Investigation of uncertainty in GCM’s projection of rainfall data (Case Study: Hashem- Abad Station)

Document Type : Thechnical Note

Authors

1 M.Sc. Student of Water Resource Engineering, Water Engineering Department, Faculty of Water and Soil, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran

2 Associate Professor of Water Engineering Department, Faculty of Water and Soil, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran

Abstract

For projection of possible climate change impacts on agriculture and water resources climate models are used but there exist uncertainties in the outputs of these models. The aim of this study is to project the possible changes of precipitation and uncertainty involved in Hashem- Abad station, north of Iran, using general circulation models. For this purpose, precipitation observations for the baseline period of (1990–2010) were collected. Then the outputs of the 8 GCM models (including ACCESS1-0, CanESM2, CMCCCMS, GISSE2H, HadGEM2CC, MIROC5, MIROCESM, and IPSLCM5AMR) under the two scenarios of RCP 4.5 and RCP 8.5 were downscaled using change factor method and compared. The uncertainties of the GCM models for both emission scenarios were also investigated. Comparison of means of precipitation time series for the period 2010–2040 was performed by t-test. The results indicated a decreasing trend in most of the months. The GISSE2H model projected the most significant decreasing trend of total monthly precipitation. The highest uncertainty was observed in July for the both scenarios. Besides, although the outputs of the models didn't show a significant difference in 82% of the cases, the models’ uncertainty band indicated a major difference among the results. Further uncertainty analysis may be recommended for more scrutiny.
 

Keywords


Ashraf, B; Alizadeh, A.; Mousavi Baygi; M., and Bannayan Aval, M. 2013. Verification of temperature and precipitation data simulated by implementing individual and group five AOGCM models for North East Iran. Journal of Soil and Water (Agricultural Science and Technology), 2: 28. 253-266. (In Farsi)
Eghdamirad, S; Johnson, F; Woldemeskel, F; Sharma, A. 2004. Quantifying the sources of uncertainty in upper air climate variables. Journal of Geophysical Research: Atmospheres, 121(8):3859-74.
Ghorbani, K;zakerinia, M and Hezarharibi,A. 2014. The effect of climate change on water requirement of soybean in Gorgan. Journal of Agricultural Meteorology: 2(1): 60-72 (In Farsi).
IPCC. 1990. Climate Change: The IPCC Scientific Assessment (1990). Cambridge University Press: Cambridge, UK, 365p.
IPCC 2013. Climate Change 2013 The Physical Science Basis, Contribution of Working Group I to the Fifth Assessment Report of the       Intergovernmental Panel on Climate Change [Stocker, T.F., D. Qin, and G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P.M. Midgley(eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
Minville, M.; Brissette, F; and Leconte, R. 2008. Uncertainty of the impact of climate change on the hydrology of a Nordic watershed, Journal of Hydrology, 358, 70– 83.
Nikbakht Shahbazi, A., Taban, H., Zahrabi, N. 2016. Uncertainty assessment of GCM models for estimating rainfall and runoff of Dez Ulya basin under climate change. Journal of the Earth and Space Physics, 44(1): 1-16. (In Farsi).
Sayari, N; Alizadeh, A; Bannayan Awal; M. Farid Hossaini, A and Hesami Kermani5, M.R. 2011. Comparison of Two GCM Models (HadCM3 and CGCM2) for the Prediction of Climate Parameters and Crop Water Use under Climate Change. Journal of Water and Soil. 25:4. 912-925. (In Farsi)