Extended Abstract (2.1M)P4.26
Improved thin cirrus and terminator cloud detection in CERES cloud mask
Qing Trepte, SAIC, Hampton, VA; and P. Minnis, R. Palikonda, and D. A. Spangenberg
Thin cirrus clouds compose about 20-30% of the total cloud coverage and affect the global radiation budget by increasing the Earth's albedo and reducing infrared emissions. Thin cirrus clouds, however, are often underestimated by traditional satellite cloud detection algorithms. This difficulty is cause by the lack of spectral contrast between optically thin cirrus and the surface in techniques that use visible (0.65 µm) and infrared (11 µm) channels.
In the CERES Aqua Edition 1 Cloud Mask, thin cirrus detection is significantly improved, both over land and over ocean, using a technique that combines MODIS high-resolution measurements from the 1.38 and 11 µm channels and brightness temperature differences (BTDs) of 11-12, 8.5-11, and 3.7-11 µm channels. To account for humidity and view angle dependencies, empirical relationships were derived with observations from the 1.38 µm refelectance and BTDs of 11-12 and 8.5-11 µm channels using 70 granules of MODIS data in 2002 and 2003. Cloud mask results over land, desert and ocean will be presented in this paper.
Another challenge in global cloud detection algorithms occurs near the day/night terminator where information from the visible 0.65 µm channel and the estimated solar component of 3.7 µm channel becomes less reliable. An improved twilight cloud algorithm utilizes multi-spectral MODIS data: visible 0.65 and 1.6 µm (2.1 µm for Aqua) reflectances, 11 µm brightness temepratures, and BTDs of 3.7-11, 6.7-11 µm to differentiate between clouds and snow surfaces. The global cloud fraction using this improved technique shows a smoother transition from the midlatitudes into polar regions. Results are presented and initial validation efforts are reported using surface observations and analyses of Meteosat-8 data using abridged versions of the new techniques.
Poster Session 4, Radiation Poster Session IV: Remote Sensing
Wednesday, 12 July 2006, 5:00 PM-7:00 PM, Grand Terrace
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