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You are here : eLibrary : IAHR World Congress Proceedings : 36th Congress - The Hague (2015) ALL CONTENT : Flood risk management and adaptation : Evaluating the use of different distance measures in statistical downscaling of climate parameters u...
Evaluating the use of different distance measures in statistical downscaling of climate parameters using the k-nn method
Author : SOROOSH SHARIFI(1), SAEED GOLIAN(2) & PHILIPPE HO(3)
ABSTRACT
The k-nearest neighbor (k-nn) algorithm is one of the simplest and most utilized tools for statistical downscaling of largescale
General Circulation Model (GCM) outputs. The accuracy of this method relies on the selected distance measure for
calculating the similarity between future and past events as well as the considered number of neighbors. In this study,
seven distance metrics were used in conjunction with the Hadley Centre climate data to downscale monthly maximum and
minimum temperature as well as average precipitation for the River Severn basin in the UK. The analysis of the results
showed that although the predictions of average minimum and maximum temperature are insensitive to the number of
neighbors and selected distance measure, the average monthly precipitation may vary by up to 40% depending on the
choice of distance measure, but is less effected by the number of considered neighbors.
File Size : 613,828 bytes
File Type : Adobe Acrobat Document
Chapter : IAHR World Congress Proceedings
Category : 36th Congress - The Hague (2015) ALL CONTENT
Article : Flood risk management and adaptation
Date Published : 18/08/2015
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