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Long-term trend analysis using discrete wavelet components of annual precipitations measurements in Marmara region (Turkey)

机译:使用离散小波分量的马尔马拉地区(土耳其)年降水量测量的长期趋势分析

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The purpose of this study is to determine the possible trends in annual total precipitation series by using the non-parametric methods such as the wavelet analysis and Mann-Kendall test. The wavelet trend (W-T) analysis is for the first time presented in this study. Using discrete wavelet components of measurement series, we aimed to find which periodicities are mainly responsible for trend of the measurement series. We found that some periodic events clearly affect the trend of precipitation series. 16-yearly periodic component is the effective component on Bahkesir annual precipitation data and is responsible for producing a real trend founded on the data. Also, global wavelet spectra and continuous wavelet transform were used for analysis to precipitation time series in order to clarify time-scale characteristics of the measured series. The effects of regional differences on W-T analysis are checked by using records of measurement stations located in different climatic areas. The data set spans from 1929 to 1993 and includes precipitation records from meteorological stations of Turkey. The trend analysis on DW components of the precipitation time series (W-T model) clearly explains the trend structure of data.
机译:这项研究的目的是通过使用非参数方法(例如小波分析和Mann-Kendall检验)来确定年度总降水量序列的可能趋势。小波趋势(W-T)分析是本研究中首次提出。通过使用测量序列的离散小波分量,我们旨在找出哪些周期性主要影响测量序列的趋势。我们发现一些周期性事件明显影响降水序列的趋势。 16年定期分量是Bahkesir年降水量数据的有效分量,并负责根据该数据产生真实趋势。另外,为了阐明测量序列的时标特征,还使用了全局小波谱和连续小波变换来分析降水时间序列。通过使用位于不同气候区域的测量站的记录来检查区域差异对W-T分析的影响。该数据集的时间跨度为1929年至1993年,包括土耳其气象站的降水记录。降水时间序列DW分量的趋势分析(W-T模型)清楚地解释了数据的趋势结构。

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