Grease ice in basin-scale sea-ice ocean models

The first stage of sea-ice formation is often grease ice, a mixture of sea water and frazil ice crystals. Over time, grease ice typically congeals first to pancake ice floes and then to a solid sea-ice cover. Grease ice is commonly not explicitly simulated in basin-scale sea-ice ocean models, though it affects oceanic heat loss and ice growth and is expected to play a greater role in a more seasonally icecovered Arctic Ocean. We present an approach to simulate the grease-ice layer with, as basic properties, the surface being at the freezing point, a frazil ice volume fraction of 25%, and a negligible change in the surface heat flux compared to open water. The latter governs grease-ice production, and a gradual transition to solid sea ice follows, with ∼50% of the grease ice solidifying within 24 hours. The new parameterization delays lead closing by solid ice formation, enhances oceanic heat loss in fall and winter, and produces a grease-ice layer that is variable in space and time. Results indicate a 10-30% increase in mean winter Arctic Ocean heat loss compared to a standard simulation, with instant lead closing leading to significantly enhanced ice growth

Does the Arctic Amplification peak this decade?

Temperatures rise faster in the Arctic than on global average, a phenomenon known as Arctic Amplification. While this is well established from observations and model simulations, projections of future climate (here: RCP8.5) with models of the Coupled Model Intercomparison Project phase 5 (CMIP5) also indicate that the Arctic Amplification has a maximum. We show this by means of an Arctic Amplification factor (AAF), which we define as the ratio of Arctic mean to global mean surface air temperature (SAT) anomalies. The SAT anomalies are referenced to the period 1960-1980 and smoothed by a 30-year running mean. For October, the multi-model ensemble-mean AAF reaches a maximum in 2017. The maximum moves however to later years as Arctic winter progresses: for the autumn mean SAT (September to November) the maximum AAF is found in 2028 and for winter (December to February) in 2060. Arctic Amplification is driven, amongst others, by the ice-albedo feedback (IAF) as part of the more general surface albedo feedback (involving clouds, snow cover, vegetation changes) and temperature effects (Planck and lapse-rate feedbacks).We note that sea ice retreat and the associated warming of the summer Arctic Ocean are not only an integral part of the IAF but are also involved in the other drivers. In the CMIP5 simulations, the timing of the AAF maximum coincides with the period of fastest ice retreat for the respective month. Presence of at least some sea ice is crucial for the IAF to be effective because of the contrast in surface albedo between ice and open water and the need to turn ocean warming into ice melt. Once large areas of the Arctic Ocean are ice-free, the IAF should be less effective. We thus hypothesize that the ice retreat significantly affects AAF variability and forces a decline of its magnitude after at least half of the Arctic Ocean is ice-free and the ice cover becomes basically seasonal

The Arctic-Subarctic sea ice system is entering a seasonal regime: Implications for future Arctic amplification

The loss of Arctic sea ice is a conspicuous example of climate change. Climate models project ice-free conditions during summer this century under realistic emission scenarios, reflecting the increase in seasonality in ice cover. To quantify the increased seasonality in the Arctic-Subarctic sea ice system, we define a non-dimensional seasonality number for sea ice extent, area, and volume from satellite data and realistic coupled climate models. We show that the Arctic-Subarctic, i.e. The northern hemisphere, sea ice now exhibits similar levels of seasonality to the Antarctic, which is in a seasonal regime without significant change since satellite observations began in 1979. Realistic climate models suggest that this transition to the seasonal regime is being accompanied by a maximum in Arctic amplification, which is the faster warming of Arctic latitudes compared to the global mean, in the 2010s. The strong link points to a peak in sea-ice-related feedbacks that occurs long before the Arctic becomes ice-free in summer

Impact of the ice strength formulation on the performance of a sea ice thickness distribution model in the Arctic

The impact of a subgrid-scale ice thickness distribution (ITD) and two standard ice strength formulations on simulated Arctic sea ice climate is investigated. To this end, different model configurations with and without an ITD were tuned by minimizing the weighted mean error between the simulated and observed sea ice concentration, thickness, and drift speed with an semiautomatic parameter optimization routine. The standard ITD and ice strength parameterization lead to larger errors when compared to the simple single-category model with an ice strength parameterization based on the mean ice thickness. Interestingly, the simpler ice strength formulation, which depends linearly on the mean ice thickness, also reduces the model-observation error when using an ITD. For the ice strength parameterization that makes use of the ITD, the effective ice strength depends strongly on the number of thickness categories, so that introducing more categories can lead to overall thicker ice that is more easily deformed

The impact of variable sea ice roughness on changes in Arctic Ocean surface stress: a model study

The Arctic sea ice cover is thinning and retreating, causing changes in surface roughness that in turn modify the momentum flux from the atmosphere through the ice into the ocean. New model simulations comprising variable sea ice drag coefficients for both the air and water interface demonstrate that the heterogeneity in sea ice surface roughness significantly impacts the spatial distribution and trends of ocean surface stress during the last decades. Simulations with constant sea ice drag coefficients as used in most climate models show an increase in annual mean ocean surface stress (0.003 N/m2 per decade, 4.6%) due to the reduction of ice thickness leading to a weakening of the ice and accelerated ice drift. In contrast, with variable drag coefficients our simulations show annual mean ocean surface stress is declining at a rate of -0.002 N/m2 per decade (3.1%) over the period 1980-2013 because of a significant reduction in surface roughness associated with an increasingly thinner and younger sea ice cover. The effectiveness of sea ice in transferring momentum does not only depend on its resistive strength against the wind forcing but is also set by its top and bottom surface roughness varying with ice types and ice conditions. This reveals the need to account for sea ice surface roughness variations in climate simulations in order to correctly represent the implications of sea ice loss under global warming

On the ocean's response to enhanced Greenland runoff in model experiments: relevance of mesoscale dynamics and atmospheric coupling

Increasing Greenland Ice Sheet–melting is anticipated to impact watermass transformation in the subpolar North Atlantic and ultimately the meridional overturning circulation. Complex ocean and climate models are widely applied to predict magnitude and timing of related impacts under projected future climate. We discuss the role of the ocean mean state, subpolar gyre circulation, mesoscale eddies and atmospheric coupling in shaping the response of the subpolar North Atlantic Ocean to enhanced Greenland runoff. In a suite of eight dedicated 60 to 100-year long model experiments with and without atmospheric coupling, with eddy processes parameterized and explicitly simulated, with regular and significantly enlarged Greenland runoff, we find (1) a major impact by the interactive atmosphere in enabling a compensating temperature feedback, (2) a non-negligible influence by the ocean mean state biased towards greater stability in the coupled simulations, both of which making the Atlantic Merdional Overturning Circulation less susceptible to the freshwater perturbation applied, and (3) a more even spreading of the runoff tracer in the subpolar North Atlantic and enhanced inter-gyre exchange with the subtropics in the strongly eddying simulations. Overall, our experiments demonstrate the important role of mesoscale ocean dynamics and atmosphere feedbacks in projections of the climate system response to enhanced Greenland Ice Sheet–melting and hence underline the necessity to advance scale-aware eddy parameterizations for next-generation climate models