Abstract

In this study, we have assessed the skill of decadal prediction of boreal spring (March–May) and summer (June–September) Surface Air Temperature (SAT) over India and its relation with Sea Surface Temperature (SST) in the National Centers for Environmental Prediction (NCEP) Climate Forecast System Version 2 (CFSv2) coupled model. The skill of CFSv2 is compared with CNRM (Centre National de Recherches Météorologiques) coupled model, which is the best among the selected CMIP5 (Coupled Model Intercomparison Project 5) models for long-lead forecasts (6–9 years) of global SSTs (with high skill). It is found that both models show significant skill in predicting 4-year mean SAT over central and southern peninsular India at 1–5 year leads in spring. During summer, significant skills for SAT over the northwest and southeast India are seen in CFSv2, whereas CNRM displayed significant skills over the north and central India at 1–5 years lead. The first Empirical Orthogonal Function (EOF) mode of SAT variability over India indicates a country-wide warming/cooling pattern in both observations and models for spring and summer. The analysis reveals that the decadal variability of SAT (EOF-1) over India is highly related to SST variations over the Indo-Pacific and North Atlantic regions. The strong convergence of low-level winds over the equatorial Indian Ocean and maritime continent accompanied by warm SST anomalies drive the northerly dry winds over India and favour warm SAT in both spring and summer. Further, changes in shortwave radiation also contributed to SAT variability over India. In general, the SAT relationship with SST in different parts of tropical and sub-tropical regions is underestimated in CFSv2 compared to the observations and CNRM in both boreal spring and summer. The models are able to represent the changes in the atmospheric circulation and related Indo-Western Pacific SST patterns reasonably well at the 1–5 years lead with some discrepancy. However, both models showed relatively low skills in capturing the relationship between SAT over India and equatorial Pacific SSTs. This might limit the skills of models in predicting decadal variations of SAT over India.

Research Highlights

• Decadal prediction skill of the spring and summer Surface Air temperature (SAT) over India is examined in CFSv2 and CNRM models.

• Decadal variability of SAT over India is highly related to SST variations over the Indo-Pacific and North Atlantic regions.

• The models are able to represent the changes in the atmospheric circulation and related Indo-Western Pacific SST patterns reasonably well at the 1–5 years lead with some discrepancy.

• Models have low skills in capturing the relationship between SAT over India and equatorial and southern Pacific SSTs and this might limit the skills of models.

中文翻译：

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印度春季和夏季地表气温的年代际预测技巧及其与CFSv2和CNRM耦合模型中SST模式的关联

摘要

在这项研究中，我们评估了印度国家中心地区春季（3月至5月）和夏季（6月至9月）地表气温（SAT）的年代际预测技术及其与海表温度（SST）的关系。环境预测（NCEP）气候预测系统版本2（CFSv2）耦合模型。将CFSv2的技能与CNRM（国家重金属研究中心）耦合模型进行了比较，该模型是对长期预测（6至9年）的全球SST（具有6-9年）的CMIP5（耦合模型比较项目5）模型中最好的。高技能）。结果发现，这两种模型都显示出在春季春季以1-5年的领先时间预测印度中部和南部半岛的4年平均SAT的显着技能。在夏季，CFSv2中显示了印度西北和东南部的SAT的重要技能，而CNRM在印度北部和中部地区领先1-5年，显示出显着的技能。印度SAT变异的第一个经验正交函数（EOF）模式在春季和夏季的观测值和模型中都显示了全国范围的变暖/降温模式。分析表明，印度SAT的年代际变化（EOF-1）与印度太平洋和北大西洋地区的海表温度变化高度相关。赤道印度洋和海洋大陆上的低空风强烈汇合，加上温暖的海表温度异常，驱使印度上空的北风干燥，并在春季和夏季有利于温暖的SAT。此外，短波辐射的变化也导致印度SAT的变化。一般来说，与春季和夏季的北半球观测值和CNRM相比，CFSv2中低估了热带和亚热带地区不同地区的SAT与SST的关系。这些模型能够很好地表示出大气环流的变化以及相关的印度洋-西太平洋SST模式在1-5年的领先时间，但存在一些差异。但是，这两种模型在掌握印度SAT和赤道太平洋海表温度之间的关系方面均显示出较低的技巧。这可能会限制模型预测印度SAT年代际变化的技能。但是，这两种模型在掌握印度SAT和赤道太平洋海表温度之间的关系方面均显示出较低的技巧。这可能会限制模型预测印度SAT年代际变化的技能。但是，这两种模型在掌握印度SAT和赤道太平洋海表温度之间的关系方面均显示出较低的技巧。这可能会限制模型预测印度SAT年代际变化的技能。

研究重点

• 在CFSv2和CNRM模型中检验了印度春季和夏季的地表温度（SAT）的十年代预测技巧。

• 印度SAT的年代际变化与印度太平洋和北大西洋地区的海表温度变化高度相关。

• 这些模型能够很好地表示出大气环流的变化以及相关的印度洋-西太平洋SST模式在1-5年的领先时间，但存在一些差异。

• 在掌握印度SAT与赤道和南太平洋海表温度之间的关系方面，模型的技能很低，这可能会限制模型的技能。