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Continuous, Near Real-Time Evaluation of Air Quality Models: An Approach for the Rapid Scientific Evolution of Modeling Systems
Citation:
Eder, B., R. Gilliam, G. Pouliot, R. Mathur, AND Jon Pleim. Continuous, Near Real-Time Evaluation of Air Quality Models: An Approach for the Rapid Scientific Evolution of Modeling Systems. EM Magazine. Air and Waste Management Association, Pittsburgh, PA, , 1-6, (2017).
Impact/Purpose:
Air quality models are required to address increasingly complex issues related to the representation of multiple pollutants species across multiple spatiotemporal scales, as well as those related to the design and implementation of more stringent National Ambient Air Quality Standards (NAAQS) designed to protect human health and the environment. Historically, most modeling groups have evaluated retrospective, often annual length model simulations, summarizing the performance using monthly or seasonal statistical summaries.While essential and informative, such an approach often masks finer scale temporal (e.g., diurnal to weekly) and spatial (e.g., meso to synoptic) variability in the earth–atmosphere system and, hence, air quality. In order to maintain state-of-the-science in the model, as well as the models’ ability to address emerging environmental needs, it is crucial that innovative evaluation approaches are developed and utilized that will allow for more rapid testing and hence more efficient evolution of the modeling system’s science.
Description:
As the Environmental Protection Agency's flagship air pollution modeling system, the Community Multi-scale Air Quality (CMAQ) model is being required to address increasingly complex issues related to the representation of multiple pollutants species across multiple spatiotemporal scales as well as those related to the design and implementation of more stringent NAAQS designed to protect human health and the environment. Historically, the Atmospheric Modeling and Analysis Division (now the Computational Exposure Division) has evaluated retrospective, often annual length, simulations of CMAQ, summarizing the performance using monthly or seasonal statistical summaries. While requisite and informative, such an approach often masks finer scale temporal (i.e. diurnal to weekly) and spatial (meso to synoptic) variability that influences the atmosphere and hence air quality. In order to maintain CMAQ’s state-of-the-science status, as well as its ability to address emerging Agency needs, it is crucial that innovative evaluation approaches are developed and utilized that will allow for more rapid testing and hence more efficient evolution of the modeling system’s science. Accordingly, the Divison began running CMAQ continuously and in near real-time (CMAQ-NRT) in 2014. Division scientists from both the development and evaluation branches responsible for CMAQ gather in bi-weekly meetings to examine and discuss the model’s performance (at finer spatial and temporal scales) while antecedent meteorological and air quality conditions remain familiar. This allows for immediate and ongoing analysis, thereby facilitating model evaluation (both performance and diagnostic) of PM2.5 (mass only) and O3 concentration. Observational data obtained from EPA’s Air Quality System (AQS) are used in the evaluation incorporating roughly 450 PM2.5 mass and 950 O3 monitors. The CMAQ-NRT evaluation is limited to PM2.5 mass because of the considerable lag time associated with the collection, processing and dissemination of the speciated PM2.5 observations. Results are examined using a variety of statistical and visualization tools and have led improvements across pollutants (PM2.5 and O3 concentrations), years (2014, 2015 and 2016) and meteorological, chemical and emissions processes. Additionally, output from CMAQ-NRT is being archived and has been made available for immediate dissemination to scientists across EPA and external agencies.