Modeling ice shelf cavities in a z coordinate ocean general circulation model

Abstract. 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 cli-mate models. It is shown that a new ice shelf cavity model for z-coordinate models can re-produce results from an intercomparison project of earlier approaches with vertical σ- or isopy-cnic coordinates. As a proof of concept, ice shelves are incorporated in a 100 year global in-tegration of a z-coordinate model. In this simulation, glacial melt water can be traced as far as north as 15 ◦ S. The observed effects of processes in the ice shelf cavities agree with pre-vious 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. 1

Estimating Oceanic Export Production based on 3D coupled physical-biogeochemical modelling

The study addresses various aspects of model-based estimating the oceanic primary production. In particular, we consider existent interpretations of the export fluxes; influence of implied conversions between modelled chlorophyll and biomass, expressed in nitrogen and/or carbon units, and, therefore, impact of decoupling the biogeochemical (N, C) cycles and chlorophyll. The export production is estimated by simulating global ocean biolgeochemical dynamics with the CN regulated model (REcoM) developed by Schartau et al. (2007) and coupled with the MITgcm. The model describes carbon (C) and nitrogen (N) fluxes between components of the ocean ecosystem. The nitrogen and carbon cycles as well as phytoplankton chlorophyll (Chl) dynamics are decoupled in accordance with the dynamic regulatory phytoplanktonic acclimation model sugested by Geider et al. (1998). Sensitivity of the primary production estimates to biological model parameters is also discussed

Numerical modeling on landfast ice in Arctic region

Sea ice is regarded as a significant indicator of climate change in the Arctic Ocean. Landfastice is sea ice that is immobile or almost immobile in coastal regions, decreasing the transfer of heat, moisture, and momentum. As an extension of the land for travel and hunting, landfast ice also influences the construction of ice roads and arctic shipping routes in the summertime. Despite the important role of landfast ice in the climate system, the formation and maintenance of landfast ice are not well simulated by current sea ice models. Lemieux (2015) came up with the grounding scheme, by adding a basal stress term according to the water depth, improving landfast ice representation in shallow regions while underestimating in deep regions especially in the Kara Sea. The two different resolution model configurations with the MIT General Circulation Model (MITgcm) sea ice package is compared in landfast ice simulation in the arctic region. Preliminary results show that a higher resolution model better represents landfast ice in deep regions. The proper illustration of coastlines, which serve as pinning points for sea ice arches, in the high-resolution model can improve the representation of landfast ice. We also apply a new parameterization lateral drag term, a function with sea ice thickness, drift velocity, and coastline intricacy, in the model to better simulate landfast ice. The results suggest a combination of lateral drag and basal stress terms successfully simulates fast ice in most region

Numerical modeling on landfast ice in the Arctic

Sea ice is regarded as a clear indicator of climate change in the Arctic Ocean. Landfast ice is immobile or nearly immobile sea ice in coastal regions that affects the transfer of heat, moisture, and momentum between the atmosphere and the ocean. As an extension of the land for travel and hunting, landfast ice also determines the construction of ice roads and Arctic shipping routes in the summertime. Despite the important role of landfast ice in the climate system, landfast ice is not simulated very well by current sea ice models and needs to be parameterized, for example, by a grounding scheme. Comparing landfast ice in two sea-ice simulations with different grid resolutions indicates that a higher resolution model better presents landfast ice in deep water regions, where a grounding scheme fails. The better representation of coastline details, which serve as pinning points for sea ice arches in the high-resolution model, is thought to improve the representation of landfast ice. Based on this hypothesis, a new parameterization of lateral drag as a function of sea ice thickness, drift velocity, and coastline length is presented. The results suggest that a combination of lateral drag parameterization and grounding (parameterized by basal stress) is required to simulate fast ice in most regions successfully. This work may lead to a versatile landfast ice parameterization for sea ice models in both shallow and deep coastal areas in the Arctic

Do we need non-Boussinesq effects in an ocean general circulation model for climate simulations?

The Boussinesq approximation is commonly made in ocean general circulation models (OGCMs). As a consequence, the model ocean is incompressible and conserves volume, but not mass. It has been argued that these consequence introduce errors at the noise level of coarse OGCMs, but that non-Boussinesq modeling is preferable simply for tidiness. Here, we use the height-pressure coordinate isomorphism implemented in the MITgcm to construct a non-Boussinesq OGCM and revisit the differences between Boussinesq and non-Boussinesq models at a resolution comparable to IPCC climate models. Subtleties such as the choice of a proper equation of state that includes the effect of pressure on heat capacity, but also the use of mass as a convenient alternative to pressure coordinates are discussed

Developing a dataset of Linear Kinematic Features (LKFs) for the evaluation of small-scale sea ice deformation

The Arctic sea ice deforms constantly due to stresses imposed by winds, ocean currents and interaction with coastlines. The most dominant features produced by this deformation in the ice cover are leads and pressure ridges that are often referred to as Linear Kinematic Features (LKFs). With increasing resolution of classical (viscous-plastic) sea ice models, or using new rheological frameworks (e.g. Maxwell elasto-brittle), sea-ice models start to resolve this small-scale deformation. So far, scaling properties of sea-ice deformation are commonly used to evaluate the modelled LKFs, besides other measures like lead area density. These metrics evade the problem of detecting individual LKFs by taking statistics over continuous fields like sea ice deformation or concentration. This way, they can provide specific information, but lack a comprehensive description of LKFs. We detect individual LKFs in sea ice deformation fields from satellite observations with an object detection algorithm. Combining this information with the sea ice drift fields used to derive the deformation fields, the LKFs are tracked in time. In doing so, the spatial characteristics (density, length, orientation, intersection angle, curvature) as well as the temporal evolution can be extracted from the same data-set. This algorithm can be applied to modelled sea-ice deformation and drift to enable a consistent comparison and thorough evaluation of simulated sea-ice deformation. We present preliminary results of LKFs detected in the RGPS data set and give examples of possible applications