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

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Extra resources for Analysis of Climate Variability: Applications of Statistical Techniques

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4: Sea Surface Temperature Anomalies 39 which can even be tested when no simuItaneous information is available on the weather forcing. 11), providing more stringent signatures than the power spectra. 15) which yields the cross correlation between X and Y. When Y leads, the correlation is negligible, while when Y lags, the correlation has a maximum at smalllags. 17) = -I mr XY (I) the quadrature spectrum. ). 13) is consistent with the statistical properties of the observed anomalies of mid-Iatitude sea surface temperature, soil moisture and sea ice extent, on the monthly to yearly time scales.

Components of the climate system, its evolution can be described by two subsystems: a system for the fast "weather" variables i of short time scale t:1: (geopotential height, wind stress, ... 5: Spectrum of atmospheric variability in the North Pacific (details see text) for November through March averages for the 67 years from 1924 to 1990. 1) and the 5 and 95% confidence limits. (From Trenberth and Hurrell, 1994). 0 [T"1"T'T""'T"'T"'1rn"T'TTTT"'T"'1rrr,-rTT"T"T"I"T'T""''''''''rn''T'TTTT"'T"'1''T'T,-rT-r1 nyr.

E. there is no preferred propagation direction. 4). 2: Top: Spectrum ofsensible-plus-latent heat flux at Ocean Weather Station P (50 0 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). LATENT + SENSIBLE HEAT FLUX (OWS P, 50 o N, 145°W) 1958-1967 f" N E 210 3 ~ t ~t t t ct a: ~ u LU a.

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