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Statistical Properties of Differences between Low and High Resolution CMAQ Runs with Matched Initial and Boundary Conditions
Citation:
Lim, C. Y., M. STEIN, J. K. CHING, AND R. TANG. Statistical Properties of Differences between Low and High Resolution CMAQ Runs with Matched Initial and Boundary Conditions. ENVIRONMENTAL MODELLING & SOFTWARE. Elsevier Science, New York, NY, 25(1):158-169, (2010).
Impact/Purpose:
The National Exposure Research Laboratory′s (NERL′s) Atmospheric Modeling and Analysis Division (AMAD) conducts research in support of EPA′s mission to protect human health and the environment. AMD′s research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the Nation′s air quality and for assessing changes in air quality and air pollutant exposures, as affected by changes in ecosystem management and regulatory decisions. AMD is responsible for providing a sound scientific and technical basis for regulatory policies based on air quality models to improve ambient air quality. The models developed by AMD are being used by EPA, NOAA, and the air pollution community in understanding and forecasting not only the magnitude of the air pollution problem, but also in developing emission control policies and regulations for air quality improvements.
Description:
The difficulty in assessing errors in numerical models of air quality is a major obstacle to improving their ability to predict and retrospectively map air quality. In this paper, using simulation outputs from the Community Multi-scale Air Quality Model (CMAQ), the statistical characteristics of the discrepancies due to different model resolutions are investigated as a surrogate for model error particularly due to discretization.
URLs/Downloads:
Statistical Properties of Differences between Low and High Resolution CMAQ Runs with Matched Initial and Boundary Conditions (PDF, NA pp, 4923 KB, about PDF)Environmental Modelling and Software
