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Changepoint analysis of Klementinum temperature series

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  • D. Jarušková
  • J. Antoch

Abstract

This paper presents a statistical analysis of the stationarity of the Prague–Klementinum temperature series. In the first part, the stationarity of annual means is rejected, and several nonstationary models are suggested to assess the increase in temperature in the most recent decades. The analysis shows that positions of the changepoint estimates depend largely on our decision as to whether we apply a discontinuous or a continuous piecewise linear model. In the second part, we study the stationarity of the seasonal behavior of the series, particularly the stationarity of the mean annual profiles. The analysis of the seasonal cycle shows that the increase in temperature has not the same character throughout the calendar year. Rather, an increase in temperature in winter days is larger than an increase in summer days, and the temperature difference between summer and winter days decreases.

Suggested Citation

  • D. Jarušková & J. Antoch, 2020. "Changepoint analysis of Klementinum temperature series," Environmetrics, John Wiley & Sons, Ltd., vol. 31(1), February.
    • Handle: RePEc:wly:envmet:v:31:y:2020:i:1:n:e2570
    DOI: 10.1002/env.2570
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    Cited by:

    1. Trevor Harris & Bo Li & J. Derek Tucker, 2022. "Scalable multiple changepoint detection for functional data sequences," Environmetrics, John Wiley & Sons, Ltd., vol. 33(2), March.
    2. Magda Monteiro & Marco Costa, 2023. "Change Point Detection by State Space Modeling of Long-Term Air Temperature Series in Europe," Stats, MDPI, vol. 6(1), pages 1-18, January.
    3. C. Berrett & B. Gurney & D. Arthur & T. Moon & G. P. Williams, 2023. "A Bayesian change point modeling approach to identify local temperature changes related to urbanization," Environmetrics, John Wiley & Sons, Ltd., vol. 34(3), May.

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