چکیده مقاله
Weather Generators WGs are widely used in water engineering, agriculture, ecosystem and climate change studies because observed climatic series have deficiencies related to length, completeness and spatial coverage WG models can simulate daily temperature data in a few parametric ways One way is to simulate daily minimum Tmin and maximum Tmax temperatures using an autoregressive model Another way consists of the simulation of daily average temperature Tav and daily temperature range R and then the calculation of Tmin and Tmax indirectly In this study, four different algorithms were assessed for daily temperature in combination with a well tested weather generator M1 and M2 algorithms simulated the daily Tav and R values directly and Tmin and Tmax indirectly M3 algorithm simulated Tmin and Tmax and M4 algorithm simulated Tmin and Tav directly and the other variables indirectly The results showed that each algorithm could perform better in simulating primary variables which are simulated directly This issue was more considerable in relation to daily R values M2 overestimated the crosscorrelation coefficients of this variable because of the assumption of a strong autocorrelation structure between primary variables in the WG model M3 and M4 outperformed the other algorithms in relation to most studied indices This study showed the importance of choosing the best temperature generation algorithm according to the requirements
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شیوه ارجاع
Ababaei, Behnam and Ramezani Etedali, Hadi and Sarai Tabrizi, Mahdi,1393,Comparing Different Weather Generator Algorithms for Daily Temperature as an Influential Factor on Crop Irrigation Requirement,Second National Conference on Water Crisis,Shahrekord
ارائهشده در
مجموعه مقالات دومین همایش ملی بحران آب (تغییر اقلیم، آب و محیط زیست)18 شهریور 1393 · شهرکرد