Ice Breakup Research Articles

Evaporation from boreal reservoirs: A comparison between eddy covariance observations and estimates relying on limited data

AbstractHydrological models used for reservoir management typically lack an accurate representation of open‐water evaporation and must be run in a scarce data context. This study aims to identify an accurate means to estimate reservoir evaporation with simple meteorological inputs during the open‐water season, using long‐term eddy covariance observations from two boreal hydropower reservoirs with contrasting morphometry as reference. Unlike the temperate water bodies on which the majority of other studies have focused, northern reservoirs are governed by three distinct periods: ice cover in the cold season, warming in the summer and energy release in the fall. The reservoirs of interest are Eastmain‐1 (52°N, mean depth of 11 m) and Romaine‐2 (51°N, mean depth of 42 m), both located in eastern Canada. Four approaches are analysed herein: a combination approach, a radiation‐based approach, a mass‐transfer approach, and empirical methods. Of all the approaches, the bulk transfer equation with a constant Dalton number of 1.2 x 10−3 gave the most accurate estimation of evaporation at hourly time steps, compared with the eddy covariance observations (RMSE of 0.06 mm h−1 at Eastmain‐1 and RMSE of 0.04 mm h−1 at Romaine‐2). The daily series also showed good accuracy (RMSE of 1.38 mm day−1 at Eastmain‐1 and RMSE of 0.62 mm day−1 at Romaine‐2) both in the warming and energy release phases of the open‐water season. The bulk transfer equation, on the other hand, was incapable of reproducing condensation episodes that occurred soon after ice breakup. Basic and variance‐based sensitivity analyses were conducted, in particular to measure the variation in performance when the bulk transfer equation was applied with meteorological observations collected at a certain distance (~10–30 km) from the reservoir. This exercise illustrated that accurate estimates of open water evaporation require representative measurements of wind speed and water surface temperature.

Naturalizing the freezeup regimes of regulated rivers and exploring implications to spring ice‐jam flooding

AbstractNaturalization of the flow hydrograph and ice regime is a key step in assessment of ecological and socioeconomic impacts of regulation across large portions of Europe, Asia and North America, where many rivers are dammed for hydropower generation. Building on previous naturalization of early‐freshet flows that influence the nature of breakup and jamming events, novel methodology is developed to estimate natural freezeup flows and thence determine associated water levels, also known to influence subsequent breakup events. Using reservoir inflows, the new methodology is applied to the lower portion of the regulated Peace River, Canada, which forms the northern boundary of the Peace‐Athabasca Delta (PAD), a Ramsar wetland of international importance that partially depends on spring ice‐jam flooding for recharge of its high‐elevation, or “perched” basins. The PAD provides habitat for numerous aquatic, terrestrial and avian species and is vital to the maintenance of indigenous culture and lifeways. Naturalized freezeup levels in the lower Peace River are shown to be nearly always lower than corresponding regulated values, with the difference averaging ~1.6 m. Consistent with known physics of river ice breakup processes, the present results suggest that ice‐jam flood frequency would likely have been greater under natural conditions. Though potentially adverse from the ecological standpoint, reduction of spring ice‐jam flooding can benefit riverside communities. Implications of the present results to and comparison with, other Canadian and international rivers are discussed.

Earlier ice breakup induces changepoint responses in duration and variability of spring mixing and summer stratification in dimictic lakes

AbstractReductions in ice cover duration and earlier ice breakup are two of the most prevalent responses to climate warming in lakes in recent decades. In dimictic lakes, the subsequent periods of spring mixing and summer stratification are both likely to change in response to these phenological changes in ice cover. Here, we used a modeling approach to simulate the effect of changes in latitude on long‐term trends in duration of ice cover, spring mixing, and summer stratification by “moving” a well‐studied lake across a range of latitudes in North America (35.2°N to 65.7°N). We found a changepoint relationship between the timing of ice breakup vs. spring mixing duration on 09 May. When ice breakup occurred before 09 May, which routinely occurred at latitudes < 47°N, spring mixing was longer and more variable; when ice breakup occurred after 09 May at latitudes > 47°N, spring mixing averaged 1 day with low variability. In contrast, the duration of summer stratification showed a relatively slower rate of increase when ice breakup occurred before 09 May (< 47°N) compared to a 109% faster rate of increase when ice breakup was after 09 May (> 47°N). Projected earlier ice breakup can result in important nonlinear changes in the relative duration of spring mixing and summer stratification, which can lead to mixing regime shifts that influence the severity of oxygen depletion differentially across latitudes.

The seasonal cycle and break-up of landfast sea ice along the northwest coast of Kotelny Island, East Siberian Sea

AbstractArctic landfast sea ice (LFSI) represents an important quasi-stationary coastal zone. Its evolution is determined by the regional climate and bathymetry. This study investigated the seasonal cycle and interannual variations of LFSI along the northwest coast of Kotelny Island. Initial freezing, rapid ice formation, stable and decay stages were identified in the seasonal cycle based on application of the visual inspection approach (VIA) to MODIS/Envisat imagery and results from a thermodynamic snow/ice model. The modeled annual maximum ice thickness in 1995–2014 was 2.02 ± 0.12 m showing a trend of −0.13 m decade−1. Shortened ice season length (−22 d decade−1) from model results associated with substantial spring (2.3°C decade−1) and fall (1.9°C decade−1) warming. LFSI break-up resulted from combined fracturing and melting, and the local spatiotemporal patterns of break-up were associated with the irregular bathymetry. Melting dominated the LFSI break-up in the nearshore sheltered area, and the ice thickness decreased to an average of 0.50 m before the LFSI disappeared. For the LFSI adjacent to drift ice, fracturing was the dominant process and the average ice thickness was 1.56 m at the occurrence of the fracturing. The LFSI stages detected by VIA were supported by the model results.

Ice‐Covered Lakes of Tibetan Plateau as Solar Heat Collectors

AbstractThe Qinghai‐Tibet Plateau possesses the largest alpine lake system, which plays a crucial role in the land‐atmosphere interaction. We report first observations on the thermal and radiation regime under ice of the largest freshwater lake of the Plateau. The results reveal that freshwater lakes on the Tibetan Plateau fully mix under ice. Due to strong solar heating, water temperatures increase above the maximum density value 1–2 months before the ice break, forming stable thermal stratification with subsurface temperatures >6°C. The resulting heat flow from water to ice makes a crucial contribution to ice cover melt. After the ice breakup, the accumulated heat is released into the atmosphere during 1–2 days, increasing lake‐atmosphere heat fluxes up to 500 W m−2. The direct biogeochemical consequences of the deep convective mixing are aeration of the deep lake waters and upward supply of nutrients to the upper photic layer.

Fine-Resolution Mapping of Pan-Arctic Lake Ice-Off Phenology Based on Dense Sentinel-2 Time Series Data

The timing of lake ice-off regulates biotic and abiotic processes in Arctic ecosystems. Due to the coarse spatial and temporal resolution of available satellite data, previous studies mainly focused on lake-scale investigations of melting/freezing, hindering the detection of subtle patterns within heterogeneous landscapes. To fill this knowledge gap, we developed a new approach for fine-resolution mapping of Pan-Arctic lake ice-off phenology. Using the Scene Classification Layer data derived from dense Sentinel-2 time series images, we estimated the pixel-by-pixel ice break-up end date information by seeking the transition time point when the pixel is completely free of ice. Applying this approach on the Google Earth Engine platform, we mapped the spatial distribution of the break-up end date for 45,532 lakes across the entire Arctic (except for Greenland) for the year 2019. The evaluation results suggested that our estimations matched well with both in situ measurements and an existing lake ice phenology product. Based on the generated map, we estimated that the average break-up end time of Pan-Arctic lakes is 172 ± 13.4 (measured in day of year) for the year 2019. The mapped lake ice-off phenology exhibits a latitudinal gradient, with a linear slope of 1.02 days per degree from 55°N onward. We also demonstrated the importance of lake and landscape characteristics in affecting spring lake ice melting. The proposed approach offers new possibilities for monitoring the seasonal Arctic lake ice freeze–thaw cycle, benefiting the ongoing efforts of combating and adapting to climate change.

One-dimensional channel network modelling and simulation of flow conditions during the 2008 ice breakup in the Mackenzie Delta, Canada

This paper presents recent developments to River1D's (the University of Alberta's public-domain hydrodynamic and river ice process model) channel network modelling capabilities. While previous versions of the model assumed equal water surface elevations through the junction, the approach presented in this paper takes into account the significant physical effects at channel junctions (such as gravity and flow separation forces, and channel resistance). The adapted approach is also equipped with the ability to dynamically change junction configurations (i.e. diverging to converging or vice versa) as the result of flow reversals. The intent here was to develop an approach that would permit the simulation of flow in a channel network that includes the more important physical effects at junctions but without the need to adjust model parameters or redefine junctions should a flow reversal occur. This momentum based approach to simulate junctions is assessed using a series of steady and unsteady tests using a 2D model, the University of Alberta's River2D, for comparison. For the diverging junction tests, the proposed 1D network model performed very well with respect to the discharge split. The model accurately simulated the water surface elevation in the two receiving channels but tended to overestimate the water surface elevation immediately upstream of the junction, perhaps attributable to model discretization and/or neglecting the centrifugal forces acting on the main channel as the lateral channel branches off. For the two parallel channels with a perpendicular connecting channel tests, the 1D model agreed well with the 2D model for all steady and unsteady tests. The unsteady test results demonstrated how capable the 1D model is at handling transient flow reversals. The model is then applied to a network of channels in the Mackenzie Delta. The model was calibrated and validated for three open water events, and subsequently used to simulate flow conditions during the 2008 breakup. Model results agreed well with observed water level data collected using data loggers. A comparison of the model flows for the pre-jam and ice-jam conditions suggests that ice jamming can significantly impact the distribution of flow in the upper Mackenzie Delta. For the ice-jam conditions, the simulated flow reversal in the Peel Mackenzie Connector is consistent with observations in this channel during the 2008 breakup.

Snow Phenology and Hydrologic Timing in the Yukon River Basin, AK, USA

The Yukon River basin encompasses over 832,000 km2 of boreal Arctic Alaska and northwest Canada, providing a major transportation corridor and multiple natural resources to regional communities. The river seasonal hydrology is defined by a long winter frozen season and a snowmelt-driven spring flood pulse. Capabilities for accurate monitoring and forecasting of the annual spring freshet and river ice breakup (RIB) in the Yukon and other northern rivers is limited, but critical for understanding hydrologic processes related to snow, and for assessing flood-related risks to regional communities. We developed a regional snow phenology record using satellite passive microwave remote sensing to elucidate interactions between the timing of upland snowmelt and the downstream spring flood pulse and RIB in the Yukon. The seasonal snow metrics included annual Main Melt Onset Date (MMOD), Snowoff (SO) and Snowmelt Duration (SMD) derived from multifrequency (18.7 and 36.5 GHz) daily brightness temperatures and a physically-based Gradient Ratio Polarization (GRP) retrieval algorithm. The resulting snow phenology record extends over a 29-year period (1988–2016) with 6.25 km grid resolution. The MMOD retrievals showed good agreement with similar snow metrics derived from in situ weather station measurements of snowpack water equivalence (r = 0.48, bias = −3.63 days) and surface air temperatures (r = 0.69, bias = 1 day). The MMOD and SO impact on the spring freshet was investigated by comparing areal quantiles of the remotely sensed snow metrics with measured streamflow quantiles over selected sub-basins. The SO 50% quantile showed the strongest (p < 0.1) correspondence with the measured spring flood pulse at Stevens Village (r = 0.71) and Pilot (r = 0.63) river gaging stations, representing two major Yukon sub-basins. MMOD quantiles indicating 20% and 50% of a catchment under active snowmelt corresponded favorably with downstream RIB (r = 0.61) from 19 river observation stations spanning a range of Yukon sub-basins; these results also revealed a 14–27 day lag between MMOD and subsequent RIB. Together, the satellite based MMOD and SO metrics show potential value for regional monitoring and forecasting of the spring flood pulse and RIB timing in the Yukon and other boreal Arctic basins.

Changes in sea ice travel conditions in Uummannaq Fjord, Greenland (1985–2019) assessed through remote sensing and transportation accessibility modeling

ABSTRACT Shorefast sea ice provides an important platform for winter and spring travel between coastal Arctic communities unconnected by road networks. In the past two decades, local Arctic residents have reported thinning and earlier breakup of shorefast ice. Despite these assertions, however, there are few quantitative assessments of how these changes have impacted travel on sea ice. In this study, we use high-resolution satellite remote sensing and transportation modeling to assess snow mobile travel in Uummannaq Fjord, Greenland. Following classification of satellite imagery, we generate optimal least-cost travel routes according to surface types present in the fjord. We then estimate distance and duration of snowmobile travel potential between communities from 1985 through 2019. We find that snowmobile travel in Uummannaq Fjord has potentially become slower and more unpredictable in recent years (2014–2019) relative to thirty years prior (1985–2000), with greater changes for communities located more proximal to the shorefast ice edge. Our results also suggest that reductions in on-ice snow cover impede snowmobile travel more than fractures do. Overall, our analysis demonstrates how remote sensing and transportation modeling may be used to quantify the community-scale impacts of changing shorefast ice conditions and has potential to help manage localized climate-related risk.

A systematic evaluation of criteria for river ice breakup initiation using River1D model and field data

Mechanical breakup of river ice cover is often associated with ice runs, ice jams, and fast-rising water levels. It not only poses great flood threats to riverside communities, but also has great implications to environment and river ecosystems. Our current ability to model the onset of mechanical breakup is limited. Existing river ice models either require the user to manually specify the breakup times and locations or they employ empirical criteria to simulate ice cover breakup. This paper presents a systematic evaluation of existing empirical and semi-empirical/physics-based breakup criteria using the University of Alberta's River1D model. Each criterion was evaluated according to its ability to capture the breaking front propagation observed on the Athabasca River and Peace River during three breakup seasons, as well as the transferability of the calibrated parameter(s). The storage release from broken ice cover has been postulated to lead to the formation of a non-attenuating, i.e. self-sustaining wave, which in turn maintains fast ice cover breaking over very long distance. This study shows that the characteristics of self-sustaining wave under natural river conditions are greatly affected by the varying resistance to ice breaking along a river, which is different than previous findings based on numerical studies in prismatic channels.

Geographic variation and temporal trends in ice phenology in Norwegian lakes during the period 1890–2020

Abstract. Long-term observations of ice phenology in lakes are ideal for studying climatic variation in time and space. We used a large set of observations from 1890 to 2020 of the timing of freeze-up and break-up, and the length of ice-free season, for 101 Norwegian lakes to elucidate variation in ice phenology across time and space. The dataset of Norwegian lakes is unusual, covering considerable variation in elevation (4–1401 m a.s.l.) and climate (from oceanic to continental) within a substantial latitudinal and longitudinal gradient (58.2–69.9∘ N, 4.9–30.2∘ E). The average date of ice break-up occurred later in spring with increasing elevation, latitude and longitude. The average date of freeze-up and the length of the ice-free period decreased significantly with elevation and longitude. No correlation with distance from the ocean was detected, although the geographical gradients were related to regional climate due to adiabatic processes (elevation), radiation (latitude) and the degree of continentality (longitude). There was a significant lake surface area effect as small lakes froze up earlier due to less volume. There was also a significant trend that lakes were completely frozen over later in the autumn in recent years. After accounting for the effect of long-term trends in the large-scale North Atlantic Oscillation (NAO) index, a significant but weak trend over time for earlier ice break-up was detected. An analysis of different time periods revealed significant and accelerating trends for earlier break-up, later freeze-up and completely frozen lakes after 1991. Moreover, the trend for a longer ice-free period also accelerated during this period, although not significantly. An understanding of the relationship between ice phenology and geographical parameters is a prerequisite for predicting the potential future consequences of climate change on ice phenology. Changes in ice phenology will have consequences for the behaviour and life cycle dynamics of the aquatic biota.

Arctic char enter the marine environment before annual ice breakup in the high Arctic

Mobile consumers often match their movements to short-term resource pulses. In the Arctic, seasonal ice breakup facilitates an ephemeral productivity pulse exploited by marine consumers. The migration of anadromous Arctic char (Salvelinus alpinus) to marine waters occurs around the beginning of ice breakup, but the precise timing of movement is equivocal and current evidence is conflicting. To investigate the migratory timing of Arctic char, 34 individuals were tagged with acoustic telemetry transmitters within Tremblay Sound, Nunavut, Canada in two successive years. All tagged fish entered the marine environment before the coastal ice-off date (mean ± SE: 7.56 ± 0.56 days). Further movement metrics revealed that char utilized much of the sound before the ice-off date, with only slightly higher mean home ranges (0.3 km2 larger) and residency indices (by ~ 0.05) during the period following the ice-off date than prior. Such entry and use of marine waters prior to ice breakup may impart energetic benefits to early migrants, maximizing exploitation of the short, anticipated pulse of productivity. The current study provides a unique example of resource tracking that could confer heightened fitness to a marine consumer in the rapidly warming high Arctic.

Sizes and Shapes of Sea Ice Floes Broken by Waves–A Case Study From the East Antarctic Coast

The floe size distribution (FSD) is an important characteristics of sea ice, influencing several physical processes that take place in the oceanic and atmospheric boundary layers under/over sea ice, as well as within sea ice itself. Through complex feedback loops involving those processes, FSD might modify the short-term and seasonal evolution of the sea ice cover, and therefore significant effort is undertaken by the scientific community to better understand FSD-related effects and to include them in sea ice models. An important part of that effort is analyzing the FSD properties and variability in different ice and forcing conditions, based on airborne and satellite imagery. In this work we analyze a very high resolution (pixel size: 0.3 m) satellite image of sea ice from a location off the East Antarctic coast (65.6°S, 101.9°E), acquired on February 16, 2019. Contrary to most previous studies, the ice floes in the image have angular, polygonal shapes and a narrow size distribution. We show that the observed FSD can be represented as a weighted sum of two probability distributions, a Gaussian and a tapered power law, with the Gaussian part clearly dominating in the size range of floes that contribute over 90% to the total sea ice surface area. Based on an analysis of the weather, wave and ice conditions in the period preceding the day in question, we discuss the most probable scenarios that led to the breakup of landfast ice into floes visible in the image. Finally, theoretical arguments backed up by a series of numerical simulations of wave propagation in sea ice performed with a scattering model based on the Matched Eigenfunction Expansion Method are used to show that the observed dominating floe size in the three different regions of the image (18, 13 and 51 m, respectively) agree with those expected as a result of wave-induced breaking of landfast ice.

Remote sensing of lake ice phenology in Alaska

The timing of lake ice breakup and freezeup are important indicators of climate change in Arctic and boreal regions because they respond rapidly and directly to variations in climate conditions. Despite its importance, lake ice phenology remains poorly documented in most lakes of Alaska. To fill this data gap, we constructed a remote sensing-derived lake ice phenology database covering all lakes in Alaska larger than 1 km2 (n = 4241) over the period 2000–2019. This dataset, which includes lake ice on/off dates and lake ice duration, was based on an automatic method using daily moderate resolution imaging spectroradiomenter (MODIS) imagery to measure lake ice fraction. This method extracts lake ice pixels from MODIS images using a dynamic threshold that was calibrated against Landsat Fmask. Different filters that account for clouds, polar night, and other sources of error were applied to increase the accuracy of lake ice phenology estimation. Trend analysis shows earlier breakup (−5.5 d decade−1) for 440 lakes and later breakup (7.5 d decade−1) for four lakes (p < 0.05). A total of 289 lakes had significant trends toward later freezeup (2.9 d decade−1) and 11 lakes towards earlier freezeup (−3.3 d decade−1). Most lakes with significant trends are north of the Brooks Range. This dataset can contribute to increased understanding of interactions between lake processes and climate change, and it supports the study of biogeochemical, limnological and ecological regimes in Alaska and pan-Arctic regions.

Climate change and Northern Hemisphere lake and river ice phenology from 1931–2005

Abstract. At high latitudes and altitudes one of the main controls on hydrological and biogeochemical processes is the breakup and freeze-up of lake and river ice. This study uses 3510 time series from across 678 Northern Hemisphere lakes and rivers to explore historical patterns in lake and river ice phenology across five overlapping time periods (1931–1960, 1946–1975, 1961–1990, 1976–2005, and 1931–2005). These time series show that the number of annual open-water days increased by 0.63 d per decade from 1931–2005 across the Northern Hemisphere, with trends for breakup and, to a lesser extent, freeze-up closely correlating with regionally averaged temperature. Breakup and freeze-up trends display a spatiotemporally complex evolution and reveal considerable caveats with interpreting the implications of ice phenology changes at lake and river sites that may only have breakup or freeze-up data, rather than both. These results provide an important contribution by showing regional variation in ice phenology trends through time that can be hidden by longer-term trends. The overlapping 30-year time periods also show evidence for an acceleration in warming trends through time. Understanding the changes on both long- and short-term timescales will be important for determining the causes of this change, the underlying biogeochemical processes associated with it, and the wider climatological significance as global temperatures rise.

Theoretical model for predicting the break-up of ice covers due to wave-ice interaction

An approximate solution for wave transmission and reflection between open water and a finite viscoelastic ice cover is developed in the present study, in which both the water part and the ice cover are treated as a continuum, each governed by its own equation of motion. The interface conditions include matching velocities and stresses between the two continua. In this study, only two modes of the dispersion relation are considered, and horizontal boundary conditions are approximated by matching mean values. The reflection and transmission coefficients are determined for simplified cases to compare with earlier theories. Behaviors of the resonance are obtained for pure elastic ice covers. The effect of viscosity is also investigated for viscoelastic ice covers. According to the above wave-ice interaction model, the stress and strain are calculated in the ice cover. By using a stress failure criterion, the break-up condition of ice covers with different thickness and length under the interaction of waves and sea ice is determined. Finally, a dynamic evolution model of the ice floe size distribution function in the marginal ice zone is established. The present study is useful for modeling the wave-in-ice climate on a geophysical scale.

A hybrid ensemble modelling framework for the prediction of breakup ice jams on Northern Canadian Rivers

The forecasting of river ice jams faces challenges relating to both the availability of data and the complexity of river ice dynamics, resulting in difficulties in model formulation. In this study, a hybrid ensemble modelling framework is developed to address the data scarcity issue and leverage advanced machine learning techniques for the prediction of ice jams with a one-day lead time. The proposed methodology utilises data easily monitored in advance of any ice jam events and maintains a realistic balance between ice jam and non-ice jam events. A combination of both single model algorithms, including classification trees, logistic regression, k-nearest neighbors, support vector machines, and artificial neural networks, and ensemble model algorithms, including random forest, adaptive boosting, gradient boosting, variance penalizing adaptive boosting, logistic boosting, class switching, and adaptive resampling and combining, are considered for both the member models of the first layer of the hybrid ensemble and for the ensemble combiner of the second layer. The final selection of both variables and member models for the hybrid ensemble is detailed, with a focus on the reduction of false negatives, the prediction of no ice jam on a day when one occurs. The proposed method is applied to the St. John River in New Brunswick, Canada, in a location particularly prone to ice jam flooding. Using the proposed methodology, a final model combining 6 different member models using a support vector machine as the ensemble combiner was produced, with a balanced prediction accuracy of 86%. This hybrid ensemble model outperformed the other tested ensemble models, as well as a series of generalized models produced using all available input variables and member models. The model also performed well against other ensemble techniques and against the individual member models. These results demonstrate the viability of the proposed methodology in constructing a hybrid ensemble model for the forecasting of ice jams on Northern Canadian Rivers. The techniques utilised can be adapted to other locations to facilitate ice jam forecasting, requiring data that is easily available and monitored in advance of any potential flooding events.

Observing Wind-Forced Flexural-Gravity Waves in the Beaufort Sea and Their Relationship to Sea Ice Mechanics

We developed and deployed two inertial measurement units on mobile pack ice during a U.S. Navy drifting ice campaign in the Beaufort Sea. The ice camp was more than 1000 km from the nearest open water. The sensors were stationed on thick (&gt;1 m) first- and multi–year ice to record 3-D accelerations at 10 Hz for one week during March 2020. During this time, gale-force winds exceeded 21 m per second for several hours during two separate wind events and reached a maximum of 25 m per second. Our observations show similar sets of wave bands were excited during both wind events. One band was centered on a period of ~14 s. Another band arrived several hours later and was centered on ~3.5-s. We find that the observed wave bands match a model dispersion curve for flexural gravity waves in ~1.2-m ice with a Young’s modulus of 3.5 GPa under compressive stresses of ~0.3 MPa. We further evaluate the bending stress and load cycles of the individual wave bands and their potential role in break-up of sea ice. This work demonstrates how observations of waves in sea ice using these and similar sensors can potentially be a valuable field-based tool for evaluating ice mechanics. In particular, this approach can be used to observe and describe the combined mechanical behavior of consolidated floes relevant for understanding sea ice mechanical processes and model development.

Effects of Wave-Induced Sea Ice Break-Up and Mixing in a High-Resolution Coupled Ice-Ocean Model

Arctic sea ice plays a vital role in modulating the global climate. In the most recent decades, the rapid decline of the Arctic summer sea ice cover has exposed increasing areas of ice-free ocean, with sufficient fetch for waves to develop. This has highlighted the complex and not well-understood nature of wave-ice interactions, requiring modeling effort. Here, we introduce two independent parameterizations in a high-resolution coupled ice-ocean model to investigate the effects of wave-induced sea ice break-up (through albedo change) and mixing on the Arctic sea ice simulation. Our results show that wave-induced sea ice break-up leads to increases in sea ice concentration and thickness in the Bering Sea, the Baffin Sea and the Barents Sea during the ice growth season, but accelerates the sea ice melt in the Chukchi Sea and the East Siberian Sea in summer. Further, wave-induced mixing can decelerate the sea ice formation in winter and the sea ice melt in summer by exchanging the heat fluxes between the surface and subsurface layer. As our baseline model underestimates sea ice cover in winter and produces more sea ice in summer, wave-induced sea ice break-up plays a positive role in improving the sea ice simulation. This study provides two independent parameterizations to directly include the wave effects into the sea ice models, with important implications for the future sea ice model development.

Seasonal marine carbon system processes in an Arctic coastal landfast sea ice environment observed with an innovative underwater sensor platform

Studying carbon dioxide in the ocean helps to understand how the ocean will be impacted by climate change and respond to increasing fossil fuel emissions. The marine carbonate system is not well characterized in the Arctic, where challenging logistics and extreme conditions limit observations of atmospheric CO2 flux and ocean acidification. Here, we present a high-resolution marine carbon system data set covering the complete cycle of sea-ice growth and melt in an Arctic estuary (Nunavut, Canada). This data set was collected through three consecutive yearlong deployments of sensors for pH and partial pressure of CO2 in seawater (pCO2sw) on a cabled underwater observatory. The sensors were remarkably stable compared to discrete samples: While corrections for offsets were required in some instances, we did not observe significant drift over the deployment periods. Our observations revealed a strong seasonality in this marine carbon system. Prior to sea-ice formation, air–sea gas exchange and respiration were the dominant processes, leading to increasing pCO2sw and reduced aragonite saturation state (ΩAr). During sea-ice growth, water column respiration and brine rejection (possibly enriched in dissolved inorganic carbon, relative to alkalinity, due to ikaite precipitation in sea ice) drove pCO2sw to supersaturation and lowered ΩAr to &amp;lt; 1. Shortly after polar sunrise, the ecosystem became net autotrophic, returning pCO2sw to undersaturation. The biological community responsible for this early switch to autotrophy (well before ice algae or phytoplankton blooms) requires further investigation. After sea-ice melt initiated, an under-ice phytoplankton bloom strongly reduced aqueous carbon (chlorophyll-a max of 2.4 µg L–1), returning ΩAr to &amp;gt; 1 after 4.5 months of undersaturation. Based on simple extrapolations of anthropogenic carbon inventories, we suspect that this seasonal undersaturation would not have occurred naturally. At ice breakup, the sensor platform recorded low pCO2sw (230 µatm), suggesting a strong CO2 sink during the open water season.