Fly - Fight - Win 25 th Operational Weather Squadron University of Arizona 1.8km WRF Verification...

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Fly - Fight - Win 25 th Operational Weather Squadron University of Arizona 1.8km WRF Verification 2Lt Erik Neemann Weather Operations Officer 30 Apr 08
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Transcript of Fly - Fight - Win 25 th Operational Weather Squadron University of Arizona 1.8km WRF Verification...

Page 1: Fly - Fight - Win 25 th Operational Weather Squadron University of Arizona 1.8km WRF Verification 2Lt Erik Neemann Weather Operations Officer 30 Apr 08.

Fly - Fight - Win

25th Operational Weather Squadron

University of Arizona1.8km WRF Verification

2Lt Erik NeemannWeather Operations Officer

30 Apr 08

Page 2: Fly - Fight - Win 25 th Operational Weather Squadron University of Arizona 1.8km WRF Verification 2Lt Erik Neemann Weather Operations Officer 30 Apr 08.

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Purpose

To analyze data from University of Arizona 1.8km WRF model for use in 25 OWS Forecast Process Provide feedback for use in model improvements Study included forecasts for winds, temperatures, and

stability (surface-based CAPE) Additional purpose of deriving tool to approximate wind

gust speed from model sustained winds

Page 3: Fly - Fight - Win 25 th Operational Weather Squadron University of Arizona 1.8km WRF Verification 2Lt Erik Neemann Weather Operations Officer 30 Apr 08.

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Methodology

Compared actual observations to 1.8km WRF forecasts GFS and NAM output from 12z model runs

Three 25 OWS AZ forecast locations used: Davis-Monthan AFB (KDMA) Ft. Huachuca (KFHU) Luke AFB (KLUF)

Page 4: Fly - Fight - Win 25 th Operational Weather Squadron University of Arizona 1.8km WRF Verification 2Lt Erik Neemann Weather Operations Officer 30 Apr 08.

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Winds

Model wind forecasts compared to 18z and 00z observations only

Data was thrown out if observed gusts or sustained winds were at less than 15 knots

If gusts were reported, gusts were used; if no gusts were reported, sustained winds were used)

Results are from 13 Dec 07 to 30 Apr 08 KDMA: 38 obs KFHU: 58 obs KLUF: 26 obs

Page 5: Fly - Fight - Win 25 th Operational Weather Squadron University of Arizona 1.8km WRF Verification 2Lt Erik Neemann Weather Operations Officer 30 Apr 08.

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Winds

Speed error determined by average difference in observed and forecast speed

Ratio of observed speed to forecast speed used to determine “gust coefficient”

Direction error determined by absolute value of difference between observed and forecast wind direction

Page 6: Fly - Fight - Win 25 th Operational Weather Squadron University of Arizona 1.8km WRF Verification 2Lt Erik Neemann Weather Operations Officer 30 Apr 08.

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Wind Speed (knots)

GFS Gust Coef NAM Gust Coef

KDMA 2.154 1.878 2.016KFHU 2.116 2.250 2.183KLUF 3.978 4.138 4.058

2.749 2.755

Avg GFS Error Avg NAM Error

KDMA -8.632 -7.997 -8.315KFHU -10.852 -10.638 -10.745KLUF -12.038 -12.462 -12.250

-10.507 -10.366

Page 7: Fly - Fight - Win 25 th Operational Weather Squadron University of Arizona 1.8km WRF Verification 2Lt Erik Neemann Weather Operations Officer 30 Apr 08.

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Wind Speed Trends

Davis-Monthan had the best at model forecasts of wind speed, while Luke had the worst

Average for all locations was an underestimation of about 10.5 knots

Both DM and Ft. Huachuca observed/forecast ratios around 2:1 while Luke was closer to 4:1

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Wind Direction (degrees)

GFS Error NAM ErrorKDMA 30.263 24.386 27.325KFHU 21.132 22.632 21.882KLUF 36.154 34.231 35.193

29.183 27.083

Page 9: Fly - Fight - Win 25 th Operational Weather Squadron University of Arizona 1.8km WRF Verification 2Lt Erik Neemann Weather Operations Officer 30 Apr 08.

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Wind Direction Trends

Forecasts most accurate for Ft. Huachuca, and worst at Luke AFB

Overall, the models did fairly well for all three locations with error generally less than 35 degrees

Page 10: Fly - Fight - Win 25 th Operational Weather Squadron University of Arizona 1.8km WRF Verification 2Lt Erik Neemann Weather Operations Officer 30 Apr 08.

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Temperature

Compared model forecasts for Max/Min temperature to observed daily Max and Min

Number of cases limited to when both GFS and NAM model runs were available from 13 Dec 07 to 30 Apr 08 (78 days)

Absolute value or error used to examine accuracy

Average error used to determine potential model bias

Page 11: Fly - Fight - Win 25 th Operational Weather Squadron University of Arizona 1.8km WRF Verification 2Lt Erik Neemann Weather Operations Officer 30 Apr 08.

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Min Temperature (Celsius)

GFS Bias NAM BiasKDMA -0.423 -1.346 -0.885KFHU -0.649 -1.558 -1.104KLUF 1.909 1.325 1.617

0.279 -0.526

GFS Abs Err NAM Abs ErrKDMA 1.628 2.115 1.872KFHU 1.792 2.519 2.156KLUF 2.636 2.390 2.513

2.019 2.341

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Min Temperature Trends

Min temperatures did the best and DM, and the worst a Luke

GFS more accurate at DM and FHU; both models about the same at Luke

Cold biases at DM and FHU; strong warm bias at Luke

Absolute error for all locations was about 1.5° C

Page 13: Fly - Fight - Win 25 th Operational Weather Squadron University of Arizona 1.8km WRF Verification 2Lt Erik Neemann Weather Operations Officer 30 Apr 08.

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Max Temperature (Celsius)

GFS Bias NAM BiasKDMA 0.423 0.282 0.353KFHU -1.519 -1.896 -1.708KLUF 0.922 0.286 0.604

-0.058 -0.443

GFS Abs Err NAM Abs ErrKDMA 1.346 1.410 1.378KFHU 1.987 2.182 2.085KLUF 1.208 1.143 1.176

1.514 1.578

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Max Temperature Trends

Max temperature did the best at Luke and DM, while performing poorly at Ft. Huachuca

Both models had similar accuracy

Warm biases DM and Luke, strong cold bias at FHU

Absolute error for all locations was 1.5° C

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Stability

Stability results inconclusive due to scarcity of positive CAPE at any location during time period

More robust dataset expected during summer months

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Conclusion

NAM model forecast wind direction well for all locations

Wind speed gusts may be applicable for DM and Ft Huachuca with a corrective adjustment, but performed poorly at Luke

Max temps most reliable at DM and Luke using NAM model