Improvements over three generations of climate model simulations for eastern India

In the present study we investigate the performance of climate models which contributed to the past 3 Intergovernmental Panel for Climate Change (IPCC) assessment reports for the Gangetic West Bengal region of east India (6 degrees x 6 degrees). Analysing present-day seasonal rainfall and temperature over the domain, we compare the results of the models (from the 6 modelling centres common to the second, third and fourth assessment reports-SAR, TAR and AR4, respectively) in order to judge to what extent these global models have improved on a regional scale. Metrics for model evaluation are not yet firmly established in the literature, so in this paper we compare and contrast the results from a number of different statistics used in previous studies. We also analyse the impact of topography on the results obtained for the AR4 models. We find that most models improved from SAR to AR4, although there is some variation in this result depending on seasons, variables and on which statistical methods are used in the analysis. The multi-model mean of the 6 models improves from SAR to TAR to AR4. The overall best performance in this region in the AR4 is the Japanese model, MIROC, but the best model in terms of improving skill from SAR to AR4 is the GFDL model from the United States. Correcting for errors in the model topographies produced an overall improvement of spatial patterns and error statistics, and greatly improves the performance of 1 model (CGCM) which has poor topography, but does not affect the ranking of the other models.