Fixing WRF’s High Speed Wind Bias:  A New Subgrid Scale Drag Parameterization and the Role of Deta...
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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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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

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.


10 m wind bias 00 utc 24 h forecast jan 1 feb 8 2010

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


10 m wind bias 12 utc 12 h forecast jan 1 feb 8 2010

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


The problem

The Problem


Insufficient contrast between land and water

Insufficient Contrast Between Land and Water


So what is the problem

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?


The 12 km grid versus terrain

The 12-km grid versus terrain


A new drag surface drag parameterization

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.


38 different experiments multi month evaluation winter and summer

38 Different Experiments: Multi-month evaluation winter and summer


Some results for experiment 71

Some Results for Experiment “71”

  • Ran the modeling system over a five-week test period (Jan 1- Feb 8, 2010)


10 m wind speed bias winter

10-m wind speed bias: Winter


Mae 10m wind speed

MAE 10m wind speed


Case study

Case Study


Cliff mass and dave ovens university of washington

Old

New


An issue

An Issue

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


Summer 0000 tc original

Summer-0000 TC-Original


With sub grid drag

With Sub-grid drag


Summer

Summer


Improvement

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.


The end

The End


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