STOCHASTIC COASTAL/REGIONAL UNCERTAINTY MODELLING (SCRUM) 2:
CONSISTENCY, RELIABILITY, PROBABILISTIC FORECASTING, AND CONTRIBUTION TO CMEMS ENSEMBLE DATA ASSIMILATION
PI and organization: S. Sarantis (Univ. of Athens)
Co-Is: V. Vervatis (Univ. of Athens), M Kailas (Univ. of Athens), P. de Mey (CNRS/LEGOS), N, Ayoub (CNRS/LEGOS)
Abstract: The work proposed here builds upon, and expends, the previous Service Evolution SCRUM project. It aims at strengthening CMEMS in the areas of regional/coastal ocean uncertainty modelling, Ensemble consistency verification, Ensemble probabilistic forecasting, and Ensemble data assimilation. The work is based on stochastic modelling of ocean physics and biogeochemistry, in the context of coastal/regional Ensemble Data Assimilation (EDA) forecasting systems, and includes methods suitable to assess the reliability of Ensembles in probabilistic assimilation systems. The project is designed for the Service Evolution framework within “Batch 5: cross-cutting developments on observation, assimilation and product quality improvements”. In a first step, we will revisit Ensemble generation and sensitivity analysis approaches by accounting for the age of errors and considering the oceanic response to atmospheric Ensembles. In a second step, we will (1) perform and expand our Ensemble consistency analysis to correlated observational errors, and (2) develop methods to assess the reliability of Ensembles in probabilistic assimilation systems. In addition, we wish to link this project to ongoing separate projects aimed at bringing practical improvements to the design of Ensemble data assimilation schemes. Finally, we wish to contribute to the CMEMS DA team guidance in support of upcoming decisions regarding the evolution of regional/coastal data assimilation schemes in CMEMS, engaging external experts.