Analysis of Climate Variability: Applications of Statistical by Antonio Navarra (auth.), Hans von Storch, Antonio Navarra

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

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8) There are several conceptual problems with "the" Decorrelation Time: 4This section is entirely based on the paper by Zwiers and von Storch (1995). 3. 7) of a decorrelation time makes sense when dealing with the problem 0/ the mean 0/ n-consecutive serially correlated observations. 6) by, for instance, the variance. Then, the characteristic time scale is (Trenberth, 1984): Thus characteristic time scales T depends markedly on the statistical problem under consideration. These numbers are, in general, not physically defined numbers.

Power is expressed in deeibels down from the peak at eaeh frequeney at the peak meridional wavenumber. (From Chave et al. 3: Stochastic Climate Model 35 Wavenumber spectra of tropospheric variables have been primarily estimated from hemispheric or global data derived from operational products. Some spectra have been calculated for surface variables and fiuxes, but they are difficult to interpret in view of the spatial heterogeneity of the fields and their limited spatial resolution, so that idealized representations have been constructed for air-sea inter action studies (Frankignoul and Müller, 1979).

12) is that this test operates as specified by the user provided that the interval between successive observations is long enough. The disadvantage is that a reduced amount of data is utilized in the analysis. 12) is a random variable because it differs from one pair of temperature sampies to the next. 12) is an estimate of the standard deviation of the numerator and the ratio can be thought of as an expression of the difference of means in units of estimated standard deviations. 6). For sufficiently large sampies sizes the ratio t( n* )-distribution.

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Analysis of Climate Variability: Applications of Statistical by Antonio Navarra (auth.), Hans von Storch, Antonio Navarra
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