Assessment of Annual and Seasonal Surface Air Temperature Simulations in CMIP6 Models over India

IF 1.9 4区 地球科学 Q2 GEOCHEMISTRY & GEOPHYSICS
A. Sabarinath, T. Kesavavarthini, Meera M. Nair, A. Naga Rajesh
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Abstract

Surface air temperature (SAT) affects both natural systems and human activities, impacting health, agriculture, energy demand, and so on. To investigate and analyze SAT over the region of interest, it is crucial to choose suitable climate models. The study commenced with the evaluation of 42 Coupled Model Intercomparison Project phase 6 (CMIP6) models’ simulations of SAT over India for annual and all four seasons (summer, southwest monsoon, northeast monsoon, and winter) during the historical period 1985 to 2014 with respect to the gridded SAT datasets obtained from the India Meteorological Department (IMD). Multi Model Mean (MMM) of 42 models was included in the evaluation. The evaluation was performed with various statistical metrics such as root mean squared error (RMSE), mean bias error (MBE), correlation coefficient (R), mean squared error (MAE), Taylor skill score (TSS), Brier skill score (BSS), and Interannual variability skill score (IVSS). By the method of estimating Comprehensive Rating Index (CRI), the top-ranking models were identified to be CMCC-CM2-SR5 for the annual and summer season, MIROC6 for the winter season, ACCESS-ESM-1-5 for the southwest monsoon, and NorESM2-LM for northeast monsoon. The novelty of this study lies in the approach of identifying the best ensemble. For each season, statistical metric-wise top-ranked models were picked to develop the best ensemble. Again, the overall ranking of the models along with the best ensemble for each season is determined by estimating CRI. It was observed that for all seasons, the best ensemble falls within the top 3 models’ category. Future projections of SAT under four shared socio-economic pathways (SSP-2.6, 4.5, 7.0, and 8.5) were also analyzed with the best ensemble obtained for each season. The results convey that, the country will witness, especially during the summer season, there will be a 1.160 °C, 1.288 °C and 2.368 °C rise in the mean SAT between historical (1985–2014) and near future (2021–2040), near and mid future (2041–2060), mid and far future (2081–2100) if the pathway, SSP5-8.5 is followed.

Abstract Image

印度上空 CMIP6 模型的年度和季节性地表气温模拟评估
地表气温(SAT)既影响自然系统,也影响人类活动,对健康、农业、能源需求等都有影响。要研究和分析相关区域的地面气温,选择合适的气候模式至关重要。研究首先评估了 42 个耦合模式相互比较项目第 6 阶段(CMIP6)模式对 1985 年至 2014 年历史时期印度上空全年和所有四季(夏季、西南季风、东北季风和冬季)SAT 的模拟结果,以及从印度气象局(IMD)获得的网格 SAT 数据集。评估包括 42 个模型的多模型平均值(MMM)。评估采用了各种统计指标,如均值平方根误差(RMSE)、均值偏差误差(MBE)、相关系数(R)、均值平方误差(MAE)、泰勒技能得分(TSS)、布赖尔技能得分(BSS)和年际变化技能得分(IVSS)。通过估算综合评价指数(CRI)的方法,确定了全年和夏季排名最高的模式为 CMCC-CM2-SR5,冬季排名最高的模式为 MIROC6,西南季风排名最高的模式为 ACCESS-ESM-1-5,东北季风排名最高的模式为 NorESM2-LM。这项研究的新颖之处在于确定最佳集合的方法。在每个季节,从统计指标上挑选出排名最靠前的模式,以建立最佳模式集合。同样,通过估算 CRI 来确定模型的总体排名以及每个季节的最佳集合。结果表明,在所有季节,最佳集合都属于前 3 个模型的范畴。此外,还分析了在四种共同的社会经济路径(SSP-2.6、4.5、7.0 和 8.5)下对未来 SAT 的预测,以及每个季节的最佳集合。结果表明,如果采用 SSP5-8.5 路径,该国的平均 SAT 将在历史(1985-2014 年)和近期未来(2021-2040 年)、近期和中期未来(2041-2060 年)、中期和远期未来(2081-2100 年)之间上升 1.160 ℃、1.288 ℃ 和 2.368 ℃,尤其是在夏季。
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来源期刊
pure and applied geophysics
pure and applied geophysics 地学-地球化学与地球物理
CiteScore
4.20
自引率
5.00%
发文量
240
审稿时长
9.8 months
期刊介绍: pure and applied geophysics (pageoph), a continuation of the journal "Geofisica pura e applicata", publishes original scientific contributions in the fields of solid Earth, atmospheric and oceanic sciences. Regular and special issues feature thought-provoking reports on active areas of current research and state-of-the-art surveys. Long running journal, founded in 1939 as Geofisica pura e applicata Publishes peer-reviewed original scientific contributions and state-of-the-art surveys in solid earth and atmospheric sciences Features thought-provoking reports on active areas of current research and is a major source for publications on tsunami research Coverage extends to research topics in oceanic sciences See Instructions for Authors on the right hand side.
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