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Uncertainty Modeling of Statistical Downscaling to Assess Climate Change Impacts on Temperature and Precipitation

Author

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  • Roja Najafi

    (Graduate University of Advanced Technology)

  • Masoud Reza Hessami Kermani

    (Shahid Bahonar University of Kerman)

Abstract

Consideration of different Statistical Downscaling (SD) models and multi-sources global climate models’ (GCMs) data can provide a better range of uncertainty for climatic and statistical indices. In this study, results of two SD models, ASD (Automated Statistical Downscaling) and SDSM (Statistical Downscaling Model), were used for uncertainty analysis of temperature and precipitation prediction under climate change impacts for two meteorological stations in Iran. Uncertainty analysis was performed based on application of two GCMs and climate scenarios (A2, A1B, A2a and B2a) for 2011–2040, 2041–2070 and 2071–2100 future time slices. A new technique based on fuzzy logic was proposed and only used to describe uncertainties associated with downscaling methods in temperature and precipitation predictions. In this technique, different membership functions were defined to fuzzify results. Based on these functions width, precipitation had higher uncertainty in comparison with the temperature which could be attributed to the complexity of temporal and local distribution of rainfall. Moreover, little width of membership functions for temperatures in both stations indicated less uncertainty in cold months, whereas the results showed more uncertainty for summer. The results of this study highlight the significance of incorporating uncertainty associated with two downscaling approaches and outputs of GCMs (CGCM3 and HadCM3) under emission scenarios A2, A1B, A2a and B2a in hydrologic modeling and future predictions.

Suggested Citation

  • Roja Najafi & Masoud Reza Hessami Kermani, 2017. "Uncertainty Modeling of Statistical Downscaling to Assess Climate Change Impacts on Temperature and Precipitation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(6), pages 1843-1858, April.
    • Handle: RePEc:spr:waterr:v:31:y:2017:i:6:d:10.1007_s11269-017-1615-8
    DOI: 10.1007/s11269-017-1615-8
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    References listed on IDEAS

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    1. Subimal Ghosh & Sudhir Katkar, 2012. "Modeling Uncertainty Resulting from Multiple Downscaling Methods in Assessing Hydrological Impacts of Climate Change," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(12), pages 3559-3579, September.
    2. Deg-Hyo Bae & Toshio Koike & Jehangir Awan & Moon-Hwan Lee & Kyung-Hwan Sohn, 2015. "Climate Change Impact Assessment on Water Resources and Susceptible Zones Identification in the Asian Monsoon Region," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(14), pages 5377-5393, November.
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    1. Siabi, E. K. & Phuong, D. N. D. & Kabobah, A. T. & Akpoti, Komlavi & Anornu, G. & Incoom, A. B. M. & Nyantakyi, E. K. & Yeboah, K. A. & Siabi, S. E. & Vuu, C. & Domfeh, M. K. & Mortey, E. M. & Wemegah, 2023. "Projections and impact assessment of the local climate change conditions of the Black Volta Basin of Ghana based on the Statistical DownScaling Model," Papers published in Journals (Open Access), International Water Management Institute, pages 14(2):494-5.
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    3. Mahdi Valikhan Anaraki & Saeed Farzin & Sayed-Farhad Mousavi & Hojat Karami, 2021. "Uncertainty Analysis of Climate Change Impacts on Flood Frequency by Using Hybrid Machine Learning Methods," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(1), pages 199-223, January.
    4. Reyhaneh Rahimi & Hassan Tavakol-Davani & Mohsen Nasseri, 2021. "An Uncertainty-Based Regional Comparative Analysis on the Performance of Different Bias Correction Methods in Statistical Downscaling of Precipitation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(8), pages 2503-2518, June.
    5. Jan Niel & E. Uytven & P. Willems, 2019. "Uncertainty Analysis of Climate Change Impact on River Flow Extremes Based on a Large Multi-Model Ensemble," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(12), pages 4319-4333, September.
    6. Jew Das & Alin Treesa & N. V. Umamahesh, 2018. "Modelling Impacts of Climate Change on a River Basin: Analysis of Uncertainty Using REA & Possibilistic Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(15), pages 4833-4852, December.
    7. Hadi Galavi & Majid Mirzaei, 2020. "Analyzing Uncertainty Drivers of Climate Change Impact Studies in Tropical and Arid Climates," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(6), pages 2097-2109, April.
    8. Jin Hyuck Kim & Jang Hyun Sung & Shamsuddin Shahid & Eun-Sung Chung, 2022. "Future Hydrological Drought Analysis Considering Agricultural Water Withdrawal Under SSP Scenarios," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(9), pages 2913-2930, July.

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