/pdf/statistical-analysis-in-climate-research-51ik9f04rx.pdf

Statistical Analysis in Climate Research

[1] The analysis of univariate or multivariate time series provides crucial information to describe, understand, and predict climatic variability. The discovery and implementation of a number of novel methods for extracting useful information from time series has recently revitalized this classical field of study. Considerable progress has also been made in interpreting the information so obtained in terms of dynamical systems theory. In this review we describe the connections between time series analysis and nonlinear dynamics, discuss signal-to-noise enhancement, and present some of the novel methods for spectral analysis. The various steps, as well as the advantages and disadvantages of these methods, are illustrated by their application to an important climatic time series, the Southern Oscillation Index. This index captures major features of interannual climate variability and is used extensively in its prediction. Regional and global sea surface temperature data sets are used to illustrate multivariate spectral methods. Open questions and further prospects conclude the review.

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Advanced spectral methods for climatic time series

Singular-spectrum analysis: a toolkit for short, noisy chaotic signals

Climate and weather constitute a typical example where high dimensional and complex phenomena meet. The atmospheric system is the result of highly complex interactions between many degrees of freedom or modes. In order to gain insight in understanding the dynamical/physical behaviour involved it is useful to attempt to understand their interactions in terms of a much smaller number of prominent modes of variability. This has led to the development by atmospheric researchers of methods that give a space display and a time display of large space-time atmospheric data.



Empirical orthogonal functions (EOFs) were first used in meteorology in the late 1940s. The method, which decomposes a space-time field into spatial patterns and associated time indices, contributed much in advancing our knowledge of the atmosphere. However, since the atmosphere contains all sorts of features, e.g. stationary and propagating, EOFs are unable to provide a full picture. For example, EOFs tend, in general, to be difficult to interpret because of their geometric properties, such as their global feature, and their orthogonality in space and time. To obtain more localised features, modifications, e.g. rotated EOFs (REOFs), have been introduced. At the same time, because these methods cannot deal with propagating features, since they only use spatial correlation of the field, it was necessary to use both spatial and time information in order to identify such features. Extended and complex EOFs were introduced to serve that purpose.



Because of the importance of EOFs and closely related methods in atmospheric science, and because the existing reviews of the subject are slightly out of date, there seems to be a need to update our knowledge by including new developments that could not be presented in previous reviews. This review proposes to achieve precisely this goal. The basic theory of the main types of EOFs is reviewed, and a wide range of applications using various data sets are also provided. Copyright © 2007 Royal Meteorological Society

Empirical orthogonal functions and related techniques in atmospheric science: A review

Asian–Australian monsoon (A–AM) anomalies depend strongly on phases of El Nino (La Nina). Based on this distinctive feature, a method of extended singular value decomposition analysis was developed to analyze the changing characteristics of A–AM anomalies during El Nino (La Nina) from its development to decay. Two off-equatorial surface anticyclones dominate the A–AM anomalies during an El Nino—one over the south Indian Ocean (SIO) and the other over the western North Pacific (WNP). The SIO anticyclone, which affects climate conditions over the Indian Ocean, eastern Africa, and India, originates during the summer of a growing El Nino, rapidly reaches its peak intensity in fall, and decays when El Nino matures. The WNP anticyclone, on the other hand, forms in fall, attains maximum intensity after El Nino matures, and persists through the subsequent spring and summer, providing a prolonged impact on the WNP and east Asian climate. The monsoon anomalies associated with a La Nina resemble those durin...

/pdf/atmosphere-warm-ocean-interaction-and-its-impacts-on-asian-30e33ltaoz.pdf

Atmosphere-Warm Ocean Interaction and Its Impacts on Asian-Australian Monsoon Variation*

An extended empirical orthogonal function analysis technique is described which expands a data set in terms of functions which are the “best” representation of that data set for a sequence of time points. The method takes advantage of the fact that geophysical fields are often significantly correlated in both space and time. Two examples of applications of this technique are given which suggest it may be a highly useful tool for diagnosing the modes of variation of dominant sequences of events. In the first, an analysis of 300 mb relative vorticity, fairly regular advection of the major features of the spatial patterns is evident. Westward speeds of between 0.3 and 0.4 m s−1 are inferred. The second example illustrates extended functions of tropical Pacific Ocean surface temperatures. The dominant function, which is associated with El Nino, shows a high degree of persistence over a six-month sequence. The second most important function suggests opposing variations in the influences of the North a...

Examples of Extended Empirical Orthogonal Function Analyses

An automated PIXE system was used to determine the elemental concentrations on particulate samples collected in a monitoring network of 40 remote sites covering 2 million square kilometers in the western United States from 1979 to 1981 PIXE's good sensitivity for sulfur permitted the measurement of this key element in a region of low concentrations Sulfate particles comprise the major component of the fine mass and represent the largest threat to visibility in the region Two cases of sulfate transport into the pristine, scenic areas of northern Arizona and southern Utah from sources around 600 km away are described: copper smelters to the south and urban center to the southwest Evidence is also presented for the transport of sulfate to the northern Great Plains from industrial centers over 1000 km to the east The simultaneous measurement of a wide range of elements by PIXE has permitted estimates of the conversion rates of SO2 to sulfate in a clean, dry atmosphere The most important result was the large variation between summer and winter This indicates that SO2 emissions in winter are much less serious than similar emissions in summer

John S. Nasstrom

Papers

Examples of Extended Empirical Orthogonal Function Analyses

Long range transport and transformation of anthropogenic pollutants observed in a PIXE-based monitoring network

A technique for determining regional scale flow and precipitation patterns upwind of a receptor site