Retrieving cloud characteristics from ground-based daytime color all-sky images

Article


Long, C. N., Sabburg, J. M., Calbo, J. and Pages, D.. 2006. "Retrieving cloud characteristics from ground-based daytime color all-sky images." Journal of Atmospheric and Oceanic Technology. 23 (5), pp. 633-652. https://doi.org/10.1175/JTECH1875.1
Article Title

Retrieving cloud characteristics from ground-based daytime color all-sky images

ERA Journal ID1920
Article CategoryArticle
AuthorsLong, C. N. (Author), Sabburg, J. M. (Author), Calbo, J. (Author) and Pages, D. (Author)
Journal TitleJournal of Atmospheric and Oceanic Technology
Journal Citation23 (5), pp. 633-652
Number of Pages20
Year2006
Place of PublicationBoston, MA. USA
ISSN0739-0572
1520-0426
Digital Object Identifier (DOI)https://doi.org/10.1175/JTECH1875.1
Web Address (URL)http://journals.ametsoc.org/doi/abs/10.1175/JTECH1875.1
Abstract

A discussion is presented of daytime sky imaging and techniques that may be applied to the analysis of full-color sky images to infer cloud macrophysical properties. Descriptions of two different types of sky-imaging systems developed by the authors are presented, one of which has been developed into a commercially available instrument. Retrievals of fractional sky cover from automated processing methods are compared to human retrievals, both from direct observations and visual analyses of sky images. Although some uncertainty exists in fractional sky cover retrievals from sky images, this uncertainty is no greater than that attached to human observations for the commercially available sky-imager retrievals. Thus, the application of automatic digital image processing techniques on sky images is a useful method to complement, or even replace, traditional human observations of sky cover and, potentially, cloud type. Additionally, the possibilities for inferring other cloud

Keywordsirradiance; skies; surface; simulations
ANZSRC Field of Research 2020370199. Atmospheric sciences not elsewhere classified
519999. Other physical sciences not elsewhere classified
370107. Cloud physics
Byline AffiliationsPacific Northwest National Laboratory, United States
Department of Biological and Physical Sciences
University of Girona, Spain
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