Consortium MeetingJune 3, 2010

Thanks Mike!

Hit Rates

Dealing With Surface Wind Biases

• A consistent error in WRF, both here in the Northwest and elsewhere, is the tendency for:– a positive wind speed bias– winds that are excessively geostrophic.

• Also noticed that there was insufficient contrast between winds over the water and land (land winds too large).

• A number of examples were discussed at the NW Weather Workshop and the last consortium meeting.

Dealing with surface wind biases

• Last year we experimented with all available planetary boundary layer schemes (including a number of new ones) and also tried varying the number of vertical levels.

• None solved this problem.• Earlier this year we started running at 1.3 km

grid spacing over western WA and the problem seems to get much better.

Dealing with Wind Biases

• This led to a hypothesis that the problem is that the model is not resolving subgrid scale roughness elements at the surface at 12 and even 4-km resolution.

• Early experiments in increasing u*, which is related to surface drag were very suggestive—it decreased the wind and directional biases significantly.

• This was good enough that we added it to the real-time system on April 14th.

Old System Wind Speed Bias: Rerun Jan 1-Feb 8, 2010

New—Lots of Improvements

Optimizing the Approach

• An alternative, and perhaps more straightforward, way of doing the same thing is to increase the surface roughness length (z0), and others have played with this approach (like NCEP, who has never published anything on it).

• Following the hypothesis, it made sense to make the increase in roughness dependent on the variance of the subgrid scale terrain.

• More variance of terrain—more roughness.

New Surface Drag Approach

• During the past few months we have completed an extensive series of experiments (view them at: http://www.atmos.washington.edu/~ovens/windbias/) with various surface drag approaches.

• Narrowing this down substantially, but here is one of the best, with z0 dependent on surface terrain variance over land using 1-km terrain data base.

Old Wind Bias-00z

Latest Exp Wind Bias

Old-12z

Case Study

LSM Change

• The Noah LSM in the WRF 3.1.1 and 3.2 codes has a strong cold bias in max temp over the elevated terrain of the Intermountain West.

• Turning off the Noah LSM and switching to the simpler 5-layer thermal diffusion scheme (as was used in our MM5 runs) improves the surface and 2-m temperatures greatly.

• This change will, however, introduce about a 1°F higher dewpoint temperature bias.

Feb 2-m temp MAE, 00Z

Corresponding Bias

LSM

No LSM

High Resolution Data Assimilation Using EnKF

• As noted in the previous consortium meetings, we have been working to build a high-resolution analysis/data assimilation system based on the Ensemble Kalman Filter approach.

• Last year we were able to get a system working at 36-4 km that produced analyses better than RUC or NAM, with 3-h update cycle.

UW EnKF System

• But we lacked the computer power to reliably do 3-h updates, and really wanted 1-h updates.

• It also used a home-grown UW data assimilation core that had some limitations (can’t assimilate all data types).

New Development• This week we completed a new EnKF system using the

community ensemble data assimilation system (DART).• With the help of PSCAA, we have acquired new

hardware than will easily allow 3-hr cycling and probably 1-h cycling.

• This system will go operational this summer, with online graphics.

• Will also be compared to NWS high-res analyses (Match-Obs-All and RTMA)

New Development

• This summer we will also test a series of other improvements—such as a new bias correction approach.

New Interface to Model Output

• We have had graphical output that was selectable by clicking on a map (sponsored by PSCAA).

• Mike Gilroy wanted something better. The ability to see exactly what grid point the information was coming from, including its height of the clicked point and the associated grid point.

• With PSCAA support we have developed a new interface, based on the google map paradigm:

• http://www.atmos.washington.edu/~carey/projects/NWMC/index.php

Ultra-High Resolution Nest: 1.3 km grid spacing

• We are now running a 1.3 km grid nest once a day out 36h.

• Goal was to support air quality forecasting over western Washington and precipitation prediction, particularly for Howard Hanson Dam.

• Much better definition of land-water boundaries and explicit simulation of convection.

• Better wind statistics than coarser domains and helped guide PBL work.

Upcoming Changes

• With support from PSCAA ($50K in hardware), we will update the SAGE cluster (additional faster Nehalem processors, faster interconnects).

• This will greatly speed up 36-12-4 and enhance the 1.3 km domain:– Both 00 and 12 UTC cycles– Extend 1.3 km to 60 hr