OThree Chemistry Modeling of the Sept ’00 CCOS Ozone Episode: Diagnostic Experiments--Round 3 Central California Ozone Study: Bi-Weekly Presentation 4 T. W. Tesche Dennis McNally 18 December 2003

OThree Chemistry CAMx Diagnostic Runs: Round 3 CAMx Diagnostic Runs: Round 3  Round 3 Diagnostic Simulations: (four runs)  Application of Kv Patch = 1.0 m2/s (CMAQ default value)  Application of Kv Patch = 0.1 m2/s (CAMx default value)  Re-run of Base B with new CAMx (ver 4.03)  Re-run of VOC emissions scale-up run (Bn3) with new CAMx (ver 4.03)  Objectives  Assess whether adjustments to vertical mixing processes in the model have influence on Sept ’00 modeling system. [In recent CMAQ experiments, increasing Kz_min to 1.0 primarily affects vertical mixing in the nighttime stable boundary layer, reducing the concentrations of most species in the surface layer. Some influence on daytime ozone concentrations also observed.]  Quantify ozone impacts associated with migration to newest version of ENVIRON’s CAMx (ver 4.03) modeling system.  Process Analysis Update

OThree Chemistry Kv Patch Methodology Kv Patch Methodology  This routine reads the CAMx-ready Kv file and applies an ad hoc patch to layers below 100 m based on input land use. Minimum Kv’s are determined from a weighted average of land use for each cell, where each land use is assigned a Kv value of:  Urban1.0  Agricultural0.1  Range0.1  Deciduous Forest0.5  Coniferous Forest0.5  Mixed Forest0.5  Water0.1  Barren Land0.1  Nonforest Wetlands0.1  Mixed Ag-range0.1  Rocky/low shrubs0.1 Additional details on the examination of vertical mixing in ‘one atmosphere’ grid models via ‘diffusivity patches’ are given in recent EPA research (“Vertical Mixing Sensitivities in CMAQ: Comparing the Default and Two Options in Base Cases and Emissions Control Cases in the Southeast U.S.” by J. R. Arnold and R. L. Dennis, CMAQ Users Conference, Research Triangle Park, NC October 2003).

OThree Chemistry CAMx Kv Diagnostic Experiments: Round 3

OThree Chemistry 18 Sept ’00 Ozone Peaks in the SJV

OThree Chemistry 19 Sept ’00 Ozone Peaks in the SJV

OThree Chemistry 20 Sept ’00 Ozone Peaks in the SJV

OThree Chemistry

E-W Vertical Ozone Slice Plot At Parlier at 1500 PST on 18 Sept ’00: E-W Vertical Ozone Slice Plot At Parlier at 1500 PST on 18 Sept ’00: Base B

OThree Chemistry E-W Vertical Ozone Slice Plot At Parlier at 1500 PST on 18 Sept ’00: E-W Vertical Ozone Slice Plot At Parlier at 1500 PST on 18 Sept ’00: Kv Patch = 1.0 m2/s

OThree Chemistry E-W Vertical Ozone Slice Plot At Parlier at 1500 PST on 18 Sept ’00: E-W Vertical Ozone Slice Plot At Parlier at 1500 PST on 18 Sept ’00: Kv Patch = 0.1 m2/s

OThree Chemistry Kv Patch Diagnosis Findings Kv Patch Diagnosis Findings  Relative to the CAMx (ver 4.02) Base B simulation:  The Kv = 1.0 m2/s patch yields slightly mean normalized bias and mean normalized gross errors compared with the Base B and Kv =0.1 m2/s patch simulations.  Both Kv patch methods yield slightly lower peak ozone concentrations when averages across all monitors in the SJV subdomain  The Kv patch methods appear to have only very slight influence on ozone concentrations aloft at the time and locations of maximum ozone measurements (e.g., Parlier on 18 Sept) during the Sept ’00 episode  Overall, modifications to turbulent mixing regimes in the lower boundary layer via the Kv patch methodologies appear to produce no substantive change in model response for ozone.

OThree Chemistry Ozone Changes Due to New CAMx (ver 4.03)

OThree Chemistry

New CAMx (ver 4.03) Findings: MPE New CAMx (ver 4.03) Findings: MPE  Slight improvement (~ 0.4 ppb) in the accuracy of peak 1-hr ozone predictions over all monitoring stations in the SJV subdomain  Slight degradation in episode average mean normalized bias (increases by ~ 1.3 ppb)  Slight degradation in episode average mean normalized gross error (increases by ~0.7 ppb)  Slight degradation in model’s underprediction tendency (non- normalized bias increases from –18.6 ppb to –19.3 ppb, averaged across all SJV monitors for the Sept ’00 episode  Overall, no major change in apparent model response, except slight worsening of the existing ozone underprediction problem.

OThree Chemistry Model Response to Kv’s in CAMx (ver 4.03)

OThree Chemistry

New CAMx (ver 4.03) Findings: Response to Large Emissions Changes New CAMx (ver 4.03) Findings: Response to Large Emissions Changes  Migration to the newest version of CAMx (ver 4.03) appears to have no significant impact on the model’s response to significant precursor emissions changes.  Model tested with only one emissions change scenario (Base Bv3: VOC’s scaled up by factor of 3), but the resultant changes are so slight as to suggest this trend would hold for other types of emissions changes as well.  Overall, no major impact on CAMx sensitivity to precursor emissions changes in migrating to newer version of model.

OThree Chemistry Process Analysis Progress Process Analysis Progress  Initial simulations, using CAMx (ver 4.02), focused on refining definitions (e.g., size of analysis area, number of vertical layers for aggregation) and identifying optimal post-processing display methods needed for more intensive investigations.  Initial Results of Integrated Process Rate (IPR) Process Analysis analyzed for:  Arvin: Layer 1, Layers 1-10  Elk Grove: Layer 1  New runs with CAMx (ver 4.03) to produce interim PA results for detailed analysis (results expected in later Dec ’03). Utilize refined UT/OThree Chemistry PA tools as well as routine PA tools in CAMx.  Focus of PA diagnostic investigation: Sept ’00 in Elk Grove, Arvin, and Parlier subareas (see following figure).

OThree Chemistry Process Analysis Focus Subareas Process Analysis Focus Subareas Elk Grove Arvin Parlier

OThree Chemistry Next Steps  Continue PA studies with most recent version of CAMx (4.03) and focus on Elk Grove, Arvin, and Parlier. (Results expected late December)  Conduct updated MM5 simulation based on recent findings reported by NOAA on model improvements resulting from refined treatment of land use, data assimilation, and other inputs. (Results expected early January)  Conduct diagnostic CAMx simulation(s) utilizing updated top concentration boundary conditions derived from a global photochemical model (GEOS-Chem). (Results expected early January)