首页> 外文期刊>fresenius environmental bulletin >QUANTIFYING THE EFFECT OF CLIMATE CHANGE ON PRECIPITATION AND TEMPERATURE PATTERNS BY USING VARIANT OF NON-PARAMETRIC TECHNIQUES
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QUANTIFYING THE EFFECT OF CLIMATE CHANGE ON PRECIPITATION AND TEMPERATURE PATTERNS BY USING VARIANT OF NON-PARAMETRIC TECHNIQUES

机译:使用非参数技术的变体量化气候变化对降水和温度模式的影响

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摘要

The overall objective of this paper is to analyze the long-term spatio-temporal patterns of precipitation and temperature especially under changing climatic conditions. A comprehensive study of different non-parametric trend techniques for serially correlated data were performed. Four variants of Mann Kendall, Spearmen’s rho and Theil Sen’s approach were utilized to quantify the significance of precipitation and temperature trends and their magnitude. Furthermore, to investigate the non-stationary behavior of these trends, Sequential Mann Kendall technique has been used. Besides, inter-annual and seasonal variations in the precipitation and temperature patterns were analyzed to understand the climatic conditions of the study area along with their spatial fluctuating characteristics. Abrupt changes in precipitation and temperature patterns were also illustrated to understand the hydrological behaviors.It is concluded that the Modified Mann Kendall technique is more reliable for trend detection of serially correlated data. The results indicated that generally no significance trend in annual and seasonal precipitation data series exist. However, for temperature except during summer, a significant increasing trend in annual and seasonal data series has been observed with a change up to 0.17 oC/ decade. Results of Sequential Mann Kendall indicated that change in trend for annual and seasonal precipitation except for autumn season began in 1955-1965, whereas it started in 1965-1975 for annual and seasonal temperature for majority of the study regions.
机译:本文的总体目标是分析降水和温度的长期时空格局,特别是在气候变化条件下。对序列相关数据的不同非参数趋势技术进行了全面研究。利用 Mann Kendall、Spearmen 的 rho 和 Theil Sen 方法的四种变体来量化降水和温度趋势的重要性及其大小。此外,为了研究这些趋势的非平稳行为,使用了顺序 Mann Kendall 技术。此外,还分析了降水和温度模式的年际和季节变化,以了解研究区的气候条件及其空间波动特征。还说明了降水和温度模式的突然变化,以了解水文行为。结果表明,修正的Mann Kendall技术对于序列相关数据的趋势检测更为可靠。结果表明:年降水量和季节降水量数据序列总体上不存在显著性趋势。然而,除夏季外,对于温度,已观察到年度和季节性数据序列的显着增加趋势,变化高达 0.17 oC/十年。Sequential Mann Kendall的结果表明,除秋季外,年降水量和季节降水量的变化趋势始于1955-1965年,而大多数研究区的年降水量和季节降水量变化始于1965-1975年。

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