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Non-stationary Markov chains for modelling daily sunshine at São Paulo, Brazil

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Summary

Non-stationary, four-state Markov chains were used to model the sunshine daily ratios at São Paulo, Brazil. Fourier series were used to account for the periodic seasonal variations in the transition probabilities. All the regressions and tests, based on Generalized Linear Models, were made through the software GLIM. Significant seasonal variations were detected in the conditional probabilities, especially for the extreme categories of overcast and clear days. The fitted model provided a concise summary of the daily data, useful for short-range (1 day) sunshine predictions and simulations.

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Authors and Affiliations

  1. Meteorology Science Department, INPE, S. J. Campos, São Paulo, Brazil

    C. A. Sansigolo

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  1. C. A. Sansigolo
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Sansigolo, C.A. Non-stationary Markov chains for modelling daily sunshine at São Paulo, Brazil. Theor Appl Climatol 56, 225–230 (1997). https://doi.org/10.1007/BF00866429

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  • DOI: https://doi.org/10.1007/BF00866429

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