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ASSESSMENT OF AN ENSEMBLE OF SEVEN REAL-TIME OZONE FORECASTS OVER EASTERN NORTH AMERICA DURING THE SUMMER OF 2004
Citation:
MCKEEN, S., J. WILCZAK, G. GRELL, I. DJALALOVA, S. PECKHAM, E. HSIE, W. GONG, V. BOUCHET, R. S. MENARD, R. MOFFET, J. MCHENRY, J. MCQUEEN, Y. TANG, G. R. CARMICHAEL, M. PAGOWSKI, A. CHAN, T. DYE, G. FROST, P. LEE, AND R. MATHUR. ASSESSMENT OF AN ENSEMBLE OF SEVEN REAL-TIME OZONE FORECASTS OVER EASTERN NORTH AMERICA DURING THE SUMMER OF 2004. JOURNAL OF GEOPHYSICAL RESEARCH. American Geophysical Union, Washington, DC, 110(D21307):1-16, (2006).
Impact/Purpose:
The objectives of this task include: (1) to continuously evaluate and analyze the forecast results to provide diagnostic information on model performance and inadequacies to guide further evolution and refinements to the CMAQ model, and (2) extending the utility of the daily air quality forecast model data being produced by NOAA's National Weather Service (NWS) as part of a NOAA/EPA collaboration in air quality forecasting, to EPA mission-oriented activities. These objectives include developing and maintaining a long-term database of air quality modeling results (ozone and PM2.5), performing periodic analysis and assessments using the data, and making the air quality database available and accessible to States, Regions, RPO's and others to use as input data for regional/local scale air quality modeling for policy/regulatory purposes.
Description:
The real-time forecasts of ozone (O3) from seven air quality forecast models (AQFMs) are statistically evaluated against observations collected during July and August of 2004 (53 days) through the Aerometric Information Retrieval Now (AIRNow) network at roughly 340 monitoring stations throughout the eastern United States and southern Canada. One of the first ever real-time ensemble O3 forecasts, created by combining the seven separate forecasts with equal weighting, is also evaluated in terms of standard statistical measures, threshold statistics, and variance analysis. The ensemble based on the mean of the seven models and the ensemble based on the median are found to have significantly more temporal correlation to the observed daily maximum 1-hour average and maximum 8-hour average O3 concentrations than any individual model. However, root-mean-square errors (RMSE) and skill scores show that the usefulness of the uncorrected ensembles is limited by positive O3 biases in all of the AQFMs. The ensembles and AQFM statistical measures are reevaluated using two simple bias correction algorithms for forecasts at each monitor location: subtraction of the mean bias and a multiplicative ratio adjustment, where corrections are based on the full 53 days of available comparisons. The impact the two bias correction techniques have on RMSE, threshold statistics, and temporal variance is presented. For the threshold statistics a preferred bias correction technique is found to be model dependent and related to whether the model overpredicts or underpredicts observed temporal O3 variance. All statistical measures of the ensemble mean forecast, and particularly the bias-corrected ensemble forecast, are found to be insensitive to the results of any particular model. The higher correlation coefficients, low RMSE, and better threshold statistics for the ensembles compared to any individual model point to their preference as a real-time O3 forecast.