Articles | Volume 10, issue 7
https://doi.org/10.5194/gmd-10-2849-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/gmd-10-2849-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Explicit representation and parametrised impacts of under ice shelf seas in the z∗ coordinate ocean model NEMO 3.6
Pierre Mathiot
CORRESPONDING AUTHOR
British Antarctic Survey, Natural Environment Research Council, Cambridge, UK
Met Office, Exeter, UK
Adrian Jenkins
British Antarctic Survey, Natural Environment Research Council, Cambridge, UK
Christopher Harris
Met Office, Exeter, UK
Gurvan Madec
Sorbonne Universités (University Pierre et Marie Curie Paris 6)-CNRS-IRD-MNHN, LOCEAN Laboratory, Paris, France
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77 citations as recorded by crossref.
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76 citations as recorded by crossref.
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- The DOE E3SM v1.2 Cryosphere Configuration: Description and Simulated Antarctic Ice‐Shelf Basal Melting D. Comeau et al. 10.1029/2021MS002468
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- Simulating or prescribing the influence of tides on the Amundsen Sea ice shelves N. Jourdain et al. 10.1016/j.ocemod.2018.11.001
- Effects of the atmospheric forcing resolution on simulated sea ice and polynyas off Adélie Land, East Antarctica P. Huot et al. 10.1016/j.ocemod.2021.101901
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- Bathymetric Influences on Antarctic Ice‐Shelf Melt Rates D. Goldberg et al. 10.1029/2020JC016370
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- The circum-Antarctic ice-shelves respond to a more positive Southern Annular Mode with regionally varied melting D. Verfaillie et al. 10.1038/s43247-022-00458-x
- Ice‐Shelf Melt Response to Changing Winds and Glacier Dynamics in the Amundsen Sea Sector, Antarctica M. Donat‐Magnin et al. 10.1002/2017JC013059
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- Abyssal ocean overturning slowdown and warming driven by Antarctic meltwater Q. Li et al. 10.1038/s41586-023-05762-w
- Emulating Present and Future Simulations of Melt Rates at the Base of Antarctic Ice Shelves With Neural Networks C. Burgard et al. 10.1029/2023MS003829
- Predicting ocean-induced ice-shelf melt rates using deep learning S. Rosier et al. 10.5194/tc-17-499-2023
- Challenges and Prospects in Ocean Circulation Models B. Fox-Kemper et al. 10.3389/fmars.2019.00065
- Presentation and Evaluation of the IPSL‐CM6A‐LR Climate Model O. Boucher et al. 10.1029/2019MS002010
- Carbon–concentration and carbon–climate feedbacks in CMIP6 models and their comparison to CMIP5 models V. Arora et al. 10.5194/bg-17-4173-2020
- Antarctic contribution to future sea level from ice shelf basal melt as constrained by ice discharge observations E. van der Linden et al. 10.5194/tc-17-79-2023
- Pathways and Timescales of Connectivity Around the Antarctic Continental Shelf H. Dawson et al. 10.1029/2022JC018962
- Future changes in Antarctic coastal polynyas and bottom water formation simulated by a high-resolution coupled model H. Jeong et al. 10.1038/s43247-023-01156-y
- Ocean–Ice Sheet Coupling in the Totten Glacier Area, East Antarctica: Analysis of the Feedbacks and Their Response to a Sudden Ocean Warming G. Van Achter et al. 10.3390/geosciences13040106
- Ice Shelf Basal Melt Rates in the Amundsen Sea at the End of the 21st Century N. Jourdain et al. 10.1029/2022GL100629
1 citations as recorded by crossref.
Latest update: 14 Dec 2024
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