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15 September 1993 Validation of infrared cloud detection algorithms developed for TACNEPH
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A multi-year research and development program is underway to develop an automated cloud model known as TACNEPH for use by the Air Force at tactical sites. Significant features of this model include the ability to analyze real-time DMSP/OLS and NOAA/AVHRR data using only the limited resources of transportable tactical ground stations and to automatically adapt to changes in the available data mix. No supporting data from a center are available (e.g., upper air temperature and moisture fields, surface reports). To satisfy these requirements it was necessary to develop separate algorithms for each sensor platform. An infrared algorithm developed for DMSP data relies on an estimate of the clear scene radiative brightness temperature based on a dynamic correction to a surface temperature climatology. A separate NOAA IR algorithm is an adaptation of the multispectral approach of Saunders and Kriebel. Both algorithms are designed to improve cloud detection capabilities over the current Air Force operational RTNEPH model, with particular emphasis on low cloud. A major aspect of the TACNEPH development program is the validation of the cloud algorithms over globally varying conditions. Since there is no universally accepted source of ground truth data for cloud, it was necessary to develop a validation procedure based on available data sources. Algorithm validation is based on subjective man/computer analysis of the input satellite sensor data using any available additional data sources as guidance.
© (1993) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Gary B. Gustafson, Ronald G. Isaacs, Jeanne M. Sparrow, James T. Bunting, and Robert P. d'Entremont "Validation of infrared cloud detection algorithms developed for TACNEPH", Proc. SPIE 1934, Passive Infrared Remote Sensing of Clouds and the Atmosphere, (15 September 1993);

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