In the following paper the concept of weather generators producing synthetic meteorological data for use in agronomic models, is presented. A WGEN model that generates daily values of solar radiation, maximum and minimum temperature, and total precipitation was selected to show how the model works. The method was tested by comparing 300-years of generated data with 21 years of observed weather data, recorded for Elora Research Station (Ontario, Canada). Statistical analysis of the data has revealed good correlation between the generated and observed weather data, suggesting that generated daily meteorological data, using the WGEN model, may be successfully used in agricultural modelling.
The papers present analisys of econometrical modelling of the daily retail sales of liquid fuel. There were analised one petrol station of the firm which plays important role on the fuel market. The variable was described by time series hierarchical models with two types of seasonal variations: weekly variations and 12 months ones. Additionally there were included feast-days and days before and after feast-days.