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

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

Deterministic GFS Deterministic ECMWF HR Verifying 84 HR FCST

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

Deterministic GFS Deterministic ECMWF HR Verifying 96 HR FCST

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

Deterministic GFS Deterministic ECMWF HR Verifying 108 HR FCST

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

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

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

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

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

This is what happened – Is this a “Megastorm?

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

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. Conclusions - Introducing the Lagged Average Forecast and “Flip Flop” Tool Thank you for your time – Any questions?