Data assimilation in the ocean and coupled components

Convener: Yumeng ChenECSECS | Co-conveners: Lars Nerger, Tsuyoshi Wakamatsu, Anna Teruzzi, Ali Aydogdu

This session 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.