2013
DOI: 10.5194/gmd-6-929-2013
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The SURFEXv7.2 land and ocean surface platform for coupled or offline simulation of earth surface variables and fluxes

Abstract: Abstract. SURFEX is a new externalized land and ocean surface platform that describes the surface fluxes and the evolution of four types of surfaces: nature, town, inland water and ocean. It is mostly based on pre-existing, well-validated scientific models that are continuously improved. The motivation for the building of SURFEX is to use strictly identical scientific models in a high range of applications in order to mutualise the research and development efforts. SURFEX can be run in offline mode (0-D or 2-D… Show more

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Cited by 631 publications
(589 citation statements)
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References 227 publications
(263 reference statements)
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“…Within the modeling platform SURFEX (EXTernalized land and ocean SURFace platform) (Masson et al, 2013), the Crocus snowpack model (Brun et al, 1992;Vionnet et al, 2012) was run in a stand-alone mode, using meteorological forcing data from ERA-Interim. The ERA-Interim total precipitation was turned into snowfall at temperatures below 1 • C and into rainfall above.…”
Section: Surface Temperature Simulation Using Crocus Snowpack Modelmentioning
confidence: 99%
“…Within the modeling platform SURFEX (EXTernalized land and ocean SURFace platform) (Masson et al, 2013), the Crocus snowpack model (Brun et al, 1992;Vionnet et al, 2012) was run in a stand-alone mode, using meteorological forcing data from ERA-Interim. The ERA-Interim total precipitation was turned into snowfall at temperatures below 1 • C and into rainfall above.…”
Section: Surface Temperature Simulation Using Crocus Snowpack Modelmentioning
confidence: 99%
“…Based on the tiling approach, SURFEX (SURFace EXTernalisée in French) is the externalised land-surface modelling system (Salgado and Moigne, 2010;Masson et al, 2012) that has been developed at Meteo-France. It can be run in a coupled way with different meteorological models, e.g., the Meso-NH research model (Lafore et al, 1998) or the AROME weather forecasting model (Seity et al, 2011), as well as in offline configuration using atmospheric forcing coming from analyses or observation at a given height above the top of the canopy.…”
Section: Introductionmentioning
confidence: 99%
“…Cela est indispensable afin de bien représenter l'impact des événements extrêmes comme les sécheresses agricoles. Aujourd'hui, les indicateurs de sécheresse agricole produits par Météo-France proviennent de simulations numériques de l'humidité du sol réalisées grâce à la plateforme de modélisation Surfex (surface externalisée) (Masson et al, 2013). Des recherches ont été menées af in d'évaluer l'impact de l'intégration de données satellitaires dans Surfex sur le suivi des sécheresses.…”
Section: Suivi Des Sécheressesunclassified