Session CR4.2

[Programme]

CR4.2 | Rapid changes in sea ice: processes and implications

Rapid changes in sea ice: processes and implications

Convener: Rebecca FrewECSECS | Co-conveners: Daniel Feltham, Daniela Flocco, Srikanth Toppaladoddi

Orals

| Fri, 28 Apr, 10:45–12:25 (CEST)

Room L2

Posters on site

| Attendance Fri, 28 Apr, 08:30–10:15 (CEST)

Hall X5

Posters virtual

| Attendance Fri, 28 Apr, 08:30–10:15 (CEST)

vHall CR/OS

Recent years have seen significant reductions in Arctic sea ice extent, and sudden ice loss events and redistribution of sea ice in the Antarctic. Climate projections suggest a reduction of the sea ice cover in both poles, with the Arctic becoming seasonally ice free in the latter half of this century.

The scientific community is investing considerable effort in organising our current knowledge of the physical and biogeochemical properties of sea ice, exploring poorly understood sea ice processes, and forecasting future changes of the sea ice cover, such as in CMIP6.

In this session, we invite contributions regarding all aspects of sea ice science and sea ice-climate interactions, including snow and sea ice thermodynamics and dynamics, sea ice-atmosphere and sea ice-ocean interactions, sea ice biological and chemical processes, sea ice observational and field studies and models. A focus on emerging processes and implications is particularly welcome.

Orals: Fri, 28 Apr | Room L2

10:45–10:55

EGU23-8780

CR4.2

ECS

On-site presentation

Arctic and Antarctic sea ice thickness and volume changes during the last 29 years from satellites

Marion Bocquet, Sara Fleury, Frédérique Rémy, Florent Garnier, and Thomas Moreau

Sea ice is both a key witness and driver of climate change. While sea ice extent and area is well described with observations during the last four decades, sea ice thickness and volumes changes remain poorly known. However, thickness is a mandatory variable to fully understand the past, present and future changes of sea ice. Despite improvements in sea ice thickness estimation from altimetry during the past few years thanks to SAR and laser altimetry, former radar altimetry missions such as Envisat and especially ERS-1 and ERS-2 have remained under exploited so far. ERS-2 arctic sea ice thickness has been recently retrieved thanks to a machine learning approach aiming at calibrating ERS-2 and Envisat against CryoSat-2. We are now able to extend the time series from ERS-1 for both polar oceans, allowing to propose a 29 years-long sea ice thickness and volume time series. Estimates are combined with uncertainties derived from a Monte Carlo methodology. Nearly 30 years of sea ice volume time series reveals that Arctic sea ice is melting by 120 +/- 45 km³/year up to 81.5 °N (-13.1 +/- 5.1 %/decade). Antarctic sea ice evolution has no significant trends along the whole period, but a volume drop is observed since 2016. For both hemispheres, prominent regional changes have been identified with a strong heterogeneity of trends across regions. Finally, comparisons between observations and models show increasing negative bias while going back in time.

How to cite: Bocquet, M., Fleury, S., Rémy, F., Garnier, F., and Moreau, T.: Arctic and Antarctic sea ice thickness and volume changes during the last 29 years from satellites, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8780, https://doi.org/10.5194/egusphere-egu23-8780, 2023.

10:55–11:05

EGU23-3302

CR4.2

ECS

Virtual presentation

A satellite era reanalysis of the Arctic sea ice cover utilising year-round observations of sea ice thickness

(withdrawn)

Nicholas Williams, Nicholas Byrne, Daniel Feltham, Peter Jan Van Leeuwen, Ross Bannister, David Schroeder, Andrew Ridout, and Lars Nerger

11:05–11:15

EGU23-11086

CR4.2

ECS

On-site presentation

Past and future of the Arctic sea ice in HighResMIP

Julia Selivanova and Doroteaciro Iovino

Arctic sea-ice area and volume have dramatically decreased since the beginning of the satellite era. This alarming rate of ice decline raises a key scientific question: how soon will the Arctic meet the first “ice-free” summer? Coupled climate models are the primary tools to provide projections of future sea ice conditions. Increasing the horizontal resolution of general circulation models is a widely recognized way to improve the representation of the complex processes at high latitudes, and to obtain trustworthy predictions of ice variability. Here, we investigate the past and future changes of sea ice cover at hemispheric and regional scales using model outputs from the High Resolution Model Intercomparison Project (HighResMIP, Haarsma et al. 2016) of the sixth phase of the Coupled Model Intercomparison Project (CMIP6).

The main objective is to investigate the impact of ocean/atmosphere model resolution on the representation of Arctic sea ice area (SIA) and volume (SIV) and their seasonal, interannual variability, and trends in the recent past. Model results over the period 1950–2014 are compared to a set of observational datasets.

All models project substantial sea ice shrinking: from 1950 to 2050 the Arctic loses nearly 92% of SIV from 1950 to 2050. The individual models simulate the first summer ice-free Arctic as early as 2019 and as late as 2050. The ensemble mean of the three best performing models suggests the event to happen by 2044. Along with the overall reduction of sea ice cover, there are changes in the structure of sea ice cover: the marginal ice zone (MIZ) dominates the ice cover by the mid-XXI which implies the shift to a new sea ice regime closest to the Antarctic conditions. The MIZ-dominated Arctic might suggest to adapt and modify model physics parameterizations and sea ice rheology.

Our analysis does not present a strong relationship between ocean/atmosphere spatial resolution and sea ice cover representation: the impact of horizontal resolution rather depends on the model used and the examined variables. However, the refinement of the ocean mesh has a more prominent effect compared to the atmospheric one, mainly due to a more realistic representation of the sea ice edges as a result of better simulated ocean currents and heat transports in the Northern Atlantic Ocean.

How to cite: Selivanova, J. and Iovino, D.: Past and future of the Arctic sea ice in HighResMIP, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11086, https://doi.org/10.5194/egusphere-egu23-11086, 2023.

Discussion

11:15–11:25

EGU23-12844

CR4.2

ECS

On-site presentation

Evolution of heat fluxes at the Arctic sea-ice edge

Julia Steckling, Markus Ritschel, Prof. Dr. Johanna Baehr, and Prof. Dr. Dirk Notz

We analyze the evolution of heat fluxes and the resulting surface energy balance at the Arctic sea-ice edge in CMIP6 model simulations. We build on the study of Notz and Stroeve (2016), in which they show the existence of a strong linear relationship between Arctic sea-ice area and cumulative anthropogenic CO₂ emissions. In explaining this linear relationship, the authors claim that the surface energy balance at the sea-ice edge remains constant, following the conceptual idea of the sea-ice edge retreating northwards to compensate for the increasing longwave radiative input due to global warming by a decrease in shortwave radiation at higher latitudes. We examine the validity of this hypothesis by first identifying the sea-ice edge in the model data, and then scrutinize whether or not the surface energy balance at that location stays constant under future sea-ice retreat. Furthermore, we decompose the energy balance into its constituents to explore dynamical effects and oceanic influence.

We find that the annual mean surface energy balance shows stronger spatial than temporal variations. Looking at individual months, we find that the surface energy balance is negative in winter and positive in summer along the ice edge. Towards the end of the 21^st century, the surface energy balance enters a new regime, becoming less negative in winter, and more positive in summer. By showing a consistently negative relation between downwelling shortwave radiation and downwelling longwave radiation, we finally confirm the idea of the compensation of increasing longwave input by a decrease in shortwave incoming radiation due to a northward migration of the sea-ice edge.

How to cite: Steckling, J., Ritschel, M., Baehr, P. Dr. J., and Notz, P. Dr. D.: Evolution of heat fluxes at the Arctic sea-ice edge, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12844, https://doi.org/10.5194/egusphere-egu23-12844, 2023.

11:25–11:35

EGU23-16687

CR4.2

Virtual presentation

Understanding recent changes in Antarctic sea ice seasonality

Kenza Himmich, Sharon Stammerjohn, Martin Vancoppenolle, and Gurvan Madec

Changes in the timing of Antarctic sea ice retreat and advance have been analyzed over 1979-2012, based on satellite sea ice concentration retrievals. The Ross Sea showed large trends towards earlier sea ice advance and later retreat whereas the Bellingshausen and Amundsen Seas showed opposite trends.

Since 2016, however, we find the occurrence of anomalously late advance and early retreat in the Ross and Weddell Seas and anomalously early advance and late retreat, west of the Peninsula. Trends in the timing of sea ice retreat and advance are consequently weaker over 1979-2022, than over 1979-2012. Here, we investigate the possible role of ocean thermodynamics and wind-driven ice drift in causing such anomalies and resulting trend weakening, using satellite and reanalysis data.

In most of the seasonal zone, anomalies in the date of advance strongly correlate with anomalies in the previous seasonal maximum sea surface temperature (SST) and in the previous date of retreat. This suggests that anomalies in the date of advance are caused by summer ocean heat uptake anomalies, themselves constrained by anomalies in the previous date of retreat. In a large outer band of the seasonal ice zone, however, anomalies in the timing of sea ice advance seem linked to anomalies in the magnitude of winter southerlies, suggesting a possible role for ice drift anomalies there.

By contrast, we find no clear correspondence between anomalies in the date of retreat and anomalies in winds or SST. We will provide more analysis to disentangle the thermodynamic and dynamic mechanisms causing anomalies in the date of retreat, based on a sea ice concentration budget decomposition.

How to cite: Himmich, K., Stammerjohn, S., Vancoppenolle, M., and Madec, G.: Understanding recent changes in Antarctic sea ice seasonality, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16687, https://doi.org/10.5194/egusphere-egu23-16687, 2023.

11:35–11:45

EGU23-11652

CR4.2

ECS

On-site presentation

Unsupervised statistical classification of the Antarctic marginal ice zone.

Noah Day, Luke Bennetts, and Siobhan O'Farrell

This work presents a new method for quantifying the Antarctic marginal ice zone (MIZ). The MIZ acts as an interface between the open Southern Ocean and the consolidated inner pack, and is generally described as area of sea ice affected by ocean surface waves. We use standalone CICE6, which includes a floe size distribution with atmospheric, oceanic and wave forcing, to simulate the evolution of Antarctic sea ice from 2010 – 2020. CICE output variables were categorised as static (sea ice concentration, age, thickness, etc.), thermodynamic, and dynamic. Unsupervised statistical methods were used to classify distinct sea ice regions and then to identify the dominant processes which contribute to the spatial and temporal variance of Antarctic sea ice cover. The unsupervised sea ice classification agrees with recent MIZ extent estimations using altimetry observations of wave attenuation. The addition of floe size information enhanced our MIZ classification to include high concentration pancake fields (which are promoted by waves). These results support the inclusion of floe size within sea ice modelling, and the importance of multi-variate approaches to describe sea ice.

How to cite: Day, N., Bennetts, L., and O'Farrell, S.: Unsupervised statistical classification of the Antarctic marginal ice zone., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11652, https://doi.org/10.5194/egusphere-egu23-11652, 2023.

11:45–11:55

EGU23-4483

CR4.2

ECS

Virtual presentation

Drivers of very rapid sea ice loss on sub-seasonal timescales

Jake Aylmer, Daniel Feltham, John Methven, and Ambrogio Volonté

Very rapid ice loss events (VRILEs) are extreme, local reductions in Arctic sea ice extent on timescales of days to weeks. They are poorly captured in operational forecasts that are used, for instance, to inform shipping through the Arctic Ocean. A better understanding of the drivers and underlying processes is thus critical to a range of stakeholders. We analyse summertime (May–September) VRILEs occurring in a simulation (1980–2022) with the sea ice model CICE forced by atmospheric reanalyses. Our configuration includes novel marginal ice physics such as a prognostic floe size distribution and an explicit form drag scheme. Most VRILEs are dominated by thermodynamic processes. However, many events occurring near the start or end of the melt season are driven by advective redistribution, often associated with the presence of a cyclone. We illustrate this with key case studies and generalise the results to all simulated VRILEs using simple metrics quantifying the dominant contributions to the sea ice concentration tendencies and atmospheric conditions in each event. Finally, a suite of parameter sensitivity studies highlights factors with potential to improve forecasting of VRILEs.

How to cite: Aylmer, J., Feltham, D., Methven, J., and Volonté, A.: Drivers of very rapid sea ice loss on sub-seasonal timescales, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4483, https://doi.org/10.5194/egusphere-egu23-4483, 2023.

11:55–12:05

EGU23-14000

CR4.2

ECS

On-site presentation

Driving Mechanisms of an Extreme Winter Sea Ice Breakup Event in the Beaufort Sea

Richard Davy, Jonathon Rheinlaender, Pierre Rampal, Clemens Spensburger, Anton Korosov, Timothy Williams, and Thomas Spengler

The loss of thick multiyear sea ice in the Arctic leads to weaker sea ice that is more easily broken up by strong winds. As a consequence, extreme sea ice breakup events may become more frequent, even during the middle of winter when the sea ice cover is frozen solid. This can lead to an earlier onset of the melt season and potentially accelerate Arctic sea ice loss. Such extreme breakup events are generally not captured by climate models, potentially limiting our confidence in projections of Arctic sea ice. We investigated the driving forces behind sea ice breakup events during winter and how they change in a future climate. Our sea ice model is the first to reproduce such breakup events and reveals that the combination of strong winds and thin sea ice is a key factor for these breakups. We found that winter breakups have a large effect on local heat and moisture transfer and cause enhanced sea ice production, but also increase the overall movement of the sea ice cover, making it more vulnerable. Finally, we show that if the Arctic sea ice continues to thin, these extreme breakup events could become even more frequent.

How to cite: Davy, R., Rheinlaender, J., Rampal, P., Spensburger, C., Korosov, A., Williams, T., and Spengler, T.: Driving Mechanisms of an Extreme Winter Sea Ice Breakup Event in the Beaufort Sea, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14000, https://doi.org/10.5194/egusphere-egu23-14000, 2023.

12:05–12:15

EGU23-14770

CR4.2

ECS

Virtual presentation

Fractal properties of Arctic sea ice floe fragmentation processes

Rajlaxmi Basu and Byongjun Hwang

12:15–12:25

EGU23-11105

CR4.2

On-site presentation

Modelling the thermodynamic growth of sea ice: insights from quasi-static models

David Rees Jones

The thermodynamic growth of sea ice is governed by heat transfer through the ice together with appropriate boundary conditions at the interfaces with the atmosphere and ocean. Several different representations of this process have been used in climate modelling, including the simplest zero-layer models (Semtner, 1976) and more complex partial-differential-equation-based models (Maykut & Untersteiner, 1971; Bitz & Lipscomb, 1999). Recently, these latter models have been extended to include a representation of the dynamic evolution of the salinity of sea ice based on mushy-layer theory (Turner et al., 2013; Griewank & Notz, 2013; Rees Jones and Worster, 2014). Salinity variation might be expected to have a significant effect on ice growth given that it controls the relative proportions of solid ice and liquid brine, and these materials have different thermal properties.

In this study, we develop a simplified framework to investigate the effects of variations in the thermal properties of sea ice. We develop and test a quasi-static simplification. In this simplification, we apply a transformation to the underlying heat equation such that the spatial coordinate scales with the ice thickness. We then neglect the explicit time dependence. This procedure reduces the full partial differential equation to an ordinary differential equation. The solution is exact for constant forcing conditions.

We show that ice salinity has only a modest effect on the growth rate, notwithstanding its large effect on the thermal properties of sea ice. The model allows us to unpick the physical causes, which are related to the trade-off between the effect of salinity on thermal conductivity and latent heat release. We calculate the growth of ice under steady and time-dependent forcing. Under steady forcing, the ice growth equation admits an analytical approximate solution, which compares well to numerical solutions. We show that saltier ice initially grows slightly faster but subsequently grows slightly slower, a further trade-off explaining the relatively weak sensitivity of ice growth to salinity.

Under time-dependent forcing, we show that the quasi-static model compares well to full partial-differential-equation-based models. So our approach offers intermediate complexity between zero-layer Semtner models and full models based on partial differential equations such as Maykut-Untersteiner/Bitz-Lipscomb/mushy-layer models.

References:
Semtner, A. J. (1976) J. Phys. Oceanogr. 6 (3), 379–389.
Maykut, G. A. & Untersteiner, N. (1971) J. Geophys. Res. 76 (6), 1550–1575.
Bitz, C. M. & Lipscomb, W. H. (1999) J. Geophys. Res. – Oceans 104 (C7), 15669–15677.
Turner, A. K., Hunke, E. C. & Bitz, C. M. (2013) J. Geophys. Res. – Oceans 118 (5), 2279–2294.
Griewank, P. J. & Notz, D. (2013) J. Geophys. Res. – Oceans 118 (7), 3370–3386.
Rees Jones, D. W. & Worster, M. G. (2014) J. Geophys. Res. – Oceans 119 (9), 5599–5621.

How to cite: Rees Jones, D.: Modelling the thermodynamic growth of sea ice: insights from quasi-static models, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11105, https://doi.org/10.5194/egusphere-egu23-11105, 2023.

Posters on site: Fri, 28 Apr, 08:30–10:15 | Hall X5

X5.291

EGU23-5055

CR4.2

ECS

Arctic rapid sea ice loss events in CMIP6 simulations

Annelies Sticker, François Massonnet, and Thierry Fichefet

The summer Arctic sea ice is projected to disappear completely by the middle of the century in response to anthropogenic greenhouse gas emissions, according to simulations conducted with the latest global climate models. The decrease in summer Arctic sea ice extent is marked by periods of rapid ice loss, known as rapid ice loss events (RILEs), which are expected to become more frequent in the coming decades. However, the causes of RILEs are not well understood and it is difficult to predict their occurrence a season to several years ahead. It is essential to improve our understanding of these events and their potential impacts on ecosystems and societies, as the rate of sea ice decline can affect the ability to adapt to rapid change. To gain a better understanding of RILEs, we conducted an analysis using climate simulations from the Coupling Model Intercomparison Project phase 6 (CMIP6). Our results show that the frequency of RILEs increases as the Arctic sea ice extent diminishes, and the probability of observing a RILE is highest during the period from 2025 to 2030. Moreover, the observed September Arctic sea ice extent is critically approaching the value corresponding to the peak of probability of occurrence of RILEs. This suggests that we may be on the verge of a new RILE, following a slowdown since the early 2010s. In the future, we plan to identify the climatic conditions that are favorable for the formation of RILEs, with the goal of predicting the probability of their occurrence in real-time. We also aim to study the impacts of these rapid ice loss events on the wider climate system.

How to cite: Sticker, A., Massonnet, F., and Fichefet, T.: Arctic rapid sea ice loss events in CMIP6 simulations, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5055, https://doi.org/10.5194/egusphere-egu23-5055, 2023.

X5.292

EGU23-15061

CR4.2

ECS

Sea Ice Growth, Melt and Dynamics in an Increasingly Marginal Arctic

Rebecca Frew, Danny Feltham, David Schroeder, and Adam Bateson

As summer Arctic sea ice extent has retreated, the marginal ice zone (MIZ) has been widening and making up an increasing percentage of the summer Arctic sea ice. The MIZ is defined as the region of the ice cover that is influenced by waves, and for convenience here is defined as the region of the ice cover between ice concentrations of 15-80%. The MIZ is projected to become a larger percentage of the summer ice cover, as the Arctic transitions to ice free summers. We use a sea ice-mixed layer model that has a prognostic floe size distribution model including brittle fracture and form drag. The model has been compared and calibrated to FSD observations, satellite observation of sea ice extent and PIOMAS. We compare the processes of ice volume gain and loss in the ice pack to those in the MIZ to establish and contrast the relative importance of processes in the pack and MIZ, and the changes as the summer MIZ fraction increases and the amplitude of the seasonal sea ice growth/melt cycle increases. We compare the components of the sea ice volume budget in the 1980s and 2010s and then between the 2010s and the 2040s where almost the entirety summer sea ice cover has become MIZ.

How to cite: Frew, R., Feltham, D., Schroeder, D., and Bateson, A.: Sea Ice Growth, Melt and Dynamics in an Increasingly Marginal Arctic, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15061, https://doi.org/10.5194/egusphere-egu23-15061, 2023.

X5.293

EGU23-6428

CR4.2

Observations and modeling of areal surface albedo and surface types in the Arctic

Evelyn Jäkel, Tim Sperzel, Manfred Wendisch, Hannah Niehaus, Gunnar Spreen, Marcel Nicolaus, Ran Tao, Wolfgang Dorn, Lara Footh, and Annette Rinke

The spread of climate model results quantifying the snow–ice surface albedo feedback is partly caused by the significant sensitivity of the simulated sea ice surface albedo with respect to surface warming. Therefore, the accurate representation of the Arctic sea ice and its evolution throughout the year, particularly in the melting period, is crucial to obtain reliable climate model projections.

Here we evaluate the results of the surface albedo scheme of the coupled regional climate model HIRHAM–NAOSIM against airborne and ground-based measurements. The corresponding observations were conducted during the MOSAiC expedition in 2020 and during five aircraft campaigns within the framework of the (AC)³ project in different seasons between 2017 and 2022.

The comparison of measured and modeled surface albedo was based on observed fractions of four surface types (melt ponds, snow, sea ice, bare ice), which were classified using fisheye camera imagery and the measured skin temperatures along the flight track. From the modeling side, we applied the full surface albedo scheme, together with the ice sub-type fractions. We found a seasonal-dependent degree of agreement between measured and modeled surface albedo for cloud-free and cloudy situations. The current albedo scheme has projected an earlier onset of melting and a more realistic width of surface albedo frequency distributions in summer than the former albedo scheme. In spring, however, the cloud effect on surface albedo was overestimated by the model, while the albedo scheme for cloudless cases showed a smaller bias than the former scheme without cloud-depending parameters.

How to cite: Jäkel, E., Sperzel, T., Wendisch, M., Niehaus, H., Spreen, G., Nicolaus, M., Tao, R., Dorn, W., Footh, L., and Rinke, A.: Observations and modeling of areal surface albedo and surface types in the Arctic, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6428, https://doi.org/10.5194/egusphere-egu23-6428, 2023.

X5.294

EGU23-3215

CR4.2

Implementation of form drag scheme into NEMO sea ice model SI3

David Schroeder and Danny Feltham

X5.295

EGU23-9077

CR4.2

Seasonal and interannual variability in Fram Strait sea ice ridge statistics during 2006-2019 from the data of Ice Profiling Sonars.

Dmitry Divine, Hiroshi Sumata, Laura de Steur, Olga Pavlova, Mats Granskog, and Sebastian Gerland

Fram Strait is the major gateway connecting the Arctic Ocean and North Atlantic Ocean, where nearly 90% of the sea ice export from the Arctic Ocean takes place. The transported ice represents a broad range of thicknesses and types and exhibits an integrated history of thermodynamic growth/decay and deformation on its way across the Arctic. The present study utilizes high resolution sea ice draft data from ice profiling sonars (IPS) from the four moorings of the Fram Strait Outflow Observatory at 78.85 N and 3W to 6.5 W over the period 2006-2019. The analysis focuses on the identification of deformed ice/sea ice ridges and analysis of the seasonal and interannual variability in the number, geometry and shape of ridges. The study demonstrates a pronounced seasonal cycle in the number, probability density function of keel drafts and shape of ridges traversing FS with a maximum ridge count in March-April and minimum in August-September. An overall decline found in the annual ridge number is accompanied by a general shallowing of ridge keels. The observed changes are most pronounced in the easternmost mooring at 3W, and linked to continuing sea ice retreat in the FS over the studied period. The results are further compared with previous studies on ridge statistics from the area and placed in the context of the observed changes in Arctic sea ice over the last two decades.

How to cite: Divine, D., Sumata, H., de Steur, L., Pavlova, O., Granskog, M., and Gerland, S.: Seasonal and interannual variability in Fram Strait sea ice ridge statistics during 2006-2019 from the data of Ice Profiling Sonars., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9077, https://doi.org/10.5194/egusphere-egu23-9077, 2023.

X5.296

EGU23-4106

CR4.2

On the wave-ice attenuation and WSC variation in Fram Strait using clusters of miniature wave drifting buoy in 2021 & 2022

Hwa Chien, Yen-Chen Chen, and Huan-Meng Chang

The rate of reduction of Arctic Ocean sea ice cover and its change is an important key issue in the study of global climate change. Wave climate variability and the wave effects in the Arctic Ocean plays important roles in influencing the rate of sea ice melting. Aiming to improve the parameterization of wave numerical model that considers the presence of sea ice in polar region and to develop the associated satellite remote sensing technologies, in situ wave observations at the sea-ice edge and Marginal Ice Zones are essential. Currently the data and observations are scarce.

This study developed a low-cost miniature wave drifting buoy, its shape is 50 cm diameter dish, built-in IMU, Iridium satellite modem and temperature and salinity sensor, etc., to monitor the wave height, period, direction and wave spectral shape, sea surface Mean Square Slope (MSS), surface ocean temperature (SST) and GPS positioning.

The signal sampling frequency is 10Hz, the spectral analysis is carried out on-board using ARM single chip computer in the buoy. The data is then encoded to Iridium satellite in real-time. In this study, in August 2021 and 2022, 8 and 10 sets of miniature buoys were deployed in Fram Strait off the western Svalbard Islands, respectively. The buoys were deployed in cluster and placed 15 km apart from each other, forming a rectangular spatial array, and drifting with West Spitzbergen Current, transported northward into the ice edge area of Svalbard northwest sea.

The observation took place every two hours for about three months. This report presents the time series of the observation data. First, we analyzed the drift trajectories of the buoy cluster, estimated the sea surface dispersion coefficient, Lyapunov index from the spatial array shape change rate of the buoy cluster. Secondly, sea surface temperature variation along the meridional trajectories was investigated. The results showed that the surface water mass was converged around Molloy Abyss, and the surrounding water body was accompanied by rapid temperature drop. On the other hand, in the wave analysis of the MIZ, the SAR images were used to identify the sea ice edge and ice concentration and to investigate the attenuation of wave spectral shape between the sea ice zone and the open ice-free waters in the vicinity.

How to cite: Chien, H., Chen, Y.-C., and Chang, H.-M.: On the wave-ice attenuation and WSC variation in Fram Strait using clusters of miniature wave drifting buoy in 2021 & 2022, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4106, https://doi.org/10.5194/egusphere-egu23-4106, 2023.

X5.297

EGU23-15852

CR4.2

ECS

A new HPLC-MS method for fatty acid detection in sea ice

Siobhan Johnson, Chiara Giorio, and Elizabeth Thomas

The presence of marine-sourced fatty acids^1,2,3, in Antarctic ice cores has been linked to changes in sea ice conditions^2,3. It has been proposed that the phytoplankton within and around the sea ice produce these fatty acids³ which are then released into the atmosphere upon sea-ice retreat and deposited onto the continental ice sheet^2,3. While fatty acids show great potential as a proxy to reconstruct past sea ice, their transport, deposition and preservation within the ice sheet is poorly understood. Few studies have investigated sea ice as a source of fatty acids and even fewer have investigated Antarctic sea ice^4,5,6. Here we present a new study exploring the methods of detecting fatty acids in sea ice, including new results from pancake ice collected from the Antarctic Marginal Ice Zone in 2022.

Analyses of fatty acids are typically carried out using gas chromatography (GC) coupled with mass spectrometric (MS) techniques^6,7,8,9. With the rise of liquid chromatography methods in the past few decades, their use have become more common. High performance liquid chromatography (HPLC) has an advantage over GC methods with its lower temperatures during analysis, thus reducing the risk of altering or destroying the fatty acids¹⁰. A resultant HPLC-MS method, using electrospray ionisation, is presented for the detection and analysis of fatty acids in sea ice.

[1] K. Kawamura et al., “Ice core record of fatty acids over the past 450 years in Greenland,” Geophysical Research Letters, vol. 23, pp. 2665-2668, 1996.

[2] A. King et al., “Organic compounds in a sub-Antarctic ice core: A potential suite of markers” Geophysical Research Letters, vol. 46, pp. 9930-9939, 2019.

[3] E. Thomas et al., “Antarctic Sea Ice Proxies from Marine and Ice Core Archives Suitable for Reconstructing Sea Ice over the past 2000 Years,” Geosciences, vol. 9, pp. 506-539, 2019.

[4] K. Fahl and G. Kattner, "Lipid Content and fatty acid composition of algal communities in sea-ice and water ffom the Weddell Sea (Antarctica)," Polar Biology, vol. 13, pp. 405-409, 1993.

[5] P. Nichols et al., "Occurence of an isoprenoid C25 diunsaturated alkene and high neutral lipid content in antarctic sea-ice diatom communities," Journal of Phycology, vol. 24, pp. 90-96, 1988.

[6] D. Nichols et al., "Fatty acid, sterol and hydrocarbon composition of Antarctic sea ice diatom communities during the spring bloom in McMurdo Sound," Antarctic Science, vol. 5, pp. 271-278, 1993.

[7] S. Wang et al., "Fatty acid and stable isotope characteristics of sea ice and pelagic particulate organic matter in the Bering Sea: tools for estimating sea ice algal contribution to Arctic food web production," Oecologia, vol. 174, pp. 699-712, 2014.

[8] S. Wang et al., "Importance of sympagic production to Bering Sea zooplankton as revealed from fatty acid-carbon stable isotope analyses," Marine Ecology Progress Series, vol. 518, pp. 31-50, 2015.

[9] E. Leu et al., "Spatial and Temporal Variability of Ice Algal Trophic Markers—With Recommendations about Their Application," Journal of Marine Science and Engineering, vol. 8, pp. 676, 2020.

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How to cite: Johnson, S., Giorio, C., and Thomas, E.: A new HPLC-MS method for fatty acid detection in sea ice, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15852, https://doi.org/10.5194/egusphere-egu23-15852, 2023.

Posters virtual: Fri, 28 Apr, 08:30–10:15 | vHall CR/OS

vCO.4

EGU23-9088

CR4.2

The role of brittle fracture in determining sea ice floe size distribution

Adam Bateson, Daniel Feltham, David Schröder, Yanan Wang, and Byongjun Hwang

There have been several recent efforts to develop parameterisations of the sea ice floe size distribution (FSD) for use in sea ice models such as CICE and SI3. These models aim to capture the key processes that determine the evolution of floe sizes, including melting at the edges of floes, welding together of floes, and break-up of floes by waves. However, several fragmentation processes are not yet accounted for in these models. For example, in-plane brittle fracture events can have a direct impact on the size of larger floes and potentially also smaller floes. Plausible indirect mechanisms also exist. It has been observed that thermodynamic weakening of cracks and other linear features in the sea ice cover can in some cases drive the break-up of sea ice in the central Arctic. These observations imply that linear features in the sea ice that form in winter from in-plane brittle fracture before freezing up can then determine the fragmentation of sea ice in summer as it thins and weakens.

Here we will present results from sea ice simulations including a prognostic model of sea ice FSD to show that the inclusion of brittle fracture-derived impacts on floe size improves the performance of the FSD model in simulating observed FSD shape for mid-sized floes. We will use these results to motivate the development of a more physically derived parameterisation of floe breakup via thermal weakening of floes along existing linear features. Finally, we will discuss how we can combine novel observations and recent advancements in modelling techniques such as discrete element methods applied to sea ice to aid in the development of parameterisations of these floe-scale processes for subsequent application in continuum models.

How to cite: Bateson, A., Feltham, D., Schröder, D., Wang, Y., and Hwang, B.: The role of brittle fracture in determining sea ice floe size distribution, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9088, https://doi.org/10.5194/egusphere-egu23-9088, 2023.