Abstract

Investigations have been conducted at the Center for Space Research (CSR) into approaches to correlate MODIS aerosol optical thickness (AOT) values with ground-based, PM 2.5 observations made at continuous air monitoring station locations operated by the Texas Commission on Environmental Quality (TCEQ). These correlations are needed to more fully utilize real-time MODIS AOT analyses generated at CSR in operational air quality forecasts issued by TCEQ using a trajectory-based forecast model developed by NASA. Initial analyses of two data sets collected during 3 months in 2003 and all of 2004 showed linear correlations in the 0.4–0.5 range in the data collected over Texas. Stronger correlations (exceeding 0.9) were obtained by averaging these same data over longer timescales but this approach is considered unsuitable for use in issuing air quality forecasts. Peculiarities in the MODIS AOT analyses, referred to as hot spots, were recognized while attempting to improve these correlations. It is demonstrated that hot spots are possible when pixels that contain surface water are not detected and removed from the AOT retrieval algorithms. An approach to reduce the frequency of hot spots in AOT analyses over Texas is demonstrated by tuning thresholds used to detect inland water surfaces and remove pixels that contain them from the analysis. Finally, the potential impact of hot spots on MODIS AOT-PM 2.5 correlations is examined through the analysis of a third data set that contained sufficient levels of aerosols to mask inland water surfaces from the AOT algorithms. In this case, significantly stronger correlations, that exceed the 0.9 value considered suitable for use in a real-time air quality prediction system, were observed between the MODIS AOT observations and ground-based PM 2.5 measurements.

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