Modeling monthly temperature data in Lisbon and Prague

This paper examines monthly average temperature series in two widely separated European cities, Lisbon ( 18561999) and Prague (1841-2000). The statistical methodology used begins by fitting a straight line to the temperature measurements in each month of the year. Hence, the 12 intercepts describe the seasonal variation of temperature and the 12 slopes correspond to the rise in temperature in each month of the year. Both cities show large variations in the monthly slopes. In view of this, an overall model is constructed to integrate the data of each city. Sine/cosine waves were included as independent variables to describe the seasonal pattern of temperature, and sine/cosine waves multiplied by time were used to describe the increase in temperature corresponding to the different months. The model also takes into account the autoregressive, AR(I), structure that was found in the residuals. A test of the significance of the variables that describe the variation of the increase in temperature shows that both Lisbon and Prague had an increase in temperature that is different according to the month. The winter months show a higher increase than the Summer months. Copyright (C) 2009 John Wiley & Sons, Ltd.