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The Development of a Hybrid Meteorological Field

The Development of a Hybrid Meteorological Field to Improve Ozone Simulation Results in the CCOS Domain. Bruce Jackson * , Kemal Gurer, Daniel Chau, and Ajith Kaduwela California Environmental Protection Agency/Air Resources Board

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The Development of a Hybrid Meteorological Field

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  1. The Development of a Hybrid Meteorological Field to Improve Ozone Simulation Results in the CCOS Domain Bruce Jackson*, Kemal Gurer, Daniel Chau, and Ajith Kaduwela California Environmental Protection Agency/Air Resources Board Planning and Technical Support Division California Air Resources Board/PTSD April, 2005

  2. Pacific Ocean Central California Ozone Study (CCOS) Modeling Domain and RWP/RASS Locations California Air Resources Board/PTSD April, 2005

  3. Why Use Hybrid Meteorological Fields? Prognostic Models are: -- “the latest science” -- “the state-of-the-art” -- observational FDDA to improve simulations California Air Resources Board/PTSD April, 2005

  4. Prognostic Model Contributions to CCOS Episodes California Air Resources Board NOAA/ETL Bay Area Air Quality Management District ENVIRON Desert Research Institute Alpine Geophysics California Air Resources Board/PTSD April, 2005

  5. CCOS MM5 Simulations MM5 Domain Lambert Projection at 30 N, 60 N, and 120.5 W 36-km, 12-km, and 4-km nested domains 4-km domain, 189x189 grid cells 50 vertical layers -- first layer ~ 23 m MM5_N1: observational FDDA included Land Surface Module ETA Boundary Layer Module MM5_N2: no observational FDDA 5-Layer Soil Module ETA Boundary Layer Module California Air Resources Board/PTSD April, 2005

  6. Simulated surface winds for August 02, 2000 at 0200 PDT using the MM5 model without observational FDDA (MM5_N2) California Air Resources Board/PTSD April, 2005

  7. Simulated surface winds for August 02, 2000 at 0200 PDT using the MM5 model with observational FDDA (MM5_N1) California Air Resources Board/PTSD April, 2005

  8. Simulated 500 magl winds for August 01, 2000 at 0200 PDT using the MM5 model without observational FDDA (MM5_N2) California Air Resources Board/PTSD April, 2005

  9. Simulated 500 magl winds for August 01, 2000 at 0600 PDT using the MM5 model with observational FDDA (MM5_N1) California Air Resources Board/PTSD April, 2005

  10. Objective/Prognostic Hybrid Wind Fields S ( Uk *1/Rk2 ) * (1 - W) + ( Upij * 1/Rp2 ) * W Uij = S (1/Rk2) * (1 - W) + 1/Rp2 * W where: Uij wind component for cell ‘ij’ Uk observed wind component for site ‘k’ Rk radial distance to site ‘k’ Upij prognostic wind component for cell ‘ij’ Rp effective radial distance for prognostic component W relative weighting factor for prognostic wind components California Air Resources Board/PTSD April, 2005

  11. Objective/Prognostic Hybrid Meteorology CALMET Diagnostic Model The horizontal coordinate system for the objective analysis is identical to that used in MM5 Surface winds extrapolated vertically to 200 magl Air temperatures adjusted for height prior to extrapolation Interpolation barriers were added along the crests of the mountain ranges California Air Resources Board/PTSD April, 2005

  12. CCOS Air Quality Modeling Domain Horizontal Domain: 185 x 185, 4-km cells Vertical Domain: 16 vertical layers to 5000 magl Air Quality Model: CAMx/SAPRC99 Episode Period: July 31 - August 02, 2000 Simulation Period: July 29 - August 02, 2000 Model Performance Subregions: San Francisco Bay Area Sacramento and Sacramento River Delta Southern San Joaquin Valley California Air Resources Board/PTSD April, 2005

  13. SAC SF So.SJV CCOS Domain Model Performance Subregions California Air Resources Board/PTSD April, 2005

  14. Maximum Ozone Concentrations* Observed During the July/August, 2000 CCOS Episode Jul 31 Aug 01 Aug 02 Subregion ppb ppb ppb ------------------------------------------------ SF Bay Area 126 109 100 Sacramento Area 110 134 131 So. San Joaquin 115 116 151 ------------------------------------------------ * the peak concentrations for the episode have been highlighted California Air Resources Board/PTSD April, 2005

  15. USEPA (1991) Model Performance Guidelines for Ozone Statistical Measure Acceptance Range Unpaired Peak Ratio (UPkR) : 0.80 - 1.20 Paired Normalized Bias (NB) **: +/- 15% ** for observed ozone concentrations in excess of 60 ppb California Air Resources Board/PTSD April, 2005

  16. Ozone Model Performance (USEPA, 1991)* for the CCOS July/August, 2000 Episode Using CAMx/SAPRC99f Jul 31 Aug 01 Aug 02 UPkR NB UPkR NB UPKR NB ppb % ppb % ppb % --------------------------------------------------- CMHb Model SF Bay Area 0.97 +061.14 -04 1.16 -41 Sacramento 1.35 +09 0.99 00 0.99 -10 Southern SJV 1.10 -02 1.03 -10 0.88 -09 MM5_N1 Model (w/ FDDA) SF Bay Area 0.88 +01 1.05 -11 1.04 -37 Sacramento 1.22 +02 1.00 -10 0.90 -18 Southern SJV 0.95 -07 0.88 -17 0.73 -19 MM5_N2 Model (wo/ FDDA) SF Bay Area 0.98 +03 1.11 -23 1.16 -14 Sacramento 1.32 +08 0.93 -18 0.96 -03 Southern SJV 1.06 -03 1.03 -11 0.78 -19 --------------------------------------------------- UPkR -- Unpaired Peak Ratio NB -- Paired Mean Normalized Bias * simulations meeting USEPA model performance guidelines are highlighted California Air Resources Board/PTSD April, 2005

  17. Conclusions Hybrid meteorological fields using objective analysis can result in better agreement with observed winds, resulting in improved air quality model performance. Prognostic model results are not a substitute for meteorological fields built on a good observational network. Prognostic models such as MM5 should not be promoted to the exclusion of alternative methodologies. California Air Resources Board/PTSD April, 2005

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