_______________________________________________________________Advanced CMAQ Concepts ___________________________________________________Community Modeling and Analysis System 1 Advanced CMAQ Concepts l Plume in Grid l Process Analysis l Model Performance Evaluation and QA Procedures

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

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

_______________________________________________________________Advanced CMAQ Concepts ___________________________________________________Community Modeling and Analysis System 4 Plume in Grid (PinG) (3) Emissions Meteorology PDM CCTM PinG Adapted from: Gillani and Godowitch (1999), Science Algorithms of the EPA Models-3 CMAQ Modeling System, EPA/600/R-99/030, pp

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

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

_______________________________________________________________Advanced CMAQ Concepts ___________________________________________________Community Modeling and Analysis System 7 Process Analysis (PA) (1) 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 l PA is a configuration system within Eulerian models that provides quantitative information about the impacts of individual processes on the cumulative chemical concentrations l PA is an optional feature of CMAQ that provides insight into the reasons for a model’s predictions

_______________________________________________________________Advanced CMAQ Concepts ___________________________________________________Community Modeling and Analysis System 8 Process Analysis (PA) (2) l Two classes of PA – Integrated reaction rates (IRR) – Integrated process rates (IPR) l 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

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

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

_______________________________________________________________Advanced CMAQ Concepts ___________________________________________________Community Modeling and Analysis System 11

_______________________________________________________________Advanced CMAQ Concepts ___________________________________________________Community Modeling and Analysis System 12 Process Analysis (PA) (7) l IRR quantifies the mass throughput of a particular reaction within a chemical mechanism l IRR can diagnose mechanistic and kinetic problems within the chemistry model l IRR can reveal NO x vs. VOC sensitivity regimes l IRR generally more difficult to interpret than IPR

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

_______________________________________________________________Advanced CMAQ Concepts ___________________________________________________Community Modeling and Analysis System 14 Quantitative vs Qualitative l Qualitative model evaluation targets intuitive features in results – Effects of urban areas – Boundary layer effects – Effects of large point sources and highways – Diurnal phenomena l 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

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

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

_______________________________________________________________Advanced CMAQ Concepts ___________________________________________________Community Modeling and Analysis System 17 Operational Evaluation (mostly quantitative) l Compute suite of statistical measures of performance – 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 l Time-series analyses – Hourly, weekly, monthly l Grid (tile) plots l Scatter plots l Pie-charts

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

_______________________________________________________________Advanced CMAQ Concepts ___________________________________________________Community Modeling and Analysis System 19 Analyses Tools for MPE l sitecmp to prepare obs-model pairs – Part of CMAQ Distribution l PAVE – l I/O API Utilities – l netCDF Operators – l NCAR Command-line Language – l Python I/O API Tools – portal/Members/azubrow/ioapiTools/index_html portal/Members/azubrow/ioapiTools/index_html l Atmospheric Model Evaluation Tool (AMET) – Under development at EPA

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

_______________________________________________________________Advanced CMAQ Concepts ___________________________________________________Community Modeling and Analysis System 21 MPE Example 2 Spatial Variability of Peak Predictions

_______________________________________________________________Advanced CMAQ Concepts ___________________________________________________Community Modeling and Analysis System 22 MPE Example 3 Wind and Obs Overlay

_______________________________________________________________Advanced CMAQ Concepts ___________________________________________________Community Modeling and Analysis System 23 MPE Example 4 Scatter Plot Analyses l Regression analyses present model results across multiple observation points or time periods O3O3 SO 4

_______________________________________________________________Advanced CMAQ Concepts ___________________________________________________Community Modeling and Analysis System 24 MPE Example 5 Time Series Analyses

_______________________________________________________________Advanced CMAQ Concepts ___________________________________________________Community Modeling and Analysis System 25 MPE Example 6 Attainment Demonstration for O 3

_______________________________________________________________Advanced CMAQ Concepts ___________________________________________________Community Modeling and Analysis System 26 MPE Example 7 Forecast Model Evaluation