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Three-dimensional Variational Data Assimilation of Ozone and Fine Particular Matter. Some Results With Weather Research and Forecasting - Chemistry Model and Gridpoint Statistical Interpolation


In operational air-quality forecasting, initial concentrations of chemical species are often obtained using previous-day forecasts with limited or no account for the observations. In this article we assess the role that assimilation of surface measurements of ozone and fine aerosols can play in improving the skill of air-quality forecasts. An assimilation experiment is performed using the Weather Research and Forecasting—Chemistry model and Grid-point Statistical Interpolation, a three-dimensional variational assimilation tool. The modelling domain covers the northeastern region of North America. The measurements come from the United States Environmental Protection Agency AIRNow network and are available hourly. Background error covariance statistics are derived from forecasts in July 2004. Comparison of forecasts issued in August and September 2006 and initialized with and without the assimilation follows. Results show that forecasts of ozone and fine aerosol concentrations benefit from the assimilation in terms of standard verification scores for a period of at least 24 hours. However, significant reduction of errors as a consequence of the assimilation is accompanied by fast model error growth in the early forecast hours. Published in 2010 by John Wiley & Sons, Ltd.

Article / Publication Data
Available Metadata
Accepted On
September 09, 2010
Fiscal Year
Publication Name
Quarterly Journal of The Royal Meteorological Society
Published On
October 01, 2010
Final Online Publication On
December 01, 2010
Print Volume
Print Number
Page Range
2013 - 2024
Submitted On
November 16, 2009

This publication was presented at the following:

12th Conference on Atmospheric Chemistry


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Authors who have authored or contributed to this publication.