Abstract
In this paper, we present a formalized approach to statistical modeling of the sunshine number, binary indicator of whether the Sun is covered by clouds introduced previously by Badescu (Theor Appl Climatol 72:127–136, 2002). Our statistical approach is based on Markov chain and logistic regression and yields fully specified probability models that are relatively easily identified (and their unknown parameters estimated) from a set of empirical data (observed sunshine number and sunshine stability number series). We discuss general structure of the model and its advantages, demonstrate its performance on real data and compare its results to classical ARIMA approach as to a competitor. Since the model parameters have clear interpretation, we also illustrate how, e.g., their inter-seasonal stability can be tested. We conclude with an outlook to future developments oriented to construction of models allowing for practically desirable smooth transition between data observed with different frequencies and with a short discussion of technical problems that such a goal brings.
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Acknowledgments
The authors thank the reviewers for useful comments and suggestions. This work was supported in part by a grant of the Romanian National Authority for Scientific Research, CNCS-UEFISCDI, project number PN-II-ID-PCE-2011-3-0089, by the European Cooperation in Science and Technology project COST ES1002, by the Grant LD12009 (Ministry of Education, Young and Sports of the Czech Republic) and by the (Czech) Institutional Research Plan AV0Z10300504 “Computer Science for the Information Society: Models, Algorithms, Applications”.
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Brabec, M., Badescu, V. & Paulescu, M. Nowcasting sunshine number using logistic modeling. Meteorol Atmos Phys 120, 61–71 (2013). https://doi.org/10.1007/s00703-013-0240-1
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DOI: https://doi.org/10.1007/s00703-013-0240-1