- 1Institute of Oceanology PAS, Marine Dynamics Department, Sopot, Poland (jjakacki@iopan.gda.pl)
- 2Institute of Geodesy and Geoinformation, University of Bonn, Bonn, Germany (fenoglio@geod.uni-bonn.de)
- 3GEOMAR, Germany (alehmann@geomar.de)
- 4Albavador, Spain (rafael.catany@albavalor.es)
- 5ACRI-ST, France (marine.bretagnon@acri-st.fr)
- 6Nansen Environmental and Remote Sensing Center, Bergen, Norway (Laurent.Bertino@nersc.no)
- 7European Space Agency (roberto.sabia@esa.int)
Modern satellite data offer powerful and unprecedented tools for monitoring the marine environment on a global scale. However, due to their inherent nature, these observations are predominantly limited to the sea surface, thus providing only a partial understanding of the marine ecosystem. This limitation can be addressed by integrating numerical models (NMs), which represent the physical processes in the marine environment through mathematical equations.
The 4D BaltDyn project aims to develop four-dimensional physical and bio-geochemical parameters by merging advanced satellite earth observation data with numerical models and AI methods. Firstly, the project will develop new SSH, SSS and ocean color products that will be later used in the assimilation and development of 4D (x,y,z,t) fields. In this study, we employ three principal models together with novel ML and AI methods used for the 4D reconstruction of ocean currents, temperature, salinity, oxygen, chlorophyll-a and nutrients:
- The Coupled Sea Ice-Ocean Model of the Baltic Sea (BSIOM - GEOMAR): Utilized to improve the general representation of salinity distribution by nudging a new product in the coupled model.
- The 3D Coupled Ecosystem Model of the Baltic Sea (CEMBS - IOPAN): Based on the Community Earth System Model (CESM), this model will be adapted for assimilating sea surface temperature and chlorophyll-a data.
- Recently developed Climate and Environmental Modelling System (CEMS - IOPAN, current version consists of coupled Community Ice CodE (CICE) to Regional Ocean Modelling System (ROMS)): Applied to enhance the barotropic components of numerical models.
- SOCA- Artificial intelligence method adapted for merging satellite observations and BGC-Argo floats for estimation of the vertical structure of particulate backscattering coefficient
All these models will incorporate satellite data developed within the framework of the project consortium. By integrating satellite and modeling data, we aim to create one of the most accurate reanalyzed datasets to date, surpassing the quality of currently available datasets.
The poster will present preliminary results, focusing on the adapted methodologies. Given the well-known advantages and limitations of both satellite data and numerical model outputs, we anticipate significant improvements, which will be showcased in this work.
The results are a part of the 4D BaltDyn project. Study financed by the European Space Agency, project number 4000143924/24/I-DT
How to cite: Jakacki, J., Darecki, M., Muzyka, M., Bulczak, A., Rak, D., Dzierzbicka-Głowacka, L., Janecki, M., Nowicki, A., Dybowski, D., Fenoglio, L., Chen, J., Lehmann, A., Catany, R., Bretagnon, M., Bertino, L., Prat, A., Jutard, Q., and Sabia, R.: Reconstruction of the Spatial Physical and Bio-Geochemical Fields based on of earth observations, numerical modeling and AI methods within the framework of 4DBaltDyn ESA project, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12195, https://doi.org/10.5194/egusphere-egu25-12195, 2025.
