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Communication Dans Un Congrès Année : 2017

Exploiting ocean observation and simulation big data to improve satellite-derived geophysical products: Analog strategies

Résumé

The ever increasing geophysical data streams pouring from earth observation satellite missions and numerical simulations along with the development of dedicated big data infrastructure advocate for truly exploiting the potential of these datasets, through novel data-driven strategies, to deliver enhanced satellite-derived geophysical products from partial satellite observations. We here demonstrate a proof-of-concept of the analog data assimilation for an application to the reconstruction of cloud-free level-4 gridded Sea Surface Temperature (SST) fields. Our results point out the relevance of big-data-oriented analog strategies to benefit from large-scale observation and/or simulation datasets for enhanced satellite-derived geophysical products.
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Dates et versions

hal-01801014 , version 1 (28-05-2018)

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  • HAL Id : hal-01801014 , version 1

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Ronan Fablet, Phi Huynh Viet, Redouane Lguensat, Bertrand Chapron. Exploiting ocean observation and simulation big data to improve satellite-derived geophysical products: Analog strategies. BiDS'17: Big Data from Space Conference , Nov 2017, Toulouse, France. ⟨hal-01801014⟩
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