Cycles and trends in the Czech temperature series using wavelet transforms

Temperature variability in the Czech Republic is analyzed by means of the wavelet transform. This advanced time-frequency analysis provides information about the nature and time-frequency localization of present oscillations. The data-set comprises four mean monthly temperature series from Prague-Klementinum, Brno, Mt. Milesovka and the gridded temperature series for the Czech Republic. The results of their wavelet transforms are presented as a) trend analysis (computed by the inverse wavelet transform) and b) periodicities and oscillations (distinguishable from the series wavelet power spectra and global wavelet spectra). The results show considerable similarity among individual series. Examples are the common time period between 1930 and 2002 expressed in all power spectra, the pronounced oscillations of about 8 and 12-14 years in all series, and the noticeable increase of temperatures in all cases. As a supplement to this study, wavelet transforms were performed on the variance-adjusted version of combined land and marine temperature anomalies for the Northern Hemisphere from the Hadley Centre. Only some results of this analysis are mentioned and discussed.

[1]  R. Brázdil,et al.  An urban bias in air temperature fluctuations at the Klementinum, Prague, The Czech Republic , 1999 .

[2]  C. Torrence,et al.  A Practical Guide to Wavelet Analysis. , 1998 .

[3]  Bogumił Jakubiak,et al.  Multiscale Oscillations of the Global Climate System as Revealed by Wavelet Transform of Observational Data Time Series , 1999 .

[4]  D. Sonechkin,et al.  Seasonality of multidecadal and centennial variability in European temperatures: The wavelet approach , 2001 .

[5]  R. Thews,et al.  Wavelets in Physics , 1998 .

[6]  P. Jones,et al.  Representing Twentieth-Century Space-Time Climate Variability. Part II: Development of 1901-96 Monthly Grids of Terrestrial Surface Climate , 2000 .

[7]  van den Berg Wavelets in Physics: Contents , 1999 .

[8]  Carl Wunsch,et al.  The Interpretation of Short Climate Records, with Comments on the North Atlantic and Southern Oscillations , 1999 .

[9]  J. Hurrell Influence of variations in extratropical wintertime teleconnections on northern hemisphere temperature , 1996 .

[10]  M. Schulz,et al.  Tracing Climate-Variability: The Search for Climate Dynamics on Decadal to Millennial Time Scales , 2002 .

[11]  P. Jones,et al.  REPRESENTING TWENTIETH CENTURY SPACE-TIME CLIMATE VARIABILITY. , 1998 .

[12]  R. Voss,et al.  Multi-fingerprint detection and attribution analysis of greenhouse gas, greenhouse gas-plus-aerosol and solar forced climate change , 1997 .

[13]  J. Lean,et al.  Reconstruction of solar irradiance since 1610: Implications for climate change , 1995 .

[14]  T. D. Mitchell,et al.  Climate data for political areas , 2002 .

[15]  Douglas V. Hoyt,et al.  A discussion of plausible solar irradiance variations, 1700-1992 , 1993 .

[16]  W. Soon,et al.  Time scales and trends in the central England temperature data (1659–1990): A wavelet analysis , 1997 .

[17]  William James Burroughs,et al.  Weather Cycles: Real or Imaginary? , 1994 .

[18]  Michael E. Mann,et al.  Interannual Temperature Events and Shifts in Global Temperature: A ''Multiwavelet'' Correlation Approach , 2000 .

[19]  H. Alexandersson A homogeneity test applied to precipitation data , 1986 .

[20]  Victor J. Yohai,et al.  A Bivariate Test for the Detection of a Systematic Change in Mean , 1978 .

[21]  M. Mann Lessons for a New Millennium , 2000, Science.

[22]  A. Walden,et al.  Wavelet Methods for Time Series Analysis , 2000 .

[23]  Andrew J. Weaver,et al.  Freshwater flux forcing of decadal and interdecadal oceanic variability , 1991, Nature.

[24]  J. Marshall,et al.  Observations of atmosphere‐ocean coupling in the North Atlantic , 2001 .