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Use of observed temperature statistics in ranking CMIP5 model performance over the Western Himalayan Region of India

Assessing warming over the Western Himalayan Region (WHR) of India is challenging due to its limited station data availability and poor data quality. The missing values in the station data were replaced using the Multiple Imputation Chained Equation technique. Finally, 16 stations having continuous records during 1969–2009 were considered as the ‘reference stations’ for assessing the warming/cooling trends in addition to evaluate the Coupled Model Intercomparison, phase 5 (CMIP5), Global Circulation Model (GCM). Station data indicates winter (DJF) warming is higher and rapid (1.41 °C) than the other seasons and less warming was observed in the post‐monsoon (0.31 °C) season. Overall mean annual warming over WHR is ∼0.84 °C during 1969–2009. The performance of 34 CMIP5 models was evaluated based on three different criteria namely (1) mean seasonal cycle, (2) temporal trends and (3) spatial correlation between simulated and observed signals for common available period of 1969–2003 over the study area. Models are provided a final rank on the basis of the cumulative rank obtained in each of three approaches. CMCC‐CM, GISS‐E2‐H and MIROC 5 are three top‐ranked models while MIROC‐ESM, MIROC‐ESM‐CHEM and bcc‐csm1‐1 are three bottom‐ranked models over the WHR. The study also extended to judge whether the selected top‐ranked models perform well through two alternative data sources namely European Reanalysis (ERA)‐interim and Climate Research Unit (CRU), which have not used in the process of model evaluation. The spatial patterns of top‐ranked GCM are similar to the spatial pattern obtained through ERA‐interim and CRU while zoomed in to WHR but bottom‐ranked models fail to reproduce such spatial patterns indicating the top‐ranked GCMs would offer more reliability for projecting future climate over WHR.