 32–km North American Regional Reanalysis (NARR)

  • Cross sections contain …

    • Saturation equivalent potential temperature – θe (K)

    • Relative humidity (%)

    • 2D Petterssen Frontogenesis (ºC 100 km-1 3 h-1)

    • Saturation equivalent potential vorticity - EPV* (PVU) (calculated with the full wind)

    • Vertical motion (μb s-1)

    • Dendritic growth zone, i.e., −12ºC and −18ºC isotherms

*


Cross Section Analysis: Classic Band

2100 UTC 7 Feb 2003

Strong, steep, surface-based frontogenesisStrong, tilted ascent rooted in the boundary layerWeakly positive EPV*CI unimportant


Cross Section Analysis: Uniform

2100 UTC 22 Jan 2005

Weak, flat frontogenesis

Upright ascent

Ascent strength not a factor

Weakly positive & negative EPV*has no effect

No CI


Cross Section Analysis: Transient Band

1500 UTC 16 Feb 2003

Weak, decoupled frontogenesisInhibits continuous boundary layer moisture feed

Weakly positive EPV* seen in all modes


Cross Section Analysis: Bandlets

0000 UTC 1 Mar 2005

Frontogenesis lifts air parcels to CI region

Escalator-elevator


Cross Section Analysis: Fractured

1500 UTC 16 Mar 2004

Weak, decoupled, fragmented frontogenesis

SeparateEPV mins and ascent maxesLower RH


Summary of Results: Distinguishing features

‡= some look like a bandCI enhances updrafts & downdrafts


Summary of Results: Nondistinguishing features

  • Ascent 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)

  • Intersection of max ascent with CI region

  • RH patterns

  • Reduced EPV** All cases contain EPV* 0–0.25 PVU (WMSS) and CSI* Shape and location of reduced EPV* regions


Summary of Results: Nondistinguishing features

  • 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 + RH ≥ 70% + Ascent

    • Max vertical speed shear

    • 850–500 hPa vertical speed shear


*

g

Summary of Results: EPV* vs. EPV

*

g

  • Reasons for EPV

    • Symmetric instability theory: thermal wind balance

    • Mg 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?


*

g

EPV*

0600 UTC 23 Jan 2005

EPV


*

*

*

g

g

g

  • Because… 1) Value does not seem to matter2) WMSS is a necessary but not distinguishing factor3) CI plays an important role

  • Use EPV* because it produces a cleaner image

  • If classic band is indicated, use EPV for position

Summary of Results: EPV* vs. EPV

*

g

  • EPV produces a messier pattern with more negative values, especially in dry areas

  • EPV “bull’s-eyes” line up with band positions


Summary of Results: Conceptual Models


Summary of Results: Conceptual Models


Summary of Results: Conceptual Models


Summary of Results: Conceptual Models


Summary of Results: Conceptual Models


Summary of Results: Flowchart


*

g

Future Work

  • Is the “fractured” mode really just a hybrid of “bandlets” & “transient bands” but with drier spaces?

  • Prove decoupled frontogenesis hypothesis

  • Investigate band lag

  • Examine the EPV “bull’s-eyes”


  • Lance and Dan

Special Thanks

  • David Ahijevych (NCAR)

  • Kevin Tyle

  • Alan Srock

  • Anantha Aiyyer

  • Keith Wagner

  • Celeste, Sharon, and Lynn

  • My parents


Questions? Comments?

e-mail: [email protected]


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