Thin cirrus cloud detection: a preliminary study

Maria Paz Ramos-Johnson; R. Gary Rasmussen

doi:10.1117/12.154930

15 September 1993 Thin cirrus cloud detection: a preliminary study

Maria Paz Ramos-Johnson, R. Gary Rasmussen

Author Affiliations +

Proceedings Volume 1934, Passive Infrared Remote Sensing of Clouds and the Atmosphere; (1993) https://doi.org/10.1117/12.154930
Event: Optical Engineering and Photonics in Aerospace Sensing, 1993, Orlando, FL, United States

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.

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Maria Paz Ramos-Johnson and R. Gary Rasmussen "Thin cirrus cloud detection: a preliminary study", Proc. SPIE 1934, Passive Infrared Remote Sensing of Clouds and the Atmosphere, (15 September 1993); https://doi.org/10.1117/12.154930

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