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<p>Global climate models (GCMs) play a crucial role in studying climate change and forecasting future climate events. The reliability and independence of GCM simulations are key factors in selecting models for research and decision-making. In this study, the performance of 22 GCMs of the Coupled Model Intercomparison Project Phase 6 (CMIP6) is evaluated to identify the ideal model for daily maximum temperature. The models are evaluated against daily gridded data provided by the India Meteorological Department for the period 1951–2014. This study evaluates the performance of different GCMs representing maximum temperature over time. It provides a comprehensive analysis by integrating Goodness of Fit (GoF) metrics to reveal the strengths and weaknesses of individual models across various temporal scales. The compromise rating index (CRI) approach is employed to identify the most suitable subset of GCMs for the East India region. The findings indicate that the methodology applied consistently identifies MIROC-ES2L, GISS-E2, and ACCESS-ESM1-5 as the top-performing models across different temporal durations. While climate change is expected to affect temperature variability, we recommend conducting a regional, multi-temporal, and comprehensive assessment of an ensemble of GCMs to better understand and address these changes.</p>

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Multi-temporal evaluation of CMIP6 models for maximum temperature in East India: improving climate dynamics understanding

  • 期刊论文

  • 发表日期：

    2025年4月7日

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  • Gaurav Patel,
  • Subhasish Das

摘要

Global climate models (GCMs) play a crucial role in studying climate change and forecasting future climate events. The reliability and independence of GCM simulations are key factors in selecting models for research and decision-making. In this study, the performance of 22 GCMs of the Coupled Model Intercomparison Project Phase 6 (CMIP6) is evaluated to identify the ideal model for daily maximum temperature. The models are evaluated against daily gridded data provided by the India Meteorological Department for the period 1951–2014. This study evaluates the performance of different GCMs representing maximum temperature over time. It provides a comprehensive analysis by integrating Goodness of Fit (GoF) metrics to reveal the strengths and weaknesses of individual models across various temporal scales. The compromise rating index (CRI) approach is employed to identify the most suitable subset of GCMs for the East India region. The findings indicate that the methodology applied consistently identifies MIROC-ES2L, GISS-E2, and ACCESS-ESM1-5 as the top-performing models across different temporal durations. While climate change is expected to affect temperature variability, we recommend conducting a regional, multi-temporal, and comprehensive assessment of an ensemble of GCMs to better understand and address these changes.