Title: Robust weighted regression as a downscaling tool in temperature projections

Authors: Manish Kumar Goyal, C.S.P. Ojha

Addresses: Department of Civil Engineering, Indian Institute of Technology Roorkee, Roorkee, India. ' Department of Civil Engineering, Indian Institute of Technology Roorkee, Roorkee, India

Abstract: Downscaling models are developed using robust version of locally weighted regression smoothing scatter plots technique (LOWESS) regression approach for obtaining projections of mean monthly maximum and minimum temperatures (Tmax and Tmin) to Pichola watershed in an arid region in India. Variable Importance in the Projection (VIP) score from Partial Least Squares (PLSs) regression is used to select the variables. A comparison is also done with LOWESS regression approach. The results show that an increasing trend is observed for Tmax and Tmin for A1B, A2 and Bl scenarios whereas no trend is discerned with the COMMIT.

Keywords: LOWESS regression; robust weighted regression; VIP score; maximum temperatures; minimum temperatures; downscaling models; arid regions; India; partial least squares; PLS regression; global warming.

DOI: 10.1504/IJGW.2010.036135

International Journal of Global Warming, 2010 Vol.2 No.3, pp.234 - 251

Received: 21 Apr 2010
Accepted: 25 Jun 2010

Published online: 22 Oct 2010 *

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