Air quality forecasts in the mid-Atlantic region: Current practice and benchmark skill

William F. Ryan, Charles A. Piety, Eric D. Luebehusen

Research output: Contribution to journalArticlepeer-review

33 Scopus citations


Air quality forecasts for the mid-Atlantic region (including the metropolitan areas of Baltimore, Washington, D.C., and Philadelphia) began in 1992. These forecasts were issued to the public beginning in 1995 and predict daily peak O3 concentrations (1-h average) within each metropolitan area. The purpose of the forecasts are to warn sensitive populations of concentrations that are in excess of the National Ambient Air Quality Standard (NAAQS) for O3 and initiate voluntary control programs ('ozone action days') designed to reduce pollution. Ozone is a photochemical pollutant whose concentration reach a maximum during the summer months when day length is long and solar zenith angle low. Forecasts are issued daily from mid-May to mid-September at approximately 1900 UTC and are valid the following day. The forecasts are based on statistical models that use primarily meteorological predictors. Output from the statistical model is used as guidance and modified by the forecasters to account for features not resolved by those methods. The forecast is issued to the public in the form of a color code with 'code red' indicating unhealthy conditions. The range of peak O3 concentrations in the mid-Atlantic region during a given season is typically 30-180 parts per billion by volume (ppbv). For the period of this study (1995-98) the Baltimore forecast area observed seasonal mean peak O3 of 85.7 ppbv. Median absolute forecast error for the 1995-98 seasons was 9.0 ppbv and root-mean-square error was 14.8 ppbv. This represents a 40% increase in skill over simple persistence forecasts. Nine of the 10 most severe cases during this period were correctly forecast code red with the remaining case forecast 'code orange' (O3 watch). Currently, real-time photochemical models are being developed to forecast O3. The results presented here represent benchmark skill from which to judge improvements occasioned by numerical models or other forecasting techniques.

Original languageEnglish (US)
Pages (from-to)46-60
Number of pages15
JournalWeather and Forecasting
Issue number1
StatePublished - Feb 2000

All Science Journal Classification (ASJC) codes

  • Atmospheric Science


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