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Proceedings Paper

Thin cirrus cloud detection: a preliminary study
Author(s): Maria Paz Ramos-Johnson; R. Gary Rasmussen
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Paper Abstract

Coincident lidar and satellite observations of thin and subvisual cirrus were collected to determine the probability of cirrus detection as a function of optical depth for several satellite systems. Satellite observations include those from DMSP (smooth), NOAA Polar Orbiter (GAC), GOES, GOES VAS and NOAA HIRS processed with the CO2 slicing algorithm, and the RTNEPH. Different cirrus cloud detection techniques, namely, those of the RTNEPH, manual detection, Phillips Laboratory's (PL) multispectral image analysis scheme, and the CO2 slicing algorithm were applied to the lidar-coincident satellite data. Each satellite image was examined for evidence of cirrus clouds at the lidar location. The binary (yes/no) results were then used in a nonlinear regression technique to determine the probability of detection as a function of optical depth. The results show that the VAS and HIRS data processed with the CO2 slicing algorithm detected thin cirrus most of the time with probability of detection (POD) of 91% and 75%, respectively.

Paper Details

Date Published: 15 September 1993
PDF: 7 pages
Proc. SPIE 1934, Passive Infrared Remote Sensing of Clouds and the Atmosphere, (15 September 1993); doi: 10.1117/12.154930
Show Author Affiliations
Maria Paz Ramos-Johnson, The Analytic Sciences Corp. (United States)
R. Gary Rasmussen, The Analytic Sciences Corp. (United States)


Published in SPIE Proceedings Vol. 1934:
Passive Infrared Remote Sensing of Clouds and the Atmosphere
David K. Lynch, Editor(s)

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