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A new perspective on the sunshine duration variability

  • Marek Brabec
  • Alexandru Dumitrescu
  • Marius PaulescuEmail author
  • Viorel Badescu
Original Paper
  • 22 Downloads

Abstract

The sunshine duration data is analysed here from a new perspective, different from the traditional ones. The study is focused on pairs of periods of shining sun (called clear periods) followed by periods with the sun covered by clouds (called dark periods). Their statistical and sequential properties are illustrated by using results obtained from satellite observations and ground measurements at Timisoara (Romania). Solar irradiance time series measured at ground are converted into a database consisting of pairs of clear/dark periods. These pairs are associated with three cloud classes derived from satellite observations: C1 (the sky is cloud-free), C2 (cloudy sky) and C3 (sky with semi-transparent or fractional clouds). The study was conducted by using tools from survival analysis. This is a novelty in sunshine duration analysis. Since information is missing during the night, the clear/dark period correlation was studied considering a censoring procedure (for all nine combinations of cloud types at the beginning of dark and clear intervals). Cox regression has been used to study the influence of covariates (such as extraterrestrial solar irradiance and sun elevation angle) on sunshine duration distribution. Results show that increase of extraterrestrial solar radiation tends to increase the risk of stopping any clear or dark interval, i.e. it tends to increase the variability in solar irradiance. Regardless of cloud class, stochastically shorter intervals are found for increasing sun elevation angle.

Notes

Funding information

This work was partially supported by a grant of the Romanian National Authority for Scientific Research and Innovation, CCCDI-UEFISCDI, project number COFUND-SUSCROP-SUSCAP-2, within PNCDI III.

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Copyright information

© Springer-Verlag GmbH Austria, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Statistical ModelingInstitute of Computer Science of the Czech Academy of SciencesPrague 8Czech Republic
  2. 2.Department of Climatology, National Meteorological Administration (Meteo Romania)BucharestRomania
  3. 3.Physics DepartmentWest University of TimisoaraTimisoaraRomania
  4. 4.Candida Oancea InstitutePolytechnic University of BucharestBucharestRomania
  5. 5.Romanian AcademyBucharestRomania

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