1. Evaluation of sulfate simulations using CMAQ version 4.6: The role of cloud Chao Luo 1, Yuhang Wang 1, Stephen Mueller 2, and Eladio Knipping 3 1 Georgia Institute of Technology 2 Tennessee Valley Authority 3 Electric Power Research Institute

2. Modeling framework (from EPA)

3. Modeling system configurations MM5: version 3.6.2 with FDDA. Resolution: 36kmx36 kmx34 vertical layers. MM5: version 3.6.2 with FDDA. Resolution: 36kmx36 kmx34 vertical layers. SMOKE: version 2.2 with the input of the VISTAS emission inventory for 2002, resolution:36kmx36kmx19vertical layers. SMOKE: version 2.2 with the input of the VISTAS emission inventory for 2002, resolution:36kmx36kmx19vertical layers. CMAQ4.6: Standard version 4.6 with SAPRC99 gas phase chemistry, AERO4 module for aerosols, Cloud convection is computed by cloud_radm and cloud_acm, resolution: 36kmx36kmx19 vertical layers. CMAQ4.6: Standard version 4.6 with SAPRC99 gas phase chemistry, AERO4 module for aerosols, Cloud convection is computed by cloud_radm and cloud_acm, resolution: 36kmx36kmx19 vertical layers.

4. Domain and observation sites

5. US EPA Regions (used for model evaluation over the continental domain)

6. SO 2 evaluation (simulated SO 2 > obs.)

7. Simulated sulfate smaller than observations in all regions except in winter

8. Sulfate comparison in July, 2002 The underestimation is slightly larger in the ACM scheme than RADM.

9. Partition of SO 2 and sulfate is biased towards SO 2

10. Simulated SO 4 wet deposition larger than observation especially in summer

11. SO 2 SO 2 oxidation pathways Sulfate OH H 2 O 2, O 3 Loss Dry Deposition Wet Deposition Precip. Cloud Deposition

12. The effects of cloud on sulfate Precipitating cloud is a sink of sulfate (through wet scavenging) and a source of sulfate (heterogeneous production). Precipitating cloud is a sink of sulfate (through wet scavenging) and a source of sulfate (heterogeneous production). Non-precipitating cloud is a source of sulfate (heterogeneous production). Non-precipitating cloud is a source of sulfate (heterogeneous production). Simulated cloud properties affect simulations of SO 2 and sulfate. Simulated cloud properties affect simulations of SO 2 and sulfate.

13. Modeled vs. Observed Cloud Cover over Atlanta for 2002 Definitions Clear: <1/8 sky cover Scattered: 1/8 through 4/8 sky cover Broken: >4/8 through 9/10 sky cover Overcast: >9/10 sky cover Steve Mueller, TVA

14. MODIS cloud fractions are much larger than CMAQ over the continent

15. Cloud water path for July AMSR and TMI (microwave) are more accurate than MODIS (Terra & Aqua) Default setting overestimates precipitating cloud path; ACM overestimation is more than RADM. 10%

16. Almost all clouds in CMAQ is convective, which has a larger liquid water content. Excessive precipitation removes non-precipitating cloud. RADM and ACM in CMAQ underestimate cloud fractions, but overestimate cloud liquid water content. Could there be a compensating effect in that heterogeneous conversion of SO 2 occurs in smaller regions with faster rates? The lifetime of SO 2 is long enough that it is insensitive to where the conversion takes place if we look at monthly averages.

17. Experiments: increase subgrid convective non-precipitating cloud cover Fixed fraction of the amount of precipitating cloud cover no more than 15%. Fixed fraction of the amount of precipitating cloud cover no more than 15%. Fixed fraction of amount of precipitating cloud cover no more than 10%. Fixed fraction of amount of precipitating cloud cover no more than 10%. FRNP = min(1-FRPR,0.9)*((RH-0.7)/(0.9-0.7)), 0.7<RH<0.9 FRNP = min(1-FRPR,0.9)*((RH-0.7)/(0.9-0.7)), 0.7<RH<0.9 FRNP = min(1-FRPR,0.9), RH>=0.9 FRNP = min(1-FRPR,0.9), RH>=0.9 FRNP: non-precipitating cloud cover fraction; FRPR: precipitating cloud cover fraction FRNP: non-precipitating cloud cover fraction; FRPR: precipitating cloud cover fraction

18. Experiments design RADM_1: RADM cloud, limit subgrid convective precipitating cloud fraction no more than 15%. RADM_1: RADM cloud, limit subgrid convective precipitating cloud fraction no more than 15%. RADM_2: RADM cloud, limit subgrid convective precipitating cloud fraction no more than 10%. RADM_2: RADM cloud, limit subgrid convective precipitating cloud fraction no more than 10%. ACM_1: ACM cloud, limit subgrid convective precipitating cloud fraction no more than 15%. ACM_1: ACM cloud, limit subgrid convective precipitating cloud fraction no more than 15%. ACM_2: ACM cloud, limit subgrid convective precipitating cloud fraction no more than 10%. ACM_2: ACM cloud, limit subgrid convective precipitating cloud fraction no more than 10%. These are attempts of a temporary fix These are attempts of a temporary fix

19. Sulfate calculated from standard CMAQ v4.6 with RADM and ACM schemes in July 2002 ACM S = 0.49 RADM S = 0.58

20. Limiting precip cloud fractions improves the model simulations ACM_1 S = 0.90 ACM_2 S = 0.97 RADM_1 S = 0.85 RADM_2 S = 0.90

21. SO 2 evaluations: effect insignificant

22. RADM sulfate budget STD RADM (RADM2) Aqueous phase Gas phase total Deposition (ug/m 2 /hr) 44(36)21(19)65(55) Column (mg/m 2 ) 1.5(2.2)1.6(2.3)3.1(4.5) Residence time (day) 2.9(5.2)6.1(9.3)2.0(3.4)

23. ACM sulfate budget STD. ACM (ACM2) Aqueous phase Gas phase total Deposition (ug/m 2 /hr) 48(37)23(18)71(55) Column (mg/m 2 ) 1.4(2.3)1.5(2.3)2.9(4.6) Residence time (day) 2.5(5.2)5.3(11)1.7(3.5)

24. Sulfate budget summary RADMRADM1RADM2ACMACM1ACM2 Total dep. (ug/m 2 /hr) 665955716155 Total column (mg/m 2 ) 3.14.44.52.94.04.6 Residence time (day) 2.03.13.41.72.73.5 Median conc. (ug/m 3 ) 1.82.72.91.32.72.9

25. Discussion and Conclusions Gas and aqueous-phase column contributions are about the same although aqueous-phase production is larger. Gas and aqueous-phase column contributions are about the same although aqueous-phase production is larger. Aqueous production and wet scavenging are strongly affected by simulated cloud properties. Aqueous production and wet scavenging are strongly affected by simulated cloud properties. Both cloud_radm and cloud_acm schemes underestimate cloud fractions but overestmate cloud liquid water content over the cloudy regions. The two biases appear to have compensated for one another and the aqueous- phase conversion from SO 2 to sulfate appear to be adequate in summer. Both cloud_radm and cloud_acm schemes underestimate cloud fractions but overestmate cloud liquid water content over the cloudy regions. The two biases appear to have compensated for one another and the aqueous- phase conversion from SO 2 to sulfate appear to be adequate in summer. Since almost all simulated clouds are convective, both schemes have excessive scavenging of sulfate. Consequently, standard CMAQ simulations of sulfate using these schemes have low biases. The bias is larger in the ACM than RADM scheme. Since almost all simulated clouds are convective, both schemes have excessive scavenging of sulfate. Consequently, standard CMAQ simulations of sulfate using these schemes have low biases. The bias is larger in the ACM than RADM scheme. We introduce a model fix by limiting the precipitating cloud fractions to 10-15%. The resulting model sulfate simulations have no significant biases. The ACM scheme performs better than RADM. We introduce a model fix by limiting the precipitating cloud fractions to 10-15%. The resulting model sulfate simulations have no significant biases. The ACM scheme performs better than RADM.