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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

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Mesoscale Structure of Precipitation Regions in Northeast Winter Storms

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  1. 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

  2. Outline • Introduction • Case selection • Radar classification • Cross section analysis • Summary of results • Future work

  3. 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

  4. Introduction • Precipitation regions have multiple modes (patterns) • Goal is to examine ingredients … • * Lift * Instability * Moisture * Microphysics • … to find ways of distinguishing the modes

  5. Introduction: Previous banded studies • Matejka, Houze, and Hobbs (1980) Surge Postfrontal Warm frontal Cold frontal Warm sector

  6. Introduction: Previous banded studies • Nicosia and Grumm (1999)

  7. Introduction: Previous banded studies • Novak et al. (2004) Banded Nonbanded

  8. Introduction: Previous banded studies • Novak et al. (2004) Banded Nonbanded

  9. 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)

  10. 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

  11. 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

  12. 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

  13. Radar Classification: Uniform 1200 UTC 27 Nov 2002

  14. Radar Classification: Classic Band 1900 UTC 7 Feb 2003

  15. Radar Classification: Transient Band 1200–2100 UTC 16 Feb 2003 Evolving Band

  16. Radar Classification: Transient Band 1600 UTC 6 Dec 2003 Broken Band

  17. Radar Classification: Transient Band 2115 UTC 14 Dec 2003 Messy Band

  18. Radar Classification: Bandlets 1500 UTC 17 Feb 2003

  19. Radar Classification: Fractured 1500 UTC 16 Mar 2004

  20. 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

  21. 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 *

  22. 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

  23. 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

  24. 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

  25. Cross Section Analysis: Bandlets 0000 UTC 1 Mar 2005 Frontogenesis lifts air parcels to CI region Escalator-elevator

  26. Cross Section Analysis: Fractured 1500 UTC 16 Mar 2004 Weak, decoupled, fragmented frontogenesis SeparateEPV mins and ascent maxesLower RH

  27. Summary of Results: Distinguishing features ‡ ‡ ‡= some look like a bandCI enhances updrafts & downdrafts

  28. 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

  29. 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

  30. * 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?

  31. * g EPV* 0600 UTC 23 Jan 2005 EPV

  32. * * * g g g • Because… 1) Value does not seem to matter 2) WMSS is a necessary but not distinguishing factor 3) 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

  33. Summary of Results: Conceptual Models

  34. Summary of Results: Conceptual Models

  35. Summary of Results: Conceptual Models

  36. Summary of Results: Conceptual Models

  37. Summary of Results: Conceptual Models

  38. Summary of Results: Flowchart

  39. * 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”

  40. Lance and Dan Special Thanks • David Ahijevych (NCAR) • Kevin Tyle • Alan Srock • Anantha Aiyyer • Keith Wagner • Celeste, Sharon, and Lynn • My parents

  41. Questions? Comments? e-mail: greenstein@atmos.albany.edu

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