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2002 MM5 Model Evaluation 12 vs. 36 km Results. Chris Emery, Yiqin Jia, Sue Kemball-Cook, and Ralph Morris ENVIRON International Corporation Zion Wang UCR CE-CERT Western Regional Air Partnership (WRAP) Regional Modeling Center (RMC) National RPO Meeting May 25, 2004. - PowerPoint PPT Presentation
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2002 MM5 Model Evaluation12 vs. 36 km Results
Chris Emery, Yiqin Jia, Sue Kemball-Cook, and Ralph Morris
ENVIRON International Corporation
Zion Wang
UCR CE-CERT
Western Regional Air Partnership (WRAP)
Regional Modeling Center (RMC)
National RPO Meeting
May 25, 2004
2002 MM5 Evaluation Review
• IA/WI 2002 MM5 Configuration on National RPO 36 km Grid, except:> Used MM5 v3.6.2> Invoked Reisner II, disregarded INTERPX
• Evaluation Methodology> Synoptic Evaluation> Statistical Evaluation using METSTAT and surface data
• WS, WD, T, RH> Evaluation against upper-air obs
• Compared statistical performance against EDAS, VISTAS
METSTAT Evaluation Package
• Statistics:> Absolute Bias and Error, RMSE, IOA
• Daily and, where appropriate, hourly evaluation• Statistical Performance Benchmarks
> Based on an analysis of > 30 MM5 and RAMS runs > Not meant as a pass/fail test, but to put modeling results
into perspective Wind Speed Wind Direction Temperature Humidity RMSE 2 m/s Mean Bias 0.5m/s 10 0.5K 1g/kg Index of Agreement 0.6 0.8 0.6 Gross Error 30 2K 2g/kg
Datasets for Met Evaluation
• NCAR dataset ds472 airport surface met observations• Twice-Daily Upper-Air Profile Obs (~120 in US)
> Temperature> Moisture
• Scatter plots of performance metrics> Include box for benchmark> Include historical MM5/RAMS simulation results> WS RMSE vs. WD Gross Error> Temperature Bias vs. Temperature Error> Humidity Bias vs. Humidity Error
Subdomains for Model Evaluation
1 = Pacific NW
2 = SW
3 = North
4 = Desert SW
5 = CenrapN
6 = CenrapS
7 = Great Lakes
8 = Ohio Valley
9 = SE
10 = NE
11 = MidAtlantic
Evaluation of 36-km WRAP MM5 Results
• Model performed reasonably well for eastern subdomains, but not the west (WRAP region)> General cool moist bias in Western US> Difficulty with resolving Western US orography?
• May get better performance with higher resolution> Pleim-Xiu scheme optimized more for eastern US?
• More optimization needed for desert and rocky ground?
• MM5 performs better in winter than in summer> Weaker forcing in summer
• July 2002 Desert SW subdomain exhibits low temperature and high humidity bias
Comparison: EDAS vs. WRAP MM5
• Is it possible that 36-km MM5 biases may be caused by the analyses used to nudge (FDDA) the model?
• We evaluated EDAS analysis fields to see whether biases exist> Used Metstat to look at the EDAS surface fields
• Input EDAS fields do not have the cold moist bias seen in the 36 km MM5 simulation, but wind speed underestimation bias is present> Performance issues not due to EDAS analysis fields,
must be internally generated by MM5
Comparison: VISTAS vs. WRAP MM5
• Evaluate VISTAS 2002 MM5 simulation to see whether similar bias exists> Different configuration: KF II, Reisner I
• Both MM5 simulations had trouble in western U.S. – same subdomains lie outside the statistical benchmarks
• Both MM5 simulations performed better in winter than in summer
Comparison: VISTAS vs. WRAP MM5
• VISTAS:> Better simulation of PBL temperature and humidity
profiles> Less surface humidity bias in the western U.S.> Markedly better summer precipitation field
• WRAP:> Less surface temperature bias than VISTAS during
winter• Overall, VISTAS did better in the west
> Further tests indicate use of KF II has larger effect on performance than Reisner I
Addition of 12-km WRAP Grid
• IC/BC’s extracted from 36-km MM5 fields• 3-D FDDA fields extracted from 36-km MM5 fields• Preliminary 5-day run starting 12Z July 1
CMAQ MM5 Dot points 208 x 187 220 x 199 Cross points 207 x 186 219 x 198 SW corner coordinate -2376, -936 -2248, -1008 NE corner coordinate 108, 1296 180, 1368
Comparison: 12 vs. 36-km WRAP MM5
• Performance scatter plots prepared> Directly compare 36-km statistics with 12-km statistics
for each western sub-region> Provides mean stats over July 1-6 preliminary test
period
WRAP 36km/12km July Wind Performance Comparison
0
20
40
60
80
100
120
0 0.5 1 1.5 2 2.5 3 3.5
Wind Speed RMSE (m/s)
Win
d D
ierc
tio
n E
rro
r (m
/s)
Benchmark 12 km Subdomains MM5/RAMS Runs 36 km Subdomains
DesertSW
North
SWPacNW
WRAP 36km/12km July Temperature Performance Comparison
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
-2 -1.5 -1 -0.5 0 0.5 1 1.5 2
Temperature Bias (K)
Tem
ep
ratu
re E
rro
r (K
)
Benchmark 12 km Subdomain MM5/RAMS Runs 36 km Subdomains
DesertSW
SW
North
PacNW
Desert SW
SWNorth
PacNW
WRAP 36km/12km July Humidity Performance Comparison
0
1
2
3
4
5
-3 -2 -1 0 1 2 3
Humidity Bias (g/kg)
Hu
mid
ity
Err
or
(g/k
g)
Benchmark 12km Subdomains MM5/RAMS Runs 36 km Subdomains
DesertSW
NorthSWPacNW
Comparison: 12 vs. 36-km WRAP MM5
• Results:> No significant or consistent impact on wind
speed/direction performance> Temperature bias dramatically improved for all areas,
but gross error is made worse > Impacts on humidity performance are minor, and worse
in the Desert SW• There appear to be larger issues that 12-km grid
resolution does not improve upon> Remember that all IC/BC and 3-D FDDA are derived
from 36-km results> This issue addressed in 12-km sensitivity tests
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