A Tracer of Opportunity Dataset for Atmospheric Transport and Dispersion Model Evaluation

The development of atmospheric transport and dispersion models (ATDM’s) has been hampered by the lack of field experiment data which can be used to evaluate model developments. Current model evaluation tends to be limited to comparison of model results with measurements obtained during tracer experiments, which are very limited in number, and in temporal and geographical coverage. These limited data sets struggle to provide sufficient statistical significance to definitively assess the model’s skills and evolutionary improvement. Here we describe the use of a large existing set of emissions and ambient concentration measurements to provide a data set for the evaluation of the HYSPLIT model which is used operationally at the National Oceanic and Atmospheric Administration (NOAA). SO₂ emissions from U.S. power plants using continuous emissions monitoring systems (CEMS) are available from 1995 through the present. Contemporaneous measurements of air concentrations of SO₂ at ground stations are also available. The time resolution of the emissions and ambient measurement data is at least hourly and the data includes many thousands of quantified “plume hits” from known emissions sources at measurement sites. The temporal and spatial scales are relevant for ATDM applications such as response to a chemical release such as occurs during a refinery fire, or the development of top-down emission estimates of greenhouse gases. We describe how this data can be processed so it is suitable for evaluating an ATDM model, suggest a set of statistical parameters to use for evaluation, and present some initial results using this approach to evaluate the HYSPLIT model.