Advanced CMAQ Concepts l l l Plume in

________________________________Advanced CMAQ Concepts l l l Plume in Grid Process Analysis Model Performance Evaluation and QA Procedures 1 __________________________Community Modeling and Analysis System

________________________________Advanced CMAQ Concepts Plume in Grid (Pin. G)(1) l l l Subgrid scale treatment of major emitting point sources (MEPSE) For more realistic treatment of dynamic and chemical processes impacting elevated point sources CMAQ currently has one implementation of a Pin. G treatment CMAQ Pin. G consists of a Plume Dynamics Model (PDM) and a Lagrangian reactive plume model Capable of both gas-phase and aerosol treatment 2 __________________________Community Modeling and Analysis System

________________________________Advanced CMAQ Concepts Plume in Grid (Pin. G)(2) l l l The PDM is a stand-alone preprocessor that simulates plume rise, horizontal and vertical growth, dispersion, and transport at sub-grid scales The PDM controls the interaction between the plumes and the parent grid The Lagrangian plume model is internal to the CCTM and simulates the chemistry within the plumes themselves Intended for grid resolutions of 20 -40 km Both physical and chemical criteria for plume handover to parent grid 3 __________________________Community Modeling and Analysis System

________________________________Advanced CMAQ Concepts Plume in Grid (Pin. G)(3) CCTM Emissions PDM Pin. G Meteorology Adapted from: Gillani and Godowitch (1999), Science Algorithms of the EPA Models-3 CMAQ Modeling System , EPA/600/R-99/030, pp. 9. 1 9. 31 4 __________________________Community Modeling and Analysis System

________________________________Advanced CMAQ Concepts Plume in Grid (Pin. G)(4) l l CMAQ implementation requires compiling the CCTM with the Pin. G option invoked and running the PDM preprocessor to prepare special emissions inputs Two CCTM compiler options for Pin. G – – l ping_noop: No Pin. G treatment ping_smvgear: Pin. G with internal Gear chemistry solver Emissions requirements: 2 -d MEPSE file that defines which sources to receive Pin. G treatment – SMOKE instrumented to create CMAQ-ready MEPSE files 5 __________________________Community Modeling and Analysis System

________________________________Advanced CMAQ Concepts Plume in Grid (Pin. G)(5) l l l The PDM uses a MEPSE file and meteorology inputs to create a CCTM input file Build and execute the PDM similar to the other CMAQ preprocessors (e. g. ICON, BCON) CCTM compiled with the Pin. G option will look for the additional PDM and MEPSE input files during execution Additional CCTM Pin. G output includes an unmerged/active plume net. CDF file Post-processing utility to overlay the active plumes onto the parent grid without chemical coupling 6 __________________________Community Modeling and Analysis System

________________________________Advanced CMAQ Concepts Process Analysis (PA)(1) l l l Eulerian grid models are based on partial differential equations that define the time-rate of change in species concentrations due to chemical and physical processes PA is a configuration system within Eulerian models that provides quantitative information about the impacts of individual processes on the cumulative chemical concentrations PA is an optional feature of CMAQ that provides insight into the reasons for a model’s predictions 7 __________________________Community Modeling and Analysis System

________________________________Advanced CMAQ Concepts Process Analysis (PA)(2) l Two classes of PA – – l Integrated reaction rates (IRR) Integrated process rates (IPR) PA is useful for – – – Identifying sources of error Interpreting model results Determining the important characteristics of chemical mechanisms (IRR) Determining the important characteristics of different implementations of physical processes (IPR) IPR quantifies the contribution of each source and sink process for a particular species at the end of each time step 8 __________________________Community Modeling and Analysis System

________________________________Advanced CMAQ Concepts Process Analysis (PA)(3) l l CMAQ implementation requires compiling the CCTM with PA include files generated by the PROCAN preprocessor PA include files specify – – l l IRR or IPR Chemical species or groups to collect PA information about A PROCAN configuration file defines the contents of the include files A PROCAN run script uses information in the configuration file and calls the executable to create the include files 9 __________________________Community Modeling and Analysis System

________________________________Advanced CMAQ Concepts Process Analysis (PA)(4) PA_CMN pa. inp PROCAN PA_CTL CCTM PA PA_DAT Configuration File Include Files 10 __________________________Community Modeling and Analysis System

________________________________Advanced CMAQ Concepts 11 __________________________Community Modeling and Analysis System

________________________________Advanced CMAQ Concepts Process Analysis (PA)(7) l l IRR quantifies the mass throughput of a particular reaction within a chemical mechanism IRR can diagnose mechanistic and kinetic problems within the chemistry model IRR can reveal NOx vs. VOC sensitivity regimes IRR generally more difficult to interpret than IPR 12 __________________________Community Modeling and Analysis System

________________________________Advanced CMAQ Concepts Model Performance Evaluation (MPE) l l l l Question why a model is doing what it is doing What are the inherent uncertainties and how do they impact the model results Qualitative and quantitative evaluation Diagnostic versus operational evaluation Comparisons against observations Evaluate at different temporal and spatial scales Categorical model evaluation (used for Forecasting) – Contingency Table, False Alarm Rate, Skill Scores, CSI, etc. 13 __________________________Community Modeling and Analysis System

________________________________Advanced CMAQ Concepts Quantitative vs Qualitative l Qualitative model evaluation targets intuitive features in results – – l Effects of urban areas Boundary layer effects Effects of large point sources and highways Diurnal phenomena Quantitative evaluation provides statistical evidence for model performance – – – Daily, seasonal, annual comparisons with observed data At coarse grids, compare observations with the concentrations in the model grid cell in which the monitor is located At fine grids, compare observations with the concentrations in a matrix of cells surrounding the cell in which the monitor is located 14 __________________________Community Modeling and Analysis System

________________________________Advanced CMAQ Concepts Problems/Issues l Modeling scales have grown tremendously both spatially and temporally – – l Heterogeneous nature of observational datasets – l Vary by network, by quality, by format, by frequency Measurement or model artifacts – – l Datasets becoming larger Need to process and digest voluminous amount of information What is modeled is not always measured Need adjustments before comparisons Problem of incommensurability – Comparing point measurement with volume average 15 __________________________Community Modeling and Analysis System

________________________________Advanced CMAQ Concepts Observational Databases l l l l l AIRS (hourly) (~4000) IMPROVE (every 3 rd day) (~160) CASTNET (hourly, weekly) (123) NADP (weekly) (over 200) EPA Supersites (sub-hourly) (8) EPA STN (hourly) (215) PAMS (hourly) (~130) AERONET Special field campaigns – – l e. g. AIRMAP, ASACA, BRAVO, CCOS, CRPAQS, NARSTO, SEARCH, SOS, TXAQS, etc. Aircraft Data Remote Sensing Data (AURA, MODIS, etc. ) 16 __________________________Community Modeling and Analysis System

________________________________Advanced CMAQ Concepts Operational Evaluation (mostly quantitative) l Compute suite of statistical measures of performance – – – l Time-series analyses – l l l Peak Prediction Accuracy, Bias metrics (MB, MNB, NMB, FB), Error metrics (RMSE, FE, GE, MGE, NMGE), etc. “Goodness-of-fit” measures (based on correlation coefficients and their variations) Various temporal scales Hourly, weekly, monthly Grid (tile) plots Scatter plots Pie-charts 17 __________________________Community Modeling and Analysis System

________________________________Advanced CMAQ Concepts Diagnostic Evaluation (qualitative and quantitative) l Compute various ratios – l Metrics different for each problem being diagnosed / studied • O 3/NOz, , H 2 O 2/HNO 3 for NOx versus VOC limitation • NOz/NOy for chemical aging • PM species ratios such as NH 3/NHx, NO 3/(total nitrate) for gasparticle partitioning, NH 4/SO 4, NH 4/NO 3, etc. • Others? Innovative Techniques – – – Empirical Orthogonal Functions Principal Component Analyses Process Analyses Source Apportionment (available for Carbon and Sulfur) Decoupled-direct method (DDM) Others? 18 __________________________Community Modeling and Analysis System

________________________________Advanced CMAQ Concepts Analyses Tools for MPE l sitecmp to prepare obs-model pairs – l PAVE – l http: //www. ncl. ucar. edu Python I/O API Tools – l http: //nco. sourceforge. net NCAR Command-line Language – l http: //www. baronams. com/products/ioapi net. CDF Operators – l http: //www. cmascenter. org I/O API Utilities – l Part of CMAQ Distribution http: //www-pcmdi. llnl. gov/softwareportal/Members/azubrow/ioapi. Tools/index_html Atmospheric Model Evaluation Tool (AMET) – Under development at EPA 19 __________________________Community Modeling and Analysis System

________________________________Advanced CMAQ Concepts MPE Example 1 Grid Resolution Variability 36 -km 4 -km 12 -km 20 __________________________Community Modeling and Analysis System

________________________________Advanced CMAQ Concepts MPE Example 2 Spatial Variability of Peak Predictions 21 __________________________Community Modeling and Analysis System

________________________________Advanced CMAQ Concepts MPE Example 3 Wind and Obs Overlay 22 __________________________Community Modeling and Analysis System

________________________________Advanced CMAQ Concepts MPE Example 4 Scatter Plot Analyses l Regression analyses present model results across multiple observa O 3 SO 4 23 __________________________Community Modeling and Analysis System

________________________________Advanced CMAQ Concepts MPE Example 5 Time Series Analyses 24 __________________________Community Modeling and Analysis System

________________________________Advanced CMAQ Concepts MPE Example 6 Attainment Demonstration for O 3 25 __________________________Community Modeling and Analysis System

________________________________Advanced CMAQ Concepts MPE Example 7 Forecast Model Evaluation 26 __________________________Community Modeling and Analysis System