Articles | Volume 16, issue 1
https://doi.org/10.5194/gmd-16-157-2023
https://doi.org/10.5194/gmd-16-157-2023
Development and technical paper
 | 
04 Jan 2023
Development and technical paper |  | 04 Jan 2023

How does 4DVar data assimilation affect the vertical representation of mesoscale eddies? A case study with observing system simulation experiments (OSSEs) using ROMS v3.9

David E. Gwyther, Shane R. Keating, Colette Kerry, and Moninya Roughan

Related authors

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
Evaluating an accelerated forcing approach for improving computational efficiency in coupled ice sheet-ocean modelling
Qin Zhou, Chen Zhao, Rupert Gladstone, Tore Hattermann, David Gwyther, and Benjamin Galton-Fenzi
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-244,https://doi.org/10.5194/gmd-2023-244, 2024
Preprint under review for GMD
Short summary
Observing system simulation experiments reveal that subsurface temperature observations improve estimates of circulation and heat content in a dynamic western boundary current
David E. Gwyther, Colette Kerry, Moninya Roughan, and Shane R. Keating
Geosci. Model Dev., 15, 6541–6565, https://doi.org/10.5194/gmd-15-6541-2022,https://doi.org/10.5194/gmd-15-6541-2022, 2022
Short summary
Evaluation of an emergent feature of sub-shelf melt oscillations from an idealized coupled ice sheet–ocean model using FISOC (v1.1) – ROMSIceShelf (v1.0) – Elmer/Ice (v9.0)
Chen Zhao, Rupert Gladstone, Benjamin Keith Galton-Fenzi, David Gwyther, and Tore Hattermann
Geosci. Model Dev., 15, 5421–5439, https://doi.org/10.5194/gmd-15-5421-2022,https://doi.org/10.5194/gmd-15-5421-2022, 2022
Short summary
The impact of tides on Antarctic ice shelf melting
Ole Richter, David E. Gwyther, Matt A. King, and Benjamin K. Galton-Fenzi
The Cryosphere, 16, 1409–1429, https://doi.org/10.5194/tc-16-1409-2022,https://doi.org/10.5194/tc-16-1409-2022, 2022
Short summary

Related subject area

Oceanography
Skin sea surface temperature schemes in coupled ocean–atmosphere modelling: the impact of chlorophyll-interactive e-folding depth
Vincenzo de Toma, Daniele Ciani, Yassmin Hesham Essa, Chunxue Yang, Vincenzo Artale, Andrea Pisano, Davide Cavaliere, Rosalia Santoleri, and Andrea Storto
Geosci. Model Dev., 17, 5145–5165, https://doi.org/10.5194/gmd-17-5145-2024,https://doi.org/10.5194/gmd-17-5145-2024, 2024
Short summary
DELWAVE 1.0: deep learning surrogate model of surface wave climate in the Adriatic Basin
Peter Mlakar, Antonio Ricchi, Sandro Carniel, Davide Bonaldo, and Matjaž Ličer
Geosci. Model Dev., 17, 4705–4725, https://doi.org/10.5194/gmd-17-4705-2024,https://doi.org/10.5194/gmd-17-4705-2024, 2024
Short summary
StraitFlux – precise computations of water strait fluxes on various modeling grids
Susanna Winkelbauer, Michael Mayer, and Leopold Haimberger
Geosci. Model Dev., 17, 4603–4620, https://doi.org/10.5194/gmd-17-4603-2024,https://doi.org/10.5194/gmd-17-4603-2024, 2024
Short summary
Comparison of the Coastal and Regional Ocean COmmunity model (CROCO) and NCAR-LES in non-hydrostatic simulations
Xiaoyu Fan, Baylor Fox-Kemper, Nobuhiro Suzuki, Qing Li, Patrick Marchesiello, Peter P. Sullivan, and Paul S. Hall
Geosci. Model Dev., 17, 4095–4113, https://doi.org/10.5194/gmd-17-4095-2024,https://doi.org/10.5194/gmd-17-4095-2024, 2024
Short summary
Intercomparisons of Tracker v1.1 and four other ocean particle-tracking software packages in the Regional Ocean Modeling System
Jilian Xiong and Parker MacCready
Geosci. Model Dev., 17, 3341–3356, https://doi.org/10.5194/gmd-17-3341-2024,https://doi.org/10.5194/gmd-17-3341-2024, 2024
Short summary

Cited articles

Abernathey, R. and Haller, G.: Transport by Lagrangian Vortices in the Eastern Pacific, J. Phys. Oceanogr., 48, 667–685, https://doi.org/10.1175/jpo-d-17-0102.1, 2018. a
Ballabrera-Poy, J., Hackert, E., Murtugudde, R., and Busalacchi, A. J.: An Observing System Simulation Experiment for an Optimal Moored Instrument Array in the Tropical Indian Ocean, J. Climate, 20, 3284–3299, https://doi.org/10.1175/jcli4149.1, 2007. a
Bannister, R. N.: A review of forecast error covariance statistics in atmospheric variational data assimilation. I: Characteristics and measurements of forecast error covariances, Q. J. Roy. Meteor. Soc., 134, 1951–1970, https://doi.org/10.1002/qj.339, 2008a. a, b
Bannister, R. N.: A review of forecast error covariance statistics in atmospheric variational data assimilation. II: Modelling the forecast error covariance statistics, Q. J. Roy. Meteor. Soc., 134, 1971–1996, https://doi.org/10.1002/qj.340, 2008b. a
Bonavita, M., Raynaud, L., and Isaksen, L.: Estimating background-error variances with the ECMWF Ensemble of Data Assimilations system: some effects of ensemble size and day-to-day variability, Q. J. Roy. Meteor. Soc., 137, 423–434, https://doi.org/10.1002/qj.756, 2011. a, b
Download
Short summary
Ocean eddies are important for weather, climate, biology, navigation, and search and rescue. Since eddies change rapidly, models that incorporate or assimilate observations are required to produce accurate eddy timings and locations, yet the model accuracy is rarely assessed below the surface. We use a unique type of ocean model experiment to assess three-dimensional eddy structure in the East Australian Current and explore two pathways in which this subsurface structure is being degraded.