The cloud vertical distribution and especially the cloud base height, which is linked to cloud type, is an important characteristic in order to describe the impact of clouds in a changing climate. In this work several methods to estimate the cloud vertical structure (CVS) based on atmospheric sounding profiles are compared, considering number and position of cloud layers, with a ground based system which is taken as a reference: the Active Remote Sensing of Clouds (ARSCL). All methods establish some conditions on the relative humidity, and differ on the use of other variables, the thresholds applied, or the vertical resolution of the profile. In this study these methods are applied to 125 radiosonde profiles acquired at the ARM Southern Great Plains site during all seasons of year 2009 and endorsed by GOES images, to confirm that the cloudiness conditions are homogeneous enough across their trajectory. The overall agreement for the methods ranges between 44–88%; four methods produce total agreements around 85%. Further tests and improvements are applied on one of these methods. In addition, we attempt to make this method suitable for low resolution vertical profiles, which could be useful in atmospheric modeling. The total agreement, even when using low resolution profiles, can be improved up to 91% 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