1 11.4. 13 th WRF Users’ Workshop – 25-29 June 2012, Boulder, CO Tropical Channel NEMO-OASIS-WRF Coupled simulations at very high resolution Masson, S.*, C. Hourdin*, R. Benshila*, E. Maisonnave  , Y. Meurdesoif ★ , C. Mazauric ✪ , G. Samson  , F. Colas*, G. Madec*, R. Bourdalle-Badie  , S. Valcke  , L. Coquart  * LOCEAN-IPSL, u CERFACS, ★ LSCE-IPSL, ✪ Bull S.A, v Mercator-ocean Introduction Climate modeling has become one of the major technical and scientific challenges of the century. Numerical simulations are an indispensable approache to gather important information on numerous issues ranging from the comprehension of physical processes to climate predictability, socio-economic impacts and support to decision makers. Despite tremendous increase in computing power, current climate models resolution (~100km) is still too low to explicitly represent several key processes in the atmosphere and ocean, which must therefore be parameterized and constitute one of the main causes of systematic errors in global ocean-atmosphere coupled models (Randall et al. 2007). Small-scale processes can indeed play a key role in the variability of the climate at the global scale through the intrinsic nonlinearity of the system and the positive feedbacks associated with the ocean-atmosphere interactions. These mechanisms, known as “upscaling” processes, govern the spatial and temporal scale interactions embedded in climate variability. It is then essential to: • Identify the upscaling processes that play a key role on climate among the long list of mechanisms that are poorly or even not represented in climate models. • Quantify to what extent the explicit representation of these small-scale phenomena in climate models can contribute to reduce models errors and improve the large-scale characteristics of the climate mean state and variability as simulated by current state of the art coupled models. A large variety of misfits between observations and outputs of climate models outputs exist. However, some of these biases are systematic and common to many climate models and must therefore be the focus of the main research efforts on the impact of upscaling processes. Peta-scale supercomputers represent an inestimable opportunity to explore these questions and we propose to take up this scientific challenge in this project. However, instead of choosing the crude solution of a massive increase of the models resolution, we plan to explore new pathways toward a better representation of the multi-scale physics that drive climate variability and therefore to limit the use of the highest resolutions in limited areas. Our efforts will concentrate on key upscaling processes taking place in costal areas characterized by cold surface waters (upwelling), which hold the models strongest biases in the Tropics at local but also at basin scales Figure 1: The 5 steps of our project.