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Utilization of a High Resolution Weather and Impact Model to Predict Hurricane Irene

Utilization of a High Resolution Weather and Impact Model to Predict Hurricane Irene. Northeast Regional Operations Workshop 2011 Albany, NY Brandon Hertell. Lloyd Treinish, Anthony Priano , Hongfei Li, James Cipriani IBM – Thomas J. Watson Research Center.

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Utilization of a High Resolution Weather and Impact Model to Predict Hurricane Irene

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  1. Utilization of a High Resolution Weather and Impact Model to Predict Hurricane Irene • Northeast Regional Operations Workshop 2011 • Albany, NY • Brandon Hertell Lloyd Treinish, Anthony Priano, Hongfei Li, James Cipriani IBM – Thomas J. Watson Research Center

  2. OverviewCon Edison, Inc. Service Territory Con Edison Co. of New York • 3.2 million electric customers • 1.0 million gas customers • 1,800 steam customers • 709 MW of regulated generation Orange and Rockland • 300,000 electric customers • 127,000 gas customers 2

  3. OverviewWeather Model • Utilize WRF-ARW • 2km resolution forecast • Assimilate additional weather data • 24hr/84hr forecast • 2x daily (0z,12z) • Temp, wind, wet bulb, precip • Content available via web browser • Email alert system 18 km 2 km 6 km Model Domain

  4. OverviewImpact Model • Westchester County overhead electric • Post-Process of weather model • Output # of jobs per substation • Quantifies uncertainty • Email alert system • Predictive & Nowcast “mode” Westchester Substation Map

  5. OverviewImpact Model Deep Thunder Weather Model Forecast Historical Weather Data Real Time Observations Calibrated Weather Model Gust Calculation Impact Model Historical Damage Data Model Training Model Training NowCast Predictive Predictive vs. Nowcast Model Design

  6. OverviewTropical Storm Irene • Land fall over NYC as a Tropical Storm • Long duration by hurricane standards (18+ hours) • Sustained winds 20-50mph • Wind gusts 40-70mph • Tornado in Queens • Rainfall 5-10” (12” north NYC) • 187,800 customers affected

  7. Results Predicted jobs vs. actual jobs Sunday 28th Saturday 27th Friday 26th 12z 0z 12z 0z Actual Nowcast Predictive Predictive

  8. Results

  9. ResultsFriday – 0z Sustained Wind Max. Daily Gust MPH

  10. ResultsFriday – 0z Number of Jobs Probability

  11. ResultsFriday – 12z Sustained Wind Max. Daily Gust MPH

  12. ResultsFriday – 12z Number of Jobs Probability

  13. Results

  14. ResultsSaturday – 0z Sustained Wind Max. Daily Gust MPH

  15. ResultsSaturday – 0z Number of Jobs Probability

  16. ResultsNowcast Number of Jobs Probability • Nowcast used to check model assumptions • In this case may not be a good check on model accuracy • Dependant on good actual wind data inputs

  17. ResultsObservations AWS wind seem low 00hrs 29th 00hrs 28th

  18. ResultsObservations Gusts more reasonable 00hrs 29th 00hrs 28th

  19. Summary • Impact forecast was close to actual • Forecasts can have large variances • Few large scale events in database • Observational data quality check • Study other cases to check wind accuracy

  20. Questions? Brandon Hertell Meteorologist ConEdison Emergency Management hertellb@coned.com 212-460-3129

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