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| Titel |
Comparing the cloud vertical structure derived from several methods based on radiosonde profiles and ground-based remote sensing measurements |
| VerfasserIn |
M. Costa-Surós, J. Calbó, J. A. González, C. N. Long |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1867-1381
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Measurement Techniques ; 7, no. 8 ; Nr. 7, no. 8 (2014-08-27), S.2757-2773 |
| Datensatznummer |
250115886
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| Publikation (Nr.) |
 copernicus.org/amt-7-2757-2014.pdf |
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| Zusammenfassung |
| The
cloud vertical distribution and especially the cloud base height, which is
linked to cloud type, are important characteristics in order to describe the
impact of clouds on climate. In this work, several methods for estimating the
cloud vertical structure (CVS) based on atmospheric sounding profiles are
compared, considering the number and position of cloud layers, with a
ground-based system that is taken as a reference: the Active Remote Sensing
of Clouds (ARSCL). All methods establish some conditions on the relative
humidity, and differ in the use of other variables, the thresholds applied,
or the vertical resolution of the profile. In this study, these methods are
applied to 193 radiosonde profiles acquired at the Atmospheric Radiation Measurement (ARM) Southern Great Plains
site during all seasons of the year 2009 and endorsed by Geostationary Operational Environmental Satellite (GOES) images, to
confirm that the cloudiness conditions are homogeneous enough across their
trajectory. The perfect agreement (i.e., when the whole CVS is estimated
correctly) for the methods ranges between 26 and 64%; the methods show
additional approximate agreement (i.e., when at least one cloud layer is
assessed correctly) from 15 to 41%. Further tests and improvements are
applied to one of these methods. In addition, we attempt to make this method
suitable for low-resolution vertical profiles, like those from the outputs of
reanalysis methods or from the World Meteorological Organization's (WMO) Global Telecommunication System. The
perfect agreement, even when using low-resolution profiles, can be improved
by up to 67% (plus 25% of the approximate agreement) if the thresholds
for a moist layer to become a cloud layer are modified to minimize false
negatives with the current data set, thus improving overall agreement. |
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