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Stephen Jessup M.S. Student Dept. of Atmospheric Science Cornell Univ.

Stephen Jessup M.S. Student Dept. of Atmospheric Science Cornell Univ. An Examination of the Climatology and Environmental Characteristics of Flash Flooding in the Binghamton, New York County Warning Area. Project Objectives.

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Stephen Jessup M.S. Student Dept. of Atmospheric Science Cornell Univ.

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  1. Stephen Jessup M.S. Student Dept. of Atmospheric Science Cornell Univ. An Examination of the Climatology and Environmental Characteristics of Flash Flooding in the Binghamton, New York County Warning Area

  2. Project Objectives • Develop a long-term climatology of flash flood events for the BGM CWA. • Identify any spatial differences in flash flood frequency and flood producing meteorological conditions across the CWA. • Analyze a set of meteorological variables to quantitatively identify combinations of variables that are associated with flash flooding. • Compare the conditions associated with flash floods to the conditions associated with non-events

  3. Flash Flood Climatology • Spatially: FF's most common in NY/PA border counties and in eastern NY counties • Diurnally: • Peak in late afternoon/early evening • Secondary max. in morning • Seasonally: • Peak in summer (June max.) • Min. in late fall/winter

  4. 16 7 5 8 6 6 16 8 7 9 18 6 16 13 25 24 13 7 5 28 8 4 2 11

  5. Flash floods per county area 13.2 9.0 18.5 7.6 17.8 11.5 16.0 16.0 21.3 10.1 12.6 35.4 12.9 25.0 58.8 11.1 6.1 24.3 13.4 9.6 5.0 17.4 7.3 12.3

  6. Mostly Spring/Summer Mostly Fall/Winter/Spring

  7. Antecedent Precipitation • Determined for one week (7 days) and one month (30 days) prior to flash floods • Climatology for comparison • Consists of all non-flood years (from 1986-2003) for each flash flood date • To test hypothesis that floods tend to occur during periods of above-normal precipitation • Flash floods tend to occur in anomalously wet periods

  8. Climatology vs. Flash Flood Antecedent Precip. (7-day)

  9. Climatology vs. Flash Flood Antecedent Precip. (30-day)

  10. Improving FF Forecasting Procedures for NWS BGM: Methodology • Construct independent databases of flash flood and null event cases • Determine meteorologically significant parameters and their values during events • Find combinations of variables that improve predictability • Plot composites to determine whether the synoptic situations of FF's and null events differ • Merge these into a forecasting methodology

  11. Datasets • Warm-season flash flood cases (~May-Oct), n=51 • Separated by at least one week (7 days) • Drawn from 1986-2003 • Warm-season heavy precipitation events, n=36 • At least 1” in one hour, at least 1.5” in six hours • Separated from each other & FF's by at least one week • Drawn from 1986-2003 • Random days representing same seasonality as FF's, n=51 • Random year (1986-2003) assigned to the date of each FF case • Separated from each other & FF's by at least one week • Watches/warnings that did not verify, n=17 • Separated from each other by at least one week • Drawn from 1995-2003

  12. Dataset Methodology • NCEP Regional Reanalysis used as primary data source: 32 km, 3-hour resolution • Three time periods used: time closest to the flood, two time steps of three hours prior • Most variables averaged over quadrilateral area containing FF counties • Area for prior time periods determined by backtracking four corners of this area using 850 mb wind • 850 wind, storm motion vectors backtracked an extra timestep to reflect inflow • Backtracking not used for several variables classified as synoptic; parameter representing large-scale field used instead

  13. Highlights: Current BGM FF Checklist • Winds/storm motion • Slow storm movement (MBE/Corfidi vector) • Low level jet >= 20 kts • 700 – 500 mb winds < 30 kts • Weak mid-level (700-500 mb) shear • Upper level divergence • Atmospheric Moisture • Mean 1000-500 relative humidity >= 70% • Precipitable water >=150% normal or >= 1.4 inches

  14. BGM FF Checklist, continued • Synoptic-scale features • Nearby surface boundary • Low-level theta-e axis • Upper level ridge axis • 1000-500 mb thickness diffluence • Other parameters • “Tall and skinny” CAPE • Warm cloud depth exceeding 3-4 km

  15. Summary: Results • Thresholds in checklist generally agree with FF results, but are often exceeded in non-events • Exception: Low-level jet apparently not as important for flash flooding, but more common for heavy rainfall non-events • Measures of antecedent soil moisture a good first-guess criterion between both flood/heavy and flood/watch • Properties of the 850-mb theta-e field differ in both flood/heavy and flood/watch comparisons • Measures of 850-mb and 700-mb moisture (dewpoints and RH) differ for flood/heavy and flood/watch • Notable differences in large-scale mid and low level wind patterns • Notable differences in 850-500 relative humidity patterns

  16. Heavy Flood Watch Sea Level Pressure

  17. 850-mb wind speed Expect strong LLJ

  18. 850-mb wind direction Mostly SW to W Some SE

  19. F = flood H = heavy W = watch R = random 850-mb wind speed vs. 850-mb wind direction NW often non-events Fast winds either SE mostly floods

  20. Weak LLJ, convergence Stronger LLJ Strong LLJ, convergence 850 mb wind vector

  21. Storm Motion Speed Not necessarily slow storm motion

  22. Storm motion direction Primarily SSW to W

  23. Mid-level (500 mb – 700 mb) Shear Speed Weak shear

  24. Mid-level (500mb-700mb) shear direction Weak directional shear

  25. Mid level shear: direction vs. speed Larger shear can flood!

  26. Weak, convergence Strong Strong, convergence 700 mb wind vector

  27. Weaker Stronger Stronger 500 mb wind vector

  28. 250 mb wind vector

  29. Precipitable water (% normal)

  30. Weekly Ant. ppt. vs. Precipitable Water (% normal)

  31. Localized moisture Frontal signature? Perhaps some of both? Precipitable Water (anomaly)

  32. 850 mb Theta-e vs. weekly antecedent precipitation Floods lower theta-e and wetter antecedent

  33. CAPE Long, skinny CAPE?

  34. 850 Wind Direction vs. 850 Dewpoint Floods: lower 850 Td

  35. Floods have higher RH than heavy 850 mb RH

  36. 700 mb RH

  37. 500 mb RH

  38. Summary • LLJ not as significant in FF's as in null events • Composites suggest theta-e ridging is less significant in FF's than in null events • Atmospheric moisture greater and more localized in FF's than in null events • Possible connection between antecedent soil moisture and local maximum in moisture content during FF's? • Caveat: small sample size, small spatial domain!

  39. Acknowledgements • COMET Outreach Project S05-52254 • Art DeGaetano, Cornell University • Mike Evans, NWS Binghamton

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