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首页> 外文期刊>Chaos, Solitons and Fractals: Applications in Science and Engineering: An Interdisciplinary Journal of Nonlinear Science >Study of Saudi Arabian climatic conditions using Hurst exponent and climatic predictability index
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Study of Saudi Arabian climatic conditions using Hurst exponent and climatic predictability index

机译:基于赫斯特指数和气候可预测性指数的沙特阿拉伯气候条件研究

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This paper utilizes Hurst exponent to study the persistency of meteorological parameters individually and dependency of rainfall/precipitation on pressure and temperature using climate predictability index. For the purpose, daily averages of surface pressure and temperature and daily total rainfall data for a period of 7 years for three locations and 14 years for seven locations has been utilized. The Hurst exponents (H) for above mentioned meteorological parameters were calculated using rescaled range analysis (R/S) and absolute moments methods. These H values were used to calculate the fractal dimension D for pressure, temperature and rainfall data. Finally, these D’s were used to calculate the climate predictability index PIC in terms of pressure predictability index (PIP), temperature predictability index (PIT) and rainfall predictability index (PIR). The Hurst exponent analysis showed that H values for rainfall, relative humidity and wind speed time series data for all the stations were >0.5 which is indicative of persistence behavior of the parameters on the previous values while for pressure and temperature H values were <0.5 means anti-persistence behavior. The climate predictability index showed that in most of the cases the rainfall was dependent on both pressure and temperature predictability indices. In some cases it was more dependent on pressure index than the temperature and in some cases otherwise. In Saudi Arabia there is no prevalent or established rainy season and the present analysis could not result into concrete results. It is therefore recommended to analyze the data by breaking the entire data set into seasons and further into different years.
机译:本文利用赫斯特(Hurst)指数分别利用气候可预测性指标研究了气象参数的持久性以及降雨/降水对压力和温度的依赖性。为此,使用了三个地点的7年和7个地点的14年的地表压力和温度的每日平均值和每日总降雨数据。使用重标范围分析(R / S)和绝对矩方法计算了上述气象参数的赫斯特指数(H)。这些H值用于计算压力,温度和降雨数据的分形维数D。最后,这些D用于根据压力可预测性指数(PIP),温度可预测性指数(PIT)和降雨可预测性指数(PIR)来计算气候可预测性指数PIC。 Hurst指数分析显示,所有站点的降雨,相对湿度和风速时间序列数据的H值均大于0.5,这表明参数在先前值上的持久性,而压力和温度的H值均小于0.5。反坚持行为。气候可预测性指数表明,在大多数情况下,降雨取决于压力和温度可预测性指数。在某些情况下,与温度相比,压力指数对温度的依赖性更大;在某些情况下,压力指数对温度的依赖性更大。在沙特阿拉伯,没有普遍的或确定的雨季,目前的分析无法得出具体结果。因此,建议通过将整个数据集分解为季节然后分解为不同的年份来分析数据。

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