1. 1 Neil Wheeler, Kenneth Craig, and Clinton MacDonald Sonoma Technology, Inc. Petaluma, California Presented at the Sixth Annual Community Modeling and Analysis System (CMAS) Conference October 1-3, 2007 Chapel Hill, North Carolina STI-3229 Innovative Methods for Evaluating Meteorological Model Performance during the Central California Air Quality Studies

2. 2 Introduction Prior Measurement, Analysis, and Modeling Studies The Question The Central California Air Quality Studies (CCAQS) –California Regional PM 10 /PM 2.5 Air Quality Study (CRPAQS) –Central California Ozone Study (CCOS)

3. 3 The Central Valley of California

4. 4 Central California Air Quality Studies Multi-year Meteorological and Air Quality Monitoring Quality Assurance and Quality Control Data Analysis Emission Inventory Development Meteorological and Air Quality Modeling Back to basics…

5. 5 Meteorological Assessment Objective: Assess the readiness of meteorological data and models to drive the air quality simulation models Issues investigated: (1)the sufficiency of data precision, accuracy, bias, consistency, and time-resolution; (2)The adequacy and validity of measurement methods; (3)the ability of models to represent important processes and phenomena; and (4)new model evaluation techniques.

6. 6 Model Performance Evaluations Typical Operational Evaluations Focus on “important” Parameters Statistical Graphical – Temporal and Spatial Comparisons; Animations Diagnostic and Sensitivity Simulations

7. 7 “Innovative” Methods (1 of 2) Data-Based Analysis: Understanding Processes and Phenomena Community Modeling and Analysis System (CMAS): 1997 – 2007 Analysis Replication Derived and Integrated Parameters –Transport Statistics –Flux Calculations –Trajectories and Tracers

8. 8 “Innovative” Methods (2 of 2) Process-Based Analysis Assess Meteorology with an AQM Assess Processes and Performance between Sources and Receptors but… Synthesis –Relate Physical and Chemical Processes –Multi-Parameter Analysis –“Big Picture”

9. 9 Examples Based on Important Data Analysis Findings Tracer Concentration Distribution Wildfires and Ozone Aloft Flux Calculations and Transports Statistics Plume Rise Carbon vs. Nitrate Aerosols Recirculation Nighttime Nitrate Formation Aloft Fog and Stratus Soil Temperature-Air Temperature-Fog-Mixing Heights

10. 10 Tracer Distribution CRPAQS: MM5-CAMx with 1 ppm initial concentration Analysis after 60 hours: –Surface concentration –Peak tracer concentrations by region –Mass balance

11. 11 High Ozone Day Temperatures

12. 12 Maximum Predicted Temperatures September 19, 2000

13. 13 Air Quality Aloft

14. 14 Aircraft Spirals 37.0N 120.1W 35.9N 19.5W

15. 15 Ozonesondes

16. 16 Ozone Aloft

17. 17 Ozone Correlation by Level 0.9 km 1.8 km 7.5 km 0.25 km

18. 18 Ozonesonde – Transport?

19. 19 Wild Fire Tracers 16 km

20. 20 Hydrocarbons Aloft

21. 21 Transport Statistics RWP MM5

22. 22 Ventilation Index

23. 23 Mixing Depth Growth

24. 24 Vertical Wind Profiles RWP CAMx Input MM5

25. 25 Mass Flux Analysis

26. 26 Concentration Fluxes

27. 27 Plume Rise Experiments

28. 28 Soil Temperature

29. 29 Extent of Fog MM5 tends to overestimate the extent of fog and stratus.

30. 30 Summary Think beyond traditional approaches Analysis Multi-method Multi-parameter Phenomena and Processes Synthesis Challenge models to replicate the synthesis Maybe then the atmosphere will behave as models predict

31. 31 Acknowledgements The evaluation methods discussed in this paper were developed over the past decade with funding from many agencies. Analyses and evaluations specific to the CCAQS were funded by the San Joaquin Valleywide Air Pollution Study Agency. The statements and conclusions in this paper are those of the authors and not necessarily those of the California Air Resources Board, the San Joaquin Valleywide Air Pollution Study Agency, or its Policy Committee, their employees or their members. The mention of commercial products, their source, or their use in connection with the material reported herein is not to be construed as actual or implied endorsement of such products.

32. 32 Parting Thought Why aren’t meteorological models instrumented with process analysis tools like photochemical grid models?