1. 1 Using Hemispheric-CMAQ to Provide Initial and Boundary Conditions for Regional Modeling Joshua S. Fu 1, Xinyi Dong 1, Kan Huang 1, and Carey Jang 2 1 University of Tennessee, Knoxville 2 Office of Air Quality Planning and Standards, USEPA Oct 17, 2012 11 th Annual CMAS Conference 15-17 th October, 2012

2. 2 Objective Study the potential applications of Hemispheric- scale CMAQ (H-CMAQ) to: Provide initial and boundary conditions (IC/BC) for regional modeling Provide initial and boundary conditions (IC/BC) for regional modeling Provide support for hemispheric scale studies with CMAQ Provide support for hemispheric scale studies with CMAQ intercontinental transport intercontinental transport public relevant background ozone public relevant background ozone Arctic black carbon Arctic black carbon

3. 3 Motivation Uncertainties remain in current methods to produce IC/BC Profile IC/BC: Limited horizontal and vertical variations Profile IC/BC: Limited horizontal and vertical variations Ordinary downscaling IC/BC: excessive transport of O 3 in the upper troposphere Ordinary downscaling IC/BC: excessive transport of O 3 in the upper troposphere Dynamic downscaling: inconsistent modeling system, discontinuity between different chemical and transport schemes Dynamic downscaling: inconsistent modeling system, discontinuity between different chemical and transport schemes Uncertainties remain in current global-regional modeling application Introduce uncertainties during downscaling Introduce uncertainties during downscaling Global and regional models are not using exactly the same emissions over the same domain Global and regional models are not using exactly the same emissions over the same domain

4. 4 Methodology Overview How to evaluate the capability of H-CMAQ to reproduce air pollutants concentrations, and provide IC/BC for regional CMAQ modeling ? GEOS-Chem Re-projection Species mapping Re-projection Layer interpolation Dynamic downscaling H-CMAQ Nest down IC/BC Regional CMAQ Part 1. Compare modeling results from two different models Part 3. Compare modeling results from two different CMAQ simulations driven by two different sets of IC/BCs Part 2. Produce IC/BC

5. 5 Domain Configuration GEOS-Chem H-CMAQ CMAQ GEOS-ChemH-CMAQCMAQ Model VersionV9-01-02V4.7.1 Horizontal Grid Spacing 2 x 2.5°108 x 108 km36 x 36 km Vertical Grid Spacing 48 layers (0.01mb top)34 layers (100mb top) 34 layers (100mb top) ProjectionGeographic Lat/LonPolarLambert Conformal Conic Met FieldGEOS-5WRFv3.2.1 3 Domains: - Global: GEOS-Chem - North Hemisphere: H-CMAQ - CONUS: CMAQ Model Configurations

6. 6 H-CMAQ Emission Preparation Base data: 2008 Annual Emission Database for Global Atmospheric Research (EDGARv4.2) Species: SO 2, NOx, CO, NMVOC, NH 3, PM 10, PM 2.5, OC, BC Resolution: 16 sectors, annual emission, 0.1x0.1°grid spacing Three processing steps: Temporal Allocation Speciation Vertical Distribution Hourly Scaling Factors Vertical Profile

7. 7 Model-ready Emissions SO 2 (10 -10 moles/(m 2 s)) EDGAR H-CMAQ H-CMAQ emission in July 2008 compared with EDGAR emission, with both units transferred to moles/(m 2 s) NO x (10 -10 moles/(m 2 s))CO (10 -7 moles/(m 2 s))

8. 8 H-CMAQ Meteorology Field Parameters RussiaUSChinaBenchmark* T2 Bias (K) -0.51-0.64-1.35±0.5 Gross Error(K) 1.952.272.55 ≤2≤2 IOA 0.950.940.92≥0.8 Wind Speed Bias (m/s) 0.26-0.330.23±0.5 RMSE (m/s) 1.571.831.66 ≤2≤2 IOA 0.770.72 ≥0.6 Wind Direction Bias (deg)0.990.052.6±10 Gross Error (deg) 37.0136.8448.82 ≤ 30 Water Vapor Mixing Ratio Bias (g/kg) -0.250.71-0.36±1 Gross Error (g/kg) 1.161.621.91 ≤2≤2 IOA 0.910.930.94≥0.6 Observation Sites WRF Evaluation Statistics (July, 2008) WRF performance is evaluated against NCDC data Three countries (Russia, United States, and China) are selected to show the hemispheric scale WRF performance Three countries (Russia, United States, and China) are selected to show the hemispheric scale WRF performance Higher latitude region has a generally better predictions from WRF, while the overall meteorology filed is reliable for H-CMAQ Higher latitude region has a generally better predictions from WRF, while the overall meteorology filed is reliable for H-CMAQ *Bench mark values suggested by Emory et al. (2001)

9. 9 Global Scale Models Performance in CONUS GEOS-Chem -Projection distortion along the latitude -Hard to capture peak values H-CMAQ -Projection distortion along the diagonal Statistics Daily Max O 3 July 2008 Both GEOS-Chem and H-CMAQ generally reproduce ozone distribution over CONUS ppbv

10. 10 Boundary Conditions Profile BC derived from H-CMAQ is close to dynamic downscaled BC from GEOS-Chem

11. 11 Modeling with Different IC/BCs Driven by IC/BC from GEOS-Chem Driven by IC/BC from H-CMAQ StatisticsDaily Max O 3 July.2008 ppbv

12. 12 Summary Preliminary Conclusions: Hemispheric-CMAQ is capable of reproducing the air quality generally agree well with observation over CONUS domain, and IC/BC derived from Hemispheric-CMAQ is close to that from GEOS-Chem Hemispheric-CMAQ is capable of reproducing the air quality generally agree well with observation over CONUS domain, and IC/BC derived from Hemispheric-CMAQ is close to that from GEOS-Chem Regional CMAQ simulation over CONUS domain demonstrate the capability of H-CMAQ to provide IC/BC for regional modeling Regional CMAQ simulation over CONUS domain demonstrate the capability of H-CMAQ to provide IC/BC for regional modeling Next steps: Stability check: H-CMAQ derived IC/BC performance in different seasons, at different regional areas Stability check: H-CMAQ derived IC/BC performance in different seasons, at different regional areas Inter-continental transport application: can H-CMAQ better track the pollutants transportation ? Inter-continental transport application: can H-CMAQ better track the pollutants transportation ? Update H-CMAQ emission with local emission inventory: NEI, EMEP, BRAVO, CAC, INTEX-B … Update H-CMAQ emission with local emission inventory: NEI, EMEP, BRAVO, CAC, INTEX-B …

13. 13 Acknowledgement The authors acknowledge GEOS-Chem team for their user support.

14. 14 Thanks !