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Garrett Wedam Lynn McMurdie, Cliff Mass

East Coast vs. West Coast: A Documentation of Model Forecast Failures for Eta, NAM, GFS, GEM, and ECMWF. Garrett Wedam Lynn McMurdie, Cliff Mass. 72-hour NAM Forecast: Ridging. 1024 mb contour. 24. 72-hr NAM forecast with Obs verification Valid Dec 24, 2006.

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Garrett Wedam Lynn McMurdie, Cliff Mass

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  1. East Coast vs. West Coast: A Documentation of Model Forecast Failures for Eta, NAM, GFS, GEM, and ECMWF Garrett Wedam Lynn McMurdie, Cliff Mass

  2. 72-hour NAM Forecast: Ridging 1024 mb contour 24 72-hr NAM forecast with Obs verification Valid Dec 24, 2006

  3. 72-hour Reality: Low Center 1000 mb contour 00-hr NAM analysis and obs verification Dec 24, 2006

  4. 72-hour forecast errors • Eta/NAM: 24.1 mb • CMC-GEM: 14.4 mb • ECMWF: 10.0 mb • GFS: 3.2 mb Verifying buoy • 48-hour forecast errors • Eta/NAM: 13.7 mb • CMC-GEM: 9.1 mb • ECMWF: 7.6 mb • GFS: 1.5 mb • 24-hour forecast errors • Eta/NAM: 4.7 mb • CMC-GEM: 2.4 mb • ECMWF: 2.7 mb • GFS: -0.2 mb GFS 72-hour forecast verifying 12-26

  5. 72-hour Forecast: Low Center 992 mb contour -31 -20 -24 -27 24 27 21 25 -8 72-hr NAM forecast with Obs verification Valid Dec 24, 2006

  6. 72-hour Reality: Ridging 1020 mb contour 00-hr NAM Analysis and Obs verification Dec 24, 2006

  7. Method • Directly compare observations to interpolated model forecasts • Emphasize East and West Coasts • Buoys eliminate terrain effects • Emphasize Sea Level Pressure comparisons • SLP is good indicator of model performance (i.e., storm strength and location can be defined and compared using SLP) • Insufficient off-coast upper-level observations

  8. Method • Useful Tools for Comparing Forecast Skill • Mean Absolute Error (MAE) • Mean Error, or Bias (ME) • Frequency of Errors which exceed an arbitrary “Large Error” criterion (different for 24, 48, 72-hr forecasts) • Timelines of said “Large Errors” to cross-reference failure dates between models • Error Histograms to compare distributions and sizes of largest errors

  9. Matching Variance in Sea Level Pressure:

  10. West Coast: Number of Large Errors by model and month > 3 mb > 5 mb > 7 mb Eta to WRF-NAM operational switchover

  11. East Coast: Number of Large Errors by model and month CMC - GEM major model update. Included: increase in vertical and horizontal resolution, new physics scheme, decreased time step, data assimilation changes

  12. Number of Large Errors: West Coast *minus* East Coast

  13. Mean Absolute Error: West Coast *minus* East Coast For reference, typical MAE values: GFS West Coast average for winter 2006/07: 24-hr: 1mb; 48-hr: 1.4 mb; 72-hr: 2.0 mb

  14. Comparing models: East Coast Mean Absolute Error *Standardized* to ECMWF CMC – GEM update

  15. Comparing models: West Coast Mean Absolute Error *Standardized* to ECMWF

  16. Results • Comparing models: ECMWF generally outperforms and NAM underperforms others. There are indications that a CMC-GEM model update significantly improved some forecasts, and that GFS has not performed as well this season as the past season. • The East Coast is better forecast in terms of MAE in sea level pressure • More “forecast bust” events occur on the West than East Coast for 24, 48, and 72 hour forecasts

  17. On the Horizon Dates of Large Forecast Errors (by model) Errors greater than 5 mb

  18. On the Horizon • Forecast Failures can be a result of initialization errors, insufficient “realism” of the model, and other model inadequacies. Knowing the most common causes of failure for high-impact forecast failures can help determine policy: do we invest more in improving models or in a new observation buoy? • One cause of failure is High Model Sensitivity…

  19. On the Horizon Courtesy of Ryan Torn

  20. On the Horizon

  21. On the Horizon

  22. On the Horizon

  23. On the Horizon

  24. On the Horizon • Thirty-four of 420 forecasts showed the highest sensitivity • Nineteen of the 34 “sensitive” cases (55%) resulted in multiple models meeting “large error criterion” • Compare to: 10-20% of all forecasts result in multiple models meeting “large error criterion” •  motivates a more formal investigation!

  25. On the Horizon Are Two Winters Representative? Currently adding data from 2004/05 and remainder of 2006/07 to further examine year-to-year variability in forecast skill What About The Rest of the Country? And Beyond? Will examine open-ocean buoys, and land sites; over land will use 850 mb observations instead of SLP What Are the Features of “Busts”: Forecast failures with high impacts on people still occur. What are their features? And why do some models fail when others don’t? Picture from fijaciones.org

  26. Thank You! East Coast vs. West Coast: A Documentation of Model Forecast Failures for Eta, NAM, GFS, GEM, and ECMWF Garrett Wedam Lynn McMurdie, Cliff Mass

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