Periodic Reporting for period 2 - SEAMLESS (Services based on Ecosystem data AssiMiLation: Essential Science and Solutions)
Okres sprawozdawczy: 2022-01-01 do 2023-12-31
The ocean provides us with vital climate services and food resources, by absorbing 30% of anthropogenic carbon emissions and supplying 17% of animal proteins to the world’s population. However, state-of-the-art operational centers such as the Copernicus Marine Service (CMEMS) are still challenged by accurately estimating these services by means of operational models.
The main aim of SEAMLESS is to develop ensemble methods to provide the CMEMS Monitoring and Forecasting Centres (MFCs) with unprecedented capabilities to deliver indicators of climate-change impacts and food security in ocean ecosystems, such as particulate carbon export and plankton phenology.
SEAMLESS has developed entirely new - or advanced the existing - ensemble methods within the CMEMS MFCs and has demonstrated that such methods can help improving the prediction of a range of essential marine ecosystem indicators, either already provided by CMEMS, or offered to CMEMS as new products. SEAMLESS has shown that ensemble methods can provide major advances to CMEMS’s systems through (i) better representing forecast uncertainties, (ii) improving capability to combine physical and biogeochemical predictions, (iii) better merging observations from variety of sources (satellites, in situ) and (iv) improving model dynamics through better parametrization.
The main aim of SEAMLESS is to develop ensemble methods to provide the CMEMS Monitoring and Forecasting Centres (MFCs) with unprecedented capabilities to deliver indicators of climate-change impacts and food security in ocean ecosystems, such as particulate carbon export and plankton phenology.
SEAMLESS has developed entirely new - or advanced the existing - ensemble methods within the CMEMS MFCs and has demonstrated that such methods can help improving the prediction of a range of essential marine ecosystem indicators, either already provided by CMEMS, or offered to CMEMS as new products. SEAMLESS has shown that ensemble methods can provide major advances to CMEMS’s systems through (i) better representing forecast uncertainties, (ii) improving capability to combine physical and biogeochemical predictions, (iii) better merging observations from variety of sources (satellites, in situ) and (iv) improving model dynamics through better parametrization.
The key, overall outcomes of the project are the following:
• We developed three cutting-edge ensemble data assimilation systems (for the Mediterranean Sea North West Shelf and Baltic) and advanced further two existing ensemble data assimilation systems (for the Arctic Sea, the North East Atlantic/Global ocean) for the coupled physical-biogeochemical model used by the CMEMS MFCs;
• We produced a list of biogeochemical variables and ecosystem indicators of which we have assessed the technological readiness level for future possible production in CMEMS.
• We produced, disseminated and trained both experts and Early Career Oceanographer on the use of a novel, unique, free tool for the assimilation of biogeochemical observations in the biogeochemical models of CMEMS, in one- user-friendly one-dimensional water-column configurations, which is freely available here: https://github.com/BoldingBruggeman/eat/wiki;
• We provided a detailed list of expert recommendations, in the form of reports, on key aspects of designing and setting-up biogeochemical observational, modelling and ensemble assimilation systems (e.g. on design of biogeochemical model ensembles, (ii) combined in situ/satellite data assimilation, (iii) joint physical/biogeochemical data assimilation, joint (iv) biogeochemical/state parameter estimation)
• We provided CMEMS with a detailed roadmap for the uptake and implementation of the SEAMLESS innovation in their operational Monitoring and Forecasting Centers
These outcomes were achieved through the following work and results during the last reporting period:
• Completed the configuration of the prototype data assimilation tools for the 1D sites as well as the further enhancements of the data assimilation functionality and public delivery with full documentation
• Finalized the development and testing of the ensemble generation and assimilation methods identified in WP3 for biogeochemical estimation including uncertainties
• Assessed the observability/controllability properties of ten relevant SEAMLESS ecosystem indicators. Recommendations were formulated as guidelines to help the CMEMS teams in the future upgrade of their systems
• Evaluated pros and cons of weakly and strongly coupled assimilation with the new ensemble assimilation systems developed in SEAMLESS
• Performed and assessed benefits of joint assimilation of biogeochemical data from in situ and remote sensing platforms
• Developed joint state-parameter estimation and performed multiannual reanalysis of the indicators with the optimal configurations of the ensemble data assimilation systems
• Delivered a detailed roadmap for the transfer of the SEMLESS R&D to the Copernicus Marine Service
SEAMLESS researchers have actively participated in various working groups and task forces, including the CMEMS Science and Technology Advisory Board meetings, CMEMS biogeochemical Data Assimilation working group, the Ocean Predict Marine Ecosystem Analysis and Prediction Task Team, the The Mediterranean Oceanographic Network for the Global Ocean Observing System, the CMEMS Arctic Monitoring Forecasting Centre, and CMEMS Mediterranean Monitoring Forecasting Centre. Their concerted efforts have effectively heightened awareness within the community regarding the significant potential of SEAMLESS biogeochemical data assimilation in addressing contemporary technological and societal challenges.
The SEAMLESS Roadmap delineates timelines for MFCs to integrate new codes and algorithms for ensemble generation, assimilation, and ecosystem indicators. This integration is expected to enhance the characterization of marine biogeochemical and ecosystem indicators through novel model parameterizations and data assimilation techniques.
In close collaboration with the project’s Entrusted Entity, Mercator Ocean International, presentations and outcomes were disseminated at several pivotal strategic events, including the "Biodiversity in Coastal Ecosystems" organized by EC DEFIS in October 2022, and the Digital Twin Ocean Forum in April 2022. These initiatives aimed to assess the potential future incorporation of project outcomes into the European strategy for the Green Deal and the EU Mission Restore our Ocean and Waters in particular.
SEAMLESS partners actively shared and promoted their work through numerous external engagement activities from 2021 to 2023, including the organization of conferences and workshops. Researchers expanded their networks and disseminated results through participation in 80 international conferences and workshops, in addition to sharing findings through the project website and social media channels. Furthermore, SEAMLESS successfully fulfilled its objectives of training future users and the next generation of ecosystem modelers in the utilization of SEAMLESS tools and software through various hands-on and online training courses, reaching over 140 external participants.
With a total of 28 publicly available outputs, including 11 peer-reviewed publications, a book chapter, and key project documentation, SEAMLESS has made substantial contributions to the field. These resources are readily accessible through the project website, ensuring broad dissemination and accessibility.
• We developed three cutting-edge ensemble data assimilation systems (for the Mediterranean Sea North West Shelf and Baltic) and advanced further two existing ensemble data assimilation systems (for the Arctic Sea, the North East Atlantic/Global ocean) for the coupled physical-biogeochemical model used by the CMEMS MFCs;
• We produced a list of biogeochemical variables and ecosystem indicators of which we have assessed the technological readiness level for future possible production in CMEMS.
• We produced, disseminated and trained both experts and Early Career Oceanographer on the use of a novel, unique, free tool for the assimilation of biogeochemical observations in the biogeochemical models of CMEMS, in one- user-friendly one-dimensional water-column configurations, which is freely available here: https://github.com/BoldingBruggeman/eat/wiki;
• We provided a detailed list of expert recommendations, in the form of reports, on key aspects of designing and setting-up biogeochemical observational, modelling and ensemble assimilation systems (e.g. on design of biogeochemical model ensembles, (ii) combined in situ/satellite data assimilation, (iii) joint physical/biogeochemical data assimilation, joint (iv) biogeochemical/state parameter estimation)
• We provided CMEMS with a detailed roadmap for the uptake and implementation of the SEAMLESS innovation in their operational Monitoring and Forecasting Centers
These outcomes were achieved through the following work and results during the last reporting period:
• Completed the configuration of the prototype data assimilation tools for the 1D sites as well as the further enhancements of the data assimilation functionality and public delivery with full documentation
• Finalized the development and testing of the ensemble generation and assimilation methods identified in WP3 for biogeochemical estimation including uncertainties
• Assessed the observability/controllability properties of ten relevant SEAMLESS ecosystem indicators. Recommendations were formulated as guidelines to help the CMEMS teams in the future upgrade of their systems
• Evaluated pros and cons of weakly and strongly coupled assimilation with the new ensemble assimilation systems developed in SEAMLESS
• Performed and assessed benefits of joint assimilation of biogeochemical data from in situ and remote sensing platforms
• Developed joint state-parameter estimation and performed multiannual reanalysis of the indicators with the optimal configurations of the ensemble data assimilation systems
• Delivered a detailed roadmap for the transfer of the SEMLESS R&D to the Copernicus Marine Service
SEAMLESS researchers have actively participated in various working groups and task forces, including the CMEMS Science and Technology Advisory Board meetings, CMEMS biogeochemical Data Assimilation working group, the Ocean Predict Marine Ecosystem Analysis and Prediction Task Team, the The Mediterranean Oceanographic Network for the Global Ocean Observing System, the CMEMS Arctic Monitoring Forecasting Centre, and CMEMS Mediterranean Monitoring Forecasting Centre. Their concerted efforts have effectively heightened awareness within the community regarding the significant potential of SEAMLESS biogeochemical data assimilation in addressing contemporary technological and societal challenges.
The SEAMLESS Roadmap delineates timelines for MFCs to integrate new codes and algorithms for ensemble generation, assimilation, and ecosystem indicators. This integration is expected to enhance the characterization of marine biogeochemical and ecosystem indicators through novel model parameterizations and data assimilation techniques.
In close collaboration with the project’s Entrusted Entity, Mercator Ocean International, presentations and outcomes were disseminated at several pivotal strategic events, including the "Biodiversity in Coastal Ecosystems" organized by EC DEFIS in October 2022, and the Digital Twin Ocean Forum in April 2022. These initiatives aimed to assess the potential future incorporation of project outcomes into the European strategy for the Green Deal and the EU Mission Restore our Ocean and Waters in particular.
SEAMLESS partners actively shared and promoted their work through numerous external engagement activities from 2021 to 2023, including the organization of conferences and workshops. Researchers expanded their networks and disseminated results through participation in 80 international conferences and workshops, in addition to sharing findings through the project website and social media channels. Furthermore, SEAMLESS successfully fulfilled its objectives of training future users and the next generation of ecosystem modelers in the utilization of SEAMLESS tools and software through various hands-on and online training courses, reaching over 140 external participants.
With a total of 28 publicly available outputs, including 11 peer-reviewed publications, a book chapter, and key project documentation, SEAMLESS has made substantial contributions to the field. These resources are readily accessible through the project website, ensuring broad dissemination and accessibility.
SEAMLESS has advanced the development of ensemble data assimilation tools, which are either currently in use or anticipated to be adopted by the Copernicus Marine Service. These tools are slated to facilitate the operational delivery of biogeochemical products by CMEMS to over 50 thousand users, spanning from academia to policy-making spheres, in the forthcoming years. Developed by SEAMLESS partners, these tools address key challenges in biogeochemical data assimilation science, including ensemble generation, integration of observations from underwater and satellite platforms, mitigation of biogeochemical simulation degradation caused by physical data assimilation, and enhancement of biogeochemical model parameter identifiability. These advancements are actively embraced by the academic community, leveraging the published papers and freely available online code.