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Innovative Trend Methodology Applications to Precipitation Records in Turkey

机译:创新趋势方法在土耳其降水记录中的应用

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摘要

There are trend identification methodologies in the literature but they have three crucial points that should be cared with great attention in practical applications. These points are that the available time series should have independent serial correlation structure, Gaussian (normal) distribution and monotonic trend fitting to whole time series through the least square technique. The existing methods consider the whole duration of the time series and try to identify a monotonic trend in increasing or decreasing forms. This paper presents partial trend methodology as an innovative and simple trend identification method, which yields low, medium and high cluster trends separately. It provides the opportunity to segregate between the low, high and medium flow trends and their relative intensities, durations as well as magnitudes. The application of the partial trend methodology is presented for 7 precipitation stations from 7 different sub-climatic regions of Turkey leading to spatial and temporal trend interpretations.
机译:文献中有趋势识别方法,但它们具有三个关键点,在实际应用中应予以高度重视。这些要点是,可用时间序列应具有独立的序列相关结构,高斯(正态)分布和通过最小二乘法拟合整个时间序列的单调趋势。现有方法考虑了时间序列的整个持续时间,并尝试确定递增或递减形式的单调趋势。本文介绍了部分趋势方法,将其作为一种创新的简单趋势识别方法,可分别产生低,中和高聚类趋势。它提供了在低流量趋势,高流量趋势和中流量趋势及其相对强度,持续时间和强度之间进行隔离的机会。介绍了部分趋势方法在土耳其7个不同亚气候区的7个降水站的应用,从而解释了时空趋势。

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