A Case Study of Monthly Values Probability Using Global Historical Climatology Network Data

Abstract

The paper presents a study of a monthly temperatures time series, using data available from the Global Historical Climatology Network for Sibiu. Only by analysing the time series variability, it is possible to correctly identify the range of “normal” climate conditions and the fluctuations or eventually climate changes that could affect forest dynamics. A simple empirical method, the quantile plot, was used for estimating the probabilities associated with different temperature monthly values, which are very useful and possible to be easily estimated using this procedure by researchers and managers from forestry, agriculture, land planning, etc.