Abstract

The climate change assessment in the context of urban areas is very crucial for policy making regarding hazard mitigation and citizen’s health, especially for the smart cities. The past climate assessment and present climate monitoring is somewhere easy, but the projection of future climate at city level is very difficult as most climate models fail to resolve the cities spatially. Over the highly populated areas like the region of Gangetic Plains the precise city specific climate projection becomes more important. The present study aims to project the future temperature, covering both minimum temperature (Tmin) and maximum temperature (Tmax) and analyse the extreme indices over smart cities in the Gangetic Plains, as one of the pioneer works using CMIP6 model’s downscaled outputs using SDSM model. The study reveals that these smart cities are likely to experience warmer and more extreme temperatures in the upcoming decades. The future temperature projections were generated under two emission scenarios (SSP245 and SSP585), and for near future (2030–2065) and far future (2066–2100) periods. The drastic change in minimum temperature (Tmin) was observed over New Delhi, Prayagraj, Kolkata, and Lucknow by the end of the century under SSP585. Four extreme temperature indices were also analyzed for future time series: (1) TXgt40(No. of days Tmax > 40ºC); (2) TNlt10(No. of days when Tmin < 10ºC); (3) TX90p (Percentage of days when Tmax > 90th percentile); and (4) TN10P (Percentage of days when Tmin < 10th percentile). The increasing trend of warm temperature Indices and decreasing trend of cool temperature indices were observed over all the stations. The drastic change in extreme temperature indices may have a significant effect on urban climate, it could impact public health by increasing the incidence of heat-related illnesses such as heat stress or heat exhaustion. The present study can be also utilized as a probable baseline for assessing the extreme climate conditions in the future. As this study is one of the very first attempts under the aspect of smart cities and thus it may help in developing early warning systems for smart cities in the Gangetic Plain.

中文翻译：

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使用统计缩小的 CMIP6 预测评估恒河平原智慧城市的未来城市温度

摘要

城市地区的气候变化评估对于减灾和公民健康的政策制定非常重要，特别是对于智慧城市。过去的气候评估和现在的气候监测很容易，但在城市层面预测未来气候却非常困难，因为大多数气候模型无法在空间上解析城市。在恒河平原等人口稠密的地区，精确的城市特定气候预测变得更加重要。本研究旨在预测未来温度，涵盖最低温度 (Tmin) 和最高温度 (Tmax)，并分析恒河平原智慧城市的极端指数，作为使用 SDSM 模型使用 CMIP6 模型缩小输出的先驱工作之一。研究表明，这些智慧城市在未来几十年可能会经历更温暖、更极端的气温。未来温度预测是根据两种排放情景（SSP245 和 SSP585）以及近期（2030-2065）和远未来（2066-2100）时期生成的。到本世纪末，在 SSP585 的影响下，新德里、普拉亚格拉吉、加尔各答和勒克瑙的最低气温 (Tmin) 发生了巨大变化。还分析了未来时间序列的四个极端温度指数：（1）TXgt40（Tmax > 40℃的天数）；(2) TNlt10(Tmin<10℃的天数)；(3) TX90p（Tmax>90%的天数百分比）；(4) TN10P（Tmin < 10% 的天数百分比）。各站暖气温指数均呈上升趋势，冷气温指数呈下降趋势。极端温度指数的急剧变化可能对城市气候产生重大影响，可能会增加热应激或热衰竭等与热有关的疾病的发生率，从而影响公共健康。本研究还可以用作评估未来极端气候条件的可能基线。由于这项研究是智慧城市方面的首次尝试之一，因此可能有助于开发恒河平原智慧城市的预警系统。