east coast vs. west coast: a documentation of model forecast failures for eta, nam, gfs, gem, and...
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East Coast vs. West Coast: A Documentation of Model Forecast
Failures for Eta, NAM, GFS, GEM, and ECMWF
Garrett WedamLynn McMurdie, Cliff Mass
72-hour NAM Forecast: Ridging 1024 mb contour
72-hr NAM forecast with Obs verification Valid Dec 24, 2006
24
• 72-hour forecast errors– Eta/NAM: 24.1 mb
– CMC-GEM: 14.4 mb
– ECMWF: 10.0 mb
– GFS: 3.2 mb
• 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
Verifying buoy
72-hour Forecast: Low Center
72-hr NAM forecast with Obs verification Valid Dec 24, 2006
992 mb contour
24
-24
-20
-27
-31
27
25
21
-8
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
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
Eta to WRF-NAM operational switchover
> 7 mb
> 5 mb
> 3 mb
West Coast: Number of Large Errors by model and month
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
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
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.
• More “forecast bust” events occur on the West than East Coast for 24, 48, and 72 hour forecasts
• The East Coast is better forecast in terms of MAE in sea level pressure
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…
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!
On the Horizon
Picture from fijaciones.org
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?