Abstract
Seasonal autoregression and integrated moving average models are employed to represent the contemporary variability of several meteorological time series. In all, global/monthly records of 16 different variables, produced and archived by Nimbus 7 Radiation Budget and Cloud Data Processing teams, International Satellite Cloud Climatology Project (ISCCP), and TIROS-N Microwave Sounding Unit channel 2 measurements are analysed. Two different types of model have been applied depending on the variability of initial series: an autoregression one with explicitly involved annual cycle and a simple first order moving average model for monthly increments.
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© 1996 Springer-Verlag Berlin Heidelberg
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Kärner, O. (1996). Stochastic Models toRepresent the Temporal Variability of Global Average Radiation Budget, Cloudiness and Temperature. In: Treut, H.L. (eds) Climate Sensitivity to Radiative Perturbations. NATO ASI Series, vol 34. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-61053-0_7
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DOI: https://doi.org/10.1007/978-3-642-61053-0_7
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