عنوان مقاله [English]
نویسندگان [English]چکیده [English]
Background and objectives: Hydrological and environmental models have become important tools for natural resource and environmental management. However, these models require different input data (i.e., solar radiation, wind speed, maximum and minimum temperature, precipitation, soil water content, streamflow, and sediment concentration) at variable time intervals (e.g. daily, hourly) which are often limited. Many climate monitoring stations have very short periods of record and often carry missing data in the time series. Therefore, hydrological models often require generating synthetic climate data derived from short-term observations using different statistical distributions. The generators are widely used to produce long synthetic weather series with statistical characteristics corresponding to those of the historical records which tend to be relatively short or contain considerable amount of missing data. CLIGEN (CLImate GENerator) is a stochastic weather generator to simulate 10 meteorological variables, such as daily precipitation, storm duration, storm intensity, solar radiation, maximum and minimum daily temperature and wind velocity and direction. CLIGEN has primarily been used to provide climate input for WEPP model. The aim of this paper is to evaluate CLIGEN at Zidasht station in Alborz province of Iran.
Materials and methods: Monthly values of requirement variable of CLIGEN were collected for variable relate to precipitation (mean liquid precipitation, probability of a wet day following a wet day, probability of a wet day following a dry day, mean maximum daily 30 minute liquid precipitation intensity, time to peak rainfall intensity in 12 class ) from 2002-2013 and for other variable (max. and min, temperature, solar radiation, dew point temperature, wind velocity and direction in 16 direction) from 2007- 2013 at Zidasht station. For calculation of time to peak intensity has used pattern of intensity of 165 storm. Finally, statistical test of t were conducted to compare the differences between observed weather data and each of the sets of CLIGEN generated weather data.
Results: The results showed no significant difference in the mean between observed and generated values for considered variables including yearly total precipitation, yearly number of rainy days, maximum and minimum temperature and CLIGN preserves the means quite well. Also, the efficiency of CLIGEN is well for generating of the monthly total precipitation.
Conclusion: Although the results of this study indicate the acceptable performance, but considering that this is the first study of its kind in iran, and also period of observation was somewhat short in this study, final confirmation of CLIGEN needs to further evaluations in various weather stations.