Cloud Optical Depth Retrieval
Cloud Optical Depth Retrieval is a methodological framework in atmospheric remote sensing that belongs to the class of cloud property inference techniques, distinguished by its specific aim of quantitatively estimating the cloud optical depth from satellite or ground-based radiometric measurements through inversion of radiative transfer models.
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Publications
25.8K
Citations
1.3K
Authors
380
Institutions
Publications per year
2017–2026
85
Parents
441
Cloud Detection with MODIS. Part II: Validation
Steven A. Ackerman, Robert E. Holz, R. Frey et al. · Journal of Atmospheric and Oceanic Technology · 2008 · 465 citations · Full text
David Painemal, Paquita Zuidema · Journal of Geophysical Research Atmospheres · 2011 · 339 citations · Full text
Eight Years of High Cloud Statistics Using HIRS
Donald P. Wylie, W. Paul Menzel · Journal of Climate · 1999 · 330 citations
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Goddard Space Flight Center
Greenbelt, United States
44 h-index
168 publications
13.8K citations

Langley Research Center
Hampton, United States
40 h-index
155 publications
11.6K citations
University of Wisconsin–Madison
Madison, United States
28 h-index
64 publications
7.1K citations
Science Systems and Applications (United States)
Lanham, United States
27 h-index
120 publications
10.3K citations
University of Maryland, Baltimore County
Baltimore, United States
26 h-index
41 publications
2.6K citations
Jet Propulsion Laboratory
Pasadena, United States
20 h-index
65 publications
3.3K citations
Texas A&M University
College Station, United States
18 h-index
38 publications
2.2K citations

Centre National de la Recherche Scientifique
Paris, France
18 h-index
73 publications
3.4K citations
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JGR · 75 publications · 5.1K citations
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48 publications · 2K citations
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32 publications · 3.5K citations
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JGR · 34 publications · 1.6K citations
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31 publications · 1.6K citations
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