Abstract
In order to account for the day-to-day variation in the solair temperature data, the coefficients in its Fourier series representation have been assumed to be time dependent. The variation in the numerical values of the coefficient being random, they have been modelled as a stochastic process. Explicit expressions for the mean and for the autocorrelation function of the ground temperature distribution have been obtained assuming the stochastic processes to be: (i) white noise (delta correlated) and (ii) Markov (exponentially correlated). Whilst the expression for the mean ground temperature distribution is found to be identical with that obtained by a periodic theory, the variance is found to decrease rapidly with depth.
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