1. Atmospheric Modeling and Analysis Division,
Indirect radiative forcing of climate due to aerosols in the two-way coupled WRF-CMAQ: model description, development, evaluation and regional analysis
Shaocai Yu, Rohit Mathur, Jonathan Pleim, David Wong, Rob Gilliam, Steve Howard*, and S.T. Rao*
Atmospheric Modeling and Analysis Division,
National Exposure Research Lab, U.S. EPA, RTP, NC 27711
*retired

2. Largest uncertainty (IPCC, 2007):
indirect aerosol forcing

4. Model Description (Configuration)
Calculation of indirect aerosol forcing (IAF) in WRF-CMAQ
Aerosols: number, size, chemical composition
Coupled WRF-CMAQ aerosol simulation
Sulfate, BC, OC, dust
CAM ice nucleation scheme (Liu et al. 2007)
Aerosol activation scheme (Abdul-Razzak and Ghan, 2000, 2002)
Updraft velocity, ice water content (WRF), temperature
Updraft velocity, liquid water content (WRF)
Cloud microphysics (Morrison): cloud vapor and water, rain, ice, snow, graupel
CCN, Cloud droplet number
Ice number Conc., IN
Radiative transfer model: CAM: re (4-20) mm; RRTMg: re(2-60) mm
Cloud effective radius (re), COD
Ice effective radius (rie), IOD
Met fields (WRF)
The 1st and 2nd IAF
Glaciation IAF

6. Model domain (12 km and 4 km)
12 km domain over CONUS
PM2.5
4 km nested domain over Gulf of Mexico

7. Results: (August, 2006) Evaluation for PM2.5 at AIRNOW sites
Model gets obs PM2.5 reasonably good
Over Houston domain, model overestimated PM 2.5, especially for 4-km simulation
WRF-CMAQ-CAM (CAM)
WRF-CMAQ-RRTMG (RRTMG)
WRF-CAM (CAM-D)
WRF-RRTMG (RRTMG-D)
NMB (%)
CAM
RRTMG
East US (long<100)
5.3
-0.1
West US (long>100)
0.4
-5.2
Houston domain (12km)
37.1
2.0
Houston domain (4km)
65.4

8. Results: PM2.5 composition over the CONUS (12-km) (August)
Model underestimates SO4 over E US but overestimate OC, EC,TC at IMPROVE sites
SO4
NMB (%)
E US
W US
CAM
RRTMG
CASTNet
SO4
-27.6
-32.1
-23.9
-24.5
NH4
-23.0
-27.7
-34.1
-35.9
NO3
19.4
9.7
-80.6
-82.3
SO2
101.1
98.9
47.0
47.5
IMPROVE
PM25
-13.2
-16.8
15.0
7.1
-12.5
-18.9
13.9
11.6
50.4
22.4
-51.9
-61.1 OC
25.9
23.8
51.4
38.6 EC
54.9
52.2
110.6
94.5 TC
31.9
29.7
59.2
46.0
STN
-0.7
-6.2
1.5
-5.3
-7.9
-14.8
-4.2
-9.5
2.8
-6.7
-47.3
-53.6
64.2
37.1
-81.1
-84.1
2.2
-0.9
-7.0
NH4
NO3 OC TC

9. Results:Evaluation at STN sites (August) over the Houston
PM25
SO4
overestimated obs PM2.5 because of TC overestimation
12-km run underestimates SO4, 4-km run is good.
NMB
CAM-4km
rrtmg-4km
PM25
92.4
53.4
SO4
6.7
-7.6
NH4
-22.2
-61.1
NO3
-16.4
-33.8 TC
142.7
89.1
Cam-12km
rrtmg-12km
43.1
12.7
-42.6
-48.0
-57.3
-84.3
-56.9
-62.9
103.1
69.3
NH4
NO3 TC

10. Results (Shortwave cloud forcing)
Interpolate to 12 km resolution for model (August)
WRF (only)
WRF-CMAQ
CAM
12 km (CERES)
RRTMG

11. Results (Shortwave cloud forcing)
Interpolate to 4 km resolution for model (August)
WRF (only)
WRF-CMAQ
CAM
4 km (CERES)
RRTMG

12. Results (Shortwave cloud forcing)
Comparison of Monthly means SWCF (August):
Land
12-km simulations with both indirect and direct aerosol forcing (WRF-CMAQ) are the best with very good correlation coefficients
12-km runs still underestimate SWCF over land
Land
Ocean
Obs (CERES)
Corr
NMB (%)
CAM
WRF-CMAQ
0.96
-18.18
0.90
1.21
WRF (only)
0.50
-5.01
-0.55
53.86
RRTMG
-27.44
0.93
-18.91
0.72
-30.45
-0.48
14.90
Ocean

13. Results (Shortwave cloud forcing)
Comparison of Monthly means SWCF (August):
4-km simulations with both indirect and direct aerosol forcing (WRF-CMAQ) are the best
4-km runs are better than 12-km runs for SWCF, less underestimation.
Obs (CERES)
NMB (%)
CAM
WRF-CMAQ -5
WRF (only)
-24
RRTMG -7
-28

14. Results (Longwave cloud forcing)
Comparison of Monthly means LWCF (August):
Land
12-km WRF-CMAQ simulations with both indirect and direct aerosol forcing are the best with very good correlation coefficients
12-km WRF-CMAQ runs underestimate LWCF
Land
Ocean
Obs (CERES)
Corr
NMB (%)
CAM
WRF-CMAQ
0.82
-31.57
0.90
-23.18
WRF (only)
0.26
40.15
0.38
168.46
RRTMG
0.83
-33.53
-30.56
0.36
-6.60
0.45
95.29
Ocean

15. Results (Longwave cloud forcing)
Comparison of Monthly means LWCF (August):
4-km simulations with both indirect and direct aerosol forcing (WRF_CMAQ) are the best
4-km runs are better than 12-km runs for LWCF, less bias
Obs (CERES)
NMB (%)
CAM
WRF-CMAQ 3
WRF (only) 4
RRTMG -8
-13

16. Results (cloud optical depth (COD))
Comparison of Monthly means COD (August):
Land
12-km simulations with both indirect and direct aerosol forcing (WRF-CMAQ) are the best
12-km runs underestimate COD
Land
Ocean
Obs (CERES)
Corr
NMB (%)
CAM
WRF-CMAQ
0.86
-31.98
0.88
-2.51
WRF (only)
0.71
-69.11
0.41
-65.42
RRTMG
0.85
-57.77
0.87
-42.76
0.80
-91.40
0.45
-90.53
Ocean

17. Results (COD) Obs (CERES) NMB (%) CAM WRF-CMAQ -7 WRF (only) -75 RRTMG
Comparison of Monthly means COD (August):
4-km simulations with both indirect and direct aerosol forcing (WRF-CMAQ) are the best
4-km WRF-CMAQ runs are better than 12-km runs for COD, less underestimation
Obs (CERES)
NMB (%)
CAM
WRF-CMAQ -7
WRF (only)
-75
RRTMG
-31
-89

18. Results (Cloud Fraction)
Comparison of Monthly means CldFrac (August):
Land
12-km simulations with both indirect and direct aerosol forcing (WRF-CMAQ) are the best
12-km runs underestimate cloud fraction slightly
Land
Ocean
Obs (CERES)
Corr
NMB (%)
CAM
WRF-CMAQ
0.97
-8.67
0.87
-0.83
WRF (only)
0.30
37.51
-0.06
41.60
RRTMG
-13.49
0.90
-10.28
0.39
24.02
-0.17
30.18
Ocean

19. Results (Cloud Fraction)
Comparison of Monthly means CldFrac (August):
For 4-km runs, all models performed very well with slight overestimation
4-km runs are very good
Obs (CERES)
NMB (%)
CAM
WRF-CMAQ 12
WRF (only) 6
RRTMG 1 7

20. Contacts:
Brian K. Eder

21. Results (Cloud effective radius)
Interpolate to 12 km resolution for model (August)
WRF-CMAQ
WRF (only)
12 km (CERES)
CAM
RRTMG

22. Results (Cloud optical depth (COD))
Interpolate to 12 km resolution for model (August)
WRF-CMAQ
WRF (only)
12 km (CERES)
CAM
RRTMG

23. Results (Longwave cloud forcing)
Interpolate to 12 km resolution for model (August)
WRF-CMAQ
WRF (only)
CAM
12 km (CERES)
RRTMG

24. Results (Cloud Fraction (CldFrac))
Interpolate to 12 km resolution for model (August)
WRF-CMAQ
WRF (only)
12 km (CERES)
CAM
RRTMG

25. Coupler Two-way coupled WRF-CMAQ modeling System
(Interaction and feedback)
Meteorological Model
WRF modeling System:
x=12 km, 4km
34 layers
Land-Surface: PX LSM
PBL: ACM2
Cloud Physics: Morrison
Cumulus: Kain-Fritsch,
not for 4km
Shortwave: RRTMg,
or CAM
Longwave: RRTMg,
Chemical Transport Model
CMAQ Modeling System:
Photochemistry: CB05
59 organic and inorganic species,
156 chemical reactions
Aerosol module: AE6
3 lognormal modes,
organic and inorganic
Emission: SMOKE
In-line emission
for biogenic species
AQPREP
Prepares virtual CMAQ compatible input met. files
Coupler
CMAQ-mixactivate:
cloud drop, ice number conc.
Direct forcing:
Aerosol size, composition, conc.

26. Results (preliminary): Temp along ship track over the Gulf of Mexico
Models got Temp. very well
Obs (Ship)
28.49
NMB (%)
CAM
WRF-CMAQ
28.19
-1.1
WRF-CMAQ (direct)
28.57
0.3
WRF (only)
28.68
0.7
RRTMG
28.89
1.4
28.86
1.3
28.88

27. Results (Cloud Fraction (CldFrac))
Interpolate to 4 km resolution for model (August)
WRF-CMAQ
WRF (only)
4 km (CERES)
CAM
RRTMG

28. Results (Cloud optical depth (COD))
Interpolate to 4 km resolution for model (August)
WRF-CMAQ
WRF (only)
4 km (CERES)
CAM
RRTMG

29. Results (Longwave cloud forcing)
Interpolate to 4 km resolution for model (August)
WRF-CMAQ
WRF (only)
CAM
4 km (CERES)
RRTMG

30. Site location

31. Tracks of P-3 flights
Tracks of ship

32. Results (Cloud Effective Radius)
Interpolate to 4 km resolution for model (August)
4 km (CERES)
WRF-CMAQ
WRF (only)
CAM
RRTMG

33. Results (Cloud Effective radius)
Comparison of Monthly means CldRadius (August):
CERES measure CldEffc at cloud top, it is difficult to compare with the models
WRF-CMAQ underestimate obs by ~60%
Mean:
Obs (CERES)
12.59
NMB (%)
CAM
WRF-CMAQ
5.04
-60
WRF (only)
14.00 11
RRTMG
4.23
-66

34. Results (Cloud Effective Radius)
Interpolate to 4 km resolution for model (September)
4 km (CERES)
WRF-CMAQ
WRF (only)
CAM
RRTMG

35. Results (Cloud Effective radius)
Comparison of Monthly means Cldradius (September):
WRF-CMAQ underestimate obs by ~40%
Mean: (mm)
Obs (CERES)
11.11
NMB (%)
CAM
WRF-CMAQ
6.31
-43
WRF (only)
14.00 26
RRTMG
5.24
-53

36. Results (Ice Effective Radius)
Interpolate to 4 km resolution for model (August)
4 km (CERES)
WRF (only)
WRF-CMAQ
CAM
RRTMG

37. Results (Ice Effective radius)
Comparison of Monthly means CldEffi (August):
CERES measure CldEffi at cloud top, it is difficult to compare with the models
WRF-CMAQ overestimate obs by ~70%
CAM is slightly better than RRTMG
Mean: (mm)
Obs (CERES)
27.10
NMB (%)
CAM
WRF-CMAQ
44.87 66
WRF (only)
20.65
-24
RRTMG
47.29 74
20.89
-23

38. Results (Ice Effective Radius)
Interpolate to 4 km resolution for model (September)
4 km (CERES)
WRF-CMAQ
WRF (only)
CAM
RRTMG

39. Results (Ice Effective radius)
Comparison of Monthly means CldEffi (September):
WRF-CMAQ overestimate obs by ~160%
Mean: (mm)
Obs (CERES)
21.69
NMB (%)
CAM
WRF-CMAQ
56.49
160
WRF (only)
20.86 -4
RRTMG
57.75
166
20.98 -3