Bias Correction of Climate Model Outputs Using IMD Srinagar Data for Climate Change Impact Assessment
Syed Rouhullah Ali *
Sher-e-Kashmir University of Agricultural Sciences and Technology, Kashmir-190025, India.
Junaid N. Khan
Sher-e-Kashmir University of Agricultural Sciences and Technology, Kashmir-190025, India.
Rohitashw Kumar
Sher-e-Kashmir University of Agricultural Sciences and Technology, Kashmir-190025, India.
Farooq Ahmad Lone
Sher-e-Kashmir University of Agricultural Sciences and Technology, Kashmir-190025, India.
Shakeel Ahmad Mir
Sher-e-Kashmir University of Agricultural Sciences and Technology, Kashmir-190025, India.
Imran Khan
Sher-e-Kashmir University of Agricultural Sciences and Technology, Kashmir-190025, India.
*Author to whom correspondence should be addressed.
Abstract
Regional climate models (RCMs) give more credible findings for a regional climate change impact assessment, but they still have a bias that must be rectified. Two correction functions using two methods, the modified difference approach and linear scaling method, were utilized for local bias correction of Tmax, Tmin, and precipitation data at monthly scales and validated to minimize the bias between modelled (HAD GEM2-ES-GCM) and observed climate data at IMD Srinagar Station, J&K. Linear scaling technique at monthly time scale for Tmax, Tmin, and precipitation was superior to modified difference approach for bias correction of modelled data to close it to observed data.
Keywords: Bias correction, Central Kashmir, GCM, RCM, modified difference approach, linear scaling method