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An operational evaluation of the Eta-CMAQ air quality forecast model [An article from: Atmospheric Environment]
Book Details
PublisherElsevier
ISBN / ASINB000P6OA78
ISBN-13978B000P6OA75
AvailabilityAvailable for download now
Sales Rank99,999,999
MarketplaceUnited States 🇺🇸
Description
This digital document is a journal article from Atmospheric Environment, published by Elsevier in 2006. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.
Description:
The National Oceanic and Atmospheric Administration (NOAA), in partnership with the United States Environmental Protection Agency (EPA), are developing an operational, nationwide Air Quality Forecasting (AQF) system. An experimental phase of this program, which couples NOAA's Eta meteorological model with EPA's Community Multiscale Air Quality (CMAQ) model, began operation in June of 2004 and has been providing forecasts of ozone (O"3) concentrations over the northeastern United States. An important component of this AQF system has been the development and implementation of an evaluation protocol. Accordingly, a suite of statistical metrics that facilitates evaluation of both discrete- and categorical-type forecasts was developed and applied to the system in order to characterize its performance. The results reveal that the AQF system performed reasonably well in this inaugural season (mean domain wide correlation coefficient=0.59), despite anomalously cool and wet conditions that were not conducive to the formation of O"3. Due in part to these conditions, the AQF system overpredicted concentrations, resulting in a mean bias of +10.2ppb (normalized mean bias=+22.8%). In terms of error, the domain-wide root mean square error averaged 15.7ppb (normalized mean error=28.1%) for the period. Examination of the discrete and categorical metrics on a daily basis revealed that the AQF system's level of performance was closely related to the synoptic-scale meteorology impacting the domain. The model performed very well during periods when anticyclones, characterized by clear skies, dominated. Conversely, periods characterized by extensive cloud associated with fronts and/or cyclones, resulted in poor model performance. Subsequent analysis revealed that factors associated with CMAQ's cloud cover scheme contributed to this overprediction. Accordingly, changes to the cloud schemes are currently underway that are expected to significantly improve the AQF system's performance in anticipation of its second year of operation.
Description:
The National Oceanic and Atmospheric Administration (NOAA), in partnership with the United States Environmental Protection Agency (EPA), are developing an operational, nationwide Air Quality Forecasting (AQF) system. An experimental phase of this program, which couples NOAA's Eta meteorological model with EPA's Community Multiscale Air Quality (CMAQ) model, began operation in June of 2004 and has been providing forecasts of ozone (O"3) concentrations over the northeastern United States. An important component of this AQF system has been the development and implementation of an evaluation protocol. Accordingly, a suite of statistical metrics that facilitates evaluation of both discrete- and categorical-type forecasts was developed and applied to the system in order to characterize its performance. The results reveal that the AQF system performed reasonably well in this inaugural season (mean domain wide correlation coefficient=0.59), despite anomalously cool and wet conditions that were not conducive to the formation of O"3. Due in part to these conditions, the AQF system overpredicted concentrations, resulting in a mean bias of +10.2ppb (normalized mean bias=+22.8%). In terms of error, the domain-wide root mean square error averaged 15.7ppb (normalized mean error=28.1%) for the period. Examination of the discrete and categorical metrics on a daily basis revealed that the AQF system's level of performance was closely related to the synoptic-scale meteorology impacting the domain. The model performed very well during periods when anticyclones, characterized by clear skies, dominated. Conversely, periods characterized by extensive cloud associated with fronts and/or cyclones, resulted in poor model performance. Subsequent analysis revealed that factors associated with CMAQ's cloud cover scheme contributed to this overprediction. Accordingly, changes to the cloud schemes are currently underway that are expected to significantly improve the AQF system's performance in anticipation of its second year of operation.
