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Cliff Mass and Dave Ovens University of Washington

Fixing WRF’s High Speed Wind Bias: A New Subgrid Scale Drag Parameterization and the Role of Detailed Verification. Cliff Mass and Dave Ovens University of Washington. Problems with WRF winds. WRF generally has a substantial overprediction bias for all but the lightest winds.

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Cliff Mass and Dave Ovens University of Washington

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  1. Fixing WRF’s High Speed Wind Bias: A New Subgrid Scale Drag Parameterization and the Role of Detailed Verification Cliff Mass and Dave Ovens University of Washington

  2. Problems with WRF winds • WRF generally has a substantial overprediction bias for all but the lightest winds. • Not enough light winds. • Winds are generally too geostrophic over land. • Not enough contrast between winds over land and water. • This problem is evident virtually everywhere and appears to occur in all PBL schemes available with WRF.

  3. 10-m wind bias, 00 UTC, 24-h forecast, Jan 1-Feb 8, 2010

  4. 10-m wind bias, 12 UTC, 12-h forecast, Jan 1-Feb 8, 2010

  5. The Problem

  6. Insufficient Contrast Between Land and Water

  7. So What is the Problem? • As noted earlier, tried all available WRF PBL schemes…no magic bullet there. We are using the YSU scheme in most work. • Doesn’t improve going from 36 to 12 km resolution, 1.3 km somewhat better. • Inherent problem with all PBL schemes? • What about the roughness of subgrid terrain that we are not resolving?

  8. The 12-km grid versus terrain

  9. A new drag surface drag parameterization • Determine the subgrid terrain variance and make surface drag or roughness used in model dependent on it. • Consulting with Jimy Dudhia of NCAR came up with an approach—enhancing u* and only in the boundary layer scheme (YSU). • For our 12-km and 36-km runs used the variance of 1-km grid spacing terrain.

  10. 38 Different Experiments: Multi-month evaluation winter and summer

  11. Some Results for Experiment “71” • Ran the modeling system over a five-week test period (Jan 1- Feb 8, 2010)

  12. 10-m wind speed bias: Winter

  13. MAE 10m wind speed

  14. Case Study

  15. Old New

  16. An Issue • Our method appears to hurt slightly during strong wind speeds and near maximum temperatures in summer.

  17. Summer-0000 TC-Original

  18. With Sub-grid drag

  19. Summer

  20. Improvement? • Next step—could have the parameterizaton fade out for higher winds speeds and lower stability, possibility by depending on Richardson number. • Actually, this makes some sense…sometimes the atmosphere is well-mixed, and at these times variations in sub-grid roughness would be less important.

  21. The End

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