EGU22-323, updated on 26 Mar 2022
EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Study of Downscaling Techniques and Standings of Bias Corrected Global Climate Models for Brahmani Basin at Odisha, India

Minduri Uma Maheswar Rao1, Kanhu Charan Patra2, and Akhtar Jahan3
Minduri Uma Maheswar Rao et al.
  • 1NIT,Rourkela,India, National Institute of Technology, Rourkela, Civil Engineering, ROURKELA, India (
  • 2Professor, Department of Civil Engineering, NIT Rourkela, Odisha, India Email:
  • 3Ph.D. Scholar, Department of Earth Sciences, IIT Roorkee, Uttarakhand, India Email:

Climate change is emerging as one of the most pressing issues facing our environment since it will have severe consequences for both natural and human systems. The ability to estimate future climate is required to investigate the influence of climate change on a river basin. The most reliable instruments for simulating climate change are Global Climate Models (GCMs), also known as General Circulation Models. The performance of a precipitation simulation for the Brahmani river basin spanning 94 locations (with a grid resolution of 0.25° X 0.25°) is evaluated in the present study. The observed and model historical temperature datasets cover the period from 2000-2019. Twelve Coupled Model Intercomparison Project – Phase 6 (CMIP6) GCMs (ACCESS- CM2, CESM2, CIESM, FGOALS- g3, HadGEM3, GFDL- ESM4, INM- CM5-0, MIROC- ES2L, NESM3, UKESM1, MPI- ESM1, NorESM2) are used for the climate variable (Pr) using five indicators of performance. Indicators used are Average Absolute Relative Deviation (AARD), Skill Score (SS), Absolute Normalized Mean Bias Deviation (ANMBD), Correlation Coefficient (CC), Normalized Root Mean Square Deviation (NRMSD). GCMs are downscaled to finer spatial resolution before ranking them. The statistical downscaling technique is applied to eliminate the systematic biases in GCM simulations. Weights are determined using the Entropy technique for each performance metric. Cooperative Game Theory (CGT), Compromise programming (CP), Weighted Average Technique, Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), and Preference Ranking Organization Method of Enrichment Evaluation (PROMETHEE-2) methods are utilized to rank the GCMs for the study area. GDM is an approach utilized to integrate the ranking techniques of GCMs to get a collective single rank. The results obtained for precipitation suggest that MIROC-ES2L, HadGEM3, GFDL-ESM4, UKESM1, FGOALS-g3 are the top five models that are preferred for the prediction of precipitation in the Brahmani River Basin.

How to cite: Rao, M. U. M., Patra, K. C., and Jahan, A.: Study of Downscaling Techniques and Standings of Bias Corrected Global Climate Models for Brahmani Basin at Odisha, India, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-323,, 2022.