Articles | Volume 15, issue 7
https://doi.org/10.5194/tc-15-3207-2021
© 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/tc-15-3207-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
12 Jul 2021
Research article |
| 12 Jul 2021
| 12 Jul 2021
Presentation and evaluation of the Arctic sea ice forecasting system neXtSIM-F
Timothy Williams
CORRESPONDING AUTHOR
Nansen Environmental and Remote Sensing Center, Jahnebakken 3, 5007 Bergen, Norway, and Bjerknes Centre for Climate Research, Bergen, Norway
Anton Korosov
Nansen Environmental and Remote Sensing Center, Jahnebakken 3, 5007 Bergen, Norway, and Bjerknes Centre for Climate Research, Bergen, Norway
Pierre Rampal
CNRS, Institut Géophysique de l'Environnement, Grenoble, France
Nansen Environmental and Remote Sensing Center, Jahnebakken 3, 5007 Bergen, Norway, and Bjerknes Centre for Climate Research, Bergen, Norway
Einar Ólason
Nansen Environmental and Remote Sensing Center, Jahnebakken 3, 5007 Bergen, Norway, and Bjerknes Centre for Climate Research, Bergen, Norway
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18 citations as recorded by crossref.
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- Sea Ice Remote Sensing—Recent Developments in Methods and Climate Data Sets S. Sandven et al. 10.1007/s10712-023-09781-0
- The MET Norway Ice Service: a comprehensive review of the historical and future evolution, ice chart creation, and end user interaction within METAREA XIX W. Copeland et al. 10.3389/fmars.2024.1400479
- Machine learning for the physics of climate A. Bracco et al. 10.1038/s42254-024-00776-3
- Arctic sea ice mass balance in a new coupled ice–ocean model using a brittle rheology framework G. Boutin et al. 10.5194/tc-17-617-2023
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- A comparison of an operational wave–ice model product and drifting wave buoy observation in the central Arctic Ocean: investigating the effect of sea-ice forcing in thin ice cover T. Nose et al. 10.33265/polar.v42.8874
- Response of Arctic benthic foraminiferal traits to past environmental changes K. Hansen et al. 10.1038/s41598-023-47603-w
- Subseasonal-to-seasonal prediction of arctic sea ice Using a Fully Coupled dynamical ensemble forecast system A. Liu et al. 10.1016/j.atmosres.2023.107014
- Data-Driven Short-Term Daily Operational Sea Ice Regional Forecasting T. Grigoryev et al. 10.3390/rs14225837
- Arctic sea ice data assimilation combining an ensemble Kalman filter with a novel Lagrangian sea ice model for the winter 2019–2020 S. Cheng et al. 10.5194/tc-17-1735-2023
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- Probabilistic Forecasts of Sea Ice Trajectories in the Arctic: Impact of Uncertainties in Surface Wind and Ice Cohesion S. Cheng et al. 10.3390/oceans1040022
- Calibration of sea ice drift forecasts using random forest algorithms C. Palerme & M. Müller 10.5194/tc-15-3989-2021
- Circumpolar Thin Arctic Sea Ice Thickness and Small-Scale Roughness Retrieval Using Soil Moisture and Ocean Salinity and Soil Moisture Active Passive Observations S. Jo et al. 10.3390/rs11232835
15 citations as recorded by crossref.
- Towards improving short-term sea ice predictability using deformation observations A. Korosov et al. 10.5194/tc-17-4223-2023
- Modelling the Arctic wave-affected marginal ice zone: a comparison with ICESat-2 observations G. Boutin et al. 10.1098/rsta.2021.0262
- Sea Ice Remote Sensing—Recent Developments in Methods and Climate Data Sets S. Sandven et al. 10.1007/s10712-023-09781-0
- The MET Norway Ice Service: a comprehensive review of the historical and future evolution, ice chart creation, and end user interaction within METAREA XIX W. Copeland et al. 10.3389/fmars.2024.1400479
- Machine learning for the physics of climate A. Bracco et al. 10.1038/s42254-024-00776-3
- Arctic sea ice mass balance in a new coupled ice–ocean model using a brittle rheology framework G. Boutin et al. 10.5194/tc-17-617-2023
- An Evaluation of the Performance of Sea Ice Thickness Forecasts to Support Arctic Marine Transport T. Bilge et al. 10.3390/jmse10020265
- High-resolution regional sea-ice model based on the discrete element method with boundary conditions from a large-scale model for ice drift A. Tsarau et al. 10.1017/aog.2024.26
- Improving short-term sea ice concentration forecasts using deep learning C. Palerme et al. 10.5194/tc-18-2161-2024
- A comparison of an operational wave–ice model product and drifting wave buoy observation in the central Arctic Ocean: investigating the effect of sea-ice forcing in thin ice cover T. Nose et al. 10.33265/polar.v42.8874
- Response of Arctic benthic foraminiferal traits to past environmental changes K. Hansen et al. 10.1038/s41598-023-47603-w
- Subseasonal-to-seasonal prediction of arctic sea ice Using a Fully Coupled dynamical ensemble forecast system A. Liu et al. 10.1016/j.atmosres.2023.107014
- Data-Driven Short-Term Daily Operational Sea Ice Regional Forecasting T. Grigoryev et al. 10.3390/rs14225837
- Arctic sea ice data assimilation combining an ensemble Kalman filter with a novel Lagrangian sea ice model for the winter 2019–2020 S. Cheng et al. 10.5194/tc-17-1735-2023
- Local analytical optimal nudging for assimilating AMSR2 sea ice concentration in a high-resolution pan-Arctic coupled ocean (HYCOM 2.2.98) and sea ice (CICE 5.1.2) model K. Wang et al. 10.5194/tc-17-4487-2023
3 citations as recorded by crossref.
- Probabilistic Forecasts of Sea Ice Trajectories in the Arctic: Impact of Uncertainties in Surface Wind and Ice Cohesion S. Cheng et al. 10.3390/oceans1040022
- Calibration of sea ice drift forecasts using random forest algorithms C. Palerme & M. Müller 10.5194/tc-15-3989-2021
- Circumpolar Thin Arctic Sea Ice Thickness and Small-Scale Roughness Retrieval Using Soil Moisture and Ocean Salinity and Soil Moisture Active Passive Observations S. Jo et al. 10.3390/rs11232835
Latest update: 14 Dec 2024
Short summary
neXtSIM (neXt-generation Sea Ice Model) includes a novel and extremely realistic way of modelling sea ice dynamics – i.e. how the sea ice moves and deforms in response to the drag from winds and ocean currents. It has been developed over the last few years for a variety of applications, but this paper represents its first demonstration in a forecast context. We present results for the time period from November 2018 to June 2020 and show that it agrees well with satellite observations.
neXtSIM (neXt-generation Sea Ice Model) includes a novel and extremely realistic way of...
