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- W2561231053 abstract "This paper analyzes temperature data obtained from 96 world wide weather stations, as well as reconstructed data from the last two millennia. Our model is derived from three invariance hypotheses. The first one is that the temperature process is stationary. The second one is that the distribution of the average temperature over any specific time period does not depend on the length of the period apart from a scale transformation. The third one is that the temperature process is Gaussian. These hypotheses imply that the temperature process is a so-called Fractional Gaussian noise process. This type of processes exhibits long range dependence. In order to test our hypotheses we have applied a graphical test based on the empirical characteristic function and a Chi-square test. The tests indicate that the most of the observed data are consistent with the Fractional Gaussian noise model as a representation of the temperature process. The tests also imply that the reconstructed data are consistent with Fractional Gaussian noise model." @default.
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- W2561231053 date "2020-03-20" @default.
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- W2561231053 title "How does temperature vary over time?: evidence on the stationary and fractal nature of temperature fluctuations" @default.
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- W2561231053 doi "https://doi.org/10.1111/rssa.12557" @default.
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