caa a22 4500 445302844 CHVBK 20180317142603.0 cr unu---uuuuu 170323e20101001xx s 000 0 eng 10.1134/S0001433810050026 doi (NATIONALLICENCE)springer-10.1134/S0001433810050026 Fortus M. Obukhov Institute of Atmospheric Physics, Russian Academy of Sciences, Pyzhevskii per. 3, 119017, Moscow, Russia aut Determining confidence intervals in analyzing climatic series [Elektronische Daten] [M. Fortus] In the context of the problem of global warming, the question of how much the observed increase in the mean air temperature over the last decades is likely due only to natural variability is studied. It is assumed that an observed temperature-data series of length N is a segment of a stationary random sequence with a spectrum known on an interval that does not include the lowest frequencies. The variance σ2(N) of the sample mean m* and the standard deviation σ(N), which determines the width of the confidence interval of m*, are calculated for different continuations of the spectrum to the low-frequency region. For a continuation of the spectrum that boundlessly increases, as does ω−2α (0 < α < 1/2) when the frequency ω tends to zero (red-noise spectrum), it is shown that, the closer the parameter α is to 1/2, the more slowly σ(N) tends to zero at N → ∞. Using an empirical spectrum of a global mean annual temperature series as an example, it is shown that the standard deviation significantly depends on the form of the spectrum in the lowest frequency region. An attempt has been made to assess the measure of standard-deviation uncertainty due to a lack of exact information on the spectrum in the low-frequency region. Important series characteristics—the equivalent number of independent observations N eq(N) and the time scale of correlation T 1(N) which are determined through the variance σ2(N) of m*—also depend on the form of the spectrum in the low-frequency region. For the red-noise spectrum, N eq(N) increases with an increase in N proportionally to N 1-2α (but not proportionally to N as in the case of bounded spectrum); the correlation scale T 1(N) is no longer constant (as in the case of bounded spectrum) and increases with an increase in N proportionally to N 2α. Pleiades Publishing, Ltd., 2010 global warming nationallicence climatic spectra nationallicence estimation of mean nationallicence Izvestiya, Atmospheric and Oceanic Physics SP MAIK Nauka/Interperiodica 46/5(2010-10-01), 563-573 0001-4338 46:5<563 2010 46 11485 https://doi.org/10.1134/S0001433810050026 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1134/S0001433810050026 text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Fortus M. Obukhov Institute of Atmospheric Physics, Russian Academy of Sciences, Pyzhevskii per. 3, 119017, Moscow, Russia aut NATIONALLICENCE 773 0- Izvestiya, Atmospheric and Oceanic Physics SP MAIK Nauka/Interperiodica 46/5(2010-10-01), 563-573 0001-4338 46:5<563 2010 46 11485 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer