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<p>Historical data (1995–2014) from 48 global climate models (GCMs) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) were validated across three South Asian countries (Pakistan, Nepal, and Bangladesh) as part of the Asia–Pacific Network for Global Change Research (APN) project <a href="https://doi.org/10.30852/p.4583">https://doi.org/10.30852/p.4583</a>. The GCMs outputs were compared to a new gridded dataset based on meteorological station observations, and the models’ performance was ranked using various statistical metrics in order to identify the best-performing models across three countries. Three analyses were conducted using a ranking method to identify the best models: (1) evaluated precipitation and air temperature independently for each country; (2) evaluated precipitation and air temperature independently but combined data from all countries; and (3) evaluated both precipitation and air temperature together, combining data from all countries. The comprehensive analysis of the countries and variables identifies the top five models out of the 48 models as EC-Earth3-Veg, NorESM2-MM, KACE-1–0-G, EC-Earth3, and AWI-CM-1–1-MR.</p>

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Selecting the best CMIP6 GCMs for application and downscaling studies over Pakistan, Nepal and Bangladesh

  • 期刊论文

  • 发表日期：

    2025年7月19日

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  • Shaukat Ali,
  • Michelle Simões Reboita,
  • Zulfiqar A. Bhutta,
  • Muhammad Arif Goheer,
  • Joao Gabriel Martins Ribeiro,
  • Christie André de Souza,
  • Glauber Willian Ferreira,
  • Jai Das,
  • Rida S. Kiani,
  • Azfar Hussain,
  • Fatima Saeed,
  • Muhammad Adnan Abid,
  • Madan L. Shrestha

摘要

Historical data (1995–2014) from 48 global climate models (GCMs) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) were validated across three South Asian countries (Pakistan, Nepal, and Bangladesh) as part of the Asia–Pacific Network for Global Change Research (APN) project https://doi.org/10.30852/p.4583. The GCMs outputs were compared to a new gridded dataset based on meteorological station observations, and the models’ performance was ranked using various statistical metrics in order to identify the best-performing models across three countries. Three analyses were conducted using a ranking method to identify the best models: (1) evaluated precipitation and air temperature independently for each country; (2) evaluated precipitation and air temperature independently but combined data from all countries; and (3) evaluated both precipitation and air temperature together, combining data from all countries. The comprehensive analysis of the countries and variables identifies the top five models out of the 48 models as EC-Earth3-Veg, NorESM2-MM, KACE-1–0-G, EC-Earth3, and AWI-CM-1–1-MR.