Analysis of the mid-latitude weather regimes in the 200-year control integration of the SINTEX model
Analysis of the mid-latitude weather regimes in the 200-year control integration of the SINTEX model
复制标题
SINTEX模式200年控制积分中的中纬度天气状况分析
DOI：
10.4401/ag-3386
复制
发表时间：
2003
影响因子：
1
通讯作者：
A. Navarra
中科院分区：
文献类型：
--
作者：
S. Corti;S. Gualdi;A. Navarra
最近的结果表明，气候预测需要能够准确模拟自然循环的模式
制度及其相关的可变性。本研究的主要目的是调查是否（以及如何）
耦合模式能较好地模拟真实的世界天气状况。耦合GCM的200年控制集成
(the«SINTEX模型»）。分析的输出包括北方半球的月平均值
冬季（11月至4月）500百帕位势高度延长。一个经验正交函数（英文）
首先应用分析，以便基于可变性的主导模式来定义缩减的相空间。因此
计算由两个前导EOF跨越的缩减相空间中的主分量PDF。基于
PDF分析的相空间跨越的领先EOF1和REOF2，大量的证据，非高斯
发现了SINTEX北方冬季环流的区域结构，
函数（PDF）显示三个最大值。这些密度极大值的500百帕高度地理分布是
强烈地让人联想到北方半球的天气状况。这个结果表明
SINTEX模式不仅能模拟气候吸引子的非高斯结构，
再现系统的自然变化模式。
Recent results indicate that climate predictions require models which can simulate accurately natural circulation
regimes and their associated variability. The main purpose of this study is to investigate whether (and how) a
coupled model can simulate the real world weather regimes. A 200-year control integration of a coupled GCM
(the «SINTEX model») is considered. The output analysed consists of monthly mean values of Northern Hemisphere
extended winter (November to April) 500-hPa geopotential heights. An Empirical Orthogonal Function (EOF)
analysis is first applied in order to define a reduced phase space based on the leading modes of variability. Therefore
the principal component PDF in the reduced phase space spanned by two leading EOFs is computed. Based on a
PDF analysis in the phase space spanned by the leading EOF1 and REOF2, substantial evidence of the nongaussian
regime structure of the SINTEX northern winter circulation is found. The model Probability Density
Function (PDF) exhibits three maxima. The 500-hPa height geographical patterns of these density maxima are
strongly reminiscent of well-documented Northern Hemisphere weather regimes. This result indicates that the
SINTEX model can not only simulate the non-gaussian structure of the climatic attractor, but is also able to
reproduce the natural modes of variability of the system.