Comparison of CENRAP 36 km and 

12 km MM5 Model Runs for 2002

Jeremiah Johnson, Yiqin Jia, Chris Emery and Ralph Morris

ENVIRON International Corporation

Zion Wang and Gail Tonnesen

University of California at Riverside

Central Regional Air Planning Association (CENRAP)

Modeling Workgroup

May 23, 2006
Introduction

• CENRAP is performing regional Particulate Matter (PM) 

modeling to address the requirements of the Regional Haze 

Rule (RHR)

• Both the CMAQ and CAMx models are being applied for 

the 2002 annual period on a 36 km continental U.S. domain

• 12 km sensitivity modeling was conducted for three episodes 

on a Central States domain:

> Spring: March 7th to April 23th

> Summer: August 27th to September 13th

> Winter: November 26th to December 15th

• Model Performance was compared using 36 km and 12 km 

grids

• CAMx 12 km flexi-nesting was used to determine whether 

effects of 12 km domains are due to 12 km meteorology or 

emissions
12 km Sensitivity Results

• Presented at Feb 6-8, 2006 CENRAP meeting in 

Baton Rouge:

> http://pah.cert.ucr.edu/aqm/cenrap/ppt_files/Morris_36vs12km_Feb6-8_2006.ppt

• CMAQ model performance fairly insensitive to 

36 km and 12 km grid

• CAMx exhibited more sensitivity when 12 km 

was used

> Summer SO4 over-prediction bias greatly reduced using 

12 km grid

> CAMx flexi-nesting (12 km meteorology w/ 36 km 

emissions) found improved SO4 performance due to 12 

km meteorology and not 12 km emissions
Recommendations: 12 km Modeling

• Key Findings:

> Except for CAMx SO4 little difference in model 

performance using 36 and 12 km grid

> Substantial more resources needed for 12 km grid

> Effects of grid on emission controls not nested

• Feb 6-8, 2006 Baton Rouge CENRAP Meeting 

Recommended the Following:

> Perform most runs using just 36 km grid

> Process 12 km MM5 for modeling in case needed

• Need to evaluate 12 km MM5 data

> If 12 km runs are needed, results suggest can just run 

with 12 km meteorological inputs
Model Setup for CENRAP Runs

• National RPO 36 km Grid, 164 x 128 x 34

• 12 km Grid, 264 x 240 x 34

• Lambert Conformal Projection

• Pleim-Xiu/ACM LSM/PBL

• RRTM Longwave and Dudhia Shortwave
Model Setup for CENRAP Runs (continued)

• No shallow convection

• Kain-Fritsch 2 cumulus convection

• Reisner 1 moist physics

• Nudging analysis: u/v surface

u/v/t/q aloft
Surface Evaluation Method

• Use Metstat statistical package to compare model surface 

output to surface station data

• Metstat calculates statistics which describe how well the model 

output fields agree with observations

• Metstat analysis divides U.S. into subdomains to show 

how MM5 performs region by region

• Metstat statistics summarized in scatter plots which contain a

model performance benchmark box as well as results of other

MM5/RAMS runs used for air quality modeling
METSTAT Evaluation Package

• Average observed and predicted

• Absolute Bias and Error

• RMSE

• Index of Agreement (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 

in the proper 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
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
Datasets for Met Evaluation

• NCAR dataset ds472 airport surface met observations

surface temperature surface pressure sea level pressure visibility

cloud cover height of cloud base maximum

temperature

minimum 

temperature

dewpoint precipitation sunshine snowfall

snow cover wind direction wind force (speed) u wind component

v wind component wind gust descriptive weather
MM5 36 km vs. 12 km Model Performance

• Previously evaluated CENRAP 36 km MM5 simulation 

across US domains and compared results with VISTAS 

and WRAP 36 km MM5 runs:

> http://pah.cert.ucr.edu/aqm/cenrap/ppt_files/CENRAP_VIST

AS_WRAP_2002_36km_MM5_eval.ppt

• Now evaluate CENRAP 12 km MM5 and compare with 

36 km MM5 results:

> CenrapN and CenrapS domains

> Wind Speed and Direction, Temperature and Moisture

> Compare against performance “Benchmarks”

> Follows are examples for Jan, Mar, Jul and Oct 2002
CENRAP 36km vs. 12km January Temperature Performance

Comparison

0

0.5

1

1.5

2

2.5

3

3.5

-2 -1.5 -1 -0.5 0 0.5 1

Temperature Bias (K)

T

e

m

p

e

r

atu

r

e

E

r

r

o

r (K)

Benchmark 36km 12km

CENRAP N

CENRAP S

• Highest temperature error for 

CenrapN subdomain in January
CENRAP 36km vs. 12km January Humidity Performance Comparison

0

0.5

1

1.5

2

2.5

3

-1.5 -1 -0.5 0 0.5 1 1.5 2 2.5

Humidity Bias (g/kg)

H

u

midity

E

r

r

o

r (g/k

g)

Benchmark 36km 12km

CENRAP N

CENRAP S

• Comparable humidity 

performance for both runs
CENRAP 36km vs. 12km January Wind Performance Comparison

0

10

20

30

40

50

60

70

80

0 0.5 1 1.5 2 2.5 3

Wind Speed RMSE (m/s)

Win

d

Dire

ctio

n

E

r

r

o

r (m/s)

Benchmark 36km 12km

CENRAP N

CENRAP S

• Comparable wind 

performance for both runs
CENRAP 36km vs. 12km March Temperature Performance Comparison

0

0.5

1

1.5

2

2.5

3

3.5

-2 -1.5 -1 -0.5 0 0.5 1

Temperature Bias (K)

T

e

m

p

erature

Error (K)

Benchmark 36km 12km

CENRAP N

CENRAP S

• CenrapN subdomain outside goal, 

but better than January
CENRAP 36km vs. 12km March Humidity Performance Comparison

0

0.5

1

1.5

2

2.5

3

-1.5 -1 -0.5 0 0.5 1 1.5 2 2.5

Humidity Bias (g/kg)

H

u

midity

E

r

ro

r (g/k

g)

Benchmark 36km 12km

CENRAP N

CENRAP S

• Comparable humidity 

performance for both runs
CENRAP 36km vs. 12km March Wind Performance Comparison

0

10

20

30

40

50

60

70

80

0 0.5 1 1.5 2 2.5 3

Wind Speed RMSE (m/s)

Win

d

Dir

e

ctio

n

E

r

r

o

r (m/s)

Benchmark 36km 12km

CENRAP N

CENRAP S

• CenrapS subdomain falls 

just within goal
CENRAP 36km vs. 12km July Temperature Performance Comparison

0

0.5

1

1.5

2

2.5

3

3.5

-2 -1.5 -1 -0.5 0 0.5 1

Temperature Bias (K)

T

e

m

p

erature

Error (K)

Benchmark 36km 12km

CENRAP N

CENRAP S

• Greatest temperature 

performance 

improvement using 12km 

grid

• CenrapS outside goal 

for 36km run
CENRAP 36km vs. 12km July Humidity Performance Comparison

0

0.5

1

1.5

2

2.5

3

-1.5 -1 -0.5 0 0.5 1 1.5 2 2.5

Humidity Bias (g/kg)

H

u

midity

E

r

ro

r (g/k

g)

Benchmark 36km 12km

CENRAP N

CENRAP S

• Highest humidity error in 

July, still within goal
CENRAP 36km vs. 12km July Wind Performance Comparison

0

10

20

30

40

50

60

70

80

0 0.5 1 1.5 2 2.5 3

Wind Speed RMSE (m/s)

Win

d

Dire

ctio

n

Error (m/s)

Benchmark 36km 12km

CENRAP N

CENRAP S

• Comparable wind 

performance for both runs
CENRAP 36km vs. 12km October Temperature Performance

Comparison

0

0.5

1

1.5

2

2.5

3

3.5

-2 -1.5 -1 -0.5 0 0.5 1

Temperature Bias (K)

T

e

m

p

e

ratu

re

E

r

r

o

r (K)

Benchmark 36km 12km

CENRAP N

CENRAP S

• Temperature performance 

comparable for 36 and 12km runs
CENRAP 36km vs. 12km October Humidity Performance Comparison

0

0.5

1

1.5

2

2.5

3

-1.5 -1 -0.5 0 0.5 1 1.5 2 2.5

Humidity Bias (g/kg)

H

u

midity

E

r

r

o

r (g/k

g)

Benchmark 36km 12km

CENRAP N

CENRAP S

• Comparable humidity 

performance for both runs
CENRAP 36km vs. 12km October Wind Performance Comparison

0

10

20

30

40

50

60

70

80

0 0.5 1 1.5 2 2.5 3

Wind Speed RMSE (m/s)

Win

d

Dire

ctio

n

E

r

ro

r (m/s)

Benchmark 36km 12km

CENRAP N

CENRAP S

• Comparable wind 

performance for both runs
Overview of CENRAP 36/12 km Surface 

Performance

• Generally, performance was within the benchmarks 

over the two CENRAP regions, and little improvement 

was gained with the addition of the 12km grid 

(exception of 12 km temperature for July)

• Both 36 and 12km runs had very similar wind and 

humidity performance

• Temperature performance for the CenrapN subdomain 

fell outside the benchmark in January and March for 

both the 36 and 12km runs
Overview of CENRAP 36/12 km Surface 

Performance

• Wind performance slightly better in the summer than 

in winter for both runs

• Both runs display a cold bias in the winter and warm 

bias in the summer over the CenrapN subdomain

• Humidity performance is worse in summer than in the 

winter for the 36 and 12 km runs
Overview of CENRAP 36/12 km Surface 

Performance

• Adding the 12 km CENRAP grid resulted in only 

modest performance increases for both CENRAP 

subdomains

• 12 km grid requires significantly more computer time 

than for the 36 km coarse grid

• It may not be worth the extra processing time to 

include the 12km CENRAP grid, especially for annual 

modeling purposes.
CENRAP 36/12 km Surface Performance

• Evaluation of 36 and 12 km MM5 runs found:

> Little difference in MM5 model performance

> No new problems found with 12 km MM5 fields

> Conclusions from CMAQ/CAMx 36/12 km modeling 

still hold:

• For regional haze modeling of Class I areas the 36 km 

grid appears to be sufficient

• Conclusions may not be true for 8-hour ozone and PM2.5

modeling of urban areas

– Midwest and Southeast U.S. modeling indicates that 

higher resolution than 36 km (e.g., 12 km and/or 4 

km) is needed for 8-hour ozone and PM2.5 issues