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David M. Holland

Abstract

A coupled sea-ice–ocean numerical model is used to study the impact of an ill-resolved subgrid-scale sea-ice–ocean dynamical process on the areal coverage of the sea-ice field. The process of interest is the transmission of stress from the ocean into the sea-ice cover and its subsequent interaction with the sea-ice internal stress field. An idealized experiment is performed to highlight the difference in evolution of the sea-ice cover in the circumstance of a relatively coarse-resolution grid versus that of a fine-resolution one. The experiment shows that the ubiquitous presence of instabilities in the near-surface ocean flow field as seen on a fine-resolution grid effectively leads to a sink of sea-ice areal coverage that does not occur when such flow instabilities are absent, as on a coarse-resolution grid. This result also implies that a fine-resolution grid may have a more efficient atmosphere–sea-ice–ocean thermodynamic exchange than a coarse one. This sink of sea-ice areal coverage arises because the sea-ice undergoes sporadic, irreversible plastic failure on a fine-resolution grid that, by contrast, does not occur on a coarse-resolution grid. This demonstrates yet again that coarse-resolution coupled climate models are not reaching fine enough resolution in the polar regions of the world ocean to claim that their numerical solutions have reached convergence.

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Marika M. Holland

Abstract

Recent observations suggest that large and widespread changes are occurring in the Arctic climate system. Many of these are associated with the North Atlantic Oscillation (NAO) or the closely related Arctic Oscillation (AO). Here, the Arctic climate and its response to the NAO–AO is examined in a control simulation of the newly released Community Climate System Model, version 2 (CCSM2). Variability in the atmosphere and sea ice systems are considered and the physical mechanisms that drive the variations are discussed. It is found that the model reasonably simulates the spatial structure and variance of the sea level pressure, surface air temperature, and precipitation associated with the NAO–AO. The sea ice response to the NAO–AO also compares well to observations. However, it varies over the length of the time series, which is related to variations in the spatial structure of the sea level pressure anomalies associated with the NAO–AO over time. The model results suggest that these variations, which are similar to changes that occur over the observed record, are common and part of the natural variability of the system. However, the magnitude of the observed trends over the last 40 yr in the NAO–AO index are never realized in the model simulations, suggesting that these trends may be associated with changes in anthropogenic forcing, which the simulation examined here does not include.

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Hugues Goosse and Marika M. Holland

Abstract

Several mechanisms have been proposed to explain natural climate variability in the Arctic. These include processes related to the influence of the North Atlantic Oscillation/Arctic Oscillation (NAO/AO), anticyclonic/cyclonic regimes, changes in the oceanic and atmospheric North Atlantic–Arctic exchange, and changes in the Atlantic meridional overturning circulation. After a brief critical review, the influence and interrelation of the above processes in a long climate integration of the Community Climate System Model, version 2 (CCSM2) are examined. The analysis is based on the time series of surface air temperature integrated northward of 70°N, which serves as a useful proxy for general Arctic climate conditions. This gives a large-scale view of the evolution of Arctic climate. It is found that changes in oceanic exchange and heat transport in the Barents Sea dominate in forcing the Arctic surface air temperature variability in CCSM2. Changes in atmospheric circulation are consistent with a wind forcing of this variability, while changes in the deep overturning circulation in the Atlantic are more weakly related in CCSM2. Over some time periods, the NAO/AO is significantly related to these changes in Arctic climate conditions. However, this is not robust over longer time scales.

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David M. Holland and Adrian Jenkins

Abstract

Much of the Antarctic coastline comprises large, floating ice shelves, beneath which waters from the open ocean circulate. The interaction of the seawater with the base of these ice shelves has a bearing both on the rate at which Antarctic Bottom Water is formed and on the mass balance of the ice sheet. An isopycnic coordinate ocean general circulation model has been modified so as to allow the incorporation of a floating ice shelf as an upper boundary to the model domain. The modified code admits the introduction of an arbitrary surface pressure field and includes new algorithms for the diagnosis of entrainment into, and detrainment from, the surface mixed layer. Special care is needed in handling the cases where the mixed layer, and isopycnic interior layers, interact with surface and basal topography. The modified model is described in detail and then applied to an idealized ice shelf–ocean geometry. Simple tests with zero surface buoyancy forcing indicate that the introduction of the static surface pressure induces an insignificant motion in the underlying water. With nonzero surface buoyancy forcing the model produces a cyclonic circulation beneath the ice shelf. Outflow along the ice shelf base, driven by melting of the thickest ice, is balanced by deep inflow. The abrupt change in water column thickness at the ice shelf front does not form a barrier to buoyancy-driven circulation across the front.

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Irena Vaňková and David M. Holland

Abstract

When glaciers calve icebergs, a fraction of the released potential energy is radiated away via gravity waves. The characteristics of such waves, caused by iceberg calving on Helheim Glacier in east Greenland, are investigated. Observations were collected from an array of five high-frequency bottom pressure meters placed along Sermilik Fjord. Calving-generated tsunami waves were identified and used to construct a calving event catalog. Calving events are observed to cluster around high and low semidiurnal tides and around high and prior-to-low semimonthly tides. In the postcalving ocean state, discrete spectral peaks associated with calving events are observed, and they are consistent among all the events. A numerical model is used to compute the resonant modes of the fjord and to simulate calving-generated ocean waves. Damped oscillator boundary forcing with 5- to 10-min periods is found to reproduce well the observed properties of calving waves. These observations and modeling are relevant for better understanding of wave dynamics in glacier fjords.

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Marika M. Holland and Donald Perovich

Abstract

Arctic sea ice has undergone significant change with large reductions in thickness and areal extent over the historical record. Numerical models project sea ice loss to continue for the foreseeable future, with the possibility of September ice-free conditions later this century. Understanding the mechanisms behind ice loss and its consequences for the larger Arctic and global systems is important if we are to anticipate and plan for the future. Meeting this challenge requires the collective and collaborative insights of scientists investigating the system from numerous perspectives. One impediment to progress has been a disconnect between the observational and modeling research communities. Advancing the science requires enhanced integration between these communities and more collaborative approaches to understanding Arctic sea ice loss. This paper discusses a successful effort to further these aims: a weeklong sea ice summer camp held in Barrow, Alaska (now known as Utqiaġvik), in May 2016. The camp brought together 25 participants who were a heterogeneous mix of observers and modelers from 13 different institutions at career stages from graduate students to senior researchers. The summer camp provided an accelerated program on sea ice observations and models and also fostered future collaborative interdisciplinary activities. A dialogue with Barrow community members was initiated in order to further understand the local consequences of Arctic sea ice loss. The discussion herein describes lessons learned from this activity and paths forward to advance the understanding and prediction of Arctic climate change.

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David M. Holland and Adrian Jenkins

Abstract

Models of ocean circulation beneath ice shelves are driven primarily by the heat and freshwater fluxes that are associated with phase changes at the ice–ocean boundary. Their behavior is therefore closely linked to the mathematical description of the interaction between ice and ocean that is included in the code. An hierarchy of formulations that could be used to describe this interaction is presented. The main difference between them is the treatment of turbulent transfer within the oceanic boundary layer. The computed response to various levels of thermal driving and turbulent agitation in the mixed layer is discussed, as is the effect of various treatments of the conductive heat flux into the ice shelf. The performance of the different formulations that have been used in models of sub-ice-shelf circulation is assessed in comparison with observations of the turbulent heat flux beneath sea ice. Formulations that include an explicit parameterization of the oceanic boundary layer give results that lie within about 30% of observation. Formulations that use constant bulk transfer coefficients entail a definite assumption about the level of turbulence in the water column and give melt/freeze rates that vary by a factor of 5, implying very different forcing on the respective ocean models.

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Paul R. Holland, Adrian Jenkins, and David M. Holland

Abstract

A three-dimensional ocean general circulation model is used to study the response of idealized ice shelves to a series of ocean-warming scenarios. The model predicts that the total ice shelf basal melt increases quadratically as the ocean offshore of the ice front warms. This occurs because the melt rate is proportional to the product of ocean flow speed and temperature in the mixed layer directly beneath the ice shelf, both of which are found to increase linearly with ocean warming. The behavior of this complex primitive equation model can be described surprisingly well with recourse to an idealized reduced system of equations, and it is shown that this system supports a melt rate response to warming that is generally quadratic in nature. This study confirms and unifies several previous examinations of the relation between melt rate and ocean temperature but disagrees with other results, particularly the claim that a single melt rate sensitivity to warming is universally valid. The hypothesized warming does not necessarily require a heat input to the ocean, as warmer waters (or larger volumes of “warm” water) may reach ice shelves purely through a shift in ocean circulation. Since ice shelves link the Antarctic Ice Sheet to the climate of the Southern Ocean, this finding of an above-linear rise in ice shelf mass loss as the ocean steadily warms is of significant importance to understanding ice sheet evolution and sea level rise.

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Lance M. Leslie and Greg J. Holland

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The potential for predicting the skill of 36-h forecasts from the Australian region limited area model is investigated using three predictors of model forecast error (MFE) for mean sea level pressure. Two of the predictors utilize single forecasts: one is based on statistical regression of the MFE against the initial analysis and the forecast; and the other uses a measure of the degree of persistence in the forecast. The third predictor utilizes the divergence, or spread, of an ensemble of forecasts from other NWP centers.

Based on a 5-month period of daily 36-h forecasts, correlations were found between the above predictors and the MFE of 0.58, 0.18, and 0.40, respectively. Combining the three predictors in an optimal linear manner increased the correlation to 0.71. Further testing of the combined predictors on a 2-month independent dataset produced a correlation of 0.67. Thus, application of the technique to both dependent and independent datasets explained approximately 50% of the variance in the MFE. This demonstrates that the technique has operational utility for differentiating overall poor and good model forecasts. Using case studies concentrating on southeastern Australia, it is further demonstrated that the predictors can provide excellent differentiation of forecast skill across the forecast domain.

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Marika M. Holland and Judith A. Curry

Abstract

The importance of the Arctic region for global climate change has recently been highlighted in the results from general circulation model simulations under increasing atmospheric CO2 scenarios. The warming that is predicted by these studies is most pronounced in the polar regions, indicating that it may be the first place in which the effects of global climate change will be detected. However, the natural variability that is present in the Arctic climate system is largely unknown and is likely to obscure the detection of anthropogenically forced changes. Additionally, there is little information on the internal processes of the Arctic ice pack, which are important for determining the variability of the ice cover.

In an effort to address these issues, the variability of the Arctic ice volume is examined using a single column sea ice–ocean mixed layer model. The model contains an ice thickness distribution and the parameterization of export and ridging due to ice divergence and shear. Variability in the ice cover is forced by applying stochastic perturbations to the air temperature and ice divergence forcing fields.

Several sensitivity tests are performed in order to assess the role of different physical processes in determining the variability of the perennial Arctic ice pack. It is found that the surface albedo and ice–ocean feedback mechanisms act to enhance the variability of the ice volume and are particularly important for the simulated response of the sea ice to fluctuations in air temperature, accounting for approximately 62% and 25% of the ice volume variance, respectively. The details of the ice thickness distribution also significantly affect the simulated variability. In particular, the ridging process acts to decrease the simulated variability of the ice pack. It reduces the variance of the ice volume by 50% when air temperature stochastic forcing is applied.

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