Ice and Fluid Dynamics

Abstract:

The Greenland Ice Sheet loses roughly half of its mass by ice discharge at marine terminating glaciers. Some of the largest and fastest flowing glaciers around Greenland calve kilometre-scale icebergs into long, narrow and deep fjords. These enormous icebergs typically capsize, or “flip” into more gravitationally stable orientations, and in doing so are thought to vigorously mix the stratified ocean within a small region in front of the glacier front. We investigate the effect of sudden ocean mixing events on flow within an idealised, linearlystratified model fjord using the Oceananigans.jl nonhydrostatic model. A large fraction of the available potential energy is rapidly converted to kinetic energy and radiates away as internal waves. These internal waves produce pulses of elevated melt rate across the entire glacier front, with magnitudes comparable to melt rates due to subglacial discharge plumes. On longer timescales, the qualitative character of the response depends on the ratio of fjord width, W, to first baroclinic Rossby deformation radius, R. Typical Greenland fjords have W/R between 0.5 and 2.0. Within this range of W/R, our model predicts the appearance of a long-lived nearly geostrophic anticyclonic eddy spanning the entire width of the fjord, constrained to mid-depths, in front of the glacier terminus. This eddy drives a sustained melt anomaly at mid-depths for many days, which may promote undercutting. We also investigate sensitivity to the horizontal extent of the region over which the fluid is mixed, and find that increasing the mixed volume beyond some critical value destabilises the abovementioned eddy, leading to its break up and consequently reducing the predicted glacier melt rate.

Abstract:

Melt ponds formed during summer play a crucial role in the evolution of Arctic sea ice. Observations show that the salinity in melt ponds ranges from 1 to 29 PSU, and saline ponds have different thermal properties from freshwater ponds. During the melt season, ponds with different salinities can exhibit distinct flow regimes and heat-transport efficiencies under the same radiative forcing, which can affect the relative fractions of absorbed heat that is emitted back to the atmosphere versus down into the ice. These feedbacks thus impact the evolution of pond depth. In the freezing season, the brine solution within a pond forms a porous mushy layer as it solidifies. If gravity drainage is triggered, the resulting plumes may induce complex circulation within the remnant unfrozen liquid beneath the ice lid and modify salinity transport within the underlying ice layer. These effects have not yet been fully quantified in existing models, despite their potential impact on the coupled pond–ice system.We develop a one-dimensional pond-ice model based on an enthalpy method and a brine drainage model to explore how initial pond salinity influences the system over a melting–freezing cycle. We constrain the parameterised fluxes in the one-dimensional model using insight from a suite of two-dimensional high-resolution simulations, including double-diffusive convection and mushy-layer dynamics. Our two-dimensional simulations of double-diffusive convection during the melting stage show that salinity regulates the internal flow regime by controlling stratification, thus inhibiting turbulent convection at relatively high salinities. During the refreezing stage, two-dimensional simulations using the enthalpy method show that gravity drainage can occur across a wide salinity range, initiating turbulence even in the absence of external heat sources. This turbulence leads to highly efficient vertical salt transport. By varying the initial salinity in the one-dimensional model, we find that salinity can consequently influence both the maximum pond depth and the timescale of pond refreezing.

Abstract:

The physics of planetary climate features a variety of complex systems that are challenging to model as they feature turbulent flows. A key example is the heat flux from the upper ocean to the underside of sea ice which provides a key contribution to the evolution of the Arctic sea ice cover. Here, we develop a model of the turbulent ice-ocean heat flux using coupled ordinary stochastic differential equations to model fluctuations in the vertical velocity and temperature in the Arctic mixed layer. All the parameters in the model are determined from observational data. A detailed comparison between the model results and measurements made during the Surface Heat Budget of the Arctic Ocean (SHEBA) project reveals that the model is able to capture the probability density functions (PDFs) of velocity, temperature and heat flux fluctuations. Furthermore, we show that the temperature in the upper layer of the Arctic ocean can be treated as a passive scalar during the whole year of SHEBA measurements. The stochastic model developed here provides a computationally inexpensive way to compute an observationally consistent PDF of this heat flux, and has implications for its parametrization in regional and global climate models.