Evaluation of sulfate simulations using Evaluation of sulfate simulations using CMAQ version 4.6: The role of cloudCMAQ version 4.6: The role of cloud

Chao LuoChao Luo11, , Yuhang WangYuhang Wang11, Stephen , Stephen MuellerMueller22, and Eladio Knipping, and Eladio Knipping33

11Georgia Institute of TechnologyGeorgia Institute of Technology22Tennessee Valley AuthorityTennessee Valley Authority33Electric Power Research InstituteElectric Power Research Institute

Modeling framework (from EPA) Modeling framework (from EPA)

Modeling system configurationsModeling system configurations

MM5MM5: : version 3.6.2 with FDDA. Resolution: version 3.6.2 with FDDA. Resolution: 36kmx36 kmx34 vertical layers36kmx36 kmx34 vertical layers..

SMOKESMOKE: : version 2.2 with the input of the version 2.2 with the input of the VISTAS emission inventory for 2002, VISTAS emission inventory for 2002, resolution:36kmx36kmx19vertical layersresolution:36kmx36kmx19vertical layers..

CMAQ4.6CMAQ4.6: : Standard version 4.6 withStandard version 4.6 with SAPRC99 SAPRC99 gas phase chemistry, AERO4 module for aerosols, gas phase chemistry, AERO4 module for aerosols, Cloud convection is computed by cloud_radm and Cloud convection is computed by cloud_radm and cloud_acm, resolution: 36kmx36kmx19 vertical cloud_acm, resolution: 36kmx36kmx19 vertical layerslayers..

Domain and observation sitesDomain and observation sites

US EPA Regions (used for model evaluation US EPA Regions (used for model evaluation

over the continental domain)over the continental domain)

SOSO22 evaluation (simulated SO evaluation (simulated SO22 > >

obs.)obs.)

Simulated sulfate smaller than observations Simulated sulfate smaller than observations in all regions except in winterin all regions except in winter

Sulfate comparison in July, Sulfate comparison in July, 20022002

The underestimation is slightly larger in the ACM scheme than RADM.

Partition of SOPartition of SO22 and sulfate is biased towards SO and sulfate is biased towards SO22

SO2

SO2 oxidation pathways

Sulfate

OH

H2O2, O3

Loss

Dry Deposition

Wet Deposition

Precip.CloudCloud

Deposition

0

10

20

30

40

50

60

70

Fre

qu

en

cy

(%

)

Clear Scattered Broken Overcast

Sky Cover

Observations

0

10

20

30

40

50

60

70

Fre

qu

en

cy

(%

)

Clear Scattered Broken Overcast

Sky Cover

CMAQ

Modeled vs. Observed Cloud Cover over Atlanta for 2002

DefinitionsClear: <1/8 sky coverScattered: 1/8 through 4/8 sky coverBroken: >4/8 through 9/10 sky coverOvercast: >9/10 sky cover

Steve Mueller, TVA

MODIS cloud fractions are much larger than CMAQ over the continent

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%

• 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 SO2 occurs in smaller regions with faster rates? The lifetime of SO2 is long enough that it is insensitive to where the conversion takes place if we look at monthly averages.

Experiments designExperiments design RADM_1: RADM cloud, limit subgrid convective RADM_1: RADM cloud, limit subgrid convective

precipitating cloud fraction no more than precipitating cloud fraction no more than 15%.15%.

RADM_2: RADM cloud, limit subgrid convective RADM_2: RADM cloud, limit subgrid convective precipitating cloud fraction no more than precipitating cloud fraction no more than 10%.10%.

ACM_1: ACM cloud, limit subgrid convective ACM_1: ACM cloud, limit subgrid convective precipitating cloud fraction no more than precipitating cloud fraction no more than 15%15%..

ACM_2: ACM cloud, limit subgrid convective ACM_2: ACM cloud, limit subgrid convective precipitating cloud fraction no more than precipitating cloud fraction no more than 10%10%..

These are attempts of a These are attempts of a temporarytemporary fix fix

Sulfate calculated from standard CMAQ v4.6 Sulfate calculated from standard CMAQ v4.6 with RADM and ACM schemes in July 2002with RADM and ACM schemes in July 2002

ACM S = 0.49 RADM S = 0.58

Limiting precip cloud fractions Limiting precip cloud fractions improves the model simulationsimproves the model simulations

ACM_1S = 0.90

ACM_2S = 0.97

RADM_1S = 0.85

RADM_2S = 0.90

SOSO22 evaluations: effect insignificant evaluations: effect insignificant

RADM sulfate budgetRADM sulfate budget STD RADMSTD RADM

(RADM2)(RADM2)Aqueous Aqueous phasephase

Gas phaseGas phase totaltotal

Deposition Deposition (ug/m(ug/m22/hr)/hr)

4444

(36)(36)2121

(19)(19)6565

(55)(55)

Column Column (mg/m(mg/m22))

1.51.5

(2.2)(2.2)1.61.6

(2.3)(2.3)3.13.1

(4.5)(4.5)

Residence Residence time (day)time (day)

2.92.9

(5.2)(5.2)6.16.1

(9.3)(9.3)2.02.0

(3.4)(3.4)

ACM sulfate budgetACM sulfate budget

STD. ACMSTD. ACM

(ACM2)(ACM2)Aqueous Aqueous phasephase

Gas phaseGas phase totaltotal

Deposition Deposition (ug/m(ug/m22/hr)/hr)

4848

(37)(37)2323

(18)(18)7171

(55)(55)

Column Column (mg/m(mg/m22))

1.41.4

(2.3)(2.3)1.51.5

(2.3)(2.3)2.92.9

(4.6)(4.6)

Residence Residence time (day)time (day)

2.52.5

(5.2)(5.2)5.35.3

(11)(11)1.71.7

(3.5)(3.5)

Sulfate budget summarySulfate budget summary

RADMRADM RADM1RADM1 RADM2RADM2 ACMACM ACM1ACM1 ACM2ACM2

Total dep. Total dep. (ug/m(ug/m22/hr)/hr)

6666 5959 5555 7171 6161 5555

Total Total column column (mg/m(mg/m22))

3.13.1 4.44.4 4.54.5 2.92.9 4.04.0 4.64.6

Residence Residence time (day)time (day)

2.02.0 3.13.1 3.43.4 1.71.7 2.72.7 3.53.5

Median Median conc. conc. (ug/m(ug/m33))

1.81.8 2.72.7 2.92.9 1.31.3 2.72.7 2.92.9

Discussion and ConclusionsDiscussion and Conclusions Gas and aqueous-phase column contributions are about Gas and aqueous-phase column contributions are about

the same although aqueous-phase production is larger.the same although aqueous-phase production is larger. Aqueous production and wet scavenging are strongly Aqueous production and wet scavenging are strongly

affected by simulated cloud properties.affected by simulated cloud properties. Both cloud_radm and cloud_acm schemes underestimate Both cloud_radm and cloud_acm schemes underestimate

cloud fractions but overestmate cloud liquid water cloud fractions but overestmate cloud liquid water content over the cloudy regions. The two biases appear content over the cloudy regions. The two biases appear to have compensated for one another and the aqueous-to have compensated for one another and the aqueous-phase conversion from SOphase conversion from SO22 to sulfate appear to be to sulfate appear to be adequate in summer.adequate in summer.

Since almost all simulated clouds are convective, both Since almost all simulated clouds are convective, both schemes have excessive scavenging of sulfate. schemes have excessive scavenging of sulfate. Consequently, standard CMAQ simulations of sulfate Consequently, standard CMAQ simulations of sulfate using these schemes have low biases. The bias is larger using these schemes have low biases. The bias is larger in the ACM than RADM scheme.in the ACM than RADM scheme.

We introduce a model fix by limiting the precipitating We introduce a model fix by limiting the precipitating cloud fractions to 10-15%. The resulting model sulfate cloud fractions to 10-15%. The resulting model sulfate simulations have no significant biases. The ACM scheme simulations have no significant biases. The ACM scheme performs better than RADM.performs better than RADM.