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Information Journal Paper

Title

The Isfahan values of Temperature and Precipitation Forecast Based on Two Fine Scale Models Lars_WG and SDSM and Artficial Neural Network Method

Pages

  38-49

Abstract

 The scales of Temporal and Spatial steps of Atmosphere General Circulation Models GCM are continental and global. Therefore, it is necessary the models act on the local behavior of the station data, to understand the status of a local station using these models. In this study using SDSM, LARS_WG models and artificial neural network method Based on observational data obtained from 6 Synoptic stations in Isfahan province, temperature and precipitation forecasts of these stations from 2021 to 2050 have been investigated. Pearson's correlation coefficient (r) and coefficient of determination (R2) between observational data and scenario data at all stations are above 0. 6, and root-mean-square error (RMSE) is acceptable, then good simulation has been performed. Based on the results, the temperature of Isfahan province increased from 2021 to 2050 and based on SDSM, In 2005 it had the lowest value and in 2050 it had the highest value And the temperature difference of these years is about 2/3 °,C, which indicates that the temperature will rise and Precipitation changes are almost similar to current changes and We will have the highest amount of precipitation in 1405 and 1406 which, in daran statian which, It has more rainfall than other stations, it will be about 2. 3 mm.

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    APA: Copy

    Zarfeshani, a., & Jahangir, M.H.. (2021). The Isfahan values of Temperature and Precipitation Forecast Based on Two Fine Scale Models Lars_WG and SDSM and Artficial Neural Network Method. IRANIAN JOURNAL OF IRRIGATION AND DRAINAGE, 15(1 ), 38-49. SID. https://sid.ir/paper/1053705/en

    Vancouver: Copy

    Zarfeshani a., Jahangir M.H.. The Isfahan values of Temperature and Precipitation Forecast Based on Two Fine Scale Models Lars_WG and SDSM and Artficial Neural Network Method. IRANIAN JOURNAL OF IRRIGATION AND DRAINAGE[Internet]. 2021;15(1 ):38-49. Available from: https://sid.ir/paper/1053705/en

    IEEE: Copy

    a. Zarfeshani, and M.H. Jahangir, “The Isfahan values of Temperature and Precipitation Forecast Based on Two Fine Scale Models Lars_WG and SDSM and Artficial Neural Network Method,” IRANIAN JOURNAL OF IRRIGATION AND DRAINAGE, vol. 15, no. 1 , pp. 38–49, 2021, [Online]. Available: https://sid.ir/paper/1053705/en

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