|
|
. (2003). Identification of the ionospheric footprint of magnetospheric boundaries using SuperDARN coherent HF radars. Planetary and space science, 51, 813–820.
|
|
|
|
. (2003). Turbulence characteristics inside small-scale expanding structures observed with SuperDARN HF radars. Annales geophysicae, 21, 1839–1845.
|
|
|
|
Andre R., Pinnock M. & Rodger A.S. (1999). On SuperDARN autocorrelation function observed in the ionospheric cusp. Geophysical research letters, 26(22), 3353–3356.
|
|
|
|
Andre R., Pinnock M. & Rodger A.S. (2000). Identification of the low-altitude cusp by Super Dual Auroral Radar Network radars: a physical explanation for the empirically derived signature. J. Geophys. Res., 105(a12), 27081–27093.
|
|
|
|
. (2002). Influence of magnetospheric processes on winter HF radar spectra characteristics. Annales geophysicae, 20, 1783–1793.
|
|
|
|
Andre R., Villain J.P., Krassnosel'skikh V. & Hanuise C. (2000). Super dual aurora radar network observations of velocity-divergent structures in the F region ionosphere. J. Geophys. Res., 105(a9), 20899–20908.
|
|
|
|
Andre R., Villain J.P., Senior C., Barthes L., Hanuise C., Cerisier J.C. & Thorolfsson A. (1999). Toward resolving small-scale structures in ionospheric convection from SuperDARN. Radio science, 34(5), 1165–1176.
|
|
|
|
Andrea Berbellini, Martin Schimmel, Ana MG Ferreira, Andrea Morelli. (2018). Constraining S-wave velocity using Rayleigh wave ellipticity from polarization analysis of seismic noise (Vol. 216). Bachelor's thesis, , .
Abstract: SUMMARY. We develop a new method for measuring ellipticity of Rayleigh waves from ambient noise records by degree-of-polarization (DOP) analysis. The new method, named DOP-E, shows a good capability to retrieve accurate ellipticity curves separated from incoherent noise. In order to validate the method we perform synthetic tests simulating noise in a 1-D earth model. We also perform measurements on real data from Antarctica and Northern Italy. Observed curves show a good fit with measurements from earthquake records and with theoretical ellipticity curves. The inversion of real data measurements for vS structure shows a good agreement with previous models. In particular, the shear-wave structure beneath Concordia station shows no evidence of a significant layer of liquid water at the base of the ice. The new method can be used to measure ellipticity at high frequency and therefore it will allow the imaging of near-surface structure, and possibly of temporal changes in subsurface properties. It promises to be useful to study near-surface processes in a wide range of geological settings, such as volcanoes, fault zones and glaciers.
Programme: 133
|
|
|
|
. (2019). Exploring the link between microseism and sea ice in Antarctica by using machine learning (Vol. 9).
Abstract: The most continuous and ubiquitous seismic signal on Earth is the microseism, closely related to ocean wave energy coupling with the solid Earth. A peculiar feature of microseism recorded in Antarctica is the link with the sea ice, making the temporal pattern of microseism amplitudes different with respect to the microseism recorded in low-middle latitude regions. Indeed, during austral winters, in Antarctica the oceanic waves cannot efficiently excite seismic energy because of the sea ice in the Southern Ocean. Here, we quantitatively investigate the relationship between microseism, recorded along the Antarctic coasts, and sea ice concentration. In particular, we show a decrease in sea ice sensitivity of microseism, due to the increasing distance from the station recording the seismic signal. The influence seems to strongly reduce for distances above 1,000?km. Finally, we present an algorithm, based on machine learning techniques, allowing to spatially and temporally reconstruct the sea ice distribution around Antarctica based on the microseism amplitudes. This technique will allow reconstructing the sea ice concentration in both Arctic and Antarctica in periods when the satellite images, routinely used for sea ice monitoring, are not available, with wide applications in many fields, first of all climate studies.
Programme: 133
|
|
|
|
Andrea Chiang, Gene A. Ichinose, Doug S. Dreger, Sean R. Ford, Eric M. Matzel, Steve C. Myers, W. R. Walter. (2018). (Vol. 89). Bachelor's thesis, , .
|
|
