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Patterns of Historic River Flood Events in the Mid-Atlantic Region

Patterns of Historic River Flood Events in the Mid-Atlantic Region. Richard H. Grumm NOAA/NWS Weather Forecast Office, State College, Pennsylvania and Charles Chillag NOAA/NWS Middle Atlantic River Forecast Center, State College, Pennsylvania Contributions by

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Patterns of Historic River Flood Events in the Mid-Atlantic Region

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  1. Patterns of Historic River Flood Events in the Mid-Atlantic Region Richard H. Grumm NOAA/NWS Weather Forecast Office, State College, Pennsylvania and Charles Chillag NOAA/NWS Middle Atlantic River Forecast Center, State College, Pennsylvania Contributions by Alaina MacFarlane and Ron Holmes

  2. Motivation • Ability to compare and rank flood events • For impacts and Federal disasters • Learning from the pastto gain knowledge • Understand flood events • Patterns and conditions for flooding • Education forecasters, users, students • Knowledge and data should be F U N

  3. Methods and Data • Mid-Atlantic River Forecast Center Flood data • From archive (points/stages) and research • Extensive dataset with pre-20th Century examples • Based on points over flood and ranked • Climate data rainfall observations • Where how much when. • Re-analysis data • Reconstruct the cases 20th Century, NCEP/NCAR, CFSR

  4. 20thCentury Re-analysis • Used for cases prior to 1949 • 24 pressure levels including 10 hPa • 6-hourly data • netCDF or plot-4-U

  5. 20th Century Re-analysis site

  6. MARFC Flood Power RankingsIs a arbitrary value weighted according to flood severity • Simple Method to rate flood based on • Number of points  raw number bias • Power Ranking based on severity/Type of Flood: • minor (1) – moderate(5) – major (10)– unknown (1)

  7. Flood Data Display and Access main access site • Extensive database with pre-20th Century cases • Top floods of all time and Month • Sortable by number, categories, and rankings • Event summaries

  8. Top 20Flood EventsRanked by points over flood stage

  9. January record by EventsandthenPower ranking

  10. May Rankings1946 event is shown later

  11. June Events

  12. September Events

  13. Case Example • Flooding Event of 26 May 1946 • 20th Century Re-analysis Example • Wet month with several day wet period • Sunbury, PA wet May

  14. May 1946provides summary of event type and flood data

  15. May 1946RainfallFor Month over Pennsylvania

  16. Sunbury Rainfall May 1946 • A wet period • Wettest May at Sunbury • Several days of rainfall • Antecedent conditions played a role. • Some flooding 21 May in NY 1 point!

  17. The Pattern for the Event • 20th Century re-analysis data • 250 hPa heights and anomalies sharp wave • 500 hPa heights and anomalies cut-off • High PW East-west then more north-south • LLJ • Easterly flow north of frontal boundary • Southerly flow in warm sector (+5s) • Textbook P A T T E R N

  18. End of May Pattern • Large ridge 20-26 May over northwestern Atlantic • The East Coast and Mid-Atlantic had wet period • Some location had wettest May on record • Sunbury showed wet period • Persistent pattern then big rain Flood

  19. Event Types Emerge • Strong south-north PW surges • With strong LLJ • Maddox Synoptic Pattern • Ridge to EAST often critical • Strong Frontal Systems with easterly flow • Tropical Systems • With Maddox-Frontal often record events • Lesser seen cut-off low events

  20. Cut-off Events • Lack the high PW air • Slow moving • Cold core • Instability driven? There are fewer of these and typically not many points and low power rankings.

  21. Patterns with CFSR Cases

  22. Key Issues and follow-ons • Data base exists to rank and sort floods • Not all the floods have been characterized • The data exist to accomplish this back into the 19th Century • Good learning and teaching tool • Good basic student research Project • Could be semi-automated?

  23. Summary • Ability to compare and rank flood events • For impacts and Federal disasters • Learning from the pastto gain knowledge • Power rankings are helpful • Understand flood events • Patterns and conditions for flooding • Education forecasters, users, students • Use our knowledge to improve pattern recognition and perhaps better identify Extreme Weather Events (EWE)

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