We have studied long-time daily temperature records (between 56 and 218 years) obtained from 12 meteorological stations in Europe and North America from various climatological zones. To analyse the fluctuations of the daily temperatures around their average values, we have calculated directly the autocorrelation function C(ℓ) between two days separated by ℓ days, and applied also random-walk fluctuation analysis and wavelets methods, which can systematically overcome non-stationarities in the data. In addition, we have also analysed the distribution of the daily temperature fluctuations, which in most cases is well approximated by a Gaussian. Our analysis suggests that the persistence, characterized by the autocorrelation function C(ℓ), is long ranged and approximately decays with a power law C(ℓ) ≃ ℓ-γ, with roughly the same exponent γ ≈ 2/3 for all stations considered. This universal persistence law seems to be valid at least for one decade of years, but we cannot exclude the possibility that the range of the power-law correlations even exceeds the range of the temperature series considered. © 1998 Taylor and Francis Group, LLC.
Koscielny-Bunde, E., Roman, H., Bunde, A., Havlin, S., Schellnhuber, H. (1998). Long-range power-law correlations in local daily temperature fluctuations. PHILOSOPHICAL MAGAZINE. B. PHYSICS OF CONDENSED MATTER. STATISTICAL MECHANICS, ELECTRONIC, OPTICAL AND MAGNETIC PROPERTIES, 77(5), 1331-1340 [10.1080/13642819808205026].
Long-range power-law correlations in local daily temperature fluctuations
Roman H. E.;
1998
Abstract
We have studied long-time daily temperature records (between 56 and 218 years) obtained from 12 meteorological stations in Europe and North America from various climatological zones. To analyse the fluctuations of the daily temperatures around their average values, we have calculated directly the autocorrelation function C(ℓ) between two days separated by ℓ days, and applied also random-walk fluctuation analysis and wavelets methods, which can systematically overcome non-stationarities in the data. In addition, we have also analysed the distribution of the daily temperature fluctuations, which in most cases is well approximated by a Gaussian. Our analysis suggests that the persistence, characterized by the autocorrelation function C(ℓ), is long ranged and approximately decays with a power law C(ℓ) ≃ ℓ-γ, with roughly the same exponent γ ≈ 2/3 for all stations considered. This universal persistence law seems to be valid at least for one decade of years, but we cannot exclude the possibility that the range of the power-law correlations even exceeds the range of the temperature series considered. © 1998 Taylor and Francis Group, LLC.
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