Cloud classification using whole-sky imager data

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Clouds are one of the most important moderators of the earth radiation budget and one of the least understood. The effect that clouds have on the reflection and absorption of solar and terrestrial radiation is strongly influenced by their shape, size, and composition. Physically accurate parameterization of clouds is necessary for any general circulation model (GCM) to yield meaningful results. The work presented here is part of a larger project that is aimed at producing realistic three-dimensional (3D) volume renderings of cloud scenes, thereby providing the important shape information for parameterizing GCMs. The specific goal of the current study is ... continued below

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7 p.

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Buch, K.A. Jr. & Sun, Chen-Hui February 1, 1995.

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This article is part of the collection entitled: Office of Scientific & Technical Information Technical Reports and was provided by UNT Libraries Government Documents Department to Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 34 times , with 4 in the last month . More information about this article can be viewed below.

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  • Sandia National Laboratories
    Publisher Info: Sandia National Labs., Albuquerque, NM (United States)
    Place of Publication: Albuquerque, New Mexico

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Description

Clouds are one of the most important moderators of the earth radiation budget and one of the least understood. The effect that clouds have on the reflection and absorption of solar and terrestrial radiation is strongly influenced by their shape, size, and composition. Physically accurate parameterization of clouds is necessary for any general circulation model (GCM) to yield meaningful results. The work presented here is part of a larger project that is aimed at producing realistic three-dimensional (3D) volume renderings of cloud scenes, thereby providing the important shape information for parameterizing GCMs. The specific goal of the current study is to develop an algorithm that automatically classifies (by cloud type) the clouds observed in the scene. This information will assist the volume rendering program in determining the shape of the cloud. Much work has been done on cloud classification using multispectral satellite images. Most of these references use some kind of texture measure to distinguish the different cloud types and some also use topological features (such as cloud/sky connectivity or total number of clouds). A wide variety of classification methods has been used, including neural networks, various types of clustering, and thresholding. The work presented here utilizes binary decision trees to distinguish the different cloud types based on cloud feature vectors.

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7 p.

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OSTI as DE95006501

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  • 9. symposium on meteorological observations and instrumentation, Charlotte, NC (United States), 27-31 Mar 1995

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  • Other: DE95006501
  • Report No.: SAND--95-8475C
  • Report No.: CONF-9503104--1
  • Grant Number: AC04-94AL85000
  • Office of Scientific & Technical Information Report Number: 32562
  • Archival Resource Key: ark:/67531/metadc686819

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Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

Office of Scientific and Technical Information (OSTI) is the Department of Energy (DOE) office that collects, preserves, and disseminates DOE-sponsored research and development (R&D) results that are the outcomes of R&D projects or other funded activities at DOE labs and facilities nationwide and grantees at universities and other institutions.

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  • February 1, 1995

Added to The UNT Digital Library

  • July 25, 2015, 2:20 a.m.

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  • April 13, 2016, 1:07 p.m.

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Buch, K.A. Jr. & Sun, Chen-Hui. Cloud classification using whole-sky imager data, article, February 1, 1995; Albuquerque, New Mexico. (digital.library.unt.edu/ark:/67531/metadc686819/: accessed November 19, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.