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Comparing the cloud vertical structure derived from several methods based on radiosonde profiles and ground-based remote sensing measurements
Costa Surós, Montse; Calbó Angrill, Josep; González Gutiérrez, Josep Abel; Long, Charles N.
Ministerio de Ciencia e Innovación (Espanya)
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
This research was funded by the Ministerio de Ciencia e Innovacion of the Spanish Government through grants CGL2007-62664 (NUCLIEREX) and CGL2010-18546 (NUCLIERSOL). M. Costa-Suros was supported by research fellowship FPI BES-2008-003129 from the Ministerio de Ciencia e Innovacion of the Spanish Government. C. N. Long acknowledges support from the Office of Science of the US Department of Energy as part of the Atmospheric Systems Research (ASR) program. Data and TSI animations were obtained from the Atmospheric Radiation Measurement (ARM) program sponsored by the US Department of Energy. We thank L. Dimitrieva-Arrago for her explanations and interesting discussions while visiting the University of Girona in the framework of the UE CLIMSEAS project (FP7-PEOPLE-2009-IRSES proposal no. 247512). We also thank the National Oceanic and Atmospheric Administration (NOAA) Comprehensive Large Array-data stewardship system (CLASS) for providing GOES images for research use
Núvols
Clouds
Attribution 3.0 Spain
http://creativecommons.org/licenses/by/3.0/es/
Artículo
info:eu-repo/semantics/publishedVersion
European Geosciences Union (EGU)
         

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