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Task 138

Comparison of Air Quality Models with Satellite Observations for Improved Model Predictive Capabilities

Principal Investigator(s):

C. Flynn


K. Pickering

Last Updated:

October 26, 2012 15:25:37

Description of Problem

Satellite observations provide several important benefits to air quality, including improved forecasting ability for air quality models, assessment of air quality for attribution to specific sources, and improved estimation of source emissions. However, many challenging problems remain for the use of satellite observations in diagnosing near-surface air pollution. The column-integrated quantities retrieved from satellite instruments for key trace gases and aerosols must be interpreted correctly to derive information about near-surface conditions. Despite these challenges, a major scientific goal remains the use of satellite observations to improve and validate current air quality models for more accurate predictive capability. The DISCOVER-AQ field project will provide surface, in-situ aircraft, and remote sensing data which will aid in the interpretation of satellite data for air quality. This project will be conducted in support of this overall goal, by comparing satellite observations, aircraft measurements, and surface air quality datasets with air quality model output. Such a comparison may lead to better understanding of the factors affecting the correlation of satellite observations with current models.

Scientific Objectives and Approach

Model output from the Community Multiscale Air Quality (CMAQ) model, data from the Ozone Monitoring Instrument (OMI) onboard NASA’s Aura satellite, and the DISCOVER-AQ datasets will be used in the analysis. This will allow a comparison to be made between the CMAQ model and OMI data. The correlation between the model output and satellite observations will then be analyzed in conjunction with the data from the DISCOVER-AQ field experiment.


As a preliminary step, analysis of the diurnal cycle of ozone was performed for six air quality-monitoring sites throughout Maryland from ground-based data. Hourly averages were calculated for each hour of the day for the month of July, when air pollution is high, for the years 2008, 2009, and 2010. Figure 1 displays these hourly averages as a function of local time of day for all six sites. Inspection of the diurnal cycles reveals that the daily maxima and minima of ozone occur at very similar times at all six sites. These plots give an indication of the behavior of ozone at the surface before analysis of model output and satellite observations is performed.

Task Figures

Fig. 1 – Diurnal cycles for ozone for six Maryland sites for July. Monthly mean ozone concentration in ppbv is plotted against local hour of the day. Purple diamonds are 2008 means, orange triangles are 2009 means, and green squares are 2010 means.
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