Transcript Consortium06032010.ppt

Consortium Meeting
June 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/proje
cts/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