Comparison between Performance of Statistical and Low Cost ARIMA Model with GFDL, CM2.1 and CGM 3 Atmosphere-Ocean General Circulation Models in Assessment of the Effects of Climate Change on Temperature and Precipitation in Taleghan Basin

Arash YoosefDoost^{1, 2,} , Mohammad Sadegh Sadeghian², MohammadAli NodeFarahani¹ and Ana Rasekhi¹

¹Member of Young Researchers’ Elite Club, South Tehran branch, Islamic Azad University, Iran

²Islamic Azad University Central Tehran Branch, Tehran, Iran

Cite this paper

Arash YoosefDoost, Mohammad Sadegh Sadeghian, MohammadAli NodeFarahani and Ana Rasekhi. Comparison between Performance of Statistical and Low Cost ARIMA Model with GFDL, CM2.1 and CGM 3 Atmosphere-Ocean General Circulation Models in Assessment of the Effects of Climate Change on Temperature and Precipitation in Taleghan Basin. American Journal of Water Resources. 2017; 5(4):92-99. doi: 10.12691/AJWR-5-4-1

Abstract

According to the importance of climate change, the necessity of develop a fast and accurate tool is undeniable. Although the comparison of a statistical model with specialized models which were designed regard to non-linear complexities of a phenomenon is not common, in this study ARIMA statistical model was analyzed and evaluated with GFDL CM2.1 and CGM3 Atmosphere-Ocean General Circulation Models (AOGCMs) in order to investigate on the effects of climate change on temperature and precipitation in the Taleghan basin. The results showed although GFDL CM2.1 model showed better performance in MAE and R² validation criteria and the predicted temperature had similar trend with the observational data, the difference between the model results and observations is significant. The CGM 3 model showed better performance in R² for precipitation, temperature and MAE for long term average of precipitation in addition to having similar trend to the observed data. However, for long term average of both temperature and precipitation, the general predicted trend had a considerable distance with the observational values. In contrast, although the statistical ARIMA model predictions had some fluctuations, they had better conformity to the general trend of observations. These results show that contrary to popular belief, in some cases like this investigated case, even cheap statistical models can likely provide acceptable results.

Keywords

climate change, ARIMA, AOGCM, GFDL, CM 2.1, CGM3, Taleghan Basin

Copyright

This work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

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