Coupled data assimilation for climate prediction: a focus on ocean-atmosphere coupling (PhD thesis)

Lilian Carolina Garcia Oliva (2024-10-17): Coupled data assimilation for climate prediction: a focus on ocean-atmosphere coupling. PhD thesis, University of Bergen, Bergen, Norway. https://hdl.handle.net/11250/3157446

Summary: Seasonal-to-Decadal (S2D) climate predictions can provide decision-making information for diverse sectors, such as food security, energy and climate adaptation. The initial condition of the ocean is fundamental for providing skilful S2D predictions. A method to estimate the ocean’s initial condition is by merging the model and observations through a process called Coupled Data Assimilation (CDA). Ocean observations have demonstrated their potential to achieve skilful prediction. The Norwegian Climate Prediction Model (NorCPM) features an advanced Ocean Data Assimilation (ODA) scheme based on an ensemble method. This thesis outlines our efforts to improve S2D predictions within the NorCPM using atmospheric observations.

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