slide1
Download
Skip this Video
Download Presentation
Cliff Mass and Dave Ovens University of Washington

Loading in 2 Seconds...

play fullscreen
1 / 28

Cliff Mass and Dave Ovens University of Washington - PowerPoint PPT Presentation


  • 79 Views
  • Uploaded on

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.

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about ' Cliff Mass and Dave Ovens University of Washington' - medea


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
slide1

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.
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?
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.
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)
slide20

Old

New

an issue
An Issue
  • Our method appears to hurt slightly during strong wind speeds and near maximum temperatures in 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.
ad