Interprétation des séries temporelles altimétriques sur la calotte polaire Antarctique
This work aims at improving our understanding of the altimetric time series acquired over the Antarctic Ice Sheet. Dual frequency data (S Band - 3.2GHz and Ku Band - 13.6GHz) from the altimeter onboard the ENVISAT satellite are used, during a five year time period from january 2003 until december 20...
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Other Authors: | , , , , , , , |
Format: | Doctoral or Postdoctoral Thesis |
Language: | French |
Published: |
HAL CCSD
2009
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Subjects: | |
Online Access: | https://tel.archives-ouvertes.fr/tel-01018319 https://tel.archives-ouvertes.fr/tel-01018319/document https://tel.archives-ouvertes.fr/tel-01018319/file/Parouty_Soazig.pdf |
Summary: | This work aims at improving our understanding of the altimetric time series acquired over the Antarctic Ice Sheet. Dual frequency data (S Band - 3.2GHz and Ku Band - 13.6GHz) from the altimeter onboard the ENVISAT satellite are used, during a five year time period from january 2003 until december 2007. These data cover around 80% of the surface of the Antarctic continent, up to 82°S. Having data in two different frequencies is valuable when it comes to better estimate the altimeter sensitivity regarding snow surface property changes. Over the Antarctic ice sheet, snow surface changes with respect to space and time, being affected by meteorological conditions close to the surface, and especially winds. The altimetric wave penetrates more or less deeply beneath the surface, depending on snow surface and subsurface properties. As a result, when the wave comes back to the satellite, the recorded signal, named waveform, is more or less distorted. The accuracy of the ice sheet topographic changes computed thanks to satellite altimetric techniques depends on our knowledge of the processes inducing this distortion. The purpose of the present work is to better understand the effect of changing wind conditions on altimetric data. Winds in Antarctica are indeed famous for their strength and their impact on the snow surface state. First, spatial and temporal variability of the altimetric data on the one hand, and of wind speed reanalysis fields (from ERA-Interim, NCEP/NCAR and NCEP/DOE projects) on the other hand are studied. We estimate spatial and temporal typical length scales for all datasets. As a result, we are able to smooth the data, so that all datasets have the same spatial and temporal caracterictic length scales. Furthermore, we note that our time series are well described by an annual signal. This annual cycle shows that whereas wind speed would always be maximum in austral winter, altimetric seasonal cycles have very different behaviors depending on the location. Basically, two main large areas arise that ... |
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