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Appropriate application of the Standardized Precipitation Index in and locations and dry seasons

机译:在旱季和旱季适当应用标准降水指数

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The Standardized Precipitation Index (SPI) is now widely used throughout the world in both a research and an operational mode. For and climates, or those with a distinct dry season where zero values are common, the SPI at short time scales is lower bounded, referring to non-normally distributed in this study. In these cases, the SPI is always greater than a certain value and fails to indicate a drought occurrence. The nationwide statistics based on our study suggest that the non-normality rates are closely related to local precipitation climates. In the eastern United States, SPI values at short time scales can be used in drought/flood monitoring and research in any season, while in the western United States, because of its distinct seasonal precipitation distribution, the appropriate usage and interpretation of this index becomes complicated. This would also be the case for all arid climates. From a mathematical point of view, the non-normally distributed SPI is caused by a high probability of no-rain cases represented in the mixed distribution that is employed in the SPI construction. From a statistical point of view, the 2-parameter gamma model used to estimate the precipitation probability density function and the limited sample size in dry areas and times would also reduce the confidence of the SPI values. On the basis of the results identified within this study, we recommend that the SPI user be cautious when applying short-time-scale SPIs in and climatic regimes, and interpret the SPI values appropriately. In dry climates, the user should focus on the duration of the drought rather than on just its severity. It is also worth noting that the SPI results from a statistical product of the input data. This character makes it difficult to link the SPI data to the physical functioning of the Earth system. Copyright (c) 2006 Royal Meteorological Society.
机译:标准化降水指数(SPI)现在在研究和操作模式下在全世界范围内得到广泛使用。对于和气候,或那些干旱季节通常为零值的干旱季节,短时间尺度上的SPI的下界较低,指的是本研究中的非正态分布。在这些情况下,SPI始终大于某个值,并且无法指示发生干旱。根据我们的研究,全国范围的统计数据表明,非正常率与当地降水气候密切相关。在美国东部,短时间尺度上的SPI值可用于任何季节的干旱/洪水监测和研究,而在美国西部,由于其独特的季节性降水分布,因此该指数的适当用法和解释成为复杂。在所有干旱气候中也是如此。从数学的角度来看,非正态分布的SPI是由SPI结构中采用的混合分布中表示的无雨情况的可能性很高引起的。从统计的角度来看,用于估计降水概率密度函数的二维参数伽马模型以及在干燥区域和时间中有限的样本量也会降低SPI值的置信度。根据本研究确定的结果,我们建议SPI用户在气候条件下应用短时尺度SPI时应谨慎,并适当解释SPI值。在干旱的气候中,用户应关注干旱的持续时间,而不仅仅是干旱的严重程度。还值得注意的是,SPI是由输入数据的统计乘积得出的。此特性使得很难将SPI数据链接到地球系统的物理功能。版权所有(c)2006皇家气象学会。

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