11th Conference on Satellite Meteorology and Oceanography

P1.28

Study of fog properties using LANDSAT data

Kenneth W. Fischer, Terabeam Labs., Redmond, WA; and M. Nunez, J. Ramaprasad, M. R. Witiw, and J. A. Baars

Recently, advances have been made in the analysis of fog and low clouds using satellite imagery. For example, NOAA/NESDIS has developed several experimental products derived from GOES infrared channels that describe low clouds and fog, giving the bases of low clouds as well as the thickness of the low cloud and fog layers. In our research, LANDSAT imagery is used. LANDSAT Thematic Mapper ™ images over the cities of Seattle and Chicago are analyzed to provide information on typical fog spatial structure and scale, and homogeneity and variability of liquid water content over the region of fog. Fog optical depths and visibility are mapped in the urban areas and then correlated with concurrent measurements taken in the nearby airports- Boeing Field International (BFI) near Seattle and Meigs Field near Chicago. Radiative transfer calculations using MODTRAN have been developed to estimate top of atmosphere spectral reflectances as a function of total liquid water in a vertical path, and mean droplet radii. Using these calculations, the reflectances in the visible and near infrared channels of the LANDSAT images are used to derive liquid water content and radii. The liquid water content can be correlated with visibilities observed in the airports to formulate a relationship between the two parameters. Since we know one of the important variables in defining fog is the liquid water content, its relationship to visibility is a useful one to understand. We hope to apply the techniques to interpret the readily available daily GOES images to give us an ongoing database of visibility in middle and high cloud free areas.

extended abstract  Extended Abstract (276K)

Poster Session 1, Environmental Applications
Monday, 15 October 2001, 9:45 AM-11:15 AM

Previous paper  Next paper

Browse or search entire meeting

AMS Home Page