Title: WAVELET DECOMPOSITION IN THE EARTH'S GRAVITY FIELD INVESTIGATION |
Authors: Bogusz Janusz, Klos Anna and Kosek Wieslaw |
DOI: 10.13168/AGG.2013.0004 |
Journal: Acta Geodynamica et Geomaterialia, Vol. 10, No. 1 (169), Prague 2013 |
Full Text: PDF file (3.3 MB) |
Keywords: GGP, wavelet decomposition, Earth’s gravity field changes |
Abstract: This paper presents the results of the application of wavelet decomposition to processing data from the GGP sites (The Global
Geodynamics Project). The GGP is an international project within which the Earth's gravity field changes are recorded with
high accuracy at a number of stations worldwide using superconducting gravimeters. Data with a 5-second sampling interval
from Wettzell and Bad Homburg were used for the research. The wavelet transform enables the investigation of the temporal
changes of the oscillation amplitudes or the decomposition of the time series for the analysis of the required frequencies. The
wavelet decomposition was performed using the regular orthogonal symmetric Meyer wavelet. The research concerned data
from an earthquake period recorded at various locations and a quiet period when the gravimeters worked without any
disturbances. The decomposition was followed by the Fast Fourier Transform for signal frequency components and then by
correlation analyses of corresponding frequency components (for periods from 10 to 60 000 seconds) for all sensor
combinations, for the quiet and the earthquake periods separately. Frequency components defining long term changes for all
sensor combinations, as well as combinations between two sensors at the same site for the quiet days are characterised by
high correlation coefficients. For the time of the earthquake, the Wettzell site data proved strong correlation for all frequency
components, while the Bad Homburg site data showed an unexpected decrease of correlation for the majority of frequency
components. The authors also showed that wavelet decomposition can be a good method of data interpolation, especially from
the time of earthquakes. Moreover, it is a very useful tool for filtering the data and removing the noises. |