Antarctic surface mass balance and systematic biases in general circulation models

• Published in: Journal of Geophysical Research: Atmospheres
• Main Authors: Genthon, Christophe, Krinner, Gerhard
• Other Authors: Laboratoire de glaciologie et géophysique de l'environnement (LGGE), Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB Université de Savoie Université de Chambéry )-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB Université de Savoie Université de Chambéry )-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2001
• Subjects: [SPI.MECA.STRU]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Structural mechanics [physics.class-ph]; Antarctic; The Antarctic; Antarc*; Antarctica
• Online Access: https://hal.science/hal-02915222; https://hal.science/hal-02915222/document; https://hal.science/hal-02915222/file/2001JD900136.pdf; https://doi.org/10.1029/2001JD900136

International audience Atmospheric general circulation models (GCMs) simulate two of the main components of the Antarctic surface mass balance (SMB), precipitation and sublimation, which are generally assumed to dominate the SMB. Resemblances between the Antarctic SMB simulated by seven different GCMs run at high (≈100–200 km) resolution, and differences with a recently produced observation‐based map are analyzed. A number of these differences are common to all seven models. They are called systematic model biases and are summarized as a composite of all seven models. It is found unlikely that higher model resolution would significantly affect the systematic biases. All but one of the models studied here use an inaccurate prescribed topography of Antarctica, with errors as large as 1000 m. Although wrong topography does not seem to consistently explain model SMB biases, it is strongly recommended that the Antarctic topography in GCMs be updated. Wind erosion and drifting snow are not simulated in GCMs. Because the processes of wind erosion are complex and nonlinear, evaluation of its possible contribution to systematic model biases is not straightforward. Partial correspondence between regions of strongest winds and model biases suggest that wind erosion may contribute and should be formulated in GCMs. Sublimation is another significant potential negative term in the SMB of Antarctica, but it does not seem to explain any systematic model bias. Finally, it is proposed that some of the systematic differences between models and observation‐based maps actually signal errors in the latter rather than in the models. These errors occur in regions devoid of field observation. They may thus be related to the process of interpolation used to build the SMB maps.