DEVELOPMENT OF AN ADVANCED ENSEMBLE-BASED OCEAN DATA ASSIMILATION APPROACH FOR OCEAN AND COUPLED REANALYSES
PI and organization: E. de Boisséson (ECMWF)
Co-Is: H. Zuo, M. Balmaseda, P. de Rosnay (ECMWF)
Abstract: The treatment of ocean observations, particularly at the air-sea interface, and air-sea fluxes is a crucial aspect of coupled ocean-atmosphere models with assimilative capability. Ocean analysis systems rely on thinning or super-observation schemes to average the information from ocean observations towards the scales resolved by the ocean model. A more extensive use of the ocean observing system can be achieved by combining perturbation techniques with an ensemble approach. In this project, an advanced assimilation methods will be developed based on a generic ensemble generation scheme with the focus on providing improved estimation of upper ocean properties by optimising treatment of ocean observations as well as atmospheric forcing fluxes. The method will improve the use of the information from the ocean observing system, assimilate more observations than conventional methods and provide uncertainty estimates. This approach will take into account the uncertainty linked to the representativeness of the observations as well as the uncertainty from the specification of the air-sea fluxes and the sea surface constraints. As a proof of concept, the method will be first applied to an ocean-only reanalysis system before being tested in an ocean-atmosphere coupled system. The uncertainty estimates will be analysed in both systems to identify the potential strengths of the ensemble approach and the impact of coupling in estimating uncertainties. The new ensemble generation method will be evaluated against independent observations, with reference to the CMEMS Global Reanalysis Ensemble Product (GREP). This study will provide a new ensemble generation method applicable to future CMEMS (re)analysis and forecast services, for both global and regional Monitoring and Forecasting Centres (MFCs).