Modelling and forecasting temperature and precipitation in Italy

Mario Lefebvre

Abstract


We study the monthly average temperature in Italy for the period 1991-2015. The increase or decrease of the average temperature with respect to the previous year is modelled as a discrete-time Markov chain having four possible states. Similarly, a Markov chain is proposed as a model for the variations of the monthly amount of precipitation. Based on these models, it is possible to forecast whether the temperature and the amount of precipitation are likely to vary significantly in the long term.

Keywords


Markov processes; Forecasting; Limiting probabilities.

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DOI: http://dx.doi.org/10.1478/AAPP.972A2

Copyright (c) 2019 Mario Lefebvre

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This work is licensed under a Creative Commons Attribution 4.0 International License.