Water Engineering and Management, Asian Institute of Technology, Pathum Thani 12120, Thailand.
Water Engineering and Management, Asian Institute of Technology, Pathum Thani 12120, Thailand.
Sci Total Environ. 2022 Jul 10;829:154551. doi: 10.1016/j.scitotenv.2022.154551. Epub 2022 Mar 12.
This study proposes a methodological framework to evaluate and rank climate models based on extreme climate indices of precipitation and temperature for impact studies in seven sectors: Cryosphere, Energy, Forestry/GHGs, Health, Agriculture & Food Security, Disaster Risk Reduction (flood and drought), and Water Resources & Hydrology. The ranking of the climate models is based on their performance in sector-relevant extreme climate indices. Extreme climate indices for observed and climate models' datasets for a historical period and overall performance statistics were used to create a payoff matrix. The payoff matrix then served as an input to a multi-criteria decision-making process to rank the climate models for each of the climate indices. The final sector-specific ranking was achieved by averaging the ranks obtained in the sector-relevant indices. The developed methodology is demonstrated with an application to the Songkhram River Basin (Thailand), a sub-basin of the Mekong. Eighteen CMIP6 GCMs are used for the proposed evaluation and ranking processes and four performance statistics were used. Weights to each of the four performance statistics were determined using the entropy method. Compromise programming was applied to rank the GCMs based on the distance technique. The results indicate that the six best performing models are different for different sectors, with the GFDL_CM4 model common in all the seven sectors considered in the study. KACE1_0_G, GFDL_ESM4, GFDL_CM4, MRI_ESM2_0, and ACCESS_ESM1_5 models are the five top (ranked 1 to 5 respectively) performing models for the Water Resources & Hydrology sector. The developed framework is generic and can be applied to any region or basin; at the same time, it can also provide researchers and policymakers with specific information on best-performing models for particular sectors.
本研究提出了一种方法框架，用于根据降水和温度极端气候指数评估和排名气候模型，以进行七个领域的影响研究：冰冻圈、能源、林业/温室气体、健康、农业和粮食安全、减少灾害风险（洪水和干旱）以及水资源和水文学。气候模型的排名基于其在与部门相关的极端气候指数方面的表现。使用观测数据集和气候模型数据集的极端气候指数，以及历史时期和总体表现统计数据，创建了收益矩阵。收益矩阵随后作为多准则决策过程的输入，用于对每个气候指数的气候模型进行排名。通过在相关指数中获得的排名的平均值来实现最终的特定部门排名。所开发的方法通过应用于 Songkhram 河流域（泰国），即湄公河的一个子流域进行了演示。使用 18 个 CMIP6 GCM 进行了拟议的评估和排名过程，并使用了四个性能统计数据。使用熵方法确定了每个四个性能统计数据的权重。根据距离技术应用妥协规划对 GCM 进行排名。结果表明，对于不同的部门，表现最好的六个模型是不同的，GFDL_CM4 模型在研究中考虑的七个部门中都有出现。KACE1_0_G、GFDL_ESM4、GFDL_CM4、MRI_ESM2_0 和 ACCESS_ESM1_5 模型是水资源与水文学部门排名前 5 位（分别排名 1 到 5）的表现最好的模型。所开发的框架是通用的，可以应用于任何地区或流域；同时，它还可以为研究人员和决策者提供特定部门表现最佳模型的具体信息。
