Document Type : Research Paper
Ph.D., Watershed Management, University of Tehran.
Associate Professor, Faculty of Natural Resources, University of Tehran.
Recorded daily weather data are used as climate input in a number of models that continuously simulate the natural resource systems (Yu, 2003). However, it is sometimes difficult to obtain the required data, and also to process them simply because they are lacking or unavailable. Weather generators have been accordingly developed to produce synthetic weather sequences capturing the essential features of observed weather data needed for running the models. In effect, weather generators are widely used in hydrological, ecological, and crop-yield modeling frameworks. CLIGEN (CLImate GENerator), which was first developed as a component of the Water Erosion Prediction Project (WEPP) (Nicks et al., 1995), is a stochastic weather generator that generates long sequences of daily precipitation (e.g., the pattern of each rainfall event including its duration, time to peak, and intensity), maximum and minimum daily temperature, dew point temperature, solar radiation, and wind speed and direction. CLIGEN has been currently used as a general weather generator beyond its initial intention in many locations around the world. This research was thus conducted to examine the efficiency of CLIGEN in generating the weather data in Sanganeh station in the northeast of Iran.