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

Content Provider	Springer Nature Link
Author	Najafi, Roja Hessami Kermani, Masoud Reza
Copyright Year	2017
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.
Starting Page	1843
Ending Page	1858
Page Count	16
File Format	PDF
ISSN	09204741
Journal	Water Resources Management
Volume Number	31
Issue Number	6
e-ISSN	15731650
Language	English
Publisher	Springer Netherlands
Publisher Date	2017-03-27
Publisher Institution	European Water Resources Association (EWRA)
Publisher Place	Dordrecht
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Statistical downscaling (SD) Global climate models Uncertainty Fuzzy logic Hydrogeology Hydrology/Water Resources Geotechnical Engineering & Applied Earth Sciences Atmospheric Sciences Civil Engineering Environment
Content Type	Text
Resource Type	Article
Subject	Water Science and Technology Civil and Structural Engineering

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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