This session merges the "Applications of ocean reanalyses and reconstructions" session and "'Data assimilation in the ocean and coupled components":
Ocean reanalyses are reconstructions of the recent state of the ocean, using all available observational datasets together with models. They are necessary tools for understanding ocean and climate dynamics and studying the evolution of recent ocean and climate change. They are also used to derive climatologies and anomalies for applied studies, initialisation of forecasts, and training for deep learning applications.
This session aims at deepening our understanding of the way reanalyses are used by the scientific community, by providing a forum for ocean reanalysis producers and users. The session will focus, among others, on the following applications:
- Reanalyses intercomparison studies to understand the strengths and limitations of these data
- Impact of long-term observations on reanalyses quality as well as potential uncertainties stemming from the lack of such observations.
- Representation, analysis and dynamical interpretation of specific events such as extremes.
- Synergies with deep learning applications for ocean reanalyses
The outcome of the session will provide useful insights to ocean reanalysis producers for further developments to meet the community’s needs for their applications.
Data Assimilation:
This session also focuses on recent developments and research on ocean data assimilation. Data assimilation is essential for ocean forecasting, reanalysis, and climate studies. By optimally combining numerical simulations with various observations, data assimilation provides a dynamically consistent and comprehensive estimate of the present and past ocean state. This session invites abstract submissions on developments of data assimilation for the physical ocean together with coupled components such as sea ice, marine ecosystems, land-sea interface and atmosphere for ensuring consistency with other parts of the Earth system. The session also focuses on impact of the assimilation and deployment of novel space-borne and in-situ observations such as autonomous platforms, wide-swath satellite tracks, and deep in-situ observations and biogeochemistry profilers.
Beyond state estimation, this session also welcomes contributions in parameter estimation, uncertainty quantification, and hybrid machine learning and data assimilation methods focused on the ocean.