1. Examining the Role of Mesoscale Features in the Structure and Evolution 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 David J. Nicosia National Weather Service Binghamton Weather Forecast Office, Johnson City, NY 13790 November 2, 2005

2. Outline Introduction Introduction Selection of cases Selection of cases Precipitation patterns Precipitation patterns Data analysis Data analysis Preliminary results Preliminary results Additional thoughts Additional thoughts Future work Future work

3. Introduction Forecasters can predict likely areas of precipitation Forecasters can predict likely areas of precipitation Forecasters cannot always skillfully predict mesoscale precipitation signatures within these areas Forecasters cannot always skillfully predict mesoscale precipitation signatures within these areas Forecasting mesoscale details adds value to a forecast Forecasting mesoscale details adds value to a forecast Precipitation patterns have multiple modes (forms) Precipitation patterns have multiple modes (forms) Goal is to examine the three main ingredients … Goal is to examine the three main ingredients … Moisture Moisture Stability Regime Stability Regime Lifting Mechanism Lifting Mechanism … that operate together to produce heavy snow in a variety of modes

4. Selection of Cases Cases occur in area bounded by 36.5°N, 50°N, 65°W, and 85°W Cases occur in area bounded by 36.5°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 precipitation No warm sector precipitation P–type predominantly snow P–type predominantly snow “Heavy snow” = 15+ cm in 12 h over an area the size of CT “Heavy snow” = 15+ cm in 12 h over an area the size of CT No lake effect snows and enhancements No lake effect snows and enhancements Past three winters (2002–3, 2003–4, 2004–5) Past three winters (2002–3, 2003–4, 2004–5)

5. 20 Cases 26–27 Nov 2003 26–27 Nov 2003 4–6 Dec 2002 4–6 Dec 2002 25–26 Dec 2002 25–26 Dec 2002 2–5 Jan 2003 2–5 Jan 2003 6–7 Feb 2003 6–7 Feb 2003 15–18 Mar 2003 15–18 Mar 2003 6 Mar 2003 6 Mar 2003 5–8 Dec 2003 5–8 Dec 2003 13–15 Dec 2003 13–15 Dec 2003 14–15 Jan 2004 14–15 Jan 2004 27–28 Jan 2004 27–28 Jan 2004 16–17 Mar 2004 16–17 Mar 2004 18–19 Mar 2004 18–19 Mar 2004 19–20 Jan 2005 19–20 Jan 2005 22–23 Jan 2005 22–23 Jan 2005 24–25 Feb 2005 24–25 Feb 2005 28 Feb–2 Mar 2005 28 Feb–2 Mar 2005 8–9 Mar 2005 8–9 Mar 2005 11–13 Mar 2005 11–13 Mar 2005 23–24 Mar 2005 23–24 Mar 2005

6. Precipitation Modes Uniform Uniform Fractured Fractured Banded Banded – Solid bands (with or without gaps between them) – Broken bands – Band segments During a storm life cycle and even at one time, multiple modes may be present During a storm life cycle and even at one time, multiple modes may be present Blob-like Blob-like Grainy Grainy Unclassified Unclassified

7. Precipitation Modes: Uniform

8. Precipitation Modes: Fractured / Band Segments

9. Precipitation Modes: Broken Band

10. Precipitation Modes: Fractured

11. Precipitation Modes: Segments? Blobs? Grainy?

12. Data Analysis 32–km North American Regional Reanalysis (NARR) 32–km North American Regional Reanalysis (NARR) How to evaluate the stability regime? How to evaluate the stability regime? Previous research: frontogenesis in the presence of weak moist symmetric stability yields bands Previous research: frontogenesis in the presence of weak moist symmetric stability yields bands Negative saturation equivalent potential vorticity (EPV*) indicates slantwise and/or upright instability Negative saturation equivalent potential vorticity (EPV*) indicates slantwise and/or upright instability Upright dominates slantwise instability Upright dominates slantwise instability Debate continues on EPV* or EPV* Debate continues on EPV* or EPV* Stability diagnostic: EPV* < 0.25 PVU Stability diagnostic: EPV* < 0.25 PVU g

13. Data Analysis: Diagnostic plot Depth of the EPV* < 0.25 PVU layer in hPa Depth of the EPV* < 0.25 PVU layer in hPa Examine 50 hPa layers above 850 hPa Examine 50 hPa layers above 850 hPa [Number of layers] x 50 hPa = Depth [Number of layers] x 50 hPa = Depth CI overlay CI overlay If saturation equivalent potential temperature (Θ es ) decreases upward in a 50 hPa layer If saturation equivalent potential temperature (Θ es ) decreases upward in a 50 hPa layer 700 hPa Miller 2D frontogenesis overlay 700 hPa Miller 2D frontogenesis overlay What does this diagnostic plot show for banding cases? What does this diagnostic plot show for banding cases?

14. Data Analysis: 0000 UTC 26 Dec 2002

16. Data Analysis: 1500 UTC 5 Dec 2002

18. Data Analysis: 2100 UTC 14 Dec 2003

20. Preliminary Results Examined first 13 cases (2002–3 & 2003–4 winters) Examined first 13 cases (2002–3 & 2003–4 winters) No apparent correlation found between depth and mode No apparent correlation found between depth and mode Band seems to be associated with EPV* depth gradients … but gradients still exist with other modes Band seems to be associated with EPV* depth gradients … but gradients still exist with other modes Uniform: gradients, frontogenesis poleward of snow, almost no CI Uniform: gradients, frontogenesis poleward of snow, almost no CI CI  broken or fractured … but not the converse CI  broken or fractured … but not the converse Gradients not well defined for broken bands, band segments, and fractured modes Gradients not well defined for broken bands, band segments, and fractured modes Fractured: no frontogenesis nearby Fractured: no frontogenesis nearby Bands with spaces between them have at least some CI Bands with spaces between them have at least some CI

21. Additional Thoughts This diagnostic approach roughly works, but … more ingredients are needed! This diagnostic approach roughly works, but … more ingredients are needed! EPV* alone is not sufficient! Neither is EPV* + frontogenesis! EPV* alone is not sufficient! Neither is EPV* + frontogenesis! Combine STABILITY REGIME and MESOSCALE LIFTING MECHANISM (frontogenesis) with … Combine STABILITY REGIME and MESOSCALE LIFTING MECHANISM (frontogenesis) with … … SYNOPTIC-SCALE LIFTING MECHANISMS … MOISTURE (mean layer RH?) … MICROPHYSICS (dendritic growth) Synoptic-scale forcing Synoptic-scale forcing Warm advection  smoother Warm advection  smoother Differential cyclonic vorticity advection  more jagged Differential cyclonic vorticity advection  more jagged

22. Future Work Separate depths of weak moist symmetric stability (and instability) and CI Separate depths of weak moist symmetric stability (and instability) and CI Depth of weak moist symmetric stability layer that satisfies omega and/or dendritic growth criteria Depth of weak moist symmetric stability layer that satisfies omega and/or dendritic growth criteria Depth of frontogenetical layer Depth of frontogenetical layer Ratio of synoptic-scale forcings Ratio of synoptic-scale forcings Various overlay combinations of synoptic-scale forcing, frontogenesis, EPV* < 0.25 depth, omega, and dendritic growth criteria Various overlay combinations of synoptic-scale forcing, frontogenesis, EPV* < 0.25 depth, omega, and dendritic growth criteria Magnitude of EPV* < 0.25 depth gradient Magnitude of EPV* < 0.25 depth gradient Further investigate any EPV* depth / mode correlations Further investigate any EPV* depth / mode correlations

23. Ultimate Goal Develop diagnostics for determining modes of heavy snow based on… Develop diagnostics for determining modes of heavy snow based on… Synoptic-scale and mesoscale forcings Synoptic-scale and mesoscale forcings Stability regimes Stability regimes Microphysics Microphysics Similar to tables for modes of convection (wind shear and CAPE parameters) Similar to tables for modes of convection (wind shear and CAPE parameters) Possibility of transforming diagnostic into a Smart Tool for AWIPS Possibility of transforming diagnostic into a Smart Tool for AWIPS

24. Special thanks to … David Ahijevych (NCAR) for making gridded WSI NOWrad composite data available David Ahijevych (NCAR) for making gridded WSI NOWrad composite data available Anantha Aiyyer (UAlbany) for help with FORTRAN scripts to work with gridded NARR data Anantha Aiyyer (UAlbany) for help with FORTRAN scripts to work with gridded NARR data Questions? Comments? e-mail: greenstein@atmos.albany.edu