EAT v0.9.6: a 1D testbed for physical-biogeochemical data assimilation in natural waters

Abstract

Abstract. Data assimilation (DA) in marine and freshwater systems combines numerical models and observations to deliver the best possible characterisation of a water body’s physical and biogeochemical state. This underpins the widely used 3D ocean state reanalyses and forecasts produced operationally by e.g. the Copernicus Marine Service. The use of DA in natural waters is an active field of research, but testing new developments in realistic setting can be challenging, as operational DA systems are demanding in terms of computational resources and technical skill. There is a need for testbeds that sufficiently realistic but also efficient to run and easy to operate. Here, we present the Ensemble and Assimilation Tool (EAT): 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 (1) strongly and weakly coupled data assimilation, (2) observations describing any prognostic and diagnostic element of the physical-biogeochemical model, and (3) estimation of biogeochemical parameters. Its range of capabilities is demonstrated with three applications: ensemble-based coupled physical-biogeochemical assimilation, the use of variational methods (3D-Var) to assimilate sea surface chlorophyll, and the estimation of biogeochemical parameters.

A Python interface to the Fortran-based Parallel Data Assimilation Framework: pyPDAF v1.0.0

“…For the application of DA, DAPPER provides a variety of DA algorithms for twin experiments using low-dimensional Python models. The Ensemble and Assimilation Tool, EAT (Bruggeman et al, 2023) was proposed to set up a 1D ocean-biogeochemical DA system. The Python tool only has a Python interface to a few PDAF routines while the rest of the system is coded in Fortran including the 1D ocean-biogeochemical model, GOTM-FABM.…”