Stochastic weather generators are used in different studies which often require long series of daily weather data for risk assessment. They can produce synthetic daily time series of any length. Any generator should be tested to ensure that the synthetic data is proper for the purposes for which it is to be used. The main objective of this paper is to test a stochastic weather generator, LARS-WG, at 65 sites in Iran chosen to represent different climates. Statistical tests were carried out to compare characteristics of the observed and synthetic weather data such as, the lengths of wet and dry series, the distribution of precipitation and the lengths of frost periods. The LARS-WG generator uses complex semi-empirical distributions for weather variables and tended to match the observed data well, especially in terms of the daily distributions and the mean monthly values, although there are certain characteristics of the data that the generator could not reproduce accurately, for example the monthly standard deviations. LARS-WG model showed different performance in different climates and stations. Therefore, evaluation is strongly recommended if it is going to be used in different climates and stations.
