Probability Distribution for the Visually Observed Fractional Cloud Cover over the Ocean

Author:

Aleksandrova Marina1,Gulev Sergey K.2,Belyaev Konstantin3

Affiliation:

1. Shirshov Institute of Oceanology, Moscow, Russia

2. Shirshov Institute of Oceanology, and Moscow State University, Moscow, Russia

3. Shirshov Institute of Oceanology, Moscow, Russia, and Department of Mathematics, Federal University of Bahia, Salvador, Brazil

Abstract

Abstract The authors suggest a three-parameter bounded distribution from the family of mixed gamma distributions for characterizing the probability density distributions of fractional total and low cloud cover over the global oceans. The authors derive both the continuous form of this distribution and its discrete counterpart, which can be directly applied to cloud cover reports. The distribution is applied to the cloud cover characteristics reported by voluntary observing ships (VOS) for the period from 1950 to 2011 after filtering nighttime observations with poor lunar illumination. The suggested distribution demonstrates a high goodness of fit to the data and good skill in capturing probability distributions with different shapes. The authors present seasonal climatologies of the parameters of the derived distribution for the chosen 60-yr period and demonstrate that applying the PDF-based concept to the analysis of cloud cover allows identification of areas where similar mean cloud amounts can be produced by probability distributions with very different shapes. The roles of the different parameters of the distribution in producing the observed cloud conditions in different regions of the World Ocean are discussed. The application of the derived probability distribution allows for accurate estimation of the percentiles of the distribution, which represent the probabilities of specific cloud conditions. These probabilities are presented for both total and low cloud cover, as well as for daytime and nighttime. The authors also discuss the applicability of the suggested distribution for the validation of different cloud cover data products over the globe and the prospects of additional applications.

Funder

Russian Science Foundation

Publisher

American Meteorological Society

Subject

Atmospheric Science

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