Processes at the ice shelf‐ocean interface and in particular in ice shelf cavities around Antarctica have an observable effect on the solutions of basin scale to global coupled ice‐ocean models. ...Despite this, these processes are not routinely represented in global ocean and climate models. It is shown that a new ice shelf cavity model for z coordinate models can reproduce results from an intercomparison project of earlier approaches with vertical σ or isopycnic coordinates. As a proof of concept, ice shelves are incorporated in a 100‐year global integration of a z coordinate model. In this simulation, glacial meltwater can be traced as far as north as 15°S. The observed effects of processes in the ice shelf cavities agree with previous results from a σ coordinate model, notably the increase in sea ice thickness. However, melt rates are overestimated probably because the parameterization of basal melting does not suit the low resolution of this configuration.
Stratospheric ozone depletion and emission of greenhouse gases lead to a trend of the southern annular mode (SAM) toward its high‐index polarity. The positive phase of the SAM is characterized by ...stronger than usual westerly winds that induce changes in the physical carbon transport. Changes in the natural carbon budget of the upper 100 m of the Southern Ocean in response to a positive SAM phase are explored with a coupled ecosystem‐general circulation model and regression analysis. Previously overlooked processes that are important for the upper ocean carbon budget during a positive SAM period are identified, namely, export production and downward transport of carbon north of the polar front (PF) as large as the upwelling in the south. The limiting micronutrient iron is brought into the surface layer by upwelling and stimulates phytoplankton growth and export production but only in summer. This leads to a drawdown of carbon and less summertime outgassing (or more uptake) of natural CO2. In winter, biological mechanisms are inactive, and the surface ocean equilibrates with the atmosphere by releasing CO2. In the annual mean, the upper ocean region south of the PF loses more carbon by additional export production than by the release of CO2 into the atmosphere, highlighting the role of the biological carbon pump in response to a positive SAM event.
Key Points
The response of carbon fluxes varies between seasons
More biological production at positive SAM south of 55S
Uptake of natural CO2 in summer in contrast to mean response due to biology
The field of Arctic sea ice prediction on "weather time scales" is still in its infancy with little existing understanding of the limits of predictability. This is especially true for sea ice ...deformation along so-called Linear Kinematic Features (LKFs) including leads that are relevant for marine operations. Here the potential predictability of the sea ice pack in the wintertime Arctic up to ten days ahead is determined, exploiting the fact that sea ice-ocean models start to show skill at representing sea ice deformation at high spatial resolutions. Results are based on ensemble simulations with a high-resolution sea ice-ocean model driven by atmospheric ensemble forecasts. The predictability of LKFs as measured by different metrics drops quickly, with predictability being almost completely lost after 4-8 days. In contrast, quantities such as sea ice concentration or the location of the ice edge retain high levels of predictability throughout the full 10-day forecast period. It is argued that the rapid error growth for LKFs is mainly due to the chaotic behaviour of the atmosphere associated with the low predictability of near surface wind divergence and vorticity; initial condition uncertainty for ice thickness is found to be of minor importance as long as LKFs are initialized at the right locations.
Observations in polar regions show that sea ice deformations are often narrow linear features. These long bands of deformations are referred to as Linear Kinematic Features (LKFs). Viscous‐plastic ...sea ice models have the capability to simulate LKFs and more generally sea ice deformations. Moreover, viscous‐plastic models simulate a larger number and more refined LKFs as the spatial resolution is increased. Besides grid spacing, other aspects of a numerical implementation, such as the placement of velocities and the associated degrees of freedom, may impact the formation of simulated LKFs. To explore these effects this study compares numerical solutions of sea ice models with different velocity staggering in a benchmark problem. Discretizations based on A‐,B‐, and C‐grid systems on quadrilateral meshes have similar resolution properties as an approximation with an A‐grid staggering on triangular grids (with the same total number of vertices). CD‐grid approximations with a given grid spacing have properties, specifically the number and length of simulated LKFs, that are qualitatively similar to approximations on conventional Arakawa A‐grid, B‐grid, and C‐grid approaches with half the grid spacing or less, making the CD‐discretization more efficient with respect to grid resolution. One reason for this behavior is the fact that the CD‐grid approach has a higher number of degrees of freedom to discretize the velocity field. The higher effective resolution of the CD‐discretization makes it an attractive alternative to conventional discretizations.
Plain Language Summary
Sea ice in the Arctic and Antarctic Oceans plays an important role in the exchange of heat and freshwater between the atmosphere and the ocean and hence in the climate in general. Satellite observations of polar regions show that the ice drift sometimes produces long features that are either cracks (leads) and zones of thicker sea ice (pressure ridges). This phenomenon is called deformation. It is mathematically described by the non‐uniform way in which the ice moves. For numerical models of sea ice motion it is difficult to represent this deformation accurately. Details of the numerics may affect the way these models simulate leads and ridges, their number and length. Specifically, we find by comparing different numerical models, that the way the model variables are ordered on a computational grid to solve the mathematical equations of sea ice motion has an effect of how many deformation features can be represented on a grid with a given spacing between grid points. A new discretization (ordering of model variables) turns out to resolve more details of the approximated field than traditional methods.
Key Points
The placement of the sea ice velocity has a mayor influence on the number of simulated linear kinematic features (LKFs)
The CD‐grid resolves twice as many LKFs compared to A, B, C‐grids
A, B, C‐grids on quadrilateral meshes resolve a similar number of LKFs as A‐grids on triangular meshes (with the same total number of nodes)
A new climate model has been developed that employs a multi-resolution dynamical core for the sea ice-ocean component. In principle, the multi-resolution approach allows one to use enhanced ...horizontal resolution in dynamically active regions while keeping a coarse-resolution setup otherwise. The coupled model consists of the atmospheric model ECHAM6 and the finite element sea ice-ocean model (FESOM). In this study only moderate refinement of the unstructured ocean grid is applied and the resolution varies from about 25 km in the northern North Atlantic and in the tropics to about 150 km in parts of the open ocean; the results serve as a benchmark upon which future versions that exploit the potential of variable resolution can be built. Details of the formulation of the model are given and its performance in simulating observed aspects of the mean climate is described. Overall, it is found that ECHAM6–FESOM realistically simulates many aspects of the observed climate. More specifically it is found that ECHAM6–FESOM performs at least as well as some of the most sophisticated climate models participating in the fifth phase of the Coupled Model Intercomparison Project. ECHAM6–FESOM shares substantial shortcomings with other climate models when it comes to simulating the North Atlantic circulation.
A new global climate model setup using FESOM2.0 for the sea ice‐ocean component and ECHAM6.3 for the atmosphere and land surface has been developed. Replacing FESOM1.4 by FESOM2.0 promises a higher ...efficiency of the new climate setup compared to its predecessor. The new setup allows for long‐term climate integrations using a locally eddy‐resolving ocean. Here it is evaluated in terms of (1) the mean state and long‐term drift under preindustrial climate conditions, (2) the fidelity in simulating the historical warming, and (3) differences between coarse and eddy‐resolving ocean configurations. The results show that the realism of the new climate setup is overall within the range of existing models. In terms of oceanic temperatures, the historical warming signal is of smaller amplitude than the model drift in case of a relatively short spin‐up. However, it is argued that the strategy of “de‐drifting” climate runs after the short spin‐up, proposed by the HighResMIP protocol, allows one to isolate the warming signal. Moreover, the eddy‐permitting/resolving ocean setup shows notable improvements regarding the simulation of oceanic surface temperatures, in particular in the Southern Ocean.
Key Points
A new climate model setup using an unstructured‐mesh ocean‐sea ice component has been developed
Mean state and long‐term drift under preindustrial climate conditions are evaluated
Modeled climates using coarse and eddy‐resolving ocean configurations are compared
In a feasibility study, the potential of proxy data for the temperature and salinity during the Last Glacial Maximum (LGM, about 19 000 to 23 000 years before present) in constraining the strength of ...the Atlantic meridional overturning circulation (AMOC) with a general ocean circulation model was explored. The proxy data were simulated by drawing data from four different model simulations at the ocean sediment core locations of the Multiproxy Approach for the Reconstruction of the Glacial Ocean surface (MARGO) project, and perturbing these data with realistic noise estimates. The results suggest that our method has the potential to provide estimates of the past strength of the AMOC even from sparse data, but in general, paleo-sea-surface temperature data without additional prior knowledge about the ocean state during the LGM is not adequate to constrain the model. On the one hand, additional data in the deep-ocean and salinity data are shown to be highly important in estimating the LGM circulation. On the other hand, increasing the amount of surface data alone does not appear to be enough for better estimates. Finally, better initial guesses to start the state estimation procedure would greatly improve the performance of the method. Indeed, with a sufficiently good first guess, just the sea-surface temperature data from the MARGO project promise to be sufficient for reliable estimates of the strength of the AMOC.
Ocean tides redistribute mass at high temporal frequencies. Satellite missions that aim to observe medium to low frequency mass variations need to take into account this rapidly varying mass signal. ...Correcting for the effects of ocean tides by means of imperfect models might hamper the observation of other temporal gravity field signals of interest. This paper explores different methods for mitigating aliasing errors for the specific example of observing mass variations due to land hydrology, including temporal filtering of time-series of gravity solutions, spatial smoothing and the use of satellite constellations. For this purpose, an Earth System Model (ESM) was constructed, which included state-of-the-art time varying components for ocean, atmosphere, solid Earth, hydrology, ice-sheets and ocean tides. Using the ESM, we simulated the retrieval of the hydrologically driven gravity field changes using a number of different satellite constellations. We find that (1) the ocean tide aliasing strongly depends on the satellite constellation, the choice of orbital parameters and the length of the data span; (2) the aliasing effect manifests itself differently for different geographical regions; (3) the aliasing causes a peculiar striping pattern along the ground track of the satellite orbits; (4) optimizing the choice of orbital parameters of a single GRACE-type tandem can be more effective at reducing the aliasing of ocean tide model errors than flying more tandems. Finally, we corroborate the experiences with GRACE data analysis that appropriate post-processing techniques can significantly improve the quality of the retrieved gravity changes.
The sea ice modeling community is progressing towards pan-Arctic simulations that explicitly resolve leads in the simulated sea ice cover. Evaluating these simulations against observations poses new ...challenges. A new feature-based evaluation of simulated deformation fields is introduced, and the results are compared to a scaling analysis of sea ice deformation.
Leads and pressure ridges – here combined into linear kinematic features (LKFs) – are detected and tracked automatically from deformation and drift data.
LKFs in two pan-Arctic sea ice simulations with a horizontal grid spacing of 2 km are compared with an
LKF dataset derived from the RADARSAT Geophysical Processor System (RGPS). One simulation uses a five-class ice thickness distribution (ITD).
The simulated sea ice deformation follows a multi-fractal spatial and temporal scaling, as observed from RGPS.
The heavy-tailed distribution of LKF lengths and the scale invariance of LKF curvature, which points to the self-similar nature of sea ice deformation fields, are reproduced by the model.
Interannual and seasonal variations in the number of LKFs, LKF densities, and LKF orientations in the ITD simulation are found to be consistent with RGPS observations.
The lifetimes and growth rates follow a distribution with an exponential tail. The model overestimates the intersection angle of LKFs, which is attributed to the model's viscous-plastic rheology with an elliptical yield curve. In conclusion, the new feature-based analysis of LKF statistics is found to be useful for a comprehensive evaluation of simulated deformation features, which is required before the simulated features can be used with confidence in the context of climate studies. As such, it complements the commonly used scaling analysis and provides new useful information for comparing deformation statistics. The ITD simulation is shown to reproduce LKFs sufficiently well for it to be used for studying the effect of directly resolved leads in climate simulations. The feature-based analysis of LKFs also identifies specific model deficits that may be addressed by specific parameterizations, for example, a damage parameter, a grounding scheme, and a Mohr–Coulombic yield curve.
Sea ice and snow on sea ice to a large extent determine the surface heat budget in the Arctic Ocean. In spite of the advances in modeling sea‐ice thermodynamics, a good number of models still rely on ...simple parameterizations of the thermodynamics of ice and snow. Based on simulations with an Arctic sea‐ice model coupled to an ocean general circulation model, we analyzed the impact of changing two sea‐ice parameterizations: (1) the prescribed ice thickness distribution (ITD) for surface heat budget calculations, and (2) the description of the snow layer. For the former, we prescribed a realistic ITD derived from airborne electromagnetic induction sounding measurements. For the latter, two different types of parameterizations were tested: (1) snow thickness independent of the sea‐ice thickness below, and (2) a distribution proportional to the prescribed ITD. Our results show that changing the ITD from seven uniform categories to fifteen nonuniform categories derived from field measurements, and distributing the snow layer according to the ITD, leads to an increase in average Arctic‐wide ice thickness by 0.56 m and an increase by 1 m in the Canadian Arctic Archipelago and Canadian Basin. This increase is found to be a direct consequence of 524 km3 extra thermodynamic growth during the months of ice formation (January, February, and March). Our results emphasize that these parameterizations are a key factor in sea‐ice modeling to improve the representation of the sea‐ice energy balance.
Key Points
Use of realistic ice thickness distributions in a regional Arctic Ocean model
Snow layer distributed as the ITD increases considerably the sea‐ice thickness
Model sea‐ice thickness agrees well with winter satellite retrieved data
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