流域尺度温度变量趋势调查

H. Upadhyay, P.K. Singh, M. Kothari, S. Bhakar, K. Yadav
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摘要

本研究论文利用从 MERRA-2 数据库中获取的阿布路、阿布山和平德瓦拉三个地点 40 年(1981-2020 年)的历史气温数据,对西巴那斯盆地的气温变量进行了分析,以检测是否存在潜在趋势。该研究旨在调查气温趋势的长期变化,并确定这三个地点每月、每季和每年的平均气温、最高气温和最低气温的任何重要模式或异常情况,共计 162 个系列。使用 Mann-Kendall 检验对趋势进行了评估,这是一种流行且强大的统计技术,用于分析异常分布。在使用趋势检验之前,先确定了自相关时间序列,并使用方差修正方法对趋势检验进行了修改,以纳入自相关性对结果趋势的影响。自相关分析结果显示,162 个序列中有 11 个存在自相关,其中大部分与阿布路的温度序列有关。趋势检验结果表明,在 162 个序列中,有 27 个具有显著的趋势,大多数序列的季风平均气温和最高气温呈下降趋势,而最低气温似乎呈上升趋势。总之,这项研究强调了监测气温趋势的重要性,尤其是在更容易受到气候变化影响的地区。这项研究的结果可以为未来的气候适应战略提供信息,并支持旨在减轻全球变暖对自然和建筑环境影响的决策过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Investigation of trends in basin-scale temperature variables
This research paper presents an analysis of temperature variables over the West Banas basin in order to detect the presence of underlying trends employing historical temperature data for three points viz., Abu Road, Mount Abu and Pindwara obtained for a period of 40 years (1981 – 2020) from MERRA-2 database. The study aims to investigate the long-term changes in temperature trends and identify any significant patterns or anomalies in mean, maximum and minimum temperatures at monthly, seasonal and annual timescales at the three locations amounting to a total of 162 series. The trends were evaluated using the Mann-Kendall test, a popular and powerful statistical technique formulated for analysing abnormal distributions. Prior to the application of the trend test, autocorrelated time series were identified and the trend test was modified using a variance correction approach to incorporate the influence of autocorrelations upon the resultant trends. The findings of autocorrelation analysis revealed that 11 of the 162 series were autocorrelated, a majority of which were associated with the temperature series at Abu Road. The results of the trend test showed that 27 out of the 162 series possessed significant trends with the mean and maximum monsoon temperatures in most of the series exhibiting a reducing trend while the minimum temperature appeared to be rising. Overall, the research highlights the importance of monitoring temperature trends, particularly in regions that may be more vulnerable to the impacts of climate change. The findings of this study can inform future climate adaptation strategies and support decision-making processes aimed at mitigating the effects of global warming on the natural and built environment.
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