Cloud Properties from ISCCP and PATMOS-x Corrected for Spurious Variability Related to Changes in Satellite Orbits, Instrument Calibrations, and Other Factors
d741005
A post hoc empirical correction procedure has been applied to grid box anomalies in total cloud amount from the International Satellite Cloud Climatology Project (ISCCP) dataset and the Pathfinder Atmospheres - Extended (PATMOS-x) dataset to remove spurious variability related to changes in satellite orbit, instrument calibration, and other factors. The corrected satellite cloud datasets are useful for investigation of regional cloud changes but can not be used for studies of globally averaged cloud change because the methods employed remove any real cloud variability occurring on global scales together with spurious variability. Also note that the correction procedure does not remove spatial biases in climatological mean cloud properties. The available corrected data include monthly anomalies in total cloud amount on a 2.5 degree by 2.5 degree grid for the time period 1983-2009 (the first six months of 1983 are not available for ISCCP). No data are available poleward of 60 degree latitude due to difficulty in accurately retrieving cloud properties over cold, bright surfaces.
dataset
https://rda.ucar.edu/datasets/d741005/
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climatologyMeteorologyAtmosphere
dataset
revision
2014-10-16
SATELLITES > SATELLITES
revision
2024-07-23
EARTH SCIENCE > ATMOSPHERE > CLOUDS > CLOUD PROPERTIES > CLOUD FREQUENCY
revision
2024-07-24
-180
180
90
-90
1983-01-15T12:00:00Z
2009-12-15T12:00:00Z
publication
2015-02-02
notPlanned
Creative Commons Attribution 4.0 International License
None
UCAR/NCAR - Research Data Archive
National Center for Atmospheric Research
CISL/DECS
P.O. Box 3000
Boulder
80307
U.S.A.
(303)-497-1833
303-497-1291
pointOfContact
NCAR Research Data Archive
National Center for Atmospheric Research
CISL/DECS
P.O. Box 3000
Boulder
80307
U.S.A.
303-497-1291
name: NCAR Research Data Archive
description: The Research Data Archive (RDA), managed by the Data Engineering and Curation Section (DECS) of the Computational and Information Systems Laboratory (CISL) at NCAR, contains a large and diverse collection of meteorological and oceanographic observations, operational and reanalysis model outputs, and remote sensing datasets to support atmospheric and geosciences research, along with ancillary datasets, such as topography/bathymetry, vegetation, and land use.
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2024-08-04T02:11:40Z