Climate Dynamics

, Volume 38, Issue 1–2, pp 75–86 | Cite as

A 40-year accumulation dataset for Adelie Land, Antarctica and its application for model validation

  • Cécile Agosta
  • Vincent Favier
  • Christophe Genthon
  • Hubert Gallée
  • Gerhard Krinner
  • Jan T. M. Lenaerts
  • Michiel R. van den Broeke


The GLACIOCLIM-SAMBA (GS) Antarctic accumulation monitoring network, which extends from the coast of Adelie Land to the Antarctic plateau, has been surveyed annually since 2004. The network includes a 156-km stake-line from the coast inland, along which accumulation shows high spatial and interannual variability with a mean value of 362 mm water equivalent a−1. In this paper, this accumulation is compared with older accumulation reports from between 1971 and 1991. The mean and annual standard deviation and the km-scale spatial pattern of accumulation were seen to be very similar in the older and more recent data. The data did not reveal any significant accumulation trend over the last 40 years. The ECMWF analysis-based forecasts (ERA-40 and ERA-Interim), a stretched-grid global general circulation model (LMDZ4) and three regional circulation models (PMM5, MAR and RACMO2), all with high resolution over Antarctica (27–125 km), were tested against the GS reports. They qualitatively reproduced the meso-scale spatial pattern of the annual-mean accumulation except MAR. MAR significantly underestimated mean accumulation, while LMDZ4 and RACMO2 overestimated it. ERA-40 and the regional models that use ERA-40 as lateral boundary condition qualitatively reproduced the chronology of interannual variability but underestimated the magnitude of interannual variations. Two widely used climatologies for Antarctic accumulation agreed well with the mean GS data. The model-based climatology was also able to reproduce the observed spatial pattern. These data thus provide new stringent constraints on models and other large-scale evaluations of the Antarctic accumulation.


Mass balance Antarctica Accumulation Spatial variability Temporal variability Model validation 


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Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • Cécile Agosta
    • 1
  • Vincent Favier
    • 1
  • Christophe Genthon
    • 2
  • Hubert Gallée
    • 2
  • Gerhard Krinner
    • 2
  • Jan T. M. Lenaerts
    • 3
  • Michiel R. van den Broeke
    • 3
  1. 1.UJF-Grenoble 1 / CNRS, Laboratoire de Glaciologie et de Géophysique de l’Environnement UMR 5183Saint Martin d’Hères CedexFrance
  2. 2.CNRS / UJF-Grenoble 1, Laboratoire de Glaciologie et de Géophysique de l’Environnement UMR 5183Saint Martin d’Hères CedexFrance
  3. 3.Institute for Marine and Atmospheric Research UtrechtUtrecht UniversityUtrechtThe Netherlands

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