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Trend analysis of climatic variables in an arid and semi-arid region of the Ajmer District, Rajasthan, India

机译:印度拉贾斯坦邦阿杰梅尔地区干旱和半干旱地区的气候变量趋势分析

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In the present study, trends and variations in climatic variables (i.e. rainfall, wet day frequency, surface temperature, diurnal temperature, cloud cover, and reference and potential evapotranspiration) were analyzed on seasonal (monsoon and non-monsoon) and annual time scales for the Ajmer District of Rajasthan, India. This was done using non-parametric statistical techniques, i.e. the Manna€“Kendall (MK) and Modified Manna€“Kendall (MMK) tests, over a period of 100 years. The MK test with prewhitening (MKa€“PW) of climatic series was also applied to climatic variables and the results were compared to those obtained through the MK and MMK tests in order to assess the performance of trend detection methods. The Pettitta€“Manna€“Whitney (PMW) test was applied to detect the temporal shift in climatic series. The trend analysis revealed that annual and seasonal rainfall did not show any statistically significant trend at a 10% significant level. A noticeable trend increase was found in wet day frequency, surface temperature and reference evapotranspiration (ET) during the non-monsoon season from the three non-parametric statistical tests at a 10% significance level. A statistically significant decrease in maximum temperature was found during the non-monsoon season by the MKa€“PW test alone. This analysis of several climatic variables at the district scale is helpful for the planning and management of water resources and the development of adaptation strategies in adverse climatic conditions.
机译:在本研究中,分析了季节性(季风和非季风)和年度时间尺度的气候变量(即降雨,湿天频率,地表温度,昼夜温度,云量以及参考和潜在蒸散)的趋势和变化。印度拉贾斯坦邦的阿杰梅尔区。这是使用非参数统计技术完成的,即100年内的Manna?Kendall(MK)和Modified Manna?Kendall(MMK)检验。还将带有气候系列预白化的MK测试(MKa€PW)应用于气候变量,并将结果与​​通过MK和MMK测试获得的结果进行比较,以评估趋势检测方法的性能。应用Pettitta“ Manna” Whitney(PMW)检验来检测气候序列的时间变化。趋势分析显示,年度和季节性降雨在10%的显着水平上均未显示任何统计学上的显着趋势。在三个非参数统计检验中,非季风季节的湿日频率,地表温度和参考蒸散量(ET)都有明显的趋势增加,显着性水平为10%。仅通过MKa€PW试验,在非季风季节最高温度的统计上显着降低。对地区范围内几个气候变量的分析有助于水资源的计划和管理以及在不利气候条件下制定适应策略。

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