Stochastic weather generators are used in a wide range of studies, such as hydrological, environmental applications and agricultural risk assessments and can produce time series of synthetic daily weather data of proper duration. In the present study, the performance of the LARS-WG model was analyzed in four northern and eight southern coastal stations of Iran, in relation to the simulation of wet/dry series, precipitation, temperature, solar radiation and the simulation of temperature extreme events. The results showed that the model performance was very acceptable in relation to daily distribution, monthly, and seasonal mean of almost every series. However, its performance in estimating the values of total monthly precipitation standard deviation, mean monthly temperature standard deviation and mean monthly solar radiation standard deviation was not tolerable. In the whole, the LARS-WG model had a better performance in northern stations in comparison with southern stations.
Ababaei,B. , Mirzaei,F. and Sohrabi,T. (2011). Assessment of LARS-WG Performance in 12 Coastal Stations of Iran. Iranian Water Researches Journal, 5(2), 217-222.
MLA
Ababaei,B. , , Mirzaei,F. , and Sohrabi,T. . "Assessment of LARS-WG Performance in 12 Coastal Stations of Iran", Iranian Water Researches Journal, 5, 2, 2011, 217-222.
HARVARD
Ababaei B., Mirzaei F., Sohrabi T. (2011). 'Assessment of LARS-WG Performance in 12 Coastal Stations of Iran', Iranian Water Researches Journal, 5(2), pp. 217-222.
CHICAGO
B. Ababaei, F. Mirzaei and T. Sohrabi, "Assessment of LARS-WG Performance in 12 Coastal Stations of Iran," Iranian Water Researches Journal, 5 2 (2011): 217-222,
VANCOUVER
Ababaei B., Mirzaei F., Sohrabi T. Assessment of LARS-WG Performance in 12 Coastal Stations of Iran. IWRJ, 2011; 5(2): 217-222.
