Seasonality of multidecadal and centennial variability in European temperatures: The wavelet approach

Citation
Nm. Datsenko et al., Seasonality of multidecadal and centennial variability in European temperatures: The wavelet approach, J GEO RES-A, 106(D12), 2001, pp. 12449-12461
Citations number
39
Categorie Soggetti
Earth Sciences
Volume
106
Issue
D12
Year of publication
2001
Pages
12449 - 12461
Database
ISI
SICI code
Abstract
Temperature variability on multidecadal and longer timescales is studied by application of the wavelet transform (WT) to seven seasonal early instrume ntal temperature series at locations in Europe. The WT spectra are computed for all four seasons of each record. A few spatiallly coherent components of temperature variability are detected on timescales longer than 60 years. All components appear seasonally dependent; the major differences in time- frequency patterns occur between late winter and early autumn. The WT-estim ated monotonic trends indicate warming in winter at all locations, with the mean rate 0.4 degreesC per century, and little change or cooling in summer . Superimposed on this monotonic trend, a quarter-millennial oscillation te nds to show the opposite phases in winter and summer, enhancing both the wi nter warming and the summer cooling trends. A regular oscillatory signal wi th a timescale of 60-80 years detected earlier in annual mean European temp eratures impacts central and eastern Europe during summer and autumn; over northwestern Europe and in Scandinavia the warm-season multidecadal signal is either weak or irregular. The cold-season temperature variations are dom inated by the centennial (similar to 120 years) rather than multidecadal ti mescales. The present WT analysis extends the earlier results based on mult ichannel singular spectrum analysis of the same data set and confirms the p resence of long timescales of variability in European temperatures; it furt her indicates the crucial role of seasonality in the spatiotemporal structu re of low-frequency temperature variability.