Articles | Volume 14, issue 10
https://doi.org/10.5194/gmd-14-6177-2021
https://doi.org/10.5194/gmd-14-6177-2021
Model description paper
 | 
15 Oct 2021
Model description paper |  | 15 Oct 2021

S2P3-R v2.0: computationally efficient modelling of shelf seas on regional to global scales

Paul R. Halloran, Jennifer K. McWhorter, Beatriz Arellano Nava, Robert Marsh, and William Skirving

Related authors

Climate intervention using marine cloud brightening (MCB) compared with stratospheric aerosol injection (SAI) in the UKESM1 climate model
Jim M. Haywood, Andy Jones, Anthony C. Jones, Paul Halloran, and Philip J. Rasch
Atmos. Chem. Phys., 23, 15305–15324, https://doi.org/10.5194/acp-23-15305-2023,https://doi.org/10.5194/acp-23-15305-2023, 2023
Short summary
Global analysis of the controls on seawater dimethylsulfide spatial variability
George Manville, Thomas G. Bell, Jane P. Mulcahy, Rafel Simó, Martí Galí, Anoop S. Mahajan, Shrivardhan Hulswar, and Paul R. Halloran
Biogeosciences, 20, 1813–1828, https://doi.org/10.5194/bg-20-1813-2023,https://doi.org/10.5194/bg-20-1813-2023, 2023
Short summary
Third revision of the global surface seawater dimethyl sulfide climatology (DMS-Rev3)
Shrivardhan Hulswar, Rafel Simó, Martí Galí, Thomas G. Bell, Arancha Lana, Swaleha Inamdar, Paul R. Halloran, George Manville, and Anoop Sharad Mahajan
Earth Syst. Sci. Data, 14, 2963–2987, https://doi.org/10.5194/essd-14-2963-2022,https://doi.org/10.5194/essd-14-2963-2022, 2022
Short summary
Drivers of 21st Century carbon cycle variability in the North Atlantic Ocean
Matthew P. Couldrey, Kevin I. C. Oliver, Andrew Yool, Paul R. Halloran, and Eric P. Achterberg
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-16,https://doi.org/10.5194/bg-2019-16, 2019
Revised manuscript not accepted
Short summary
Inconsistent strategies to spin up models in CMIP5: implications for ocean biogeochemical model performance assessment
Roland Séférian, Marion Gehlen, Laurent Bopp, Laure Resplandy, James C. Orr, Olivier Marti, John P. Dunne, James R. Christian, Scott C. Doney, Tatiana Ilyina, Keith Lindsay, Paul R. Halloran, Christoph Heinze, Joachim Segschneider, Jerry Tjiputra, Olivier Aumont, and Anastasia Romanou
Geosci. Model Dev., 9, 1827–1851, https://doi.org/10.5194/gmd-9-1827-2016,https://doi.org/10.5194/gmd-9-1827-2016, 2016
Short summary

Related subject area

Oceanography
PIBM 1.0: an individual-based model for simulating phytoplankton acclimation, diversity, and evolution in the ocean
Iria Sala and Bingzhang Chen
Geosci. Model Dev., 18, 4155–4182, https://doi.org/10.5194/gmd-18-4155-2025,https://doi.org/10.5194/gmd-18-4155-2025, 2025
Short summary
An effective communication topology for performance optimization: a case study of the finite-volume wave modeling (FVWAM)
Renbo Pang, Fujiang Yu, Yuanyong Gao, Ye Yuan, Liang Yuan, and Zhiyi Gao
Geosci. Model Dev., 18, 4119–4136, https://doi.org/10.5194/gmd-18-4119-2025,https://doi.org/10.5194/gmd-18-4119-2025, 2025
Short summary
GREAT v1.0: Global Real-time Early Assessment of Tsunamis
Usama Kadri, Ali Abdolali, and Maxim Filimonov
Geosci. Model Dev., 18, 3487–3507, https://doi.org/10.5194/gmd-18-3487-2025,https://doi.org/10.5194/gmd-18-3487-2025, 2025
Short summary
Using automatic calibration to improve the physics behind complex numerical models: an example from a 3D lake model using Delft3D (v6.02.10) and DYNO-PODS (v1.0)
Marina Amadori, Abolfazl Irani Rahaghi, Damien Bouffard, and Marco Toffolon
Geosci. Model Dev., 18, 3473–3486, https://doi.org/10.5194/gmd-18-3473-2025,https://doi.org/10.5194/gmd-18-3473-2025, 2025
Short summary
Improvements to the Met Office's global ocean–sea ice forecasting system including model and data assimilation changes
Davi Mignac, Jennifer Waters, Daniel J. Lea, Matthew J. Martin, James While, Anthony T. Weaver, Arthur Vidard, Catherine Guiavarc'h, Dave Storkey, David Ford, Edward W. Blockley, Jonathan Baker, Keith Haines, Martin R. Price, Michael J. Bell, and Richard Renshaw
Geosci. Model Dev., 18, 3405–3425, https://doi.org/10.5194/gmd-18-3405-2025,https://doi.org/10.5194/gmd-18-3405-2025, 2025
Short summary

Cited articles

Amante, C. and Eakins, B. W.: ETOPO1 1 Arc-Minute Global Relief Model: Procedures, Data Sources and Analysis, NOAA Tech. Memo., NESDIS NGDC-24, https://doi.org/10.1594/PANGAEA.769615, 2009. 
Australian Institute of Marine Science (AIMS): NRSYON: Northern Australia Automated Marine Weather and Oceanographic Stations, Sites: [Yongala], https://doi.org/10.25845/5c09bf93f315d, 2020. 
Bahamondes Dominguez, A. A., Hickman, A. E., Marsh, R., and Moore, C. M.: Constraining the response of phytoplankton to zooplankton grazing and photo-acclimation in a temperate shelf sea with a 1-D model – towards S2P3 v8.0, Geosci. Model Dev., 13, 4019–4040, https://doi.org/10.5194/gmd-13-4019-2020, 2020. 
Barnes, M. K., Tilstone, G. H., Suggett, D. J., Widdicombe, C. E., Bruun, J., Martinez-Vicente, V., and Smyth, T. J.: Temporal variability in total, micro- and nano-phytoplankton primary production at a coastal site in the Western English Channel, Prog. Oceanogr., 137 (Part B), 470–483​​​​​​​, https://doi.org/10.1016/j.pocean.2015.04.017, 2015. 
Beaman, R.: Project 3DGBR: a high-resolution depth model for the Great Barrier Reef and Coral Sea, MTSRF Final Report Project 2.5i.1a, Reef and Rainforest Research Centre MTSRF Final Report Marine and Tropical Sciences Research Facility, James Cook University, available at: https://www.deepreef.org/images/stories/publications/reports/Project3DGBRFinal_RRRC2010.pdf (last access: 1 July 2021), ​​​​​​​2010. 
Download
Short summary
This paper describes the latest version of a simple model for simulating coastal oceanography in...
Share