EAT: Ensemble and Assimilation Tool
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1.
Bolding & Bruggeman
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2.
Alfred Wegener Institute for Polar and Marine Research
Description
EAT is a flexible and extensible software package that enables data assimilation of physical and biogeochemical variables in a one-dimensional water column. EAT builds on established open-source components for hydrodynamics (GOTM), biogeochemistry (FABM) and data assimilation (PDAF). It is easy to install and operate, and flexible through support for user-written plugins. EAT is well suited to explore and advance the state-of-the-art in DA in natural waters thanks to its support for:
- strongly and weakly coupled data assimilation
- observations describing any prognostic and diagnostic element of the physical-biogeochemical model
- estimation of biogeochemical parameters.
On Windows, Mac and Linux systems with Anaconda or Miniconda, EAT can be installed with conda create -n eat -c conda-forge eatpy. It is then not necessary to download and compile the source code.
This record contains the EAT source code. It can be compiled and installed as described on the wiki.
Files
eat.zip
Files
(126.9 MB)
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md5:f62c79f48ef3ec220df7fdbb25f937f6
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64.2 MB | Preview Download |
Additional details
Related works
- Is described by
- Journal article: 10.5194/gmd-17-5619-2024 (DOI)
- Is documented by
- Software documentation: https://github.com/BoldingBruggeman/eat/wiki (URL)
- Is required by
- Dataset: 10.5281/zenodo.11111361 (DOI)
- Is supplement to
- Software: https://github.com/BoldingBruggeman/eat/tree/v1.0.0 (URL)