Articles | Volume 12, issue 1
https://doi.org/10.5194/gmd-12-441-2019
https://doi.org/10.5194/gmd-12-441-2019
Model evaluation paper
 | 
25 Jan 2019
Model evaluation paper |  | 25 Jan 2019

A high-resolution biogeochemical model (ROMS 3.4 + bio_Fennel) of the East Australian Current system

Carlos Rocha, Christopher A. Edwards, Moninya Roughan, Paulina Cetina-Heredia, and Colette Kerry

Related authors

Surface current variability in the East Australian Current from long-term high-frequency radar observations
Manh Cuong Tran, Moninya Roughan, and Amandine Schaeffer
Earth Syst. Sci. Data, 17, 937–963, https://doi.org/10.5194/essd-17-937-2025,https://doi.org/10.5194/essd-17-937-2025, 2025
Short summary
Comparison of 4-dimensional variational and ensemble optimal interpolation data assimilation systems using a Regional Ocean Modeling System (v3.4) configuration of the eddy-dominated East Australian Current system
Colette Gabrielle Kerry, Moninya Roughan, Shane Keating, David Gwyther, Gary Brassington, Adil Siripatana, and Joao Marcos A. C. Souza
Geosci. Model Dev., 17, 2359–2386, https://doi.org/10.5194/gmd-17-2359-2024,https://doi.org/10.5194/gmd-17-2359-2024, 2024
Short summary
Exploring multi-decadal time series of temperature extremes in Australian coastal waters
Michael Hemming, Moninya Roughan, and Amandine Schaeffer
Earth Syst. Sci. Data, 16, 887–901, https://doi.org/10.5194/essd-16-887-2024,https://doi.org/10.5194/essd-16-887-2024, 2024
Short summary
Observed multi-decadal trends in subsurface temperature adjacent to the East Australian Current
Michael P. Hemming, Moninya Roughan, Neil Malan, and Amandine Schaeffer
Ocean Sci., 19, 1145–1162, https://doi.org/10.5194/os-19-1145-2023,https://doi.org/10.5194/os-19-1145-2023, 2023
Short summary
Moana Ocean Hindcast – a  > 25-year simulation for New Zealand waters using the Regional Ocean Modeling System (ROMS) v3.9 model
Joao Marcos Azevedo Correia de Souza, Sutara H. Suanda, Phellipe P. Couto, Robert O. Smith, Colette Kerry, and Moninya Roughan
Geosci. Model Dev., 16, 211–231, https://doi.org/10.5194/gmd-16-211-2023,https://doi.org/10.5194/gmd-16-211-2023, 2023
Short summary

Related subject area

Oceanography
sedInterFoam 1.0: a three-phase numerical model for sediment transport applications with free surfaces
Antoine Mathieu, Yeulwoo Kim, Tian-Jian Hsu, Cyrille Bonamy, and Julien Chauchat
Geosci. Model Dev., 18, 1561–1573, https://doi.org/10.5194/gmd-18-1561-2025,https://doi.org/10.5194/gmd-18-1561-2025, 2025
Short summary
The Ross Sea and Amundsen Sea Ice–Sea Model (RAISE v1.0): a high-resolution ocean–sea ice–ice shelf coupling model for simulating the Dense Shelf Water and Antarctic Bottom Water in the Ross Sea, Antarctica
Zhaoru Zhang, Chuan Xie, Chuning Wang, Yuanjie Chen, Heng Hu, and Xiaoqiao Wang
Geosci. Model Dev., 18, 1375–1393, https://doi.org/10.5194/gmd-18-1375-2025,https://doi.org/10.5194/gmd-18-1375-2025, 2025
Short summary
Sensitivity of the tropical Atlantic to vertical mixing in two ocean models (ICON-O v2.6.6 and FESOM v2.5)
Swantje Bastin, Aleksei Koldunov, Florian Schütte, Oliver Gutjahr, Marta Agnieszka Mrozowska, Tim Fischer, Radomyra Shevchenko, Arjun Kumar, Nikolay Koldunov, Helmuth Haak, Nils Brüggemann, Rebecca Hummels, Mia Sophie Specht, Johann Jungclaus, Sergey Danilov, Marcus Dengler, and Markus Jochum
Geosci. Model Dev., 18, 1189–1220, https://doi.org/10.5194/gmd-18-1189-2025,https://doi.org/10.5194/gmd-18-1189-2025, 2025
Short summary
HIDRA3: a deep-learning model for multipoint ensemble sea level forecasting in the presence of tide gauge sensor failures
Marko Rus, Hrvoje Mihanović, Matjaž Ličer, and Matej Kristan
Geosci. Model Dev., 18, 605–620, https://doi.org/10.5194/gmd-18-605-2025,https://doi.org/10.5194/gmd-18-605-2025, 2025
Short summary
A wave-resolving two-dimensional vertical Lagrangian approach to model microplastic transport in nearshore waters based on TrackMPD 3.0
Isabel Jalón-Rojas, Damien Sous, and Vincent Marieu
Geosci. Model Dev., 18, 319–336, https://doi.org/10.5194/gmd-18-319-2025,https://doi.org/10.5194/gmd-18-319-2025, 2025
Short summary

Cited articles

Alvera-Azcárate, A., Barth, A., Sirjacobs, D., Lenartz, F., and Beckers, J. M.: Data Interpolating Empirical Orthogonal Functions (DINEOF): a tool for geophysical data analyses, Mediterr. Mar. Sci., 12, 5–11, https://doi.org/10.12681/mms.64, 2010. 
Andersen, V., Nival, P., and Harris, R. P.: Modelling of a planktonic ecosystem in an enclosed water column, J. Mar. Biol. Assoc. UK., 67, 407–430, 1987. 
Anderson, T. R.: Plankton functional type modelling: running before we can walk?, J. Plankton Res., 27, 1073–1081, https://doi.org/10.1093/plankt/fbi076, 2005. 
Armbrecht, L. H., Roughan, M., Rossi, V., Schaeffer, A., Davies, P. L., Waite, A. M., and Armand, L. K.: Phytoplankton composition under contrasting oceanographic conditions: Upwelling and downwelling (Eastern Australia), Cont. Shelf Res., 75, 54–67, https://doi.org/10.1016/j.csr.2013.11.024, 2013. 
Baird, M. E., Timko, P. G., Suthers, I. M., and Middleton, J. H.: Coupled physical-biological modelling study of the East Australian Current with idealised wind forcing, Part I: Biological model intercomparison, J. Mar. Syst., 59, 249–270, 2006a. 
Download
Short summary
Off southeast Australia, the East Australian Current (EAC) moves warm nutrient-poor waters towards the pole. In this region, the EAC and a large number of vortices pinching off it strongly affect phytoplankton’s access to nutrients and light. To study these dynamics, we created a numerical model that is able to solve the ocean conditions and how they modulate the foundation of the region’s ecosystem. We validated model results against available data and this showed that the model performs well.
Share