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Understanding the Predictability of the March 2009 "Megastorm": Lessons Learned

This paper discusses the predictability of the March 2009 "Megastorm," which was effectively forecasted by major meteorological centers at days 4-7. It evaluates the performance of deterministic models like GFS and ECMWF, including ensemble techniques and the "Poor Man's Ensemble." The study introduces the Lagged Average Forecast and the "Flip Flop" tool, which offers forecasters a quantitative means to assess model trends and uncertainties. This analysis emphasizes the potential of utilizing advanced tools for improving forecast confidence in significant storm events.

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Understanding the Predictability of the March 2009 "Megastorm": Lessons Learned

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  1. Lessons in Predictability: Part 2 The March 2009 “Megastorm” Michael J. Bodner, NCEP/HPC Camp Springs, MD Richard H. Grumm, NWS WFO State College, PA Neil A. Stuart, NWS WFO Albany, NY NROW 2009

  2. The storm was well predicted predicited at days 4-7 by the major meteorological centers deterministic models and ensemble packages

  3. Deterministic GFS Deterministic ECMWF HR Verifying 84 HR FCST

  4. GEFS mean 8 member Poor Man’s Ensemble (GFS and EC) Verifying 84 HR FCST

  5. Deterministic GFS Deterministic ECMWF HR Verifying 96 HR FCST

  6. GEFS mean 8 member Poor Man’s Ensemble (GFS and EC) Verifying 96 HR FCST

  7. Deterministic GFS Deterministic ECMWF HR Verifying 108 HR FCST

  8. GEFS mean 8 member Poor Man’s Ensemble (GFS and EC) Verifying 108 HR FCST

  9. Calculation for 500 hPa Flip Flop tool – results in units of decameters ________________________________ √(cycle-12hr-cycle-24hr)x(cyclecurrent-cycle-12hr)

  10. 500 hPa D-Prog/Dt Flip Flop Tool GFS and ECMWF 84 HR FCST

  11. 500 hPa D-Prog/Dt Flip Flop Tool GFS and ECMWF 96 HR FCST

  12. 500 hPa D-Prog/Dt Flip Flop Tool GFS and ECMWF 108 HR FCST

  13. This is what happened – Is this a “Megastorm?

  14. This was the first event of 2008-09 to effect all of the major eastern cities. The storm received a NESIS classification of “1”

  15. Conclusions - Introducing the Lagged Average Forecast and “Flip Flop” Tool • Lagged average forecast or “poor man’s ensemble” - average the 4 most recent deterministic runs of both the GFS and ECMWF. • Advantage of the LAF • Uses a multi model approach to ensemble forecasting • Does not lose resolution because multiple deterministic forecasts are being used instead of ensemble means and members • Less smoothing of key features • The “flip flop” tool algorithmically combines the 3 most recent deterministic model runs • Displays the magnitude of reverting trends (flip flops) when contrasting previous model runs. • Positive values indicate that the model “flip flopped.” • Both tools provide the forecaster a quantitative way to evaluate model trend and uncertainty for specific features • Both geographical and temporal evaluation of uncertainty, thereby increasing or decreasing forecast confidence. • Future work includes formal verification and looking at other model output parameters. Thank you for your time – Any questions?

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