Three-dimensional variational data assimilation of ozone and fine particulate matter observations. Some results using the Weather Research and Forecasting—Chemistry model and Gridpoint Statistical Interpolation

In routine air quality forecasting, initial conditions for chemical species are obtained from previous-day forecasts without accounting for observations. An experiment is described in this article, in which surface measurements of ozone and fine aerosols over the northeastern America are assimilated into the Weather Research and Forecasting - Chemistry model, using Gridpoint Statistical Interpolation, a three-dimensional variational assimilation tool. Metrics to obtain a background error covariance matrix are derived from forecasts during a summer season. The assimilation experiment is performed in another summer season. Results show that forecasts of ozone and fine aerosol concentrations benefit significantly from the assimilation in terms of standard verification scores for a period of at least 24 hours.