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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 bolding-bruggeman -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.

Satellite data collected between 2003 and 2022, in conjunction with gridded bathymetric data (50-150 m resolution), are used to estimate the irradiance reaching the bottom of a series of representative EU Arctic fjords. An Earth System Science Data (ESSD) manuscript, Schlegel et al. (2023, in review), that provides a detailed explanation of the methodology is currently in review.

Version of the 'Finite Volume Sea ice - Ocean Model' (FESOM2) that was used in the coupled model IFS-FESOM for nextGEMS Cycle 3 simulations. It includes all changes from FESOM2.5 plus modifications for better stability on DKRZ Levante. This is the source code used in the study Rackow, Pedruzo-Bagazgoitia, Becker, Milinski, Sandu et al. : Multi-year simulations at kilometre scale with the Integrated Forecasting System coupled to FESOM2.5/NEMOV3.4 This work was supported by the European Union's Horizon 2020 collaborative project NextGEMS (grant number 101003470). For more infos about the nextGEMS project, see https://nextgems-h2020.eu (last access: 30.11.2023) 

DIVAnd v2.7.10 Diff since v2.7.9 Merged pull requests: Jmb (#116) (@jmbeckers) Jmb (#126) (@jmbeckers) CompatHelper: add new compat entry for DelimitedFiles at version 1, (keep existing compat) (#132) (@github-actions[bot]) Closed issues: advection constrain (#47) Setting time as an unlimited dimension in netCDF (#81) NetCDF_URL e ZIP file (#85) NCODV.load failing if quality flags not defined (#92) Calculated CPME error is unrealistically low! (#95) "climatology_bounds" instead of variable names (#105) Problem reading data without local_cdi_id and edmo_code (#106) Function fit( ) not used (#108) MethodError when trying to run diva3d with fitcorrlen = true (#109) MethodError after uncomment some lines from DIVAnd_save.jl (#111) Test "test_vocab.jl" fails (#112) Http 500 Internal Server Error[🐞] (#113) [🐞]High memory consumption and inability to use divandgo or conjugate gradient inversion. (#117) [👆] Getting lists of data points that are used for each depth layer (#118) [DOC] documentation of diffusion function (#120) [Help needed] Correlation length and lengraddepth (#121) Background of all observations over time (#122) [🐞] When running DIVAnd, artifacts appear which seem to be linked to the bathymetry (#123) L-shape criterium[👆] (#124) Sigma coordinates ?[👆] (#125) Unhandled Task ERROR: EOFError: read end of file (#127) [🐞] DomainError when use background (#128) 'data access' and 'WEB_visualisation' attributes not correct anymore (#130) [Help needed]How to create and use my bathymetry file? (#131) [🐞]WARNING: Method definition DIVAnd_bc_stretch overwritten (#134) Accurate meaning of the correlation length?[DOC] (#135) adapt ODV files "load" function for WOD data[👆] (#136)

This pre-release is already usable, but we recommend waiting for the first official release before using Pygoda on your own project. If you would like to use Pygoda right now, we suggest you try the provided toy example first (see documentation), then get in touch with us to help you setup your configuration files.

Scripts used for analysis in RECCAP2 Southern Ocean chapter: Hauck, J., Gregor, L., Nissen, C., Patara, L., Hague, M., Mongwe, N. P., et al. (2023). The Southern Ocean carbon cycle 1985–2018: Mean, seasonal cycle, trends, and storage. Global Biogeochemical Cycles, 37, e2023GB007848. https://doi.org/10.1029/2023GB007848 The raw data is available at: Müller, Jens Daniel. (2023). RECCAP2-ocean data collection [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7990823 Processed data files are needed for the plotting scripts provided here. These are deposited at: Judith Hauck, Luke Gregor, Cara Nissen, Lavinia Patara, Mark Hague, & Precious Mongwe. (2023). The Southern Ocean carbon cycle 1985-2018: Mean, seasonal cycle, trends and storage - Data [Data set].Zenodo. https://doi.org/10.5281/zenodo.10074671 The scripts were downloaded from the GitHub repository: https://github.com/RECCAP2-ocean/Southern-Ocean on 06 November 2023. Funding was provided by the Initiative and Networking Fund of the Helmholtz Association (Helmholtz Young Investigator Group Marine Carbon and Ecosystem Feedbacks in the Earth System [MarESys], grant no. VH-NG-1301) and the mentioned EU projects.

Milestone release of AtlantOS_QC app under EuroGO-SHIP funding (Horizon Europe #101094690). v1.6.0 Parameter computation code fully migrated to python. Python can be used but is not anymore a requirement. Improved table in show-data to enhance data review and exporting. Fixed bugs Big performance improvements. Updated libraries. Updated appearance v1.5.0 New features and file formats were implemented. Performance and security updates on code and most libraries. Version Changelog: https://github.com/EuroGO-SHIP/AtlantOS_QC/compare/v1.5.0...v1.6.0 Full Changelog: https://github.com/EuroGO-SHIP/AtlantOS_QC/compare/v1.4.0...v1.6.0 This software was supported by EuroGO-SHIP project (Horizon Europe #101094690) and by BOCATS2 (PID2019-104279GB-C21) project funded by MCIN/AEI/10.13039/501100011033 It's a contribution to OCEANS+ CSIC PTI

The configuration files provided here produced the CROCO model output analysed in "The land-sea breeze influences the oceanography of the southern Benguela upwelling system at multiple time-scales" by Fearon et. al (2023) submitted to Frontiers in Marine Science, section Physical Oceanography. The provided files include the adopted compile options, code used to generate the model forcing files (grids, boundary conditions and surface forcing), and model runtime settings.