Community Modeling and Analysis System

Statistical and Graphical Analysis Tools

Register

The CMAS Center now offers an advanced training series for air quality modelers titled "Evaluating Air Quality Model Performance". The series will consist of modules highlighting various analysis tools and methods to understand model performance, and better inform air quality decision-making.

Availability

The table below lists the dates of the upcoming Statistical and Graphical Analysis Tools classes along with the enrollment status in each class. When enrollment is full (15 registered students) we will no longer accept applications for the class and the status column in the table will display that the class is full.

The class is subject to cancellation if there are not enough registered students. A minimum of 6 trainees must be registered to conduct a training.

The Interpretive Analysis course can also be conducted off site, provided that appropriate facilities are available and there are an adequate number of interested students. Email cmas@unc.edu to inquire about off-site trainings.

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Please note: If you are interested in another training date, please contact CMAS support (e-mail at bottom of this page).

Tile Plot

Soccer Plot

Objectives

Enable air quality modelers to become more proficient in:

  • understanding model behavior
  • identifying potential problems in model inputs or process formulations
  • devising solutions to improve model performance

Audience

Beginning and intermediate-level modelers

Format of Module I: Statistical and Graphical Analysis Tools

Two days of training combining lectures and hands-on example exercises using the Atmospheric Model Evaluation Tool (AMET) and the Visualization Environment for Rich Data Interpretation (VERDI) to quantitatively and qualitatively analyze model results. The last half of the second day will take students through the combined use of these tools in a self-paced exercise on evaluating air quality model performance in the simulation of a nitrogen deposition episode during the Rocky Mountain Atmospheric Nitrogen and Sulfur (RoMANS) observational campaign period in Spring 2006.

Agenda

TimeDay 1Day 2
8:30 AMIntroductions, logistics, course overview and objectivesGraphical Analysis: Introduction to VERDI
8:45 AM
9:00 AMConcepts of air quality model evaluationVERDI setup and running
9:15 AMLoad datasets in VERDI
9:30 AMCreate formulas in VERDI
9:45 AMCreate plots in VERDI
10:00 AMBreak 10:00 ��� 10:15 AMBreak 10:00 ��� 10:15 AM
10:15 AMStatistical Analysis: Introduction to AMETPlot menu bar options to configure plots
10:30 AMAMET overview and directory structure
10:45 AMLoad Shape files in VERDI and Areal Interpolation
11:00 AMDatabase initialization and hands-on exercise
11:15 AMScripting in VERDI
11:30 AMModel output processing using the combine utility; hands-on exercise
11:45 AMQuestions
12:00 PMLunch 12:00 ��� 1:00 PMLunch 12:00 ��� 1:00 PM
12:15PM
12:30 PM
12:45 PM
1:00 PMData matching: sitecmp and cmpairsSelf-paced exercise overview and objectives
1:15 PM
1:30 PMData load step and hands-on exercisePrepare CMAQ data, download obs data, and run AMET
1:45 PM
2:00 PMTile plots, time series plots
2:15 PMAnalyze statistical performance metrics
2:30 PMHands-on exercises
2:45 PM
3:00 PMBreak 3:00 ��� 3:15 PMBreak 3:00 ��� 3:15 PM
3:15 PMBar plots and box plotsCompare statistical performance side-by-side with graphical analyses, and prepare summary
3:30 PM
3:45 PMScatter plots
4:00 PMIndividual or group presentations by students
4:15 PMSoccer and bugle plots
4:30 PM
4:45 PMHands-on exercisesDiscussion/critique of analyses
5:00 PM
5:15 PMQuestions: 5:15-5:30 PMCourse evaluation and certificates 5:15-5:30 PM
5:30 PMEND OF DAY 1ADJOURN

Meet the Trainers

Uma Shankar

Uma Shankar, MS Research Associate, Center for Environmental Modeling for Policy Development

Uma has over 25 years experience developing and applying grid-based air quality models to assess the impacts of atmospheric PM on human health, visibility, and climate. As a developer of CMAQ, and the two-way coupled WRF-CMAQ, she has significant experience evaluating and applying these models over North America, Europe, Asia, and the Middle East to study the impacts of anthropogenic and wildfire emissions on aerosol loadings in current and future emission scenarios. Uma develops tools to post-process CMAQ model output and uses them in qualitative comparisons against satellite data. She provides guidance on the use of these tools in combination with satellite data products to the user community. Uma serves as Research Coordinator, and develops advanced air quality modeling training courses for the Community Modeling and Analysis System Center.

Liz Adams

Liz Adams, MS Research Associate, Center for Environmental Modeling for Policy Development

Ms. Adams has over 10 years of experience in model applications, model evaluation, and debugging support to developers of air quality modeling systems. Ms. Adams prepares model documentation, and performs web-based software management, software installation and testing across multiple platforms (Linux, Mac OS X, and Windows) to support public release of the Visualization Environment for Rich Data Interpretation (VERDI) tool. Ms. Adams has installed the Sparse Matrix Operator Kernel Emissions (OTHERCOURSE) training software, data and ancillary software tools to a compute server on the Amazon Web Services (AWS) Elastic Compute Cloud (EC2) for an online OTHERCOURSE training course. Ms. Adams is experienced with using Python, QGIS, Panoply, IDV, VERDI, the Atmospheric Model Evaluation Tool (AMET), and Ncview to visualize and analyze NetCDF data from the CMAQ modeling system and comparing the results to data from the observational networks. She supports the CMAS Statistical and Graphical Analysis Tools training course by preparing, testing and porting input data and scripts for VERDI and AMET to the Virtual Computing Laboratory environment, preparing and delivering classroom lectures, and providing hands-on training support to students.

Payment Info

The two day course includes all training materials, the current Statistical and Graphical Analysis Tools Manual, access to experienced atmospheric modelers, snacks, and beverages. Payment is accepted with check, credit card, or purchase order. Note that you are asked to make the payment or initiate the payment process (e.g. by providing the purchase order number) at the time of registration. We will send you a receipt by email to confirm the receipt of the registration and payment. If you find later that you are unable to attend to the class after registration, notify the CMAS Center as soon as possible. Please see our Payment Info page for our refund policy.

Prerequisites

Operational knowledge of air quality modeling, and hands-on experience with Linux and shell scripts are required. Knowledge of R, Perl, and MySQL is helpful.

Contact Information

For more information on the Statistical and Graphical Analysis Tools training, please contact the CMAS help desk by email at cmas@unc.edu.