Mathematics – Logic
Scientific paper
Dec 2004
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2004agufm.g34a..06k&link_type=abstract
American Geophysical Union, Fall Meeting 2004, abstract #G34A-06
Mathematics
Logic
1223 Ocean/Earth/Atmosphere Interactions (3339), 1239 Rotational Variations
Scientific paper
Variations in the rotational speed as well as in the direction of the Earth rotation axis are due to the gravitational torque exerted by the Sun, the Moon and the other planets and to the interactions between the solid Earth and the geophysical fluids, namely, the atmosphere, oceans, hydrology and the fluid core. The effects of the atmosphere on Earth rotation are classically computed using the so-called "angular momentum approach". In this method, the variations in the rotation of the Earth are estimated from the (opposite) variations in the atmospheric angular momentum (AAM). Several AAM time series are available, from different meteorological centers. However, the estimation of atmospheric effects on Earth rotation differs strongly when using one atmospheric model or the other. The purpose of our work is to build an objective criterion which justifies the use of one series in particular or one combined series. Because the atmosphere is not the only cause of Earth rotation variations, this criterion cannot rely only on a comparison of AAM series with Earth rotation data. We determine the quality of each series by making an estimation of their noise level, using a generalized formulation of the "three-cornered hat method". We show the existence of a link between the noise of the series and their correlation with Earth rotation. This link exists both between the series, a noisy series is usually less correlated with Earth rotation variations, and inside the series, when looking at the time variable noise and correlation. As the quality of the series varies in time, we construct a combined AAM series, using time dependent weights chosen so that the noise level of the combined series is minimal. To test our combined time series, we computed its correlation with Earth rotation data. We noted that the combined series is always amongst the best correlated series: the quality criterion, while totally independent on Earth rotation observations, appears to be convincing when atmospheric and Earth rotation data are intercompared.
de Viron Olivier
Dehant Véronique
Koot Laurence
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