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Extreme Value Statistics of the Total Energy in an Intermediate Complexity Model of the Mid-latitude Atmospheric Jet. Part I: Stationary case

机译:中纬度大气急流中间复杂度模型中总能量的极值统计。第一部分:文具盒

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摘要

A baroclinic model of intermediate complexity for the atmospheric jet at middle latitudes is used as astochastic generator of atmosphere-like time series. In this case, time series of the total energy of the systemare considered. Statistical inference of extreme values is applied to sequences of yearly maxima extractedfrom the time series in the rigorous setting provided by extreme value theory. The generalized extremevalue (GEV) family of distributions is used here as a basic model, both for its qualities of simplicity and itsgenerality. Several physically plausible values of the parameter TE, which represents the forced equatorto-pole temperature gradient and is responsible for setting the average baroclinicity in the atmosphericmodel, are used to generate stationary time series of the total energy. Estimates of the three GEV parameters—location, scale, and shape—are inferred by maximum likelihood methods. Standard statistical diagnostics,such as return level and quantile–quantile plots, are systematically applied to assess goodness-of-fit.The GEV parameters of location and scale are found to have a piecewise smooth, monotonically increasingdependence on TE. The shape parameter also increases with TE but is always negative, as is required a prioriby the boundedness of the total energy. The sensitivity of the statistical inferences is studied with respectto the selection procedure of the maxima: the roles occupied by the length of the sequences of maxima andby the length of data blocks over which the maxima are computed are critically analyzed. Issues related tomodel sensitivity are also explored by varying the resolution of the system. The method used in this paperis put forward as a rigorous framework for the statistical analysis of extremes of observed data, to study thepast and present climate and to characterize its variations.
机译:中纬度大气射流的中等复杂度斜压模型用作类似大气时间序列的随机生成器。在这种情况下,将考虑系统总能量的时间序列。极值的统计推断适用于从极值理论提供的严格设置中从时间序列中提取的年度最大值的序列。广义极值(GEV)分布族由于其简单性和通用性而在这里用作基本模型。参数TE的几个物理上合理的值(用于表示强迫的赤道至极点温度梯度并负责设置大气模型中的平均斜度)用于生成总能量的固定时间序列。通过最大似然法可以推断出三个GEV参数(位置,比例和形状)的估计值。系统地应用了标准的统计诊断方法,例如收益水平和分位数-分位数图,来评估拟合优度。发现位置和规模的GEV参数对TE的分段平滑,单调递增的依赖性。形状参数也随TE的增加而增加,但始终为负,这是先验总能量有界所要求的。关于最大值的选择过程,研究了统计推断的敏感性:严格分析了最大值序列的长度和计算最大值的数据块的长度所占据的作用。通过改变系统的分辨率,还探索了与模型敏感性有关的问题。提出了本文所采用的方法,作为对观测数据极端值进行统计分析,研究过去和现在的气候并表征其变化特征的严格框架。

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