SEAMLESS has developed an open-source, user-friendly assimilative modelling tool: the “SEAMLESS prototype”.
The core system of the prototype is a software made up of a 1-dimensional physical model coupled to five biogeochemical models and enabled with data-assimilation capabilities. The five biogeochemical models are used operationally in the Copernicus Marine Service, namely: PISCES, ERSEM, BFM, ECOSMO and ERGOM.
We have named to prototype EAT (SEAMLESS Ensemble and Assimilation Tool) (EAT) and it is publicly available on GitHub via – https://github.com/BoldingBruggeman/eat. EAT will be continually developed over the next few years of the SEAMLESS project and the GitHub page will always have the authoritative version.
EAT builds on other software projects – notably General Ocean Turbulence Model (GOTM – https://gotm.net), Framework for Aquatic Biogeochemical Models (FABM - https://fabm.net) and the Parallel Data Assimilation Framework (PDAF – http://pdaf.awi.de) and integrates these different components into a software product capable of doing data-assimilation simulations for any GOTM configuration where observations are available.
EAT will not only be a development platform for testing new assimilation methods and new biogeochemical models – but – also a production ready assimilation system for realistic 1D setups.
Realistic set-up are available for using the prototype straightforwardly in five data-reach sites in coastal areas, shelf-seas and open-ocean (stations BATS, L4, M, BOUSSOLE, Arkona) and with biogeochemical-Argo float transects.
Training courses on how to implement and run EAT are planned once the prototype is fully tested. Sign up here to join our mailing list and receive updates on training and developments.
The SEAMLESS prototype was been developed by BB and AWI. Its configurations by PML, OGS, UGA, NERSC and AWI.
EAT Video tutorial: this demonstration shows you install the ensemble and assimilation tool EAT on a windows and linux system. You will need anaconda or miniconda installed in order to follow this tutorial. More information can be found on the EAT wiki here.
Click here to view tutorial