Ranking of CMIP 6 climate models in simulating precipitation over India

IF 2.3 4区 地球科学 Acta Geophysica Pub Date : 2024-03-08 DOI:10.1007/s11600-024-01313-7
Degavath Vinod, V. Agilan
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Abstract

Understanding how precipitation fluctuates geographically and temporally over a specific place due to climate change is critical. Generally, simulations of general circulation models (GCM) under different scenarios are downscaled to the local scale to study the impact of climate change on precipitation. However, selecting suitable GCMs for the given study area is one of the most hectic tasks, as the performance of GCMs may vary with respect to space and timescale. Therefore, the current study ranks twenty-seven CMIP 6 (Coupled Modelled Intercomparison Project Phase 6) GCMs in simulating precipitation over India for nine times series, including daily, monthly, yearly, and six extreme series extracted with annual maximum and peak over threshold methods. The gridded daily rainfall data provided by the India Meteorological Department (IMD) are used as the observed data. The GCMs' outputs are corrected for the systematic bias using the linear scaling method. The performance of a GCM is assessed with three statistical performance metrics, namely NSE, RMSE, and R2. The GCMs' ranks are determined using a multi-criterion decision-making technique named the modified technique of order preference by similarity to an ideal solution (mTOPSIS) for every grid point and nine timescales (i.e., daily, monthly, yearly, and six extreme series). From the results, for the entire India, the top ten recommended CMIP 6 GCMs are FGOALS-g3, HadGEM3-GC31-MM, EC-Earth3, BCC-CSM2-MR, CNRM-CM6-1-HR, CanESM5, AWI-ESM-1-1-LR, MPI-ESM-1-2-HR, IITM-ESM, and INM-CM5-0. The identified best-performing models provide insightful information for better regional climate projections and underscore the necessity of considering multiple model outputs for reliable climate change impact assessments and adaptation strategies in the region.

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CMIP 6 气候模式在模拟印度降水方面的排名
摘要 了解气候变化对特定地区降水量在地理和时间上的影响至关重要。一般来说,不同情景下的大气环流模式(GCM)模拟结果会缩小到当地尺度,以研究气候变化对降水的影响。然而,由于 GCM 的性能可能因空间和时间尺度而异,为特定研究区域选择合适的 GCM 是最困难的任务之一。因此,本研究对 27 个 CMIP 6(耦合模式相互比较项目第 6 阶段)GCM 进行了排名,以模拟印度降水量的 9 个时间序列,包括日、月、年以及用年度最大值和峰值超过阈值方法提取的 6 个极端序列。观测数据采用印度气象局 (IMD) 提供的网格化日降雨量数据。使用线性缩放法对 GCM 的输出进行系统偏差校正。用三个统计性能指标评估 GCM 的性能,即 NSE、RMSE 和 R2。对于每个网格点和九个时间尺度(即每日、每月、每年和六个极端序列),使用一种名为 "与理想解相似性排序偏好修正技术(mTOPSIS)"的多标准决策技术确定 GCM 的等级。从结果来看,对于整个印度,推荐的前十个 CMIP 6 GCM 分别是 FGOALS-g3、HadGEM3-GC31-MM、EC-Earth3、BCC-CSM2-MR、CNRM-CM6-1-HR、CanESM5、AWI-ESM-1-1-LR、MPI-ESM-1-2-HR、IITM-ESM 和 INM-CM5-0。已确定的最佳模型为更好地进行区域气候预测提供了有洞察力的信息,并强调了考虑多种模型输出结果以在该地区进行可靠的气候变化影响评估和制定适应战略的必要性。
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来源期刊
Acta Geophysica
Acta Geophysica GEOCHEMISTRY & GEOPHYSICS-
CiteScore
3.80
自引率
13.00%
发文量
251
期刊介绍: Acta Geophysica is open to all kinds of manuscripts including research and review articles, short communications, comments to published papers, letters to the Editor as well as book reviews. Some of the issues are fully devoted to particular topics; we do encourage proposals for such topical issues. We accept submissions from scientists world-wide, offering high scientific and editorial standard and comprehensive treatment of the discussed topics.
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