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Effects of satellite data resolution on measuring the space/time variations of surfaces and cloudsThe correlated distributions of satellite-measured visible and infrared radiances, caused by spatial and temporal variations in clouds and surfaces, have been found to be characteristic of the major climate regimes and can be described by the attributes of bidimensional and monodimensional histograms and time-composite images. Most of the variability of both the surfaces and clouds is found to occur at scales larger than the minimum resolved by satellite imagery. Since satellite imaging data sets are difficult to analyze because of their large volumes, many studies reduce the volume by various sampling or averaging schemes. The effects of data resolution and sampling on the radiance histogram statistics and on the time-composite image characteristics are examined. In particular, the sampling strategy used by the International Satellite Cloud Climatology Project is tested. This sampling strategy is found to preserve the statistics of smaller cloud variations for most regions, with the exception of very rare events, if they are accumulated over large enough areas (at least 500 km in dimension) and long enough time periods (at least one month).
Document ID
19910053637
Acquisition Source
Legacy CDMS
Document Type
Reprint (Version printed in journal)
Authors
Seze, Genevieve
(CNRS Laboratoire de Meteorologie Dynamique, Palaiseau, France)
Rossow, William B.
(NASA Goddard Institute for Space Studies New York, United States)
Date Acquired
August 15, 2013
Publication Date
May 1, 1991
Publication Information
Publication: International Journal of Remote Sensing
Volume: 12
ISSN: 0143-1161
Subject Category
Meteorology And Climatology
Accession Number
91A38260
Distribution Limits
Public
Copyright
Other

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