Articles | Volume 14, issue 10
https://doi.org/10.5194/gmd-14-6177-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-6177-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
S2P3-R v2.0: computationally efficient modelling of shelf seas on regional to global scales
College of Life and Environmental Sciences, University of Exeter,
Exeter, UK
Jennifer K. McWhorter
College of Life and Environmental Sciences, University of Exeter,
Exeter, UK
School of Biological Sciences, the University of Queensland, Brisbane,
Queensland, Australia
Beatriz Arellano Nava
College of Life and Environmental Sciences, University of Exeter,
Exeter, UK
Robert Marsh
University of Southampton, National Oceanography Centre, Southampton,
UK
William Skirving
Coral Reef Watch, National Oceanic and Atmospheric Administration,
College Park, MD, USA
ReefSense Pty Ltd, Cranbrook, Queensland, Australia
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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
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The difficulties in ameliorating global warming and the associated climate change via conventional mitigation are well documented, with all climate model scenarios exceeding 1.5 °C above the preindustrial level in the near future. There is therefore a growing interest in geoengineering to reflect a greater proportion of sunlight back to space and offset some of the global warming. We use a state-of-the-art Earth-system model to investigate two of the most prominent geoengineering strategies.
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
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We present the first global investigation of controls on seawater dimethylsulfide (DMS) spatial variability over scales of up to 100 km. Sea surface height anomalies, density, and chlorophyll a help explain almost 80 % of DMS variability. The results suggest that physical and biogeochemical processes play an equally important role in controlling DMS variability. These data provide independent confirmation that existing parameterisations of seawater DMS concentration use appropriate variables.
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
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The third climatological estimation of sea surface dimethyl sulfide (DMS) concentrations based on in situ measurements was created (DMS-Rev3). The update includes a much larger input dataset and includes improvements in the data unification, filtering, and smoothing algorithm. The DMS-Rev3 climatology provides more realistic monthly estimates of DMS, and shows significant regional differences compared to past climatologies.
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EGUsphere, https://doi.org/10.5194/egusphere-2025-3886, https://doi.org/10.5194/egusphere-2025-3886, 2025
This preprint is open for discussion and under review for Weather and Climate Dynamics (WCD).
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We studied marine heatwaves in the North Indian Ocean using sea surface temperatures with long-term warming removed to capture true short-term extremes. These heatwaves often interact with the monsoon's natural wet–dry cycles (MISO), shaping rainfall during and after events. After termination, extreme rainfall anomalies appear over parts of South Asia as revived monsoon winds release stored ocean heat and moisture.
Paul Dees, Friederike Fröb, Beatriz Arellano-Nava, David G. Johns, and Christoph Heinze
EGUsphere, https://doi.org/10.5194/egusphere-2025-470, https://doi.org/10.5194/egusphere-2025-470, 2025
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In this paper we describe a novel methodology to automate the estimation of ecological regime shift probability in a single time series. We have applied this new methodology to the continuous plankton recorder dataset in the North Sea, and shown how the model is able to estimate the likelihood of a regime shift using abundance data of multiple phytoplankton and zooplankton species.
Melissa Wood, Ivan D. Haigh, Quan Quan Le, Hung Nghia Nguyen, Hoang Ba Tran, Stephen E. Darby, Robert Marsh, Nikolaos Skliris, and Joël J.-M. Hirschi
Nat. Hazards Earth Syst. Sci., 24, 3627–3649, https://doi.org/10.5194/nhess-24-3627-2024, https://doi.org/10.5194/nhess-24-3627-2024, 2024
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We look at how compound flooding from the combination of river flooding and storm tides (storm surge and astronomical tide) may be changing over time due to climate change, with a case study of the Mekong River delta. We found that future compound flooding has the potential to flood the region more extensively and be longer lasting than compound floods today. This is useful to know because it means managers of deltas such as the Mekong can assess options for improving existing flood defences.
Vasilis Dakos, Chris A. Boulton, Joshua E. Buxton, Jesse F. Abrams, Beatriz Arellano-Nava, David I. Armstrong McKay, Sebastian Bathiany, Lana Blaschke, Niklas Boers, Daniel Dylewsky, Carlos López-Martínez, Isobel Parry, Paul Ritchie, Bregje van der Bolt, Larissa van der Laan, Els Weinans, and Sonia Kéfi
Earth Syst. Dynam., 15, 1117–1135, https://doi.org/10.5194/esd-15-1117-2024, https://doi.org/10.5194/esd-15-1117-2024, 2024
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Tipping points are abrupt, rapid, and sometimes irreversible changes, and numerous approaches have been proposed to detect them in advance. Such approaches have been termed early warning signals and represent a set of methods for identifying changes in the underlying behaviour of a system across time or space that might indicate an approaching tipping point. Here, we review the literature to explore where, how, and which early warnings have been used in real-world case studies so far.
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
Short summary
The difficulties in ameliorating global warming and the associated climate change via conventional mitigation are well documented, with all climate model scenarios exceeding 1.5 °C above the preindustrial level in the near future. There is therefore a growing interest in geoengineering to reflect a greater proportion of sunlight back to space and offset some of the global warming. We use a state-of-the-art Earth-system model to investigate two of the most prominent geoengineering strategies.
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
Short summary
We present the first global investigation of controls on seawater dimethylsulfide (DMS) spatial variability over scales of up to 100 km. Sea surface height anomalies, density, and chlorophyll a help explain almost 80 % of DMS variability. The results suggest that physical and biogeochemical processes play an equally important role in controlling DMS variability. These data provide independent confirmation that existing parameterisations of seawater DMS concentration use appropriate variables.
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
Short summary
The third climatological estimation of sea surface dimethyl sulfide (DMS) concentrations based on in situ measurements was created (DMS-Rev3). The update includes a much larger input dataset and includes improvements in the data unification, filtering, and smoothing algorithm. The DMS-Rev3 climatology provides more realistic monthly estimates of DMS, and shows significant regional differences compared to past climatologies.
Matthew Clark, Robert Marsh, and James Harle
Ocean Sci., 18, 549–564, https://doi.org/10.5194/os-18-549-2022, https://doi.org/10.5194/os-18-549-2022, 2022
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The European Slope Current (SC) is a northward-flowing current running parallel to the UK coastline. It is forced by changes in the density gradient of the wider North Atlantic Ocean. As the North Atlantic has warmed since the late 1990s, these gradients have changed strength and moved, reducing the volume and speed of water feeding into the SC. The SC flows into the North Sea, where changes in the species distribution of some plankton and fish have been seen due to the warming inputs.
Gandy Maria Rosales Quintana, Robert Marsh, and Luis Alfredo Icochea Salas
Ocean Sci., 17, 1385–1402, https://doi.org/10.5194/os-17-1385-2021, https://doi.org/10.5194/os-17-1385-2021, 2021
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The Equatorial Undercurrent (EUC) is a key influence on upwelling of nutrient-rich waters associated ecosystems off Peru. To quantify this influence, we backtrack upwelling waters in a computer model of ocean currents, annually, over 1989–2007. The EUC influence varies from year to year, dominating in warm El Niño years, when the EUC extends much closer to the Peruvian coast. In other years, more
localupwelling is associated with coastal winds, coincident with major key population shifts.
Emma L. Worthington, Ben I. Moat, David A. Smeed, Jennifer V. Mecking, Robert Marsh, and Gerard D. McCarthy
Ocean Sci., 17, 285–299, https://doi.org/10.5194/os-17-285-2021, https://doi.org/10.5194/os-17-285-2021, 2021
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The RAPID array has observed the Atlantic meridional overturning circulation (AMOC) since 2004, but the AMOC was directly calculated only five times from 1957–2004. Here we create a statistical regression model from RAPID data, relating AMOC changes to density changes within the different water masses at 26° N, and apply it to historical hydrographic data. The resulting 1981–2016 record shows that the AMOC from 2008–2012 was its weakest since the mid-1980s, but it shows no overall decline.
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Short summary
This paper describes the latest version of a simple model for simulating coastal oceanography in response to changes in weather and climate. The latest revision of this model makes scientific improvements but focuses on improvements that allow the model to be run simply at large scales and for long periods of time to explore the implications of (for example) future climate change along large areas of coastline.
This paper describes the latest version of a simple model for simulating coastal oceanography in...