CR 60:103-117 (2014)  -  DOI: https://doi.org/10.3354/cr01222

Ranking of global climate models for India using multicriterion analysis

K. Srinivasa Raju1, D. Nagesh Kumar2,3,* 

1Department of Civil Engineering, Birla Institute of Technology and Science-Pilani, Hyderabad campus, India
2Center for Earth Sciences, Indian Institute of Science, 560012 Bangalore, India
3Present address: Department of Civil Engineering, Indian Institute of Science, 560012 Bangalore, India
*Corresponding author:

ABSTRACT: Eleven GCMs (BCCR-BCCM2.0, INGV-ECHAM4, GFDL2.0, GFDL2.1, GISS, IPSL-CM4, MIROC3, MRI-CGCM2, NCAR-PCMI, UKMO-HADCM3 and UKMO-HADGEM1) were evaluated for India (covering 73 grid points of 2.5° × 2.5°) for the climate variable ‘precipitation rate’ using 5 performance indicators. Performance indicators used were the correlation coefficient, normalised root mean square error, absolute normalised mean bias error, average absolute relative error and skill score. We used a nested bias correction methodology to remove the systematic biases in GCM simulations. The Entropy method was employed to obtain weights of these 5 indicators. Ranks of the 11 GCMs were obtained through a multicriterion decision-making outranking method, PROMETHEE-2 (Preference Ranking Organisation Method of Enrichment Evaluation). An equal weight scenario (assigning 0.2 weight for each indicator) was also used to rank the GCMs. An effort was also made to rank GCMs for 4 river basins (Godavari, Krishna, Mahanadi and Cauvery) in peninsular India. The upper Malaprabha catchment in Karnataka, India, was chosen to demonstrate the Entropy and PROMETHEE-2 methods. The Spearman rank correlation coefficient was employed to assess the association between the ranking patterns. Our results suggest that the ensemble of GFDL2.0, MIROC3, BCCR-BCCM2.0, UKMO-HADCM3, MPI-ECHAM4 and UKMO-HADGEM1 is suitable for India. The methodology proposed can be extended to rank GCMs for any selected region.


KEY WORDS: Entropy · Performance indicators · PROMETHEE-2 · River basin


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Cite this article as: Raju KS, Nagesh Kumar D (2014) Ranking of global climate models for India using multicriterion analysis. Clim Res 60:103-117. https://doi.org/10.3354/cr01222

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