By Antonio Navarra (auth.), Prof. Dr. Hans von Storch, Dr. Antonio Navarra (eds.)

ISBN-10: 3642085601

ISBN-13: 9783642085604

ISBN-10: 3662037440

ISBN-13: 9783662037447

Various difficulties in weather examine, which require using complex statistical concepts, are thought of during this ebook. The examples emphasize the inspiration that the information of statistical thoughts on my own isn't really enough. as an alternative, solid actual realizing of the categorical difficulties in weather learn, equivalent to the large measurement of the part house, the correlation of techniques on varied time and area scales and the supply of basically one observational checklist, is required to steer the researcher in selecting the best method of receive significant solutions. the second one variation of this publication, initially according to contributions given in the course of a faculty subsidized by way of the ecu Union at the Italian island of Elba, is still in keeping with the overall ideas that made the 1st variation a well-liked selection. the overall define has been saved an identical, masking facets resembling the exam of the observational list, stochastic weather versions, analytical concepts, e.g. EOF, teleconnections and so forth, however the chapters were revised and up to date, now and again commonly, to hide the advances within the box within the years because the first edition.

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Extra info for Analysis of Climate Variability: Applications of Statistical Techniques Proceedings of an Autumn School Organized by the Commission of the European Community on Elba from October 30 to November 6, 1993

Sample text

1) can then be set to 1 and the spectrum is white, r(k, f) = r(k,O). e. preferred propagation direction. 4). 2: Top: Spectrum of sensible-pIus-latent heat flux at Ocean Weather Station P (SO O N, 145°W) over the period 1958-1967. The error bars represent 95% confidence intervals; the continuous line shows the white noise level. Bottom: corresponding sea-surface temperature spectrum. The continuous curve is the stochastic model prediction. (From Frankignoul, 1979). 958-1967 ~N E 210 3 ~ t ~t trt

Thus, the t-test operating with the true equivalent sample size is conservative and thus wrong. More problems show up when the equivalent sample is unknown. In this case it may be possible to specify n' on the basis of physical reasoning. Assuming that conservative practices are used, this should result in underestimated values of n' and consequently even more conservative tests. In most applications, however, an attempt is made to estimate n' from the same data that are used to compute the sample mean and variance.

14), reflecting primarily the internal dynamics of the system. Stochastic climate models remain testable, however, by focusing on energy levels and, if atmospheric observations are available, cause-to-effect relationships (Muller and Frankignoul, 1981). g. by the changes in the orbital parameters of the earth), or reflect the chaotic nature of the climate subsystem. 6: SST anomaly spectrum at Ocean Weather Station I (59 0 N, 19°W) for the period 1949-1964, with 95% confidence interval. The smooth curve is the stochastic model prediction.

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Analysis of Climate Variability: Applications of Statistical Techniques Proceedings of an Autumn School Organized by the Commission of the European Community on Elba from October 30 to November 6, 1993 by Antonio Navarra (auth.), Prof. Dr. Hans von Storch, Dr. Antonio Navarra (eds.)


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