Comparison of sea-ice freeboard and thickness distributions from aircraft data and cryosat-2

DEFF Research Database (Denmark)

accurate range measurements. During the CryoSat Validation Experiment (CryoVEx) 2011 in the Lincoln Sea, Cryosat-2 underpasses were accomplished with two aircraft, which carried an airborne laser-scanner, a radar altimeter and an electromagnetic induction device for direct sea-ice thickness retrieval. Both...... aircraft flew in close formation at the same time of a CryoSat-2 overpass. This is a study about the comparison of the sea-ice freeboard and thickness distribution of airborne validation and CryoSat-2 measurements within the multi-year sea-ice region of the Lincoln Sea in spring, with respect...

Thin Sea Ice, Thick Snow, and Widespread Negative Freeboard Observed During N-ICE2015 North of Svalbard

Science.gov (United States)

Rösel, Anja; Itkin, Polona; King, Jennifer; Divine, Dmitry; Wang, Caixin; Granskog, Mats A.; Krumpen, Thomas; Gerland, Sebastian

2018-02-01

In recent years, sea-ice conditions in the Arctic Ocean changed substantially toward a younger and thinner sea-ice cover. To capture the scope of these changes and identify the differences between individual regions, in situ observations from expeditions are a valuable data source. We present a continuous time series of in situ measurements from the N-ICE2015 expedition from January to June 2015 in the Arctic Basin north of Svalbard, comprising snow buoy and ice mass balance buoy data and local and regional data gained from electromagnetic induction (EM) surveys and snow probe measurements from four distinct drifts. The observed mean snow depth of 0.53 m for April to early June is 73% above the average value of 0.30 m from historical and recent observations in this region, covering the years 1955-2017. The modal total ice and snow thicknesses, of 1.6 and 1.7 m measured with ground-based EM and airborne EM measurements in April, May, and June 2015, respectively, lie below the values ranging from 1.8 to 2.7 m, reported in historical observations from the same region and time of year. The thick snow cover slows thermodynamic growth of the underlying sea ice. In combination with a thin sea-ice cover this leads to an imbalance between snow and ice thickness, which causes widespread negative freeboard with subsequent flooding and a potential for snow-ice formation. With certainty, 29% of randomly located drill holes on level ice had negative freeboard.

Sea-ice Thickness and Draft Statistics from Submarine ULS, Moored ULS, and a Coupled Model

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set consists of estimates of mean values of sea-ice thickness and sea-ice draft in meters computed from three different input data sets: sea ice draft from...

Validation of Airborne FMCW Radar Measurements of Snow Thickness Over Sea Ice in Antarctica

Science.gov (United States)

Galin, Natalia; Worby, Anthony; Markus, Thorsten; Leuschen, Carl; Gogineni, Prasad

2012-01-01

Antarctic sea ice and its snow cover are integral components of the global climate system, yet many aspects of their vertical dimensions are poorly understood, making their representation in global climate models poor. Remote sensing is the key to monitoring the dynamic nature of sea ice and its snow cover. Reliable and accurate snow thickness data are currently a highly sought after data product. Remotely sensed snow thickness measurements can provide an indication of precipitation levels, predicted to increase with effects of climate change in the polar regions. Airborne techniques provide a means for regional-scale estimation of snow depth and distribution. Accurate regional-scale snow thickness data will also facilitate an increase in the accuracy of sea ice thickness retrieval from satellite altimeter freeboard estimates. The airborne data sets are easier to validate with in situ measurements and are better suited to validating satellite algorithms when compared with in situ techniques. This is primarily due to two factors: better chance of getting coincident in situ and airborne data sets and the tractability of comparison between an in situ data set and the airborne data set averaged over the footprint of the antennas. A 28-GHz frequency modulated continuous wave (FMCW) radar loaned by the Center for Remote Sensing of Ice Sheets to the Australian Antarctic Division is used to measure snow thickness over sea ice in East Antarctica. Provided with the radar design parameters, the expected performance parameters of the radar are summarized. The necessary conditions for unambiguous identification of the airsnow and snowice layers for the radar are presented. Roughnesses of the snow and ice surfaces are found to be dominant determinants in the effectiveness of layer identification for this radar. Finally, this paper presents the first in situ validated snow thickness estimates over sea ice in Antarctica derived from an FMCW radar on a helicopterborne platform.

A glimpse beneath Antarctic sea ice: observation of platelet-layer thickness and ice-volume fraction with multi-frequency EM

Science.gov (United States)

Hendricks, S.; Hoppmann, M.; Hunkeler, P. A.; Kalscheuer, T.; Gerdes, R.

2015-12-01

In Antarctica, ice crystals (platelets) form and grow in supercooled waters below ice shelves. These platelets rise and accumulate beneath nearby sea ice to form a several meter thick sub-ice platelet layer. This special ice type is a unique habitat, influences sea-ice mass and energy balance, and its volume can be interpreted as an indicator for ice - ocean interactions. Although progress has been made in determining and understanding its spatio-temporal variability based on point measurements, an investigation of this phenomenon on a larger scale remains a challenge due to logistical constraints and a lack of suitable methodology. In the present study, we applied a lateral constrained Marquardt-Levenberg inversion to a unique multi-frequency electromagnetic (EM) induction sounding dataset obtained on the ice-shelf influenced fast-ice regime of Atka Bay, eastern Weddell Sea. We adapted the inversion algorithm to incorporate a sensor specific signal bias, and confirmed the reliability of the algorithm by performing a sensitivity study using synthetic data. We inverted the field data for sea-ice and sub-ice platelet-layer thickness and electrical conductivity, and calculated ice-volume fractions from platelet-layer conductivities using Archie's Law. The thickness results agreed well with drill-hole validation datasets within the uncertainty range, and the ice-volume fraction also yielded plausible results. Our findings imply that multi-frequency EM induction sounding is a suitable approach to efficiently map sea-ice and platelet-layer properties. However, we emphasize that the successful application of this technique requires a break with traditional EM sensor calibration strategies due to the need of absolute calibration with respect to a physical forward model.

The relation between sea ice thickness and freeboard in the Arctic

Directory of Open Access Journals (Sweden)

V. Alexandrov

2010-09-01

Full Text Available Retrieval of Arctic sea ice thickness from CryoSat-2 radar altimeter freeboard data requires observational data to verify the relation between these two variables. In this study in-situ ice and snow data from 689 observation sites, obtained during the Sever expeditions in the 1980s, have been used to establish an empirical relation between thickness and freeboard of FY ice in late winter. Estimates of mean and variability of snow depth, snow density and ice density were produced on the basis of many field observations. These estimates have been used in the hydrostatic equilibrium equation to retrieve ice thickness as a function of ice freeboard, snow depth and snow/ice density. The accuracy of the ice thickness retrieval has been calculated from the estimated variability in ice and snow parameters and error of ice freeboard measurements. It is found that uncertainties of ice density and freeboard are the major sources of error in ice thickness calculation. For FY ice, retrieval of ≈ 1.0 m (2.0 m thickness has an uncertainty of 46% (37%, and for MY ice, retrieval of 2.4 m (3.0 m thickness has an uncertainty of 20% (18%, assuming that the freeboard error is ± 0.03 m for both ice types. For MY ice the main uncertainty is ice density error, since the freeboard error is relatively smaller than that for FY ice. If the freeboard error can be reduced to 0.01 m by averaging measurements from CryoSat-2, the error in thickness retrieval is reduced to about 32% for a 1.0 m thick FY floe and to about 18% for a 2.4 m thick MY floe. The remaining error is dominated by uncertainty in ice density. Provision of improved ice density data is therefore important for accurate retrieval of ice thickness from CryoSat-2 data.

Investigating Arctic Sea Ice Survivability in the Beaufort Sea

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Matthew Tooth

2018-02-01

Full Text Available Arctic sea ice extent has continued to decline in recent years, and the fractional coverage of multi-year sea ice has decreased significantly during this period. The Beaufort Sea region has been the site of much of the loss of multi-year sea ice, and it continues to play a large role in the extinction of ice during the melt season. We present an analysis of the influence of satellite-derived ice surface temperature, ice thickness, albedo, and downwelling longwave/shortwave radiation as well as latitude and airborne snow depth estimates on the change in sea ice concentration in the Beaufort Sea from 2009 to 2016 using a Lagrangian tracking database. Results from this analysis indicate that parcels that melt during summer in the Beaufort Sea reside at lower latitudes and have lower ice thickness at the beginning of the melt season in most cases. The influence of sea ice thickness and snow depth observed by IceBridge offers less conclusive results, with some years exhibiting higher thicknesses/depths for melted parcels. Parcels that melted along IceBridge tracks do exhibit lower latitudes and ice thicknesses, however, which indicates that earlier melt and breakup of ice may contribute to a greater likelihood of extinction of parcels in the summer.

Winter sea ice export from the Laptev Sea preconditions the local summer sea ice cover and fast ice decay

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P. Itkin

2017-10-01

Full Text Available Ice retreat in the eastern Eurasian Arctic is a consequence of atmospheric and oceanic processes and regional feedback mechanisms acting on the ice cover, both in winter and summer. A correct representation of these processes in numerical models is important, since it will improve predictions of sea ice anomalies along the Northeast Passage and beyond. In this study, we highlight the importance of winter ice dynamics for local summer sea ice anomalies in thickness, volume and extent. By means of airborne sea ice thickness surveys made over pack ice areas in the south-eastern Laptev Sea, we show that years of offshore-directed sea ice transport have a thinning effect on the late-winter sea ice cover. To confirm the preconditioning effect of enhanced offshore advection in late winter on the summer sea ice cover, we perform a sensitivity study using a numerical model. Results verify that the preconditioning effect plays a bigger role for the regional ice extent. Furthermore, they indicate an increase in volume export from the Laptev Sea as a consequence of enhanced offshore advection, which has far-reaching consequences for the entire Arctic sea ice mass balance. Moreover we show that ice dynamics in winter not only preconditions local summer ice extent, but also accelerate fast-ice decay.

The impact of the snow cover on sea-ice thickness products retrieved by Ku-band radar altimeters

Science.gov (United States)

Ricker, R.; Hendricks, S.; Helm, V.; Perovich, D. K.

2015-12-01

Snow on sea ice is a relevant polar climate parameter related to ocean-atmospheric interactions and surface albedo. It also remains an important factor for sea-ice thickness products retrieved from Ku-band satellite radar altimeters like Envisat or CryoSat-2, which is currently on its mission and the subject of many recent studies. Such satellites sense the height of the sea-ice surface above the sea level, which is called sea-ice freeboard. By assuming hydrostatic equilibrium and that the main scattering horizon is given by the snow-ice interface, the freeboard can be transformed into sea-ice thickness. Therefore, information about the snow load on hemispherical scale is crucial. Due to the lack of sufficient satellite products, only climatological values are used in current studies. Since such values do not represent the high variability of snow distribution in the Arctic, they can be a substantial contributor to the total sea-ice thickness uncertainty budget. Secondly, recent studies suggest that the snow layer cannot be considered as homogenous, but possibly rather featuring a complex stratigraphy due to wind compaction and/or ice lenses. Therefore, the Ku-band radar signal can be scattered at internal layers, causing a shift of the main scattering horizon towards the snow surface. This alters the freeboard and thickness retrieval as the assumption that the main scattering horizon is given by the snow-ice interface is no longer valid and introduces a bias. Here, we present estimates for the impact of snow depth uncertainties and snow properties on CryoSat-2 sea-ice thickness retrievals. We therefore compare CryoSat-2 freeboard measurements with field data from ice mass-balance buoys and aircraft campaigns from the CryoSat Validation Experiment. This unique validation dataset includes airborne laser scanner and radar altimeter measurements in spring coincident to CryoSat-2 overflights, and allows us to evaluate how the main scattering horizon is altered by the

Sea Ice Thickness Measurement by Ground Penetrating Radar for Ground Truth of Microwave Remote Sensing Data

Science.gov (United States)

Matsumoto, M.; Yoshimura, M.; Naoki, K.; Cho, K.; Wakabayashi, H.

2018-04-01

Observation of sea ice thickness is one of key issues to understand regional effect of global warming. One of approaches to monitor sea ice in large area is microwave remote sensing data analysis. However, ground truth must be necessary to discuss the effectivity of this kind of approach. The conventional method to acquire ground truth of ice thickness is drilling ice layer and directly measuring the thickness by a ruler. However, this method is destructive, time-consuming and limited spatial resolution. Although there are several methods to acquire ice thickness in non-destructive way, ground penetrating radar (GPR) can be effective solution because it can discriminate snow-ice and ice-sea water interface. In this paper, we carried out GPR measurement in Lake Saroma for relatively large area (200 m by 300 m, approximately) aiming to obtain grand truth for remote sensing data. GPR survey was conducted at 5 locations in the area. The direct measurement was also conducted simultaneously in order to calibrate GPR data for thickness estimation and to validate the result. Although GPR Bscan image obtained from 600MHz contains the reflection which may come from a structure under snow, the origin of the reflection is not obvious. Therefore, further analysis and interpretation of the GPR image, such as numerical simulation, additional signal processing and use of 200 MHz antenna, are required to move on thickness estimation.

Sea-ice evaluation of NEMO-Nordic 1.0: a NEMO-LIM3.6-based ocean-sea-ice model setup for the North Sea and Baltic Sea

Science.gov (United States)

Pemberton, Per; Löptien, Ulrike; Hordoir, Robinson; Höglund, Anders; Schimanke, Semjon; Axell, Lars; Haapala, Jari

2017-08-01

The Baltic Sea is a seasonally ice-covered marginal sea in northern Europe with intense wintertime ship traffic and a sensitive ecosystem. Understanding and modeling the evolution of the sea-ice pack is important for climate effect studies and forecasting purposes. Here we present and evaluate the sea-ice component of a new NEMO-LIM3.6-based ocean-sea-ice setup for the North Sea and Baltic Sea region (NEMO-Nordic). The setup includes a new depth-based fast-ice parametrization for the Baltic Sea. The evaluation focuses on long-term statistics, from a 45-year long hindcast, although short-term daily performance is also briefly evaluated. We show that NEMO-Nordic is well suited for simulating the mean sea-ice extent, concentration, and thickness as compared to the best available observational data set. The variability of the annual maximum Baltic Sea ice extent is well in line with the observations, but the 1961-2006 trend is underestimated. Capturing the correct ice thickness distribution is more challenging. Based on the simulated ice thickness distribution we estimate the undeformed and deformed ice thickness and concentration in the Baltic Sea, which compares reasonably well with observations.

Sea ice - Multiyear cycles and white ice

Science.gov (United States)

Ledley, T. S.

1985-01-01

The multiyear thickness cycles represent one of the interesting features of the sea ice studies performed by Semtner (1976) and Washington et al. (1976) with simple thermodynamic models of sea ice. In the present article, a description is given of results which show that the insulating effect of snow on the surface of the sea ice is important in producing these multiyear cycles given the physics included in the model. However, when the formation of white ice is included, the cycles almost disappear. White ice is the ice which forms at the snow-ice interface when the snow layer becomes thick enough to depress the ice below the water level. Water infiltrates the snow by coming through the ice at leads and generally freezes there, forming white ice.

Sea ice-albedo climate feedback mechanism

Energy Technology Data Exchange (ETDEWEB)

Schramm, J.L.; Curry, J.A. [Univ. of Colorado, Boulder, CO (United States); Ebert, E.E. [Bureau of Meterology Research Center, Melbourne (Australia)

1995-02-01

The sea ice-albedo feedback mechanism over the Arctic Ocean multiyear sea ice is investigated by conducting a series of experiments using several one-dimensional models of the coupled sea ice-atmosphere system. In its simplest form, ice-albedo feedback is thought to be associated with a decrease in the areal cover of snow and ice and a corresponding increase in the surface temperature, further decreasing the area cover of snow and ice. It is shown that the sea ice-albedo feedback can operate even in multiyear pack ice, without the disappearance of this ice, associated with internal processes occurring within the multiyear ice pack (e.g., duration of the snow cover, ice thickness, ice distribution, lead fraction, and melt pond characteristics). The strength of the ice-albedo feedback mechanism is compared for several different thermodynamic sea ice models: a new model that includes ice thickness distribution., the Ebert and Curry model, the Mayjut and Untersteiner model, and the Semtner level-3 and level-0 models. The climate forcing is chosen to be a perturbation of the surface heat flux, and cloud and water vapor feedbacks are inoperative so that the effects of the sea ice-albedo feedback mechanism can be isolated. The inclusion of melt ponds significantly strengthens the ice-albedo feedback, while the ice thickness distribution decreases the strength of the modeled sea ice-albedo feedback. It is emphasized that accurately modeling present-day sea ice thickness is not adequate for a sea ice parameterization; the correct physical processes must be included so that the sea ice parameterization yields correct sensitivities to external forcing. 22 refs., 6 figs., 1 tab.

SEA ICE THICKNESS MEASUREMENT BY GROUND PENETRATING RADAR FOR GROUND TRUTH OF MICROWAVE REMOTE SENSING DATA

Directory of Open Access Journals (Sweden)

M. Matsumoto

2018-04-01

Full Text Available Observation of sea ice thickness is one of key issues to understand regional effect of global warming. One of approaches to monitor sea ice in large area is microwave remote sensing data analysis. However, ground truth must be necessary to discuss the effectivity of this kind of approach. The conventional method to acquire ground truth of ice thickness is drilling ice layer and directly measuring the thickness by a ruler. However, this method is destructive, time-consuming and limited spatial resolution. Although there are several methods to acquire ice thickness in non-destructive way, ground penetrating radar (GPR can be effective solution because it can discriminate snow-ice and ice-sea water interface. In this paper, we carried out GPR measurement in Lake Saroma for relatively large area (200 m by 300 m, approximately aiming to obtain grand truth for remote sensing data. GPR survey was conducted at 5 locations in the area. The direct measurement was also conducted simultaneously in order to calibrate GPR data for thickness estimation and to validate the result. Although GPR Bscan image obtained from 600MHz contains the reflection which may come from a structure under snow, the origin of the reflection is not obvious. Therefore, further analysis and interpretation of the GPR image, such as numerical simulation, additional signal processing and use of 200 MHz antenna, are required to move on thickness estimation.

Arctic Sea Ice Thickness Estimation from CryoSat-2 Satellite Data Using Machine Learning-Based Lead Detection

Directory of Open Access Journals (Sweden)

Sanggyun Lee

2016-08-01

Full Text Available Satellite altimeters have been used to monitor Arctic sea ice thickness since the early 2000s. In order to estimate sea ice thickness from satellite altimeter data, leads (i.e., cracks between ice floes should first be identified for the calculation of sea ice freeboard. In this study, we proposed novel approaches for lead detection using two machine learning algorithms: decision trees and random forest. CryoSat-2 satellite data collected in March and April of 2011–2014 over the Arctic region were used to extract waveform parameters that show the characteristics of leads, ice floes and ocean, including stack standard deviation, stack skewness, stack kurtosis, pulse peakiness and backscatter sigma-0. The parameters were used to identify leads in the machine learning models. Results show that the proposed approaches, with overall accuracy >90%, produced much better performance than existing lead detection methods based on simple thresholding approaches. Sea ice thickness estimated based on the machine learning-detected leads was compared to the averaged Airborne Electromagnetic (AEM-bird data collected over two days during the CryoSat Validation experiment (CryoVex field campaign in April 2011. This comparison showed that the proposed machine learning methods had better performance (up to r = 0.83 and Root Mean Square Error (RMSE = 0.29 m compared to thickness estimation based on existing lead detection methods (RMSE = 0.86–0.93 m. Sea ice thickness based on the machine learning approaches showed a consistent decline from 2011–2013 and rebounded in 2014.

On the Predictability of Sea Ice

Science.gov (United States)

Blanchard-Wrigglesworth, Edward

We investigate the persistence and predictability of sea ice in numerical models and observations. We first use the 3rd generation Community Climate System Model (CCSM3) General Circulation Model (GCM) to investigate the inherent persistence of sea-ice area and thickness. We find that sea-ice area anomalies have a seasonal decay timescale, exhibiting an initial decorrelation similar to a first order auto-regressive (AR1, or red noise) process. Beyond this initial loss of memory, there is a re-emergence of memory at certain times of the year. There are two distinct modes of re-emergence in the model, one driven by the seasonal coupling of area and thickness anomalies in the summer, the other by the persistence of upper ocean temperature anomalies that originate from ice anomalies in the melt season and then influence ice anomalies in the growth season. Comparison with satellite observations where available indicate these processes appear in nature. We then use the 4th generation CCSM (CCSM4) to investigate the partition of Arctic sea-ice predictability into its initial-value and boundary forced components under present day forcing conditions. We find that initial-value predictability lasts for 1-2 years for sea-ice area, and 3-4 years for sea-ice volume. Forced predictability arises after just 4-5 years for both area and volume. Initial-value predictability of sea-ice area during the summer hinges on the coupling between thickness and area anomalies during that season. We find that the loss of initial-value predictability with time is not uniform --- there is a rapid loss of predictability of sea-ice volume during the late spring early summer associated with snow melt and albedo feedbacks. At the same time, loss of predictability is not uniform across different regions. Given the usefulness of ice thickness as a predictor of summer sea-ice area, we obtain a hindcast of September sea-ice area initializing the GCM on May 1with an estimate of observed sea-ice thickness

Simultaneous retrieval of sea ice thickness and snow depth using concurrent active altimetry and passive L-band remote sensing data

Science.gov (United States)

Zhou, L.; Xu, S.; Liu, J.

2017-12-01

The retrieval of sea ice thickness mainly relies on satellite altimetry, and the freeboard measurements are converted to sea ice thickness (hi) under certain assumptions over snow loading. The uncertain in snow depth (hs) is a major source of uncertainty in the retrieved sea ice thickness and total volume for both radar and laser altimetry. In this study, novel algorithms for the simultaneous retrieval of hi and hs are proposed for the data synergy of L-band (1.4 GHz) passive remote sensing and both types of active altimetry: (1) L-band (1.4GHz) brightness temperature (TB) from Soil Moisture Ocean Salinity (SMOS) satellite and sea ice freeboard (FBice) from radar altimetry, (2) L-band TB data and snow freeboard (FBsnow) from laser altimetry. Two physical models serve as the forward models for the retrieval: L-band radiation model, and the hydrostatic equilibrium model. Verification with SMOS and Operational IceBridge (OIB) data is carried out, showing overall good retrieval accuracy for both sea ice parameters. Specifically, we show that the covariability between hs and FBsnow is crucial for the synergy between TB and FBsnow. Comparison with existing algorithms shows lower uncertainty in both sea ice parameters, and that the uncertainty in the retrieved sea ice thickness as caused by that of snow depth is spatially uncorrelated, with the potential reduction of the volume uncertainty through spatial sampling. The proposed algorithms can be applied to the retrieval of sea ice parameters at basin-scale, using concurrent active and passive remote sensing data based on satellites.

Ice formation and growth shape bacterial community structure in Baltic Sea drift ice.

Science.gov (United States)

Eronen-Rasimus, Eeva; Lyra, Christina; Rintala, Janne-Markus; Jürgens, Klaus; Ikonen, Vilma; Kaartokallio, Hermanni

2015-02-01

Drift ice, open water and under-ice water bacterial communities covering several developmental stages from open water to thick ice were studied in the northern Baltic Sea. The bacterial communities were assessed with 16S rRNA gene terminal-restriction fragment length polymorphism and cloning, together with bacterial abundance and production measurements. In the early stages, open water and pancake ice were dominated by Alphaproteobacteria and Actinobacteria, which are common bacterial groups in Baltic Sea wintertime surface waters. The pancake ice bacterial communities were similar to the open-water communities, suggesting that the parent water determines the sea-ice bacterial community in the early stages of sea-ice formation. In consolidated young and thick ice, the bacterial communities were significantly different from water bacterial communities as well as from each other, indicating community development in Baltic Sea drift ice along with ice-type changes. The thick ice was dominated by typical sea-ice genera from classes Flavobacteria and Gammaproteobacteria, similar to those in polar sea-ice bacterial communities. Since the thick ice bacterial community was remarkably different from that of the parent seawater, results indicate that thick ice bacterial communities were recruited from the rarer members of the seawater bacterial community. © FEMS 2014. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

An Ultra-Wideband, Microwave Radar for Measuring Snow Thickness on Sea Ice and Mapping Near-Surface Internal Layers in Polar Firn

Science.gov (United States)

Panzer, Ben; Gomez-Garcia, Daniel; Leuschen, Carl; Paden, John; Rodriguez-Morales, Fernando; Patel, Azsa; Markus, Thorsten; Holt, Benjamin; Gogineni, Prasad

2013-01-01

Sea ice is generally covered with snow, which can vary in thickness from a few centimeters to >1 m. Snow cover acts as a thermal insulator modulating the heat exchange between the ocean and the atmosphere, and it impacts sea-ice growth rates and overall thickness, a key indicator of climate change in polar regions. Snow depth is required to estimate sea-ice thickness using freeboard measurements made with satellite altimeters. The snow cover also acts as a mechanical load that depresses ice freeboard (snow and ice above sea level). Freeboard depression can result in flooding of the snow/ice interface and the formation of a thick slush layer, particularly in the Antarctic sea-ice cover. The Center for Remote Sensing of Ice Sheets (CReSIS) has developed an ultra-wideband, microwave radar capable of operation on long-endurance aircraft to characterize the thickness of snow over sea ice. The low-power, 100mW signal is swept from 2 to 8GHz allowing the air/snow and snow/ ice interfaces to be mapped with 5 c range resolution in snow; this is an improvement over the original system that worked from 2 to 6.5 GHz. From 2009 to 2012, CReSIS successfully operated the radar on the NASA P-3B and DC-8 aircraft to collect data on snow-covered sea ice in the Arctic and Antarctic for NASA Operation IceBridge. The radar was found capable of snow depth retrievals ranging from 10cm to >1 m. We also demonstrated that this radar can be used to map near-surface internal layers in polar firn with fine range resolution. Here we describe the instrument design, characteristics and performance of the radar.

On the retrieval of sea ice thickness and snow depth using concurrent laser altimetry and L-band remote sensing data

Science.gov (United States)

Zhou, Lu; Xu, Shiming; Liu, Jiping; Wang, Bin

2018-03-01

The accurate knowledge of sea ice parameters, including sea ice thickness and snow depth over the sea ice cover, is key to both climate studies and data assimilation in operational forecasts. Large-scale active and passive remote sensing is the basis for the estimation of these parameters. In traditional altimetry or the retrieval of snow depth with passive microwave remote sensing, although the sea ice thickness and the snow depth are closely related, the retrieval of one parameter is usually carried out under assumptions over the other. For example, climatological snow depth data or as derived from reanalyses contain large or unconstrained uncertainty, which result in large uncertainty in the derived sea ice thickness and volume. In this study, we explore the potential of combined retrieval of both sea ice thickness and snow depth using the concurrent active altimetry and passive microwave remote sensing of the sea ice cover. Specifically, laser altimetry and L-band passive remote sensing data are combined using two forward models: the L-band radiation model and the isostatic relationship based on buoyancy model. Since the laser altimetry usually features much higher spatial resolution than L-band data from the Soil Moisture Ocean Salinity (SMOS) satellite, there is potentially covariability between the observed snow freeboard by altimetry and the retrieval target of snow depth on the spatial scale of altimetry samples. Statistically significant correlation is discovered based on high-resolution observations from Operation IceBridge (OIB), and with a nonlinear fitting the covariability is incorporated in the retrieval algorithm. By using fitting parameters derived from large-scale surveys, the retrievability is greatly improved compared with the retrieval that assumes flat snow cover (i.e., no covariability). Verifications with OIB data show good match between the observed and the retrieved parameters, including both sea ice thickness and snow depth. With

A sea ice model for the marginal ice zone with an application to the Greenland Sea

DEFF Research Database (Denmark)

Pedersen, Leif Toudal; Coon, Max D.

2004-01-01

A model is presented that describes the formation, transport, and desalinization of frazil and pancake ice as it is formed in marginal seas. This model uses as input the total ice concentration evaluated from Special Sensor Microwave Imager and wind speed and direction. The model calculates...... the areal concentration, thickness, volume concentration, and salinity of frazil ice as well as the areal concentration, thickness, and salinity of pancakes. A simple parameterization for the Odden region of the Greenland Sea is presented. The model is run for the winter of 1996-1997. There are direct...... observations of the thickness and salinity of pancakes and the volume concentration of frazil ice to compare with the model. The model results compare very well with the measured data. This new ice model can be tuned to work in marginal seas elsewhere to calculate ice thickness, motion, and brine rejection...

Sea Ice

Science.gov (United States)

Perovich, D.; Gerland, S.; Hendricks, S.; Meier, Walter N.; Nicolaus, M.; Richter-Menge, J.; Tschudi, M.

2013-01-01

During 2013, Arctic sea ice extent remained well below normal, but the September 2013 minimum extent was substantially higher than the record-breaking minimum in 2012. Nonetheless, the minimum was still much lower than normal and the long-term trend Arctic September extent is -13.7 per decade relative to the 1981-2010 average. The less extreme conditions this year compared to 2012 were due to cooler temperatures and wind patterns that favored retention of ice through the summer. Sea ice thickness and volume remained near record-low levels, though indications are of slightly thicker ice compared to the record low of 2012.

Improving Arctic Sea Ice Observations and Data Access to Support Advances in Sea Ice Forecasting

Science.gov (United States)

Farrell, S. L.

2017-12-01

The economic and strategic importance of the Arctic region is becoming apparent. One of the most striking and widely publicized changes underway is the declining sea ice cover. Since sea ice is a key component of the climate system, its ongoing loss has serious, and wide-ranging, socio-economic implications. Increasing year-to-year variability in the geographic location, concentration, and thickness of the Arctic ice cover will pose both challenges and opportunities. The sea ice research community must be engaged in sustained Arctic Observing Network (AON) initiatives so as to deliver fit-for-purpose remote sensing data products to a variety of stakeholders including Arctic communities, the weather forecasting and climate modeling communities, industry, local, regional and national governments, and policy makers. An example of engagement is the work currently underway to improve research collaborations between scientists engaged in obtaining and assessing sea ice observational data and those conducting numerical modeling studies and forecasting ice conditions. As part of the US AON, in collaboration with the Interagency Arctic Research Policy Committee (IARPC), we are developing a strategic framework within which observers and modelers can work towards the common goal of improved sea ice forecasting. Here, we focus on sea ice thickness, a key varaible of the Arctic ice cover. We describe multi-sensor, and blended, sea ice thickness data products under development that can be leveraged to improve model initialization and validation, as well as support data assimilation exercises. We will also present the new PolarWatch initiative (polarwatch.noaa.gov) and discuss efforts to advance access to remote sensing satellite observations and improve communication with Arctic stakeholders, so as to deliver data products that best address societal needs.

Variability and Trends in Sea Ice Extent and Ice Production in the Ross Sea

Science.gov (United States)

Comiso, Josefino; Kwok, Ronald; Martin, Seelye; Gordon, Arnold L.

2011-01-01

Salt release during sea ice formation in the Ross Sea coastal regions is regarded as a primary forcing for the regional generation of Antarctic Bottom Water. Passive microwave data from November 1978 through 2008 are used to examine the detailed seasonal and interannual characteristics of the sea ice cover of the Ross Sea and the adjacent Bellingshausen and Amundsen seas. For this period the sea ice extent in the Ross Sea shows the greatest increase of all the Antarctic seas. Variability in the ice cover in these regions is linked to changes in the Southern Annular Mode and secondarily to the Antarctic Circumpolar Wave. Over the Ross Sea shelf, analysis of sea ice drift data from 1992 to 2008 yields a positive rate of increase in the net ice export of about 30,000 sq km/yr. For a characteristic ice thickness of 0.6 m, this yields a volume transport of about 20 cu km/yr, which is almost identical, within error bars, to our estimate of the trend in ice production. The increase in brine rejection in the Ross Shelf Polynya associated with the estimated increase with the ice production, however, is not consistent with the reported Ross Sea salinity decrease. The locally generated sea ice enhancement of Ross Sea salinity may be offset by an increase of relatively low salinity of the water advected into the region from the Amundsen Sea, a consequence of increased precipitation and regional glacial ice melt.

Arctic Sea Ice: Using Airborne Topographic Mapper Measurements (ATM) to Determine Sea Ice Thickness

Science.gov (United States)

2011-05-10

Track Distance (Km) E le v a ti o n ( m ) ATM Elevation Profile Elevation 18 Figure 13: Geoid shape of earth’s equipotential surface , which is...inferred for the region between successive leads. Therefore, flying over a lead in the ice is very important for determining the exact sea surface elevation...inferred for the region between successive leads. Therefore, flying over a lead in the ice is very important for determining the exact sea surface

Sea ice inertial oscillations in the Arctic Basin

Directory of Open Access Journals (Sweden)

F. Gimbert

2012-10-01

Full Text Available An original method to quantify the amplitude of inertial motion of oceanic and ice drifters, through the introduction of a non-dimensional parameter M defined from a spectral analysis, is presented. A strong seasonal dependence of the magnitude of sea ice inertial oscillations is revealed, in agreement with the corresponding annual cycles of sea ice extent, concentration, thickness, advection velocity, and deformation rates. The spatial pattern of the magnitude of the sea ice inertial oscillations over the Arctic Basin is also in agreement with the sea ice thickness and concentration patterns. This argues for a strong interaction between the magnitude of inertial motion on one hand, the dissipation of energy through mechanical processes, and the cohesiveness of the cover on the other hand. Finally, a significant multi-annual evolution towards greater magnitudes of inertial oscillations in recent years, in both summer and winter, is reported, thus concomitant with reduced sea ice thickness, concentration and spatial extent.

Estimation of Antarctic Land-Fast Sea Ice Algal Biomass and Snow Thickness From Under-Ice Radiance Spectra in Two Contrasting Areas

Science.gov (United States)

Wongpan, P.; Meiners, K. M.; Langhorne, P. J.; Heil, P.; Smith, I. J.; Leonard, G. H.; Massom, R. A.; Clementson, L. A.; Haskell, T. G.

2018-03-01

Fast ice is an important component of Antarctic coastal marine ecosystems, providing a prolific habitat for ice algal communities. This work examines the relationships between normalized difference indices (NDI) calculated from under-ice radiance measurements and sea ice algal biomass and snow thickness for Antarctic fast ice. While this technique has been calibrated to assess biomass in Arctic fast ice and pack ice, as well as Antarctic pack ice, relationships are currently lacking for Antarctic fast ice characterized by bottom ice algae communities with high algal biomass. We analyze measurements along transects at two contrasting Antarctic fast ice sites in terms of platelet ice presence: near and distant from an ice shelf, i.e., in McMurdo Sound and off Davis Station, respectively. Snow and ice thickness, and ice salinity and temperature measurements support our paired in situ optical and biological measurements. Analyses show that NDI wavelength pairs near the first chlorophyll a (chl a) absorption peak (≈440 nm) explain up to 70% of the total variability in algal biomass. Eighty-eight percent of snow thickness variability is explained using an NDI with a wavelength pair of 648 and 567 nm. Accounting for pigment packaging effects by including the ratio of chl a-specific absorption coefficients improved the NDI-based algal biomass estimation only slightly. Our new observation-based algorithms can be used to estimate Antarctic fast ice algal biomass and snow thickness noninvasively, for example, by using moored sensors (time series) or mapping their spatial distributions using underwater vehicles.

Under Sea Ice phytoplankton bloom detection and contamination in Antarctica

Science.gov (United States)

Zeng, C.; Zeng, T.; Xu, H.

2017-12-01

Previous researches reported compelling sea ice phytoplankton bloom in Arctic, while seldom reports studied about Antarctic. Here, lab experiment showed sea ice increased the visible light albedo of the water leaving radiance. Even a new formed sea ice of 10cm thickness increased water leaving radiance up to 4 times of its original bare water. Given that phytoplankton preferred growing and accumulating under the sea ice with thickness of 10cm-1m, our results showed that the changing rate of OC4 estimated [Chl-a] varied from 0.01-0.5mg/m3 to 0.2-0.3mg/m3, if the water covered by 10cm sea ice. Going further, varying thickness of sea ice modulated the changing rate of estimating [Chl-a] non-linearly, thus current routine OC4 model cannot estimate under sea ice [Chl-a] appropriately. Besides, marginal sea ice zone has a large amount of mixture regions containing sea ice, water and snow, where is favorable for phytoplankton. We applied 6S model to estimate the sea ice/snow contamination on sub-pixel water leaving radiance of 4.25km spatial resolution ocean color products. Results showed that sea ice/snow scale effectiveness overestimated [Chl-a] concentration based on routine band ratio OC4 model, which contamination increased with the rising fraction of sea ice/snow within one pixel. Finally, we analyzed the under sea ice bloom in Antarctica based on the [Chl-a] concentration trends during 21 days after sea ice retreating. Regardless of those overestimation caused by sea ice/snow sub scale contamination, we still did not see significant under sea ice blooms in Antarctica in 2012-2017 compared with Arctic. This research found that Southern Ocean is not favorable for under sea ice blooms and the phytoplankton bloom preferred to occur in at least 3 weeks after sea ice retreating.

Analysis of Sea Ice Cover Sensitivity in Global Climate Model

Directory of Open Access Journals (Sweden)

V. P. Parhomenko

2014-01-01

Full Text Available The paper presents joint calculations using a 3D atmospheric general circulation model, an ocean model, and a sea ice evolution model. The purpose of the work is to analyze a seasonal and annual evolution of sea ice, long-term variability of a model ice cover, and its sensitivity to some parameters of model as well to define atmosphere-ice-ocean interaction.Results of 100 years simulations of Arctic basin sea ice evolution are analyzed. There are significant (about 0.5 m inter-annual fluctuations of an ice cover.The ice - atmosphere sensible heat flux reduced by 10% leads to the growth of average sea ice thickness within the limits of 0.05 m – 0.1 m. However in separate spatial points the thickness decreases up to 0.5 m. An analysis of the seasonably changing average ice thickness with decreasing, as compared to the basic variant by 0.05 of clear sea ice albedo and that of snow shows the ice thickness reduction in a range from 0.2 m up to 0.6 m, and the change maximum falls for the summer season of intensive melting. The spatial distribution of ice thickness changes shows, that on the large part of the Arctic Ocean there was a reduction of ice thickness down to 1 m. However, there is also an area of some increase of the ice layer basically in a range up to 0.2 m (Beaufort Sea. The 0.05 decrease of sea ice snow albedo leads to reduction of average ice thickness approximately by 0.2 m, and this value slightly depends on a season. In the following experiment the ocean – ice thermal interaction influence on the ice cover is estimated. It is carried out by increase of a heat flux from ocean to the bottom surface of sea ice by 2 W/sq. m in comparison with base variant. The analysis demonstrates, that the average ice thickness reduces in a range from 0.2 m to 0.35 m. There are small seasonal changes of this value.The numerical experiments results have shown, that an ice cover and its seasonal evolution rather strongly depend on varied parameters

A network model for electrical transport in sea ice

International Nuclear Information System (INIS)

Zhu, J.; Golden, K.M.; Gully, A.; Sampson, C.

2010-01-01

Monitoring the thickness of sea ice is an important tool in assessing the impact of global warming on Earth's polar regions, and most methods of measuring ice thickness depend on detailed knowledge of its electrical properties. We develop a network model for the electrical conductivity of sea ice, which incorporates statistical measurements of the brine microstructure. The numerical simulations are in close agreement with direct measurements we made in Antarctica on the vertical conductivity of first year sea ice.

Sea Ice Summer Camp: Bringing Together Arctic Sea Ice Modelers and Observers

Science.gov (United States)

Perovich, D. K.; Holland, M. M.

2016-12-01

The Arctic sea ice has undergone dramatic change and numerical models project this to continue for the foreseeable future. Understanding the mechanisms behind sea ice loss and its consequences for the larger Arctic and global systems is of critical importance if we are to anticipate and plan for the future. One impediment to progress is a disconnect between the observational and modeling communities. A sea ice summer camp was held in Barrow Alaska from 26 May to 1 June 2016 to overcome this impediment and better integrate the sea ice community. The 25 participants were a mix of modelers and observers from 13 different institutions at career stages from graduate student to senior scientist. The summer camp provided an accelerated program on sea ice observations and models and also fostered future collaborative interdisciplinary activities. Each morning was spent in the classroom with a daily lecture on an aspect of modeling or remote sensing followed by practical exercises. Topics included using models to assess sensitivity, to test hypotheses and to explore sources of uncertainty in future Arctic sea ice loss. The afternoons were spent on the ice making observations. There were four observational activities; albedo observations, ice thickness measurements, ice coring and physical properties, and ice morphology surveys. The last field day consisted of a grand challenge where the group formulated a hypothesis, developed an observational and modeling strategy to test the hypothesis, and then integrated the observations and model results. The impacts of changing sea ice are being felt today in Barrow Alaska. We opened a dialog with Barrow community members to further understand these changes. This included an evening discussion with two Barrow sea ice experts and a community presentation of our work in a public lecture at the Inupiat Heritage Center.

A combined approach of remote sensing and airborne electromagnetics to determine the volume of polynya sea ice in the Laptev Sea

Directory of Open Access Journals (Sweden)

L. Rabenstein

2013-06-01

Full Text Available A combined interpretation of synthetic aperture radar (SAR satellite images and helicopter electromagnetic (HEM sea-ice thickness data has provided an estimate of sea-ice volume formed in Laptev Sea polynyas during the winter of 2007/08. The evolution of the surveyed sea-ice areas, which were formed between late December 2007 and middle April 2008, was tracked using a series of SAR images with a sampling interval of 2–3 days. Approximately 160 km of HEM data recorded in April 2008 provided sea-ice thicknesses along profiles that transected sea ice varying in age from 1 to 116 days. For the volume estimates, thickness information along the HEM profiles was extrapolated to zones of the same age. The error of areal mean thickness information was estimated to be between 0.2 m for younger ice and up to 1.55 m for older ice, with the primary error source being the spatially limited HEM coverage. Our results have demonstrated that the modal thicknesses and mean thicknesses of level ice correlated with the sea-ice age, but that varying dynamic and thermodynamic sea-ice growth conditions resulted in a rather heterogeneous sea-ice thickness distribution on scales of tens of kilometers. Taking all uncertainties into account, total sea-ice area and volume produced within the entire surveyed area were 52 650 km2 and 93.6 ± 26.6 km3. The surveyed polynya contributed 2.0 ± 0.5% of the sea-ice produced throughout the Arctic during the 2007/08 winter. The SAR-HEM volume estimate compares well with the 112 km3 ice production calculated with a~high-resolution ocean sea-ice model. Measured modal and mean-level ice thicknesses correlate with calculated freezing-degree-day thicknesses with a factor of 0.87–0.89, which was too low to justify the assumption of homogeneous thermodynamic growth conditions in the area, or indicates a strong dynamic thickening of level ice by rafting of even thicker ice.

Coordinated Mapping of Sea Ice Deformation Features with Autonomous Vehicles

Science.gov (United States)

Maksym, T.; Williams, G. D.; Singh, H.; Weissling, B.; Anderson, J.; Maki, T.; Ackley, S. F.

2016-12-01

Decreases in summer sea ice extent in the Beaufort and Chukchi Seas has lead to a transition from a largely perennial ice cover, to a seasonal ice cover. This drives shifts in sea ice production, dynamics, ice types, and thickness distribution. To examine how the processes driving ice advance might also impact the morphology of the ice cover, a coordinated ice mapping effort was undertaken during a field campaign in the Beaufort Sea in October, 2015. Here, we present observations of sea ice draft topography from six missions of an Autonomous Underwater Vehicle run under different ice types and deformation features observed during autumn freeze-up. Ice surface features were also mapped during coordinated drone photogrammetric missions over each site. We present preliminary results of a comparison between sea ice surface topography and ice underside morphology for a range of sample ice types, including hummocked multiyear ice, rubble fields, young ice ridges and rafts, and consolidated pancake ice. These data are compared to prior observations of ice morphological features from deformed Antarctic sea ice. Such data will be useful for improving parameterizations of sea ice redistribution during deformation, and for better constraining estimates of airborne or satellite sea ice thickness.

Ross Sea Polynyas: Response of Ice Concentration Retrievals to Large Areas of Thin Ice

Science.gov (United States)

Kwok, R.; Comiso, J. C.; Martin, S.; Drucker, R.

2007-01-01

For a 3-month period between May and July of 2005, we examine the response of the Advanced Microwave Scanning Radiometer (AMSR-E) Enhanced NASA Team 2 (NT2) and AMSR-E Bootstrap (ABA) ice concentration algorithms to large areas of thin ice of the Ross Sea polynyas. Coincident Envisat Synthetic Aperture Radar (SAR) coverage of the region during this period offers a detailed look at the development of the polynyas within several hundred kilometers of the ice front. The high-resolution imagery and derived ice motion fields show bands of polynya ice, covering up to approximately 105 km(sup 2) of the Ross Sea, that are associated with wind-forced advection. In this study, ice thickness from AMSR-E 36 GHz polarization information serves as the basis for examination of the response. The quality of the thickness of newly formed sea ice (<10 cm) from AMSR-E is first assessed with thickness estimates derived from ice surface temperatures from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. The effect of large areas of thin ice in lowering the ice concentration estimates from both NT2/ABA approaches is clearly demonstrated. Results show relatively robust relationships between retrieved ice concentrations and thin ice thickness estimates that differ between the two algorithms. These relationships define the approximate spatial coincidence of ice concentration and thickness isopleths. Using the 83% (ABA) and 91% (NT2) isopleths as polynya boundaries, we show that the computed coverage compares well with that using the estimated 10-cm thickness contour. The thin ice response characterized here suggests that in regions with polynyas, the retrieval results could be used to provide useful geophysical information, namely thickness and coverage.

Arctic sea-ice ridges—Safe heavens for sea-ice fauna during periods of extreme ice melt?

Science.gov (United States)

Gradinger, Rolf; Bluhm, Bodil; Iken, Katrin

2010-01-01

The abundances and distribution of metazoan within-ice meiofauna (13 stations) and under-ice fauna (12 stations) were investigated in level sea ice and sea-ice ridges in the Chukchi/Beaufort Seas and Canada Basin in June/July 2005 using a combination of ice coring and SCUBA diving. Ice meiofauna abundance was estimated based on live counts in the bottom 30 cm of level sea ice based on triplicate ice core sampling at each location, and in individual ice chunks from ridges at four locations. Under-ice amphipods were counted in situ in replicate ( N=24-65 per station) 0.25 m 2 quadrats using SCUBA to a maximum water depth of 12 m. In level sea ice, the most abundant ice meiofauna groups were Turbellaria (46%), Nematoda (35%), and Harpacticoida (19%), with overall low abundances per station that ranged from 0.0 to 10.9 ind l -1 (median 0.8 ind l -1). In level ice, low ice algal pigment concentrations (Turbellaria, Nematoda and Harpacticoida also were observed in pressure ridges (0-200 ind l -1, median 40 ind l -1), although values were highly variable and only medians of Turbellaria were significantly higher in ridge ice than in level ice. Median abundances of under-ice amphipods at all ice types (level ice, various ice ridge structures) ranged from 8 to 114 ind m -2 per station and mainly consisted of Apherusa glacialis (87%), Onisimus spp. (7%) and Gammarus wilkitzkii (6%). Highest amphipod abundances were observed in pressure ridges at depths >3 m where abundances were up to 42-fold higher compared with level ice. We propose that the summer ice melt impacted meiofauna and under-ice amphipod abundance and distribution through (a) flushing, and (b) enhanced salinity stress at thinner level sea ice (less than 3 m thickness). We further suggest that pressure ridges, which extend into deeper, high-salinity water, become accumulation regions for ice meiofauna and under-ice amphipods in summer. Pressure ridges thus might be crucial for faunal survival during periods of

Retrieval of ice thickness from polarimetric SAR data

Science.gov (United States)

Kwok, R.; Yueh, S. H.; Nghiem, S. V.; Huynh, D. D.

1993-01-01

We describe a potential procedure for retrieving ice thickness from multi-frequency polarimetric SAR data for thin ice. This procedure includes first masking out the thicker ice types with a simple classifier and then deriving the thickness of the remaining pixels using a model-inversion technique. The technique used to derive ice thickness from polarimetric observations is provided by a numerical estimator or neural network. A three-layer perceptron implemented with the backpropagation algorithm is used in this investigation with several improved aspects for a faster convergence rate and a better accuracy of the neural network. These improvements include weight initialization, normalization of the output range, the selection of offset constant, and a heuristic learning algorithm. The performance of the neural network is demonstrated by using training data generated by a theoretical scattering model for sea ice matched to the database of interest. The training data are comprised of the polarimetric backscattering coefficients of thin ice and the corresponding input ice parameters to the scattering model. The retrieved ice thickness from the theoretical backscattering coefficients is compare with the input ice thickness to the scattering model to illustrate the accuracy of the inversion method. Results indicate that the network convergence rate and accuracy are higher when multi-frequency training sets are presented. In addition, the dominant backscattering coefficients in retrieving ice thickness are found by comparing the behavior of the network trained backscattering data at various incidence angels. After the neural network is trained with the theoretical backscattering data at various incidence anges, the interconnection weights between nodes are saved and applied to the experimental data to be investigated. In this paper, we illustrate the effectiveness of this technique using polarimetric SAR data collected by the JPL DC-8 radar over a sea ice scene.

Observations of Recent Arctic Sea Ice Volume Loss and Its Impact on Ocean-Atmosphere Energy Exchange and Ice Production

Science.gov (United States)

Kurtz, N. T.; Markus, T.; Farrell, S. L.; Worthen, D. L.; Boisvert, L. N.

2011-01-01

Using recently developed techniques we estimate snow and sea ice thickness distributions for the Arctic basin through the combination of freeboard data from the Ice, Cloud, and land Elevation Satellite (ICESat) and a snow depth model. These data are used with meteorological data and a thermodynamic sea ice model to calculate ocean-atmosphere heat exchange and ice volume production during the 2003-2008 fall and winter seasons. The calculated heat fluxes and ice growth rates are in agreement with previous observations over multiyear ice. In this study, we calculate heat fluxes and ice growth rates for the full distribution of ice thicknesses covering the Arctic basin and determine the impact of ice thickness change on the calculated values. Thinning of the sea ice is observed which greatly increases the 2005-2007 fall period ocean-atmosphere heat fluxes compared to those observed in 2003. Although there was also a decline in sea ice thickness for the winter periods, the winter time heat flux was found to be less impacted by the observed changes in ice thickness. A large increase in the net Arctic ocean-atmosphere heat output is also observed in the fall periods due to changes in the areal coverage of sea ice. The anomalously low sea ice coverage in 2007 led to a net ocean-atmosphere heat output approximately 3 times greater than was observed in previous years and suggests that sea ice losses are now playing a role in increasing surface air temperatures in the Arctic.

L-band radiometry for sea ice applications

Science.gov (United States)

Heygster, G.; Hedricks, S.; Mills, P.; Kaleschke, L.; Stammer, D.; Tonboe, R.

2009-04-01

Although sea ice remote sensing has reached the level of operational exploitation with well established retrieval methods, several important tasks are still unsolved. In particular during freezing and melting periods with mixed ice and water surfaces, estimates of ice concentration with passive and active microwave sensors remain challenging. Newly formed thin ice is also hard to distinguish from open water with radiometers for frequencies above 8 GHz. The SMOS configuration (planned launch 2009) with a radiometer at 1.4 GHz is a promising technique to complement observations at higher microwave frequencies. ESA has initiated a project to investigate the possibilities for an additional Level-2 sea ice data product based on SMOS. In detail, the project objectives are (1) to model the L band emission of sea ice, and to assess the potential (2) to retrieve sea ice parameters, especially concentration and thickness, and (3) to use cold water regions for an external calibration of SMOS. Modelling of L band emission: Several models have are investigated. All of them work on the same basic principles and have a vertically-layered, plane-parallel geometry. They are comprised of three basic components: (1) effective permittivities are calculated for each layer based on ice bulk and micro-structural properties; (2) these are integrated across the total depth to derive emitted brightness temperature; (3) scattering terms can also be added because of the granular structure of ice and snow. MEMLS (Microwave Emission Model of Layered Snowpacks (Wiesmann and Matzler 1999)) is one such model that contains all three elements in a single Matlab program. In the absence of knowledge about the internal structure of the sea ice, three-layer (air, ice and water) dielectric slab models which take as input a single effective permittivity for the ice layer are appropriate. By ignoring scattering effects one can derive a simple analytic expression for a dielectric slab as shown by Apinis and

On the estimation of ice thickness from scattering observations

Science.gov (United States)

Williams, T. D.; Squire, V. A.

2010-04-01

This paper is inspired by the proposition that it may be possible to extract descriptive physical parameters - in particular the ice thickness, of a sea-ice field from ocean wave information. The motivation is that mathematical theory describing wave propagation in such media has reached a point where the inherent heterogeneity, expressed as pressure ridge keels and sails, leads, thickness variations and changes of material property and draught, can be fully assimilated exactly or through approximations whose limitations are understood. On the basis that leads have the major wave scattering effect for most sea-ice [Williams, T.D., Squire, V.A., 2004. Oblique scattering of plane flexural-gravity waves by heterogeneities in sea ice. Proc. R. Soc. Lon. Ser.-A 460 (2052), 3469-3497], a model two dimensional sea-ice sheet composed of a large number of such features, randomly dispersed, is constructed. The wide spacing approximation is used to predict how wave trains of different period will be affected, after first establishing that this produces results that are very close to the exact solution. Like Kohout and Meylan [Kohout, A.L., Meylan, M.H., 2008. An elastic plate model for wave attenuation and ice floe breaking in the marginal ice zone. J. Geophys. Res. 113, C09016, doi:10.1029/2007JC004434], we find that on average the magnitude of a wave transmitted by a field of leads decays exponentially with the number of leads. Then, by fitting a curve based on this assumption to the data, the thickness of the ice sheet is obtained. The attenuation coefficient can always be calculated numerically by ensemble averaging but in some cases more rapidly computed approximations work extremely well. Moreover, it is found that the underlying thickness can be determined to good accuracy by the method as long as Archimedean draught is correctly provided for, suggesting that waves can indeed be effective as a remote sensing agent to measure ice thickness in areas where pressure ridges

The effects of additional black carbon on the albedo of Arctic sea ice: variation with sea ice type and snow cover

Directory of Open Access Journals (Sweden)

A. A. Marks

2013-07-01

Full Text Available The response of the albedo of bare sea ice and snow-covered sea ice to the addition of black carbon is calculated. Visible light absorption and light-scattering cross-sections are derived for a typical first-year and multi-year sea ice with both "dry" and "wet" snow types. The cross-sections are derived using data from a 1970s field study that recorded both reflectivity and light penetration in Arctic sea ice and snow overlying sea ice. The variation of absorption cross-section over the visible wavelengths suggests black carbon is the dominating light-absorbing impurity. The response of first-year and multi-year sea ice albedo to increasing black carbon, from 1 to 1024 ng g−1, in a top 5 cm layer of a 155 cm-thick sea ice was calculated using a radiative-transfer model. The albedo of the first-year sea ice is more sensitive to additional loadings of black carbon than the multi-year sea ice. An addition of 8 ng g−1 of black carbon causes a decrease to 98.7% of the original albedo for first-year sea ice compared to a decrease to 99.7% for the albedo of multi-year sea ice, at a wavelength of 500 nm. The albedo of sea ice is surprisingly unresponsive to additional black carbon up to 100 ng g−1 . Snow layers on sea ice may mitigate the effects of black carbon in sea ice. Wet and dry snow layers of 0.5, 1, 2, 5 and 10 cm depth were added onto the sea ice surface. The albedo of the snow surface was calculated whilst the black carbon in the underlying sea ice was increased. A layer of snow 0.5 cm thick greatly diminishes the effect of black carbon in sea ice on the surface albedo. The albedo of a 2–5 cm snow layer (less than the e-folding depth of snow is still influenced by the underlying sea ice, but the effect of additional black carbon in the sea ice is masked.

Calibration of sea ice dynamic parameters in an ocean-sea ice model using an ensemble Kalman filter

Science.gov (United States)

Massonnet, F.; Goosse, H.; Fichefet, T.; Counillon, F.

2014-07-01

The choice of parameter values is crucial in the course of sea ice model development, since parameters largely affect the modeled mean sea ice state. Manual tuning of parameters will soon become impractical, as sea ice models will likely include more parameters to calibrate, leading to an exponential increase of the number of possible combinations to test. Objective and automatic methods for parameter calibration are thus progressively called on to replace the traditional heuristic, "trial-and-error" recipes. Here a method for calibration of parameters based on the ensemble Kalman filter is implemented, tested and validated in the ocean-sea ice model NEMO-LIM3. Three dynamic parameters are calibrated: the ice strength parameter P*, the ocean-sea ice drag parameter Cw, and the atmosphere-sea ice drag parameter Ca. In twin, perfect-model experiments, the default parameter values are retrieved within 1 year of simulation. Using 2007-2012 real sea ice drift data, the calibration of the ice strength parameter P* and the oceanic drag parameter Cw improves clearly the Arctic sea ice drift properties. It is found that the estimation of the atmospheric drag Ca is not necessary if P* and Cw are already estimated. The large reduction in the sea ice speed bias with calibrated parameters comes with a slight overestimation of the winter sea ice areal export through Fram Strait and a slight improvement in the sea ice thickness distribution. Overall, the estimation of parameters with the ensemble Kalman filter represents an encouraging alternative to manual tuning for ocean-sea ice models.

Loss of sea ice in the Arctic.

Science.gov (United States)

Perovich, Donald K; Richter-Menge, Jacqueline A

2009-01-01

The Arctic sea ice cover is in decline. The areal extent of the ice cover has been decreasing for the past few decades at an accelerating rate. Evidence also points to a decrease in sea ice thickness and a reduction in the amount of thicker perennial sea ice. A general global warming trend has made the ice cover more vulnerable to natural fluctuations in atmospheric and oceanic forcing. The observed reduction in Arctic sea ice is a consequence of both thermodynamic and dynamic processes, including such factors as preconditioning of the ice cover, overall warming trends, changes in cloud coverage, shifts in atmospheric circulation patterns, increased export of older ice out of the Arctic, advection of ocean heat from the Pacific and North Atlantic, enhanced solar heating of the ocean, and the ice-albedo feedback. The diminishing Arctic sea ice is creating social, political, economic, and ecological challenges.

Knowledge-based sea ice classification by polarimetric SAR

DEFF Research Database (Denmark)

Skriver, Henning; Dierking, Wolfgang

2004-01-01

Polarimetric SAR images acquired at C- and L-band over sea ice in the Greenland Sea, Baltic Sea, and Beaufort Sea have been analysed with respect to their potential for ice type classification. The polarimetric data were gathered by the Danish EMISAR and the US AIRSAR which both are airborne...... systems. A hierarchical classification scheme was chosen for sea ice because our knowledge about magnitudes, variations, and dependences of sea ice signatures can be directly considered. The optimal sequence of classification rules and the rules themselves depend on the ice conditions/regimes. The use...... of the polarimetric phase information improves the classification only in the case of thin ice types but is not necessary for thicker ice (above about 30 cm thickness)...

Multi-decadal Arctic sea ice roughness.

Science.gov (United States)

Tsamados, M.; Stroeve, J.; Kharbouche, S.; Muller, J. P., , Prof; Nolin, A. W.; Petty, A.; Haas, C.; Girard-Ardhuin, F.; Landy, J.

2017-12-01

The transformation of Arctic sea ice from mainly perennial, multi-year ice to a seasonal, first-year ice is believed to have been accompanied by a reduction of the roughness of the ice cover surface. This smoothening effect has been shown to (i) modify the momentum and heat transfer between the atmosphere and ocean, (ii) to alter the ice thickness distribution which in turn controls the snow and melt pond repartition over the ice cover, and (iii) to bias airborne and satellite remote sensing measurements that depend on the scattering and reflective characteristics over the sea ice surface topography. We will review existing and novel remote sensing methodologies proposed to estimate sea ice roughness, ranging from airborne LIDAR measurement (ie Operation IceBridge), to backscatter coefficients from scatterometers (ASCAT, QUICKSCAT), to multi angle maging spectroradiometer (MISR), and to laser (Icesat) and radar altimeters (Envisat, Cryosat, Altika, Sentinel-3). We will show that by comparing and cross-calibrating these different products we can offer a consistent multi-mission, multi-decadal view of the declining sea ice roughness. Implications for sea ice physics, climate and remote sensing will also be discussed.

Open-Source Python Modules to Estimate Level Ice Thickness from Ice Charts

Science.gov (United States)

Geiger, C. A.; Deliberty, T. L.; Bernstein, E. R.; Helfrich, S.

2012-12-01

A collaborative research effort between the University of Delaware (UD) and National Ice Center (NIC) addresses the task of providing open-source translations of sea ice stage-of-development into level ice thickness estimates on a 4km grid for the Interactive Multisensor Snow and Ice Mapping System (IMS). The characteristics for stage-of-development are quantified from remote sensing imagery with estimates of level ice thickness categories originating from World Meteorological Organization (WMO) egg coded ice charts codified since the 1970s. Conversions utilize Python scripting modules which transform electronic ice charts with WMO egg code characteristics into five level ice thickness categories, in centimeters, (0-10, 10-30, 30-70, 70-120, >120cm) and five ice types (open water, first year pack ice, fast ice, multiyear ice, and glacial ice with a reserve slot for deformed ice fractions). Both level ice thickness categories and ice concentration fractions are reported with uncertainties propagated based on WMO ice stage ranges which serve as proxy estimates for standard deviation. These products are in preparation for use by NCEP, CMC, and NAVO by 2014 based on their modeling requirements for daily products in near-real time. In addition to development, continuing research tests the value of these estimated products against in situ observations to improve both value and uncertainty estimates.

Distributed ice thickness and glacier volume in southern South America

Science.gov (United States)

Carrivick, Jonathan L.; Davies, Bethan J.; James, William H. M.; Quincey, Duncan J.; Glasser, Neil F.

2016-11-01

South American glaciers, including those in Patagonia, presently contribute the largest amount of meltwater to sea level rise per unit glacier area in the world. Yet understanding of the mechanisms behind the associated glacier mass balance changes remains unquantified partly because models are hindered by a lack of knowledge of subglacial topography. This study applied a perfect-plasticity model along glacier centre-lines to derive a first-order estimate of ice thickness and then interpolated these thickness estimates across glacier areas. This produced the first complete coverage of distributed ice thickness, bed topography and volume for 617 glaciers between 41°S and 55°S and in 24 major glacier regions. Maximum modelled ice thicknesses reach 1631 m ± 179 m in the South Patagonian Icefield (SPI), 1315 m ± 145 m in the North Patagonian Icefield (NPI) and 936 m ± 103 m in Cordillera Darwin. The total modelled volume of ice is 1234.6 km3 ± 246.8 km3 for the NPI, 4326.6 km3 ± 865.2 km3 for the SPI and 151.9 km3 ± 30.38 km3 for Cordillera Darwin. The total volume was modelled to be 5955 km3 ± 1191 km3, which equates to 5458.3 Gt ± 1091.6 Gt ice and to 15.08 mm ± 3.01 mm sea level equivalent (SLE). However, a total area of 655 km2 contains ice below sea level and there are 282 individual overdeepenings with a mean depth of 38 m and a total volume if filled with water to the brim of 102 km3. Adjusting the potential SLE for the ice volume below sea level and for the maximum potential storage of meltwater in these overdeepenings produces a maximum potential sea level rise (SLR) of 14.71 mm ± 2.94 mm. We provide a calculation of the present ice volume per major river catchment and we discuss likely changes to southern South America glaciers in the future. The ice thickness and subglacial topography modelled by this study will facilitate future studies of ice dynamics and glacier isostatic adjustment, and will be important for projecting water resources and

ICESat Observations of Arctic Sea Ice: A First Look

Science.gov (United States)

Kwok, Ron; Zwally, H. Jay; Yi, Donghui

2004-01-01

Analysis of near-coincident ICESat and RADARSAT imagery shows that the retrieved elevations from the laser altimeter are sensitive to new openings (containing thin ice or open water) in the sea ice cover as well as to surface relief of old and first-year ice. The precision of the elevation estimates, measured over relatively flat sea ice, is approx. 2 cm. Using the thickness of thin-ice in recent openings to estimate sea level references, we obtain the sea-ice freeboard along the altimeter tracks. This step is necessitated by the large uncertainties in the sea surface topography compared to that required for accurate determination of freeboard. Unknown snow depth introduces the largest uncertainty in the conversion of freeboard to ice thickness. Surface roughness is also derived, for the first time, from the variability of successive elevation estimates along the altimeter track. Overall, these ICESat measurements provide an unprecedented view of the Arctic Ocean ice cover at length scales at and above the spatial dimension of the altimeter footprint of approx. 70 m.

Ultra-Wideband Radiometry Remote Sensing of Polar Ice Sheet Temperature Profile, Sea Ice and Terrestrial Snow Thickness: Forward Modeling and Data Analysis

Science.gov (United States)

Tsang, L.; Tan, S.; Sanamzadeh, M.; Johnson, J. T.; Jezek, K. C.; Durand, M. T.

2017-12-01

The recent development of an ultra-wideband software defined radiometer (UWBRAD) operating over the unprotected spectrum of 0.5 2.0 GHz using radio-frequency interference suppression techniques offers new methodologies for remote sensing of the polar ice sheets, sea ice, and terrestrial snow. The instrument was initially designed for remote sensing of the intragalcial temperature profile of the ice sheet, where a frequency dependent penetration depth yields a frequency dependent brightness temperature (Tb) spectrum that can be linked back to the temperature profile of the ice sheet. The instrument was tested during a short flight over Northwest Greenland in September, 2016. Measurements were successfully made over the different snow facies characteristic of Greenland including the ablation, wet snow and percolation facies, and ended just west of Camp Century during the approach to the dry snow zone. Wide-band emission spectra collected during the flight have been processed and analyzed. Results show that the spectra are highly sensitive to the facies type with scattering from ice lenses being the dominant reason for low Tbs in the percolation zone. Inversion of Tb to physical temperature at depth was conducted on the measurements near Camp Century, achieving a -1.7K ten-meter error compared to borehole measurements. However, there is a relatively large uncertainty in the lower part possibly due to the large scattering near the surface. Wideband radiometry may also be applicable to sea ice and terrestrial snow thickness retrieval. Modeling studies suggest that the UWBRAD spectra reduce ambiguities inherent in other sea ice thickness retrievals by utilizing coherent wave interferences that appear in the Tb spectrum. When applied to a lossless medium such as terrestrial snow, this coherent oscillation turns out to be the single key signature that can be used to link back to snow thickness. In this paper, we report our forward modeling findings in support of instrument

Polynyas in a dynamic-thermodynamic sea-ice model

Directory of Open Access Journals (Sweden)

E. Ö. Ólason

2010-04-01

Full Text Available The representation of polynyas in viscous-plastic dynamic-thermodynamic sea-ice models is studied in a simplified test domain, in order to give recommendations about parametrisation choices. Bjornsson et al. (2001 validated their dynamic-thermodynamic model against a polynya flux model in a similar setup and we expand on that work here, testing more sea-ice rheologies and new-ice thickness formulations. The two additional rheologies tested give nearly identical results whereas the two new-ice thickness parametrisations tested give widely different results. Based on our results we argue for using the new-ice thickness parametrisation of Hibler (1979. We also implement a new parametrisation for the parameter h⁰ from Hibler's scheme, based on ideas from a collection depth parametrisation for flux polynya models.

Airborne geophysics for mesoscale observations of polar sea ice in a changing climate

Science.gov (United States)

Hendricks, S.; Haas, C.; Krumpen, T.; Eicken, H.; Mahoney, A. R.

2016-12-01

Sea ice thickness is an important geophysical parameter with a significant impact on various processes of the polar energy balance. It is classified as Essential Climate Variable (ECV), however the direct observations of the large ice-covered oceans are limited due to the harsh environmental conditions and logistical constraints. Sea-ice thickness retrieval by the means of satellite remote sensing is an active field of research, but current observational capabilities are not able to capture the small scale variability of sea ice thickness and its evolution in the presence of surface melt. We present an airborne observation system based on a towed electromagnetic induction sensor that delivers long range measurements of sea ice thickness for a wide range of sea ice conditions. The purpose-built sensor equipment can be utilized from helicopters and polar research aircraft in multi-role science missions. While airborne EM induction sounding is used in sea ice research for decades, the future challenge is the development of unmanned aerial vehicle (UAV) platform that meet the requirements for low-level EM sea ice surveys in terms of range and altitude of operations. The use of UAV's could enable repeated sea ice surveys during the the polar night, when manned operations are too dangerous and the observational data base is presently very sparse.

Spring snow conditions on Arctic sea ice north of Svalbard, during the Norwegian Young Sea ICE (N-ICE2015) expedition

Science.gov (United States)

Gallet, Jean-Charles; Merkouriadi, Ioanna; Liston, Glen E.; Polashenski, Chris; Hudson, Stephen; Rösel, Anja; Gerland, Sebastian

2017-10-01

Snow is crucial over sea ice due to its conflicting role in reflecting the incoming solar energy and reducing the heat transfer so that its temporal and spatial variability are important to estimate. During the Norwegian Young Sea ICE (N-ICE2015) campaign, snow physical properties and variability were examined, and results from April until mid-June 2015 are presented here. Overall, the snow thickness was about 20 cm higher than the climatology for second-year ice, with an average of 55 ± 27 cm and 32 ± 20 cm on first-year ice. The average density was 350-400 kg m-3 in spring, with higher values in June due to melting. Due to flooding in March, larger variability in snow water equivalent was observed. However, the snow structure was quite homogeneous in spring due to warmer weather and lower amount of storms passing over the field camp. The snow was mostly consisted of wind slab, faceted, and depth hoar type crystals with occasional fresh snow. These observations highlight the more dynamic character of evolution of snow properties over sea ice compared to previous observations, due to more variable sea ice and weather conditions in this area. The snowpack was isothermal as early as 10 June with the first onset of melt clearly identified in early June. Based on our observations, we estimate than snow could be accurately represented by a three to four layers modeling approach, in order to better consider the high variability of snow thickness and density together with the rapid metamorphose of the snow in springtime.

A modified discrete element model for sea ice dynamics

Institute of Scientific and Technical Information of China (English)

LI Baohui; LI Hai; LIU Yu; WANG Anliang; JI Shunying

2014-01-01

Considering the discontinuous characteristics of sea ice on various scales, a modified discrete element mod-el (DEM) for sea ice dynamics is developed based on the granular material rheology. In this modified DEM, a soft sea ice particle element is introduced as a self-adjustive particle size function. Each ice particle can be treated as an assembly of ice floes, with its concentration and thickness changing to variable sizes un-der the conservation of mass. In this model, the contact forces among ice particles are calculated using a viscous-elastic-plastic model, while the maximum shear forces are described with the Mohr-Coulomb fric-tion law. With this modified DEM, the ice flow dynamics is simulated under the drags of wind and current in a channel of various widths. The thicknesses, concentrations and velocities of ice particles are obtained, and then reasonable dynamic process is analyzed. The sea ice dynamic process is also simulated in a vortex wind field. Taking the influence of thermodynamics into account, this modified DEM will be improved in the future work.

Seeking an optimal algorithm for a new satellite-based Sea Ice Drift Climate Data Record : Motivations, plans and initial results from the ESA CCI Sea Ice project

DEFF Research Database (Denmark)

Lavergne, T.; Dybkjær, Gorm; Girard-Ardhuin, Fanny

The Sea Ice Essential Climate Variable (ECV) as defined by GCOS pertains of both sea ice concentration, thickness, and drift. Now in its second phase, the ESA CCI Sea Ice project is conducting the necessary research efforts to address sea ice drift.Accurate estimates of sea ice drift direction an...... in the final product. This contribution reviews the motivation for the work, the plans for sea ice drift algorithms intercomparison and selection, and early results from our activity....

Level-Ice Melt Ponds in the Los Alamos Sea Ice Model, CICE

Science.gov (United States)

2012-12-06

terms obtained using the Bitz and Lips- comb (1999) thermodynamic model. The thickness distribution ( Thorndike et al., 1975) employs 5 ice thickness...D.L., 2004. A model of melt pond evolution on sea ice. J. Geophys. Res. 109, C12007. http://dx.doi.org/10.1029/2004JC002361. Thorndike , A.S., Rothrock

On the nature of the sea ice albedo feedback in simple models

OpenAIRE

Moon, Woosok; Wettlaufer, John S.

2013-01-01

We examine the nature of the ice-albedo feedback in a long standing approach used in the dynamic-thermodynamic modeling of sea ice. The central issue examined is how the evolution of the ice area is treated when modeling a partial ice cover using a two-category-thickness scheme; thin sea ice and open water in one category and "thick" sea ice in the second. The problem with the scheme is that the area-evolution is handled in a manner that violates the basic rules of calculus, which leads to a ...

Thermodynamic and dynamic ice thickness contributions in the Canadian Arctic Archipelago in NEMO-LIM2 numerical simulations

Science.gov (United States)

Hu, Xianmin; Sun, Jingfan; Chan, Ting On; Myers, Paul G.

2018-04-01

Sea ice thickness evolution within the Canadian Arctic Archipelago (CAA) is of great interest to science, as well as local communities and their economy. In this study, based on the NEMO numerical framework including the LIM2 sea ice module, simulations at both 1/4 and 1/12° horizontal resolution were conducted from 2002 to 2016. The model captures well the general spatial distribution of ice thickness in the CAA region, with very thick sea ice (˜ 4 m and thicker) in the northern CAA, thick sea ice (2.5 to 3 m) in the west-central Parry Channel and M'Clintock Channel, and thin ( Program data at first-year landfast ice sites except at the northern sites with high concentration of old ice. At 1/4 to 1/12° scale, model resolution does not play a significant role in the sea ice simulation except to improve local dynamics because of better coastline representation. Sea ice growth is decomposed into thermodynamic and dynamic (including all non-thermodynamic processes in the model) contributions to study the ice thickness evolution. Relatively smaller thermodynamic contribution to ice growth between December and the following April is found in the thick and very thick ice regions, with larger contributions in the thin ice-covered region. No significant trend in winter maximum ice volume is found in the northern CAA and Baffin Bay while a decline (r2 ≈ 0.6, p < 0.01) is simulated in Parry Channel region. The two main contributors (thermodynamic growth and lateral transport) have high interannual variabilities which largely balance each other, so that maximum ice volume can vary interannually by ±12 % in the northern CAA, ±15 % in Parry Channel, and ±9 % in Baffin Bay. Further quantitative evaluation is required.

Arctic Sea Ice Trafficability - New Strategies for a Changing Icescape

Science.gov (United States)

Dammann, Dyre Oliver

Sea ice is an important part of the Arctic social-environmental system, in part because it provides a platform for human transportation and for marine flora and fauna that use the ice as a habitat. Sea ice loss projected for coming decades is expected to change ice conditions throughout the Arctic, but little is known about the nature and extent of anticipated changes and in particular potential implications for over-ice travel and ice use as a platform. This question has been addressed here through an extensive effort to link sea ice use and key geophysical properties of sea ice, drawing upon extensive field surveys around on-ice operations and local and Indigenous knowledge for the widely different ice uses and ice regimes of Utqiagvik, Kotzebue, and Nome, Alaska.. A set of nine parameters that constrain landfast sea ice use has been derived, including spatial extent, stability, and timing and persistence of landfast ice. This work lays the foundation for a framework to assess and monitor key ice-parameters relevant in the context of ice-use feasibility, safety, and efficiency, drawing on different remote-sensing techniques. The framework outlines the steps necessary to further evaluate relevant parameters in the context of user objectives and key stakeholder needs for a given ice regime and ice use scenario. I have utilized this framework in case studies for three different ice regimes, where I find uses to be constrained by ice thickness, roughness, and fracture potential and develop assessment strategies with accuracy at the relevant spatial scales. In response to the widely reported importance of high-confidence ice thickness measurements, I have developed a new strategy to estimate appropriate thickness compensation factors. Compensation factors have the potential to reduce risk of misrepresenting areas of thin ice when using point-based in-situ assessment methods along a particular route. This approach was tested on an ice road near Kotzebue, Alaska, where

Winter snow conditions on Arctic sea ice north of Svalbard during the Norwegian young sea ICE (N-ICE2015) expedition

Science.gov (United States)

Merkouriadi, Ioanna; Gallet, Jean-Charles; Graham, Robert M.; Liston, Glen E.; Polashenski, Chris; Rösel, Anja; Gerland, Sebastian

2017-10-01

Snow is a crucial component of the Arctic sea ice system. Its thickness and thermal properties control heat conduction and radiative fluxes across the ocean, ice, and atmosphere interfaces. Hence, observations of the evolution of snow depth, density, thermal conductivity, and stratigraphy are crucial for the development of detailed snow numerical models predicting energy transfer through the snow pack. Snow depth is also a major uncertainty in predicting ice thickness using remote sensing algorithms. Here we examine the winter spatial and temporal evolution of snow physical properties on first-year (FYI) and second-year ice (SYI) in the Atlantic sector of the Arctic Ocean, during the Norwegian young sea ICE (N-ICE2015) expedition (January to March 2015). During N-ICE2015, the snow pack consisted of faceted grains (47%), depth hoar (28%), and wind slab (13%), indicating very different snow stratigraphy compared to what was observed in the Pacific sector of the Arctic Ocean during the SHEBA campaign (1997-1998). Average snow bulk density was 345 kg m-3 and it varied with ice type. Snow depth was 41 ± 19 cm in January and 56 ± 17 cm in February, which is significantly greater than earlier suggestions for this region. The snow water equivalent was 14.5 ± 5.3 cm over first-year ice and 19 ± 5.4 cm over second-year ice.

The Role of Sea Ice in 2 x CO2 Climate Model Sensitivity. Part 2; Hemispheric Dependencies

Science.gov (United States)

Rind, D.; Healy, R.; Parkinson, C.; Martinson, D.

1997-01-01

How sensitive are doubled CO2 simulations to GCM control-run sea ice thickness and extent? This issue is examined in a series of 10 control-run simulations with different sea ice and corresponding doubled CO2 simulations. Results show that with increased control-run sea ice coverage in the Southern Hemisphere, temperature sensitivity with climate change is enhanced, while there is little effect on temperature sensitivity of (reasonable) variations in control-run sea ice thickness. In the Northern Hemisphere the situation is reversed: sea ice thickness is the key parameter, while (reasonable) variations in control-run sea ice coverage are of less importance. In both cases, the quantity of sea ice that can be removed in the warmer climate is the determining factor. Overall, the Southern Hemisphere sea ice coverage change had a larger impact on global temperature, because Northern Hemisphere sea ice was sufficiently thick to limit its response to doubled CO2, and sea ice changes generally occurred at higher latitudes, reducing the sea ice-albedo feedback. In both these experiments and earlier ones in which sea ice was not allowed to change, the model displayed a sensitivity of -0.02 C global warming per percent change in Southern Hemisphere sea ice coverage.

The future of ice sheets and sea ice: between reversible retreat and unstoppable loss.

Science.gov (United States)

Notz, Dirk

2009-12-08

We discuss the existence of cryospheric "tipping points" in the Earth's climate system. Such critical thresholds have been suggested to exist for the disappearance of Arctic sea ice and the retreat of ice sheets: Once these ice masses have shrunk below an anticipated critical extent, the ice-albedo feedback might lead to the irreversible and unstoppable loss of the remaining ice. We here give an overview of our current understanding of such threshold behavior. By using conceptual arguments, we review the recent findings that such a tipping point probably does not exist for the loss of Arctic summer sea ice. Hence, in a cooler climate, sea ice could recover rapidly from the loss it has experienced in recent years. In addition, we discuss why this recent rapid retreat of Arctic summer sea ice might largely be a consequence of a slow shift in ice-thickness distribution, which will lead to strongly increased year-to-year variability of the Arctic summer sea-ice extent. This variability will render seasonal forecasts of the Arctic summer sea-ice extent increasingly difficult. We also discuss why, in contrast to Arctic summer sea ice, a tipping point is more likely to exist for the loss of the Greenland ice sheet and the West Antarctic ice sheet.

Understanding the Importance of Oceanic Forcing on Sea Ice Variability

Science.gov (United States)

2010-12-01

problem, which includes ice thickness. Thorndike et al. (1975) recognized that many of the physical properties of sea ice depend upon its thickness...IMB2005B are presented below. In agreement with previous studies (e.g., Thorndike and Colony 1982), they show that during the winter months (December...During the Past 100 Years, 33, 2, 143– 154. 148 Thorndike , A.S., and R. Colony, 1982: Sea ice motion in response to geostrophic winds. Journal of

A Decade of High-Resolution Arctic Sea Ice Measurements from Airborne Altimetry

Science.gov (United States)

Duncan, K.; Farrell, S. L.; Connor, L. N.; Jackson, C.; Richter-Menge, J.

2017-12-01

Satellite altimeters carried on board ERS-1,-2, EnviSat, ICESat, CryoSat-2, AltiKa and Sentinel-3 have transformed our ability to map the thickness and volume of the polar sea ice cover, on seasonal and decadal time-scales. The era of polar satellite altimetry has coincided with a rapid decline of the Arctic ice cover, which has thinned, and transitioned from a predominantly multi-year to first-year ice cover. In conjunction with basin-scale satellite altimeter observations, airborne surveys of the Arctic Ocean at the end of winter are now routine. These surveys have been targeted to monitor regions of rapid change, and are designed to obtain the full snow and ice thickness distribution, across a range of ice types. Sensors routinely deployed as part of NASA's Operation IceBridge (OIB) campaigns include the Airborne Topographic Mapper (ATM) laser altimeter, the frequency-modulated continuous-wave snow radar, and the Digital Mapping System (DMS). Airborne measurements yield high-resolution data products and thus present a unique opportunity to assess the quality and characteristics of the satellite observations. We present a suite of sea ice data products that describe the snow depth and thickness of the Arctic ice cover during the last decade. Fields were derived from OIB measurements collected between 2009-2017, and from reprocessed data collected during ad-hoc sea ice campaigns prior to OIB. Our bespoke algorithms are designed to accommodate the heterogeneous sea ice surface topography, that varies at short spatial scales. We assess regional and inter-annual variability in the sea ice thickness distribution. Results are compared to satellite-derived ice thickness fields to highlight the sensitivities of satellite footprints to the tails of the thickness distribution. We also show changes in the dynamic forcing shaping the ice pack over the last eight years through an analysis of pressure-ridge sail-height distributions and surface roughness conditions

Winter Arctic sea ice growth: current variability and projections for the coming decades

Science.gov (United States)

Petty, A.; Boisvert, L.; Webster, M.; Holland, M. M.; Bailey, D. A.; Kurtz, N. T.; Markus, T.

2017-12-01

Arctic sea ice increases in both extent and thickness during the cold winter months ( October to May). Winter sea ice growth is an important factor controlling ocean ventilation and winter water/deep water formation, as well as determining the state and vulnerability of the sea ice pack before the melt season begins. Key questions for the Arctic community thus include: (i) what is the current magnitude and variability of winter Arctic sea ice growth and (ii) how might this change in a warming Arctic climate? To address (i), our current best guess of pan-Arctic sea ice thickness, and thus volume, comes from satellite altimetry observations, e.g. from ESA's CryoSat-2 satellite. A significant source of uncertainty in these data come from poor knowledge of the overlying snow depth. Here we present new estimates of winter sea ice thickness from CryoSat-2 using snow depths from a simple snow model forced by reanalyses and satellite-derived ice drift estimates, combined with snow depth estimates from NASA's Operation IceBridge. To address (ii), we use data from the Community Earth System Model's Large Ensemble Project, to explore sea ice volume and growth variability, and how this variability might change over the coming decades. We compare and contrast the model simulations to observations and the PIOMAS ice-ocean model (over recent years/decades). The combination of model and observational analysis provide novel insight into Arctic sea ice volume variability.

Sensitivity of open-water ice growth and ice concentration evolution in a coupled atmosphere-ocean-sea ice model

Science.gov (United States)

Shi, Xiaoxu; Lohmann, Gerrit

2017-09-01

A coupled atmosphere-ocean-sea ice model is applied to investigate to what degree the area-thickness distribution of new ice formed in open water affects the ice and ocean properties. Two sensitivity experiments are performed which modify the horizontal-to-vertical aspect ratio of open-water ice growth. The resulting changes in the Arctic sea-ice concentration strongly affect the surface albedo, the ocean heat release to the atmosphere, and the sea-ice production. The changes are further amplified through a positive feedback mechanism among the Arctic sea ice, the Atlantic Meridional Overturning Circulation (AMOC), and the surface air temperature in the Arctic, as the Fram Strait sea ice import influences the freshwater budget in the North Atlantic Ocean. Anomalies in sea-ice transport lead to changes in sea surface properties of the North Atlantic and the strength of AMOC. For the Southern Ocean, the most pronounced change is a warming along the Antarctic Circumpolar Current (ACC), owing to the interhemispheric bipolar seasaw linked to AMOC weakening. Another insight of this study lies on the improvement of our climate model. The ocean component FESOM is a newly developed ocean-sea ice model with an unstructured mesh and multi-resolution. We find that the subpolar sea-ice boundary in the Northern Hemisphere can be improved by tuning the process of open-water ice growth, which strongly influences the sea ice concentration in the marginal ice zone, the North Atlantic circulation, salinity and Arctic sea ice volume. Since the distribution of new ice on open water relies on many uncertain parameters and the knowledge of the detailed processes is currently too crude, it is a challenge to implement the processes realistically into models. Based on our sensitivity experiments, we conclude a pronounced uncertainty related to open-water sea ice growth which could significantly affect the climate system sensitivity.

ICESat-2, its retrievals of ice sheet elevation change and sea ice freeboard, and potential synergies with CryoSat-2

Science.gov (United States)

Neumann, Thomas; Markus, Thorsten; Smith, Benjamin; Kwok, Ron

2017-04-01

Understanding the causes and magnitudes of changes in the cryosphere remains a priority for Earth science research. Over the past decade, NASA's and ESA's Earth-observing satellites have documented a decrease in both the areal extent and thickness of Arctic sea ice, and an ongoing loss of grounded ice from the Greenland and Antarctic ice sheets. Understanding the pace and mechanisms of these changes requires long-term observations of ice-sheet mass, sea-ice thickness, and sea-ice extent. NASA's ICESat-2 mission is the next-generation space-borne laser altimeter mission and will use three pairs of beams, each pair separated by about 3 km across-track with a pair spacing of 90 m. The spot size is 17 m with an along-track sampling interval of 0.7 m. This measurement concept is a result of the lessons learned from the original ICESat mission. The multi-beam approach is critical for removing the effects of ice sheet surface slope from the elevation change measurements of most interest. For sea ice, the dense spatial sampling (eliminating along-track gaps) and the small footprint size are especially useful for sea surface height measurements in the, often narrow, leads needed for sea ice freeboard and ice thickness retrievals. Currently, algorithms are being developed to calculate ice sheet elevation change and sea ice freeboard from ICESat-2 data. The orbits of ICESat-2 and Cryosat-2 both converge at 88 degrees of latitude, though the orbit altitude differences result in different ground track patterns between the two missions. This presentation will present an overview of algorithm approaches and how ICESat-2 and Cryosat-2 data may augment each other.

Simulation and Domain Identification of Sea Ice Thermodynamic System

Directory of Open Access Journals (Sweden)

Bing Tan

2012-01-01

Full Text Available Based on the measured data and characteristics of sea ice temperature distribution in space and time, this study is intended to consider a parabolic partial differential equation of the thermodynamic field of sea ice (coupled by snow, ice, and sea water layers with a time-dependent domain and its parameter identification problem. An optimal model with state constraints is presented with the thicknesses of snow and sea ice as parametric variables and the deviation between the calculated and measured sea ice temperatures as the performance criterion. The unique existence of the weak solution of the thermodynamic system is proved. The properties of the identification problem and the existence of the optimal parameter are discussed, and the one-order necessary condition is derived. Finally, based on the nonoverlapping domain decomposition method and semi-implicit difference scheme, an optimization algorithm is proposed for the numerical simulation. Results show that the simulated temperature of sea ice fit well with the measured data, and the better fit is corresponding to the deeper sea ice.

On the nature of the sea ice albedo feedback in simple models.

Science.gov (United States)

Moon, W; Wettlaufer, J S

2014-08-01

We examine the nature of the ice-albedo feedback in a long-standing approach used in the dynamic-thermodynamic modeling of sea ice. The central issue examined is how the evolution of the ice area is treated when modeling a partial ice cover using a two-category-thickness scheme; thin sea ice and open water in one category and "thick" sea ice in the second. The problem with the scheme is that the area evolution is handled in a manner that violates the basic rules of calculus, which leads to a neglected area evolution term that is equivalent to neglecting a leading-order latent heat flux. We demonstrate the consequences by constructing energy balance models with a fractional ice cover and studying them under the influence of increased radiative forcing. It is shown that the neglected flux is particularly important in a decaying ice cover approaching the transitions to seasonal or ice-free conditions. Clearly, a mishandling of the evolution of the ice area has leading-order effects on the ice-albedo feedback. Accordingly, it may be of considerable importance to reexamine the relevant climate model schemes and to begin the process of converting them to fully resolve the sea ice thickness distribution in a manner such as remapping, which does not in principle suffer from the pathology we describe.

A one stop website for sharing sea ice, ocean and ice sheet data over the polar regions

Science.gov (United States)

Chen, Z.; Cheng, X.; Liu, J.; Hui, F.; Ding, Y.

2017-12-01

The polar regions, including the Arctic and Antarctic, are changing rapidly. Our capabilities to remotely monitor the state of the polar regions are increasing greatly. Satellite and airborne technologies have been deployed and further improvements are underway. Meanwhile, various algorithms have been developed to retrieve important parameters to maximize the effectiveness of available remote sensing data. These technologies and algorithms promise to greatly increase our understanding of variations in sea ice, ocean and ice sheet. However, so much information is scattered out there. It is challenging to find exactly what you are looking for by just searching it through the network. Therefore, we try to establish a common platform to sharing some key parameters for the polar regions. A group of scientists from Beijing Normal University and University at Albany developed a website as a "one-stop shop" for the current state of the polar regions. The website provides real-time (or near real-time) key parameters derived from a variety of operational satellites in an understandable, accessible and credible way. Three types of parameter, which are sea ice, ocean and ice sheet respectively, are shown and available to be downloaded in the website. Several individual parameters are contained in a specific type of parameter. The parameters of sea ice include sea ice concentration, sea ice thickness, melt pond, sea ice leads and sea ice drift. The ocean parameters contain sea surface temperature and sea surface wind. Ice sheet balance, ice velocity and some other parameters are classified into the type of ice sheet parameter. Some parameters are well-calibrated and available to be obtained from other websites, such as sea ice concentration, sea ice thickness sea surface temperature. Since these parameters are retrieved from different sensors, such as SSMI, AMSR2 etc., data format, spatial resolution of the parameters are not unified. We collected and reprocessed these

Seasonal sea ice predictions for the Arctic based on assimilation of remotely sensed observations

Science.gov (United States)

Kauker, F.; Kaminski, T.; Ricker, R.; Toudal-Pedersen, L.; Dybkjaer, G.; Melsheimer, C.; Eastwood, S.; Sumata, H.; Karcher, M.; Gerdes, R.

2015-10-01

The recent thinning and shrinking of the Arctic sea ice cover has increased the interest in seasonal sea ice forecasts. Typical tools for such forecasts are numerical models of the coupled ocean sea ice system such as the North Atlantic/Arctic Ocean Sea Ice Model (NAOSIM). The model uses as input the initial state of the system and the atmospheric boundary condition over the forecasting period. This study investigates the potential of remotely sensed ice thickness observations in constraining the initial model state. For this purpose it employs a variational assimilation system around NAOSIM and the Alfred Wegener Institute's CryoSat-2 ice thickness product in conjunction with the University of Bremen's snow depth product and the OSI SAF ice concentration and sea surface temperature products. We investigate the skill of predictions of the summer ice conditions starting in March for three different years. Straightforward assimilation of the above combination of data streams results in slight improvements over some regions (especially in the Beaufort Sea) but degrades the over-all fit to independent observations. A considerable enhancement of forecast skill is demonstrated for a bias correction scheme for the CryoSat-2 ice thickness product that uses a spatially varying scaling factor.

CICE, The Los Alamos Sea Ice Model

Energy Technology Data Exchange (ETDEWEB)

2017-05-12

The Los Alamos sea ice model (CICE) is the result of an effort to develop a computationally efficient sea ice component for a fully coupled atmosphere–land–ocean–ice global climate model. It was originally designed to be compatible with the Parallel Ocean Program (POP), an ocean circulation model developed at Los Alamos National Laboratory for use on massively parallel computers. CICE has several interacting components: a vertical thermodynamic model that computes local growth rates of snow and ice due to vertical conductive, radiative and turbulent fluxes, along with snowfall; an elastic-viscous-plastic model of ice dynamics, which predicts the velocity field of the ice pack based on a model of the material strength of the ice; an incremental remapping transport model that describes horizontal advection of the areal concentration, ice and snow volume and other state variables; and a ridging parameterization that transfers ice among thickness categories based on energetic balances and rates of strain. It also includes a biogeochemical model that describes evolution of the ice ecosystem. The CICE sea ice model is used for climate research as one component of complex global earth system models that include atmosphere, land, ocean and biogeochemistry components. It is also used for operational sea ice forecasting in the polar regions and in numerical weather prediction models.

The color of melt ponds on Arctic sea ice

Science.gov (United States)

Lu, Peng; Leppäranta, Matti; Cheng, Bin; Li, Zhijun; Istomina, Larysa; Heygster, Georg

2018-04-01

Pond color, which creates the visual appearance of melt ponds on Arctic sea ice in summer, is quantitatively investigated using a two-stream radiative transfer model for ponded sea ice. The upwelling irradiance from the pond surface is determined and then its spectrum is transformed into RGB (red, green, blue) color space using a colorimetric method. The dependence of pond color on various factors such as water and ice properties and incident solar radiation is investigated. The results reveal that increasing underlying ice thickness Hi enhances both the green and blue intensities of pond color, whereas the red intensity is mostly sensitive to Hi for thin ice (Hi 1.5 m), similar to the behavior of melt-pond albedo. The distribution of the incident solar spectrum F0 with wavelength affects the pond color rather than its intensity. The pond color changes from dark blue to brighter blue with increasing scattering in ice, and the influence of absorption in ice on pond color is limited. The pond color reproduced by the model agrees with field observations for Arctic sea ice in summer, which supports the validity of this study. More importantly, the pond color has been confirmed to contain information about meltwater and underlying ice, and therefore it can be used as an index to retrieve Hi and Hp. Retrievals of Hi for thin ice (Hi measurements than retrievals for thick ice, but those of Hp are not good. The analysis of pond color is a new potential method to obtain thin ice thickness in summer, although more validation data and improvements to the radiative transfer model will be needed in future.

The implementation of sea ice model on a regional high-resolution scale

Science.gov (United States)

Prasad, Siva; Zakharov, Igor; Bobby, Pradeep; McGuire, Peter

2015-09-01

The availability of high-resolution atmospheric/ocean forecast models, satellite data and access to high-performance computing clusters have provided capability to build high-resolution models for regional ice condition simulation. The paper describes the implementation of the Los Alamos sea ice model (CICE) on a regional scale at high resolution. The advantage of the model is its ability to include oceanographic parameters (e.g., currents) to provide accurate results. The sea ice simulation was performed over Baffin Bay and the Labrador Sea to retrieve important parameters such as ice concentration, thickness, ridging, and drift. Two different forcing models, one with low resolution and another with a high resolution, were used for the estimation of sensitivity of model results. Sea ice behavior over 7 years was simulated to analyze ice formation, melting, and conditions in the region. Validation was based on comparing model results with remote sensing data. The simulated ice concentration correlated well with Advanced Microwave Scanning Radiometer for EOS (AMSR-E) and Ocean and Sea Ice Satellite Application Facility (OSI-SAF) data. Visual comparison of ice thickness trends estimated from the Soil Moisture and Ocean Salinity satellite (SMOS) agreed with the simulation for year 2010-2011.

Reducing uncertainty in high-resolution sea ice models.

Energy Technology Data Exchange (ETDEWEB)

Peterson, Kara J.; Bochev, Pavel Blagoveston

2013-07-01

Arctic sea ice is an important component of the global climate system, reflecting a significant amount of solar radiation, insulating the ocean from the atmosphere and influencing ocean circulation by modifying the salinity of the upper ocean. The thickness and extent of Arctic sea ice have shown a significant decline in recent decades with implications for global climate as well as regional geopolitics. Increasing interest in exploration as well as climate feedback effects make predictive mathematical modeling of sea ice a task of tremendous practical import. Satellite data obtained over the last few decades have provided a wealth of information on sea ice motion and deformation. The data clearly show that ice deformation is focused along narrow linear features and this type of deformation is not well-represented in existing models. To improve sea ice dynamics we have incorporated an anisotropic rheology into the Los Alamos National Laboratory global sea ice model, CICE. Sensitivity analyses were performed using the Design Analysis Kit for Optimization and Terascale Applications (DAKOTA) to determine the impact of material parameters on sea ice response functions. Two material strength parameters that exhibited the most significant impact on responses were further analyzed to evaluate their influence on quantitative comparisons between model output and data. The sensitivity analysis along with ten year model runs indicate that while the anisotropic rheology provides some benefit in velocity predictions, additional improvements are required to make this material model a viable alternative for global sea ice simulations.

On the influence of model physics on simulations of Arctic and Antarctic sea ice

Directory of Open Access Journals (Sweden)

F. Massonnet

2011-09-01

Full Text Available Two hindcast (1983–2007 simulations are performed with the global, ocean-sea ice models NEMO-LIM2 and NEMO-LIM3 driven by atmospheric reanalyses and climatologies. The two simulations differ only in their sea ice component, while all other elements of experimental design (resolution, initial conditions, atmospheric forcing are kept identical. The main differences in the sea ice models lie in the formulation of the subgrid-scale ice thickness distribution, of the thermodynamic processes, of the sea ice salinity and of the sea ice rheology. To assess the differences in model skill over the period of investigation, we develop a set of metrics for both hemispheres, comparing the main sea ice variables (concentration, thickness and drift to available observations and focusing on both mean state and seasonal to interannual variability. Based upon these metrics, we discuss the physical processes potentially responsible for the differences in model skill. In particular, we suggest that (i a detailed representation of the ice thickness distribution increases the seasonal to interannual variability of ice extent, with spectacular improvement for the simulation of the recent observed summer Arctic sea ice retreats, (ii the elastic-viscous-plastic rheology enhances the response of ice to wind stress, compared to the classical viscous-plastic approach, (iii the grid formulation and the air-sea ice drag coefficient affect the simulated ice export through Fram Strait and the ice accumulation along the Canadian Archipelago, and (iv both models show less skill in the Southern Ocean, probably due to the low quality of the reanalyses in this region and to the absence of important small-scale oceanic processes at the models' resolution (~1°.

SPH Modelling of Sea-ice Pack Dynamics

Science.gov (United States)

Staroszczyk, Ryszard

2017-12-01

The paper is concerned with the problem of sea-ice pack motion and deformation under the action of wind and water currents. Differential equations describing the dynamics of ice, with its very distinct mateFfigrial responses in converging and diverging flows, express the mass and linear momentum balances on the horizontal plane (the free surface of the ocean). These equations are solved by the fully Lagrangian method of smoothed particle hydrodynamics (SPH). Assuming that the ice behaviour can be approximated by a non-linearly viscous rheology, the proposed SPH model has been used to simulate the evolution of a sea-ice pack driven by wind drag stresses. The results of numerical simulations illustrate the evolution of an ice pack, including variations in ice thickness and ice area fraction in space and time. The effects of different initial ice pack configurations and of different conditions assumed at the coast-ice interface are examined. In particular, the SPH model is applied to a pack flow driven by a vortex wind to demonstrate how well the Lagrangian formulation can capture large deformations and displacements of sea ice.

Arctic sea ice trends, variability and implications for seasonal ice forecasting.

Science.gov (United States)

Serreze, Mark C; Stroeve, Julienne

2015-07-13

September Arctic sea ice extent over the period of satellite observations has a strong downward trend, accompanied by pronounced interannual variability with a detrended 1 year lag autocorrelation of essentially zero. We argue that through a combination of thinning and associated processes related to a warming climate (a stronger albedo feedback, a longer melt season, the lack of especially cold winters) the downward trend itself is steepening. The lack of autocorrelation manifests both the inherent large variability in summer atmospheric circulation patterns and that oceanic heat loss in winter acts as a negative (stabilizing) feedback, albeit insufficient to counter the steepening trend. These findings have implications for seasonal ice forecasting. In particular, while advances in observing sea ice thickness and assimilating thickness into coupled forecast systems have improved forecast skill, there remains an inherent limit to predictability owing to the largely chaotic nature of atmospheric variability. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Trends in Arctic Sea Ice Volume 2010-2013 from CryoSat-2

Science.gov (United States)

Tilling, R.; Ridout, A.; Wingham, D.; Shepherd, A.; Haas, C.; Farrell, S. L.; Schweiger, A. J.; Zhang, J.; Giles, K.; Laxon, S.

2013-12-01

Satellite records show a decline in Arctic sea ice extent over the past three decades with a record minimum in September 2012, and results from the Pan-Arctic Ice-Ocean Modelling and Assimilation System (PIOMAS) suggest that this has been accompanied by a reduction in volume. We use three years of measurements recorded by the European Space Agency CryoSat-2 (CS-2) mission, validated with in situ data, to generate estimates of seasonal variations and inter-annual trends in Arctic sea ice volume between 2010 and 2013. The CS-2 estimates of sea ice thickness agree with in situ estimates derived from upward looking sonar measurements of ice draught and airborne measurements of ice thickness and freeboard to within 0.1 metres. Prior to the record minimum in summer 2012, autumn and winter Arctic sea ice volume had fallen by ~1300 km3 relative to the previous year. Using the full 3-year period of CS-2 observations, we estimate that winter Arctic sea ice volume has decreased by ~700 km3/yr since 2010, approximately twice the average rate since 1980 as predicted by the PIOMAS.

Regional Changes in the Sea Ice Cover and Ice Production in the Antarctic

Science.gov (United States)

Comiso, Josefino C.

2011-01-01

Coastal polynyas around the Antarctic continent have been regarded as sea ice factories because of high ice production rates in these regions. The observation of a positive trend in the extent of Antarctic sea ice during the satellite era has been intriguing in light of the observed rapid decline of the ice extent in the Arctic. The results of analysis of the time series of passive microwave data indicate large regional variability with the trends being strongly positive in the Ross Sea, strongly negative in the Bellingshausen/Amundsen Seas and close to zero in the other regions. The atmospheric circulation in the Antarctic is controlled mainly by the Southern Annular Mode (SAM) and the marginal ice zone around the continent shows an alternating pattern of advance and retreat suggesting the presence of a propagating wave (called Antarctic Circumpolar Wave) around the circumpolar region. The results of analysis of the passive microwave data suggest that the positive trend in the Antarctic sea ice cover could be caused primarily by enhanced ice production in the Ross Sea that may be associated with more persistent and larger coastal polynyas in the region. Over the Ross Sea shelf, analysis of sea ice drift data from 1992 to 2008 yields a positive rate-of-increase in the net ice export of about 30,000 km2 per year. For a characteristic ice thickness of 0.6 m, this yields a volume transport of about 20 km3/year, which is almost identical, within error bars, to our estimate of the trend in ice production. In addition to the possibility of changes in SAM, modeling studies have also indicated that the ozone hole may have a role in that it causes the deepening of the lows in the western Antarctic region thereby causing strong winds to occur offthe Ross-ice shelf.

Exploring the utility of quantitative network design in evaluating Arctic sea ice thickness sampling strategies

OpenAIRE

Kaminski, T.; Kauker, F.; Eicken, H.; Karcher, M.

2015-01-01

We present a quantitative network design (QND) study of the Arctic sea ice-ocean system using a software tool that can evaluate hypothetical observational networks in a variational data assimilation system. For a demonstration, we evaluate two idealised flight transects derived from NASA's Operation IceBridge airborne ice surveys in terms of their potential to improve ten-day to five-month sea-ice forecasts. As target regions for the forecasts we select the Chukchi Sea, a...

Autonomous Ice Mass Balance Buoys for Seasonal Sea Ice

Science.gov (United States)

Whitlock, J. D.; Planck, C.; Perovich, D. K.; Parno, J. T.; Elder, B. C.; Richter-Menge, J.; Polashenski, C. M.

2017-12-01

The ice mass-balance represents the integration of all surface and ocean heat fluxes and attributing the impact of these forcing fluxes on the ice cover can be accomplished by increasing temporal and spatial measurements. Mass balance information can be used to understand the ongoing changes in the Arctic sea ice cover and to improve predictions of future ice conditions. Thinner seasonal ice in the Arctic necessitates the deployment of Autonomous Ice Mass Balance buoys (IMB's) capable of long-term, in situ data collection in both ice and open ocean. Seasonal IMB's (SIMB's) are free floating IMB's that allow data collection in thick ice, thin ice, during times of transition, and even open water. The newest generation of SIMB aims to increase the number of reliable IMB's in the Arctic by leveraging inexpensive commercial-grade instrumentation when combined with specially developed monitoring hardware. Monitoring tasks are handled by a custom, expandable data logger that provides low-cost flexibility for integrating a large range of instrumentation. The SIMB features ultrasonic sensors for direct measurement of both snow depth and ice thickness and a digital temperature chain (DTC) for temperature measurements every 2cm through both snow and ice. Air temperature and pressure, along with GPS data complete the Arctic picture. Additionally, the new SIMB is more compact to maximize deployment opportunities from multiple types of platforms.

Sea ice draft in the Weddell Sea, measured by upward looking sonars

Directory of Open Access Journals (Sweden)

A. Behrendt

2013-06-01

Full Text Available The presented database contains time-referenced sea ice draft values from upward looking sonar (ULS measurements in the Weddell Sea, Antarctica. The sea ice draft data can be used to infer the thickness of the ice. They were collected during the period 1990–2008. In total, the database includes measurements from 13 locations in the Weddell Sea and was generated from more than 3.7 million measurements of sea ice draft. The files contain uncorrected raw drafts, corrected drafts and the basic parameters measured by the ULS. The measurement principle, the data processing procedure and the quality control are described in detail. To account for the unknown speed of sound in the water column above the ULS, two correction methods were applied to the draft data. The first method is based on defining a reference level from the identification of open water leads. The second method uses a model of sound speed in the oceanic mixed layer and is applied to ice draft in austral winter. Both methods are discussed and their accuracy is estimated. Finally, selected results of the processing are presented. The data can be downloaded from doi:10.1594/PANGAEA.785565.

On retrieving sea ice freeboard from ICESat laser altimeter

Directory of Open Access Journals (Sweden)

K. Khvorostovsky

2016-10-01

Full Text Available Sea ice freeboard derived from satellite altimetry is the basis for the estimation of sea ice thickness using the assumption of hydrostatic equilibrium. High accuracy of altimeter measurements and freeboard retrieval procedure are, therefore, required. As of today, two approaches for estimating the freeboard using laser altimeter measurements from Ice, Cloud, and land Elevation Satellite (ICESat, referred to as tie points (TP and lowest-level elevation (LLE methods, have been developed and applied in different studies. We reproduced these methods for the ICESat observation periods (2003–2008 in order to assess and analyse the sources of differences found in the retrieved freeboard and corresponding thickness estimates of the Arctic sea ice as produced by the Jet Propulsion Laboratory (JPL and Goddard Space Flight Center (GSFC. Three main factors are found to affect the freeboard differences when applying these methods: (a the approach used for calculation of the local sea surface references in leads (TP or LLE methods, (b the along-track averaging scales used for this calculation, and (c the corrections for lead width relative to the ICESat footprint and for snow depth accumulated in refrozen leads. The LLE method with 100 km averaging scale, as used to produce the GSFC data set, and the LLE method with a shorter averaging scale of 25 km both give larger freeboard estimates comparing to those derived by applying the TP method with 25 km averaging scale as used for the JPL product. Two factors, (a and (b, contribute to the freeboard differences in approximately equal proportions, and their combined effect is, on average, about 6–7 cm. The effect of using different methods varies spatially: the LLE method tends to give lower freeboards (by up to 15 cm over the thick multiyear ice and higher freeboards (by up to 10 cm over first-year ice and the thin part of multiyear ice; the higher freeboards dominate. We show that the

Observations of sea-ice conditions in the Antarctic coastal region using ship-board video cameras

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Haruhito Shimoda

1997-03-01

Full Text Available During the 30th, 31st, and 32nd Japanese Antarctic Research Expeditions (JARE-30,JARE-31,and JARE-32, sea-ice conditions were recorded by video camera on board the SHIRASE. Then, the sea-ice images were used to estimate compactness and thickness quantitatively. Analyzed legs are those toward Breid Bay and from Breid Bay to Syowa Station during JARE-30 and JARE-31,and those toward the Prince Olav Coast, from the Prince Olav Coast to Breid Bay, and from Breid Bay to Syowa Station during JARE-32. The results show yearly variations of ice compactness and thickness, latitudinal variations of thickness, and differences in thickness histograms between JARE-30 and JARE-32 in Lutzow-Holm Bay. Albedo values were measured simultaneously by a shortwave radiometer. These values are proportional to those of ice compactness. Finally, we examined the relationship between ice compactness and vertical gradient of air temperature above sea ice.

Large sea ice outflow into the Nares Strait in 2007

DEFF Research Database (Denmark)

Kwok, R.; Pedersen, L.T.; Gudmandsen, Preben

2010-01-01

Sea ice flux through the Nares Strait is most active during the fall and early winter, ceases in mid- to late winter after the formation of ice arches along the strait, and re-commences after breakup in summer. In 2007, ice arches failed to form. This resulted in the highest outflow of Arctic sea...... at Fram Strait. Clearly, the ice arches control Arctic sea ice outflow. The duration of unobstructed flow explains more than 84% of the variance in the annual area flux. In our record, seasonal stoppages are always associated with the formation of an arch near the same location in the southern Kane Basin...... ice in the 13-year record between 1997 and 2009. The 2007 area and volume outflows of 87 x 10(3) km(2) and 254 km(3) are more than twice their 13-year means. This contributes to the recent loss of the thick, multiyear Arctic sea ice and represents similar to 10% of our estimates of the mean ice export...

Early Winter Sea Ice Dynamics in the Ross Sea from In Situ and Satellite Observations

Science.gov (United States)

Maksym, T.; Ackley, S. F.; Stammerjohn, S. E.; Tison, J. L.; Hoeppner, K.

2017-12-01

The Ross Sea sea ice cover is one of the few regions of the cryosphere that have been expanding in recent decades. However, 2017 saw a significantly delayed autumn ice advance and record low early winter sea ice extent. Understanding the causes and impacts of this variability has been hampered by a lack of in situ observations. A winter cruise into the Ross Sea in April-June 2017 provided some of the only in situ winter observations of sea ice processes in this region in almost 20 years. We present a first look at data from arrays of drifting buoys deployed in the ice pack and outflow from these polynyas, supplemented by a suite of high-resolution synthetic aperture radar (SAR) data. Additional observations included high-resolution sonar imagery of ice deformation features from an autonomous underwater vehicle, shipboard visual observations of sea ice properties, and in situ measurements of snow and thickness and structural properties. These data show that the delay in ice advance led to a thin, highly dynamic sea ice pack, with substantial ice production and export from the Ross Ice Shelf and Terra Nova Bay polynyas. Despite these high rates of ice production, the pack ice remained thin due to rapid export and northward drift. Compared to the only prior winter observations made in 1995 and 1998, the ice was thinner, with less ridging and snow cover, reflecting a younger ice cover. Granular ice was less prevalent than in these prior cruises, particularly in the outer pack, likely due to less snow ice formation and less pancake ice formation at the advancing ice edge. Despite rapid basal ice growth, the buoy data suggest that deformation may be the dominant mechanism for sea ice thickening in the pack once an initial ice cover forms.

Dynamic and thermodynamic impacts of the winter Arctic Oscillation on summer sea ice extent.

Science.gov (United States)

Park, H. S.; Stewart, A.

2017-12-01

Arctic summer sea ice extent exhibits substantial interannual variability, as is highlighted by the remarkable recovery in sea ice extent in 2013 following the record minimum in the summer of 2012. Here, we explore the mechanism via which Arctic Oscillation (AO)-induced ice thickness changes impact summer sea ice, using observations and reanalysis data. A positive AO weakens the basin-scale anticyclonic sea ice drift and decreases the winter ice thickness by 15cm and 10cm in the Eurasian and the Pacific sectors of the Arctic respectively. Three reanalysis datasets show that the (upward) surface heat fluxes are reduced over wide areas of the Arctic, suppressing the ice growth during the positive AO winters. The winter dynamic and thermodynamic thinning preconditions the ice for enhanced radiative forcing via the ice-albedo feedback in late spring-summer, leading to an additional 8-10 cm of thinning over the Pacific sector of the Arctic. Because of these winter AO-induced dynamic and thermodynamics effects, the winter AO explains about 22% (r = -0.48) of the interannual variance of September sea ice extent from year 1980 to 2015.

MIZMAS: Modeling the Evolution of Ice Thickness and Floe Size Distributions in the Marginal Ice Zone of the Chukchi and Beaufort Seas

Science.gov (United States)

2015-09-30

ITD theory of Thorndike et al. (1975) in order to explicitly simulate the evolution of FSD and ITD jointly. The FSD theory includes a FSD function and...et al., 2015). 4 RESULTS Modeling: A FSD theory is developed and coupled to the ITD theory of Thorndike et al. (1975) in order to... Thorndike , A.S., D.A. Rothrock, G.A. Maykut, and R. Colony (1975), The thickness distribution of sea ice. J. Geophys. Res., 80, 4501–4513. Zhang

Multiphase Reactive Transport and Platelet Ice Accretion in the Sea Ice of McMurdo Sound, Antarctica

Science.gov (United States)

Buffo, J. J.; Schmidt, B. E.; Huber, C.

2018-01-01

Sea ice seasonally to interannually forms a thermal, chemical, and physical boundary between the atmosphere and hydrosphere over tens of millions of square kilometers of ocean. Its presence affects both local and global climate and ocean dynamics, ice shelf processes, and biological communities. Accurate incorporation of sea ice growth and decay, and its associated thermal and physiochemical processes, is underrepresented in large-scale models due to the complex physics that dictate oceanic ice formation and evolution. Two phenomena complicate sea ice simulation, particularly in the Antarctic: the multiphase physics of reactive transport brought about by the inhomogeneous solidification of seawater, and the buoyancy driven accretion of platelet ice formed by supercooled ice shelf water onto the basal surface of the overlying ice. Here a one-dimensional finite difference model capable of simulating both processes is developed and tested against ice core data. Temperature, salinity, liquid fraction, fluid velocity, total salt content, and ice structure are computed during model runs. The model results agree well with empirical observations and simulations highlight the effect platelet ice accretion has on overall ice thickness and characteristics. Results from sensitivity studies emphasize the need to further constrain sea ice microstructure and the associated physics, particularly permeability-porosity relationships, if a complete model of sea ice evolution is to be obtained. Additionally, implications for terrestrial ice shelves and icy moons in the solar system are discussed.

Sea-level and solid-Earth deformation feedbacks in ice sheet modelling

Science.gov (United States)

Konrad, Hannes; Sasgen, Ingo; Klemann, Volker; Thoma, Malte; Grosfeld, Klaus; Martinec, Zdeněk

2014-05-01

The interactions of ice sheets with the sea level and the solid Earth are important factors for the stability of the ice shelves and the tributary inland ice (e.g. Thomas and Bentley, 1978; Gomez et al, 2012). First, changes in ice extent and ice thickness induce viscoelastic deformation of the Earth surface and Earth's gravity field. In turn, global and local changes in sea level and bathymetry affect the grounding line and, subsequently, alter the ice dynamic behaviour. Here, we investigate these feedbacks for a synthetic ice sheet configuration as well as for the Antarctic ice sheet using a three-dimensional thermomechanical ice sheet and shelf model, coupled to a viscoelastic solid-Earth and gravitationally self-consistent sea-level model. The respective ice sheet undergoes a forcing from rising sea level, warming ocean, and/or changing surface mass balance. The coupling is realized by exchanging ice thickness, Earth surface deformation and sea level periodically. We apply several sets of viscoelastic Earth parameters to our coupled model, e.g. simulating a low-viscous upper mantle present at the Antarctic Peninsula (Ivins et al., 2011). Special focus of our study lies on the evolution of Earth surface deformation and local sea level changes, as well as on the accompanying grounding line evolution. N. Gomez, D. Pollard, J. X. Mitrovica, P. Huybers, and P. U. Clark 2012. Evolution of a coupled marine ice sheet-sea level model, J. Geophys. Res., 117, F01013, doi:10.1029/2011JF002128. E. R. Ivins, M. M. Watkins, D.-N. Yuan, R. Dietrich, G. Casassa, and A. Rülke 2011. On-land ice loss and glacial isostatic adjustment at the Drake Passage: 2003-2009, J. Geophys. Res. 116, B02403, doi: 10.1029/2010JB007607 R. H. Thomas and C. R. Bentley 1978. A model for Holocene retreat of the West Antarctic Ice Sheet, Quaternary Research, 10 (2), pages 150-170, doi: 10.1016/0033-5894(78)90098-4.

First spaceborne phase altimetry over sea ice using TechDemoSat-1 GNSS-R signals

Science.gov (United States)

Li, Weiqiang; Cardellach, Estel; Fabra, Fran; Rius, Antonio; Ribó, Serni; Martín-Neira, Manuel

2017-08-01

A track of sea ice reflected Global Navigation Satellite System (GNSS) signal collected by the TechDemoSat-1 mission is processed to perform phase altimetry over sea ice. High-precision carrier phase measurements are extracted from coherent GNSS reflections at a high angle of elevation (>57°). The altimetric results show good consistency with a mean sea surface (MSS) model, and the root-mean-square difference is 4.7 cm with an along-track sampling distance of ˜140 m and a spatial resolution of ˜400 m. The difference observed between the altimetric results and the MSS shows good correlation with the colocated sea ice thickness data from Soil Moisture and Ocean Salinity. This is consistent with the reflecting surface aligned with the bottom of the ice-water interface, due to the penetration of the GNSS signal into the sea ice. Therefore, these high-precision altimetric results have potential to be used for determination of sea ice thickness.

A comparative analysis of the sea ice freeboard from CryoSat. CryoVEx and IceBridge

DEFF Research Database (Denmark)

Kildegaard Rose, Stine; Connor, Laurence N.; Farrell, Sinead L.

The CryoSat Validation Experiment (CryoVEx) has been conducted by ESA, to examine the uncertainties in the satellite measurement of e.g. sea ice thickness. In this study, we aim to estimate the sea ice freeboard from CryoSat-2, and compare it with the high-resolution Airborne Laser Scanner (ALS......) measurements collected along CryoSat-2 ground tracks from the CryoVEx 2012 campaign, together with NASA’s Operation IceBridge data. We will use the CryoSat SAR data level 1b (L1b) to discriminate the leads and from this, estimate the sea ice freeboard. Furthermore, we are looking at the CryoSat level 2 (L2...

Sea Ice Ecosystems

Science.gov (United States)

Arrigo, Kevin R.

2014-01-01

Polar sea ice is one of the largest ecosystems on Earth. The liquid brine fraction of the ice matrix is home to a diverse array of organisms, ranging from tiny archaea to larger fish and invertebrates. These organisms can tolerate high brine salinity and low temperature but do best when conditions are milder. Thriving ice algal communities, generally dominated by diatoms, live at the ice/water interface and in recently flooded surface and interior layers, especially during spring, when temperatures begin to rise. Although protists dominate the sea ice biomass, heterotrophic bacteria are also abundant. The sea ice ecosystem provides food for a host of animals, with crustaceans being the most conspicuous. Uneaten organic matter from the ice sinks through the water column and feeds benthic ecosystems. As sea ice extent declines, ice algae likely contribute a shrinking fraction of the total amount of organic matter produced in polar waters.

Remote sensing of sea ice: advances during the DAMOCLES project

Directory of Open Access Journals (Sweden)

G. Heygster

2012-12-01

ASCAT (62.5 km grid spacing, with visible AVHRR observations (20 km, with the synthetic aperture radar sensor ASAR (10 km, and a multi-sensor product (62.5 km with improved angular resolution (Continuous Maximum Cross Correlation, CMCC method is presented. CMCC is also used to derive the sea ice deformation, important for formation of sea ice leads (diverging deformation and pressure ridges (converging. The indirect determination of sea ice thickness from altimeter freeboard data requires knowledge of the ice density and snow load on sea ice. The relation between freeboard and ice thickness is investigated based on the airborne Sever expeditions conducted between 1928 and 1993.

The Sea-Ice Floe Size Distribution

Science.gov (United States)

Stern, H. L., III; Schweiger, A. J. B.; Zhang, J.; Steele, M.

2017-12-01

The size distribution of ice floes in the polar seas affects the dynamics and thermodynamics of the ice cover and its interaction with the ocean and atmosphere. Ice-ocean models are now beginning to include the floe size distribution (FSD) in their simulations. In order to characterize seasonal changes of the FSD and provide validation data for our ice-ocean model, we calculated the FSD in the Beaufort and Chukchi seas over two spring-summer-fall seasons (2013 and 2014) using more than 250 cloud-free visible-band scenes from the MODIS sensors on NASA's Terra and Aqua satellites, identifying nearly 250,000 ice floes between 2 and 30 km in diameter. We found that the FSD follows a power-law distribution at all locations, with a seasonally varying exponent that reflects floe break-up in spring, loss of smaller floes in summer, and the return of larger floes after fall freeze-up. We extended the results to floe sizes from 10 m to 2 km at selected time/space locations using more than 50 high-resolution radar and visible-band satellite images. Our analysis used more data and applied greater statistical rigor than any previous study of the FSD. The incorporation of the FSD into our ice-ocean model resulted in reduced sea-ice thickness, mainly in the marginal ice zone, which improved the simulation of sea-ice extent and yielded an earlier ice retreat. We also examined results from 17 previous studies of the FSD, most of which report power-law FSDs but with widely varying exponents. It is difficult to reconcile the range of results due to different study areas, seasons, and methods of analysis. We review the power-law representation of the FSD in these studies and discuss some mathematical details that are important to consider in any future analysis.

The role of feedbacks in Antarctic sea ice change

Science.gov (United States)

Feltham, D. L.; Frew, R. C.; Holland, P.

2017-12-01

The changes in Antarctic sea ice over the last thirty years have a strong seasonal dependence, and the way these changes grow in spring and decay in autumn suggests that feedbacks are strongly involved. The changes may ultimately be caused by atmospheric warming, the winds, snowfall changes, etc., but we cannot understand these forcings without first untangling the feedbacks. A highly simplified coupled sea ice -mixed layer model has been developed to investigate the importance of feedbacks on the evolution of sea ice in two contrasting regions in the Southern Ocean; the Amundsen Sea where sea ice extent has been decreasing, and the Weddell Sea where it has been expanding. The change in mixed layer depth in response to changes in the atmosphere to ocean energy flux is implicit in a strong negative feedback on ice cover changes in the Amundsen Sea, with atmospheric cooling leading to a deeper mixed layer resulting in greater entrainment of warm Circumpolar Deep Water, causing increased basal melting of sea ice. This strong negative feedback produces counter intuitive responses to changes in forcings in the Amundsen Sea. This feedback is absent in the Weddell due to the complete destratification and strong water column cooling that occurs each winter in simulations. The impact of other feedbacks, including the albedo feedback, changes in insulation due to ice thickness and changes in the freezing temperature of the mixed layer, were found to be of secondary importance compared to changes in the mixed layer depth.

Record low sea-ice concentration in the central Arctic during summer 2010

Science.gov (United States)

Zhao, Jinping; Barber, David; Zhang, Shugang; Yang, Qinghua; Wang, Xiaoyu; Xie, Hongjie

2018-01-01

The Arctic sea-ice extent has shown a declining trend over the past 30 years. Ice coverage reached historic minima in 2007 and again in 2012. This trend has recently been assessed to be unique over at least the last 1450 years. In the summer of 2010, a very low sea-ice concentration (SIC) appeared at high Arctic latitudes—even lower than that of surrounding pack ice at lower latitudes. This striking low ice concentration—referred to here as a record low ice concentration in the central Arctic (CARLIC)—is unique in our analysis period of 2003-15, and has not been previously reported in the literature. The CARLIC was not the result of ice melt, because sea ice was still quite thick based on in-situ ice thickness measurements. Instead, divergent ice drift appears to have been responsible for the CARLIC. A high correlation between SIC and wind stress curl suggests that the sea ice drift during the summer of 2010 responded strongly to the regional wind forcing. The drift trajectories of ice buoys exhibited a transpolar drift in the Atlantic sector and an eastward drift in the Pacific sector, which appeared to benefit the CARLIC in 2010. Under these conditions, more solar energy can penetrate into the open water, increasing melt through increased heat flux to the ocean. We speculate that this divergence of sea ice could occur more often in the coming decades, and impact on hemispheric SIC and feed back to the climate.

Record Low Sea-Ice Concentration in the Central Arctic during Summer 2010

Institute of Scientific and Technical Information of China (English)

Jinping ZHAO; David BARBER; Shugang ZHANG; Qinghua YANG; Xiaoyu WANG; Hongjie XIE

2018-01-01

The Arctic sea-ice extent has shown a declining trend over the past 30 years.Ice coverage reached historic minima in 2007 and again in 2012.This trend has recently been assessed to be unique over at least the last 1450 years.In the summer of 2010,a very low sea-ice concentration (SIC) appeared at high Arctic latitudes—even lower than that of surrounding pack ice at lower latitudes.This striking low ice concentration—referred to here as a record low ice concentration in the central Arctic (CARLIC)—is unique in our analysis period of 2003-15,and has not been previously reported in the literature.The CARLIC was not the result of ice melt,because sea ice was still quite thick based on in-situ ice thickness measurements.Instead,divergent ice drift appears to have been responsible for the CARLIC.A high correlation between SIC and wind stress curl suggests that the sea ice drift during the summer of 2010 responded strongly to the regional wind forcing.The drift trajectories of ice buoys exhibited a transpolar drift in the Atlantic sector and an eastward drift in the Pacific sector,which appeared to benefit the CARLIC in 2010.Under these conditions,more solar energy can penetrate into the open water,increasing melt through increased heat flux to the ocean.We speculate that this divergence of sea ice could occur more often in the coming decades,and impact on hemispheric SIC and feed back to the climate.

Extreme Low Light Requirement for Algae Growth Underneath Sea Ice

DEFF Research Database (Denmark)

Hancke, Kasper; Lund-Hansen, Lars C.; Lamare, Maxim L.

2018-01-01

Microalgae colonizing the underside of sea ice in spring are a key component of the Arctic foodweb as they drive early primary production and transport of carbon from the atmosphere to the ocean interior. Onset of the spring bloom of ice algae is typically limited by the availability of light......, and the current consensus is that a few tens-of-centimeters of snow is enough to prevent sufficient solar radiation to reach underneath the sea ice. We challenge this consensus, and investigated the onset and the light requirement of an ice algae spring bloom, and the importance of snow optical properties...... for light penetration. Colonization by ice algae began in May under >1 m of first-year sea ice with approximate to 1 m thick snow cover on top, in NE Greenland. The initial growth of ice algae began at extremely low irradiance (...

A Model of Icebergs and Sea Ice in a Joint Continuum Framework

Science.gov (United States)

VaÅková, Irena; Holland, David M.

2017-11-01

The ice mélange, a mixture of sea ice and icebergs, often present in front of outlet glaciers in Greenland or ice shelves in Antarctica, can have a profound effect on the dynamics of the ice-ocean system. The current inability to numerically model the ice mélange motivates a new modeling approach proposed here. A continuum sea-ice model is taken as a starting point and icebergs are represented as thick and compact pieces of sea ice held together by large tensile and shear strength, selectively introduced into the sea-ice rheology. In order to modify the rheology correctly, an iceberg tracking procedure is implemented within a semi-Lagrangian time-stepping scheme, designed to exactly preserve iceberg shape through time. With the proposed treatment, sea ice and icebergs are considered a single fluid with spatially varying rheological properties. Mutual interactions are thus automatically included without the need for further parametrization. An important advantage of the presented framework for an ice mélange model is its potential to be easily included within sea-ice components of existing climate models.

Canadian snow and sea ice: historical trends and projections

Science.gov (United States)

Mudryk, Lawrence R.; Derksen, Chris; Howell, Stephen; Laliberté, Fred; Thackeray, Chad; Sospedra-Alfonso, Reinel; Vionnet, Vincent; Kushner, Paul J.; Brown, Ross

2018-04-01

The Canadian Sea Ice and Snow Evolution (CanSISE) Network is a climate research network focused on developing and applying state of the art observational data to advance dynamical prediction, projections, and understanding of seasonal snow cover and sea ice in Canada and the circumpolar Arctic. Here, we present an assessment from the CanSISE Network on trends in the historical record of snow cover (fraction, water equivalent) and sea ice (area, concentration, type, and thickness) across Canada. We also assess projected changes in snow cover and sea ice likely to occur by mid-century, as simulated by the Coupled Model Intercomparison Project Phase 5 (CMIP5) suite of Earth system models. The historical datasets show that the fraction of Canadian land and marine areas covered by snow and ice is decreasing over time, with seasonal and regional variability in the trends consistent with regional differences in surface temperature trends. In particular, summer sea ice cover has decreased significantly across nearly all Canadian marine regions, and the rate of multi-year ice loss in the Beaufort Sea and Canadian Arctic Archipelago has nearly doubled over the last 8 years. The multi-model consensus over the 2020-2050 period shows reductions in fall and spring snow cover fraction and sea ice concentration of 5-10 % per decade (or 15-30 % in total), with similar reductions in winter sea ice concentration in both Hudson Bay and eastern Canadian waters. Peak pre-melt terrestrial snow water equivalent reductions of up to 10 % per decade (30 % in total) are projected across southern Canada.

State of Arctic Sea Ice North of Svalbard during N-ICE2015

Science.gov (United States)

Rösel, Anja; King, Jennifer; Gerland, Sebastian

2016-04-01

The N-ICE2015 cruise, led by the Norwegian Polar Institute, was a drift experiment with the research vessel R/V Lance from January to June 2015, where the ship started the drift North of Svalbard at 83°14.45' N, 21°31.41' E. The drift was repeated as soon as the vessel drifted free. Altogether, 4 ice stations where installed and the complex ocean-sea ice-atmosphere system was studied with an interdisciplinary Approach. During the N-ICE2015 cruise, extensive ice thickness and snow depth measurements were performed during both, winter and summer conditions. Total ice and snow thickness was measured with ground-based and airborne electromagnetic instruments; snow depth was measured with a GPS snow depth probe. Additionally, ice mass balance and snow buoys were deployed. Snow and ice thickness measurements were performed on repeated transects to quantify the ice growth or loss as well as the snow accumulation and melt rate. Additionally, we collected independent values on surveys to determine the general ice thickness distribution. Average snow depths of 32 cm on first year ice, and 52 cm on multi-year ice were measured in January, the mean snow depth on all ice types even increased until end of March to 49 cm. The average total ice and snow thickness in winter conditions was 1.92 m. During winter we found a small growth rate on multi-year ice of about 15 cm in 2 months, due to above-average snow depths and some extraordinary storm events that came along with mild temperatures. In contrast thereto, we also were able to study new ice formation and thin ice on newly formed leads. In summer conditions an enormous melt rate, mainly driven by a warm Atlantic water inflow in the marginal ice zone, was observed during two ice stations with melt rates of up to 20 cm per 24 hours. To reinforce the local measurements around the ship and to confirm their significance on a larger scale, we compare them to airborne thickness measurements and classified SAR-satellite scenes. The

Biopolymers form a gelatinous microlayer at the air-sea interface when Arctic sea ice melts

OpenAIRE

Galgani, Luisa; Piontek, Judith; Engel, Anja

2016-01-01

The interface layer between ocean and atmosphere is only a couple of micrometers thick but plays a critical role in climate relevant processes, including the air-sea exchange of gas and heat and the emission of primary organic aerosols (POA). Recent findings suggest that low-level cloud formation above the Arctic Ocean may be linked to organic polymers produced by marine microorganisms. Sea ice harbors high amounts of polymeric substances that are produced by cells growing within the sea-ice ...

Biopolymers form a gelatinous microlayer at the air-sea interface when Arctic sea ice melts.

Science.gov (United States)

Galgani, Luisa; Piontek, Judith; Engel, Anja

2016-07-20

The interface layer between ocean and atmosphere is only a couple of micrometers thick but plays a critical role in climate relevant processes, including the air-sea exchange of gas and heat and the emission of primary organic aerosols (POA). Recent findings suggest that low-level cloud formation above the Arctic Ocean may be linked to organic polymers produced by marine microorganisms. Sea ice harbors high amounts of polymeric substances that are produced by cells growing within the sea-ice brine. Here, we report from a research cruise to the central Arctic Ocean in 2012. Our study shows that microbial polymers accumulate at the air-sea interface when the sea ice melts. Proteinaceous compounds represented the major fraction of polymers supporting the formation of a gelatinous interface microlayer and providing a hitherto unrecognized potential source of marine POA. Our study indicates a novel link between sea ice-ocean and atmosphere that may be sensitive to climate change.

Comparison of sea-ice freeboard distributions from aircraft data and cryosat-2

DEFF Research Database (Denmark)

Ricker, Robert; Hendricks, Stefan; Helm, Veit

2012-01-01

highly accurate range measurements. During the CryoSat Validation Experiment (CryoVEx) 2011 in the Lincoln Sea Cryosat-2 underpasses were accomplished with two aircraft which carried an airborne laser scanner, a radar altimeter and an electromagnetic induction device for direct sea ice thickness...... retrieval. Both aircraft flew in close formation at the same time of a CryoSat-2 overpass. This is a study about the comparison of the sea-ice freeboard distribution of laser scanner and radar altimeter measurements with the CryoSat-2 product within the multi-year sea ice region of the Lincoln Sea in spring...

Optical properties of melting first-year Arctic sea ice

Science.gov (United States)

Light, Bonnie; Perovich, Donald K.; Webster, Melinda A.; Polashenski, Christopher; Dadic, Ruzica

2015-11-01

The albedo and transmittance of melting, first-year Arctic sea ice were measured during two cruises of the Impacts of Climate on the Eco-Systems and Chemistry of the Arctic Pacific Environment (ICESCAPE) project during the summers of 2010 and 2011. Spectral measurements were made for both bare and ponded ice types at a total of 19 ice stations in the Chukchi and Beaufort Seas. These data, along with irradiance profiles taken within boreholes, laboratory measurements of the optical properties of core samples, ice physical property observations, and radiative transfer model simulations are employed to describe representative optical properties for melting first-year Arctic sea ice. Ponded ice was found to transmit roughly 4.4 times more total energy into the ocean, relative to nearby bare ice. The ubiquitous surface-scattering layer and drained layer present on bare, melting sea ice are responsible for its relatively high albedo and relatively low transmittance. Light transmittance through ponded ice depends on the physical thickness of the ice and the magnitude of the scattering coefficient in the ice interior. Bare ice reflects nearly three-quarters of the incident sunlight, enhancing its resiliency to absorption by solar insolation. In contrast, ponded ice absorbs or transmits to the ocean more than three-quarters of the incident sunlight. Characterization of the heat balance of a summertime ice cover is largely dictated by its pond coverage, and light transmittance through ponded ice shows strong contrast between first-year and multiyear Arctic ice covers.

Amundsen Sea simulation with optimized ocean, sea ice, and thermodynamic ice shelf model parameters

Science.gov (United States)

Nakayama, Y.; Menemenlis, D.; Schodlok, M.; Heimbach, P.; Nguyen, A. T.; Rignot, E. J.

2016-12-01

Ice shelves and glaciers of the West Antarctic Ice Sheet are thinning and melting rapidly in the Amundsen Sea (AS). This is thought to be caused by warm Circumpolar Deep Water (CDW) that intrudes via submarine glacial troughs located at the continental shelf break. Recent studies, however, point out that the depth of thermocline, or thickness of Winter Water (WW, potential temperature below -1 °C located above CDW) is critical in determining the melt rate, especially for the Pine Island Glacier (PIG). For example, the basal melt rate of PIG, which decreased by 50% during summer 2012, has been attributed to thickening of WW. Despite the possible importance of WW thickness on ice shelf melting, previous modeling studies in this region have focused primarily on CDW intrusion and have evaluated numerical simulations based on bottom or deep CDW properties. As a result, none of these models have shown a good representation of WW for the AS. In this study, we adjust a small number of model parameters in a regional Amundsen and Bellingshausen Seas configuration of the Massachusetts Institute of Technology general circulation model (MITgcm) to better fit the available observations during the 2007-2010 period. We choose this time period because summer observations during these years show small interannual variability in the eastern AS. As a result of adjustments, our model shows significantly better match with observations than previous modeling studies, especially for WW. Since density of sea water depends largely on salinity at low temperature, this is crucial for assessing the impact of WW on PIG melt rate. In addition, we conduct several sensitivity studies, showing the impact of surface heat loss on the thickness and properties of WW. We also discuss some preliminary results pertaining to further optimization using the adjoint method. Our work is a first step toward improved representation of ice-shelf ocean interactions in the ECCO (Estimating the Circulation and

Complex bounds and microstructural recovery from measurements of sea ice permittivity

International Nuclear Information System (INIS)

Gully, A.; Backstrom, L.G.E.; Eicken, H.; Golden, K.M.

2007-01-01

Sea ice is a porous composite of pure ice with brine, air, and salt inclusions. The polar sea ice packs play a key role in the earth's ocean-climate system, and they host robust algal and bacterial communities that support the Arctic and Antarctic ecosystems. Monitoring the sea ice packs on global or regional scales is an increasingly important problem, typically involving the interaction of an electromagnetic wave with sea ice. In the quasistatic regime where the wavelength is much longer than the composite microstructural scale, the electromagnetic behavior is characterized by the effective complex permittivity tensor ε*. In assessing the impact of climate change on the polar sea ice covers, current satellites and algorithms can predict ice extent, but the thickness distribution remains an elusive, yet most important feature. In recent years, electromagnetic induction devices using low frequency waves have been deployed on ships, helicopters and planes to obtain thickness data. Here we compare two sets of theoretical bounds to extensive outdoor tank and in situ field data on ε* at 50MHz taken in the Arctic and Antarctic. The sea ice is assumed to be a two phase composite of ice and brine with known constituent permittivities. The first set of bounds assumes only knowledge of the brine volume fraction or porosity, and the second set further assumes statistical isotropy of the microstructure. We obtain excellent agreement between theory and experiment, and are able to observe the apparent violation of the isotropic bounds as the vertically oriented microstructure becomes increasingly connected for higher porosities. Moreover, these bounds are inverted to obtain estimates of the porosity from the measurements of ε*. We find that the temporal variations of the reconstructed porosity, which is directly related to temperature, closely follow the actual behavior

Sea-ice monitoring by ship-based visual observation during JARE ―Simplification of observation method based on the ASPeCt protocol―

OpenAIRE

Kay I. Ohshima; Shuki Ushio; Akihisa S. Otsuki

2006-01-01

A protocol for ship-based visual observation of sea ice is proposed for the Japanese Antarctic Research Expedition (JARE). The protocol is a simplified version of the ASPeCt protocol, used for extracting quantitative information on sea ice. The ship-based visual observations started from JARE-46. In the pack ice region, ice thickness, ratio of deformed ice, and total ice volume increased toward the coast. Continuous monitoring of sea ice, particularly its thickness, by ship-based observation ...

Ikaite crystal distribution in winter sea ice and implications for CO2 system dynamics

Science.gov (United States)

Rysgaard, S.; Søgaard, D. H.; Cooper, M.; Pućko, M.; Lennert, K.; Papakyriakou, T. N.; Wang, F.; Geilfus, N. X.; Glud, R. N.; Ehn, J.; McGinnis, D. F.; Attard, K.; Sievers, J.; Deming, J. W.; Barber, D.

2013-04-01

The precipitation of ikaite (CaCO3 ⋅ 6H2O) in polar sea ice is critical to the efficiency of the sea ice-driven carbon pump and potentially important to the global carbon cycle, yet the spatial and temporal occurrence of ikaite within the ice is poorly known. We report unique observations of ikaite in unmelted ice and vertical profiles of ikaite abundance and concentration in sea ice for the crucial season of winter. Ice was examined from two locations: a 1 m thick land-fast ice site and a 0.3 m thick polynya site, both in the Young Sound area (74° N, 20° W) of NE Greenland. Ikaite crystals, ranging in size from a few μm to 700 μm, were observed to concentrate in the interstices between the ice platelets in both granular and columnar sea ice. In vertical sea ice profiles from both locations, ikaite concentration determined from image analysis, decreased with depth from surface-ice values of 700-900 μmol kg-1 ice (~25 × 106 crystals kg-1) to values of 100-200 μmol kg-1 ice (1-7 × 106 crystals kg-1) near the sea ice-water interface, all of which are much higher (4-10 times) than those reported in the few previous studies. Direct measurements of total alkalinity (TA) in surface layers fell within the same range as ikaite concentration, whereas TA concentrations in the lower half of the sea ice were twice as high. This depth-related discrepancy suggests interior ice processes where ikaite crystals form in surface sea ice layers and partly dissolve in layers below. Melting of sea ice and dissolution of observed concentrations of ikaite would result in meltwater with a pCO2 of <15 μatm. This value is far below atmospheric values of 390 μatm and surface water concentrations of 315 μatm. Hence, the meltwater increases the potential for seawater uptake of CO2.

Processes driving sea ice variability in the Bering Sea in an eddying ocean/sea ice model: Mean seasonal cycle

Science.gov (United States)

Li, Linghan; McClean, Julie L.; Miller, Arthur J.; Eisenman, Ian; Hendershott, Myrl C.; Papadopoulos, Caroline A.

2014-12-01

The seasonal cycle of sea ice variability in the Bering Sea, together with the thermodynamic and dynamic processes that control it, are examined in a fine resolution (1/10°) global coupled ocean/sea-ice model configured in the Community Earth System Model (CESM) framework. The ocean/sea-ice model consists of the Los Alamos National Laboratory Parallel Ocean Program (POP) and the Los Alamos Sea Ice Model (CICE). The model was forced with time-varying reanalysis atmospheric forcing for the time period 1970-1989. This study focuses on the time period 1980-1989. The simulated seasonal-mean fields of sea ice concentration strongly resemble satellite-derived observations, as quantified by root-mean-square errors and pattern correlation coefficients. The sea ice energy budget reveals that the seasonal thermodynamic ice volume changes are dominated by the surface energy flux between the atmosphere and the ice in the northern region and by heat flux from the ocean to the ice along the southern ice edge, especially on the western side. The sea ice force balance analysis shows that sea ice motion is largely associated with wind stress. The force due to divergence of the internal ice stress tensor is large near the land boundaries in the north, and it is small in the central and southern ice-covered region. During winter, which dominates the annual mean, it is found that the simulated sea ice was mainly formed in the northern Bering Sea, with the maximum ice growth rate occurring along the coast due to cold air from northerly winds and ice motion away from the coast. South of St Lawrence Island, winds drive the model sea ice southwestward from the north to the southwestern part of the ice-covered region. Along the ice edge in the western Bering Sea, model sea ice is melted by warm ocean water, which is carried by the simulated Bering Slope Current flowing to the northwest, resulting in the S-shaped asymmetric ice edge. In spring and fall, similar thermodynamic and dynamic

There goes the sea ice: following Arctic sea ice parcels and their properties.

Science.gov (United States)

Tschudi, M. A.; Tooth, M.; Meier, W.; Stewart, S.

2017-12-01

Arctic sea ice distribution has changed considerably over the last couple of decades. Sea ice extent record minimums have been observed in recent years, the distribution of ice age now heavily favors younger ice, and sea ice is likely thinning. This new state of the Arctic sea ice cover has several impacts, including effects on marine life, feedback on the warming of the ocean and atmosphere, and on the future evolution of the ice pack. The shift in the state of the ice cover, from a pack dominated by older ice, to the current state of a pack with mostly young ice, impacts specific properties of the ice pack, and consequently the pack's response to the changing Arctic climate. For example, younger ice typically contains more numerous melt ponds during the melt season, resulting in a lower albedo. First-year ice is typically thinner and more fragile than multi-year ice, making it more susceptible to dynamic and thermodynamic forcing. To investigate the response of the ice pack to climate forcing during summertime melt, we have developed a database that tracks individual Arctic sea ice parcels along with associated properties as these parcels advect during the summer. Our database tracks parcels in the Beaufort Sea, from 1985 - present, along with variables such as ice surface temperature, albedo, ice concentration, and convergence. We are using this database to deduce how these thousands of tracked parcels fare during summer melt, i.e. what fraction of the parcels advect through the Beaufort, and what fraction melts out? The tracked variables describe the thermodynamic and dynamic forcing on these parcels during their journey. This database will also be made available to all interested investigators, after it is published in the near future. The attached image shows the ice surface temperature of all parcels (right) that advected through the Beaufort Sea region (left) in 2014.

Ice shelf thickness change from 2010 to 2017

Science.gov (United States)

Hogg, A.; Shepherd, A.; Gilbert, L.; Muir, A. S.

2017-12-01

Floating ice shelves fringe 74 % of Antarctica's coastline, providing a direct link between the ice sheet and the surrounding oceans. Over the last 25 years, ice shelves have retreated, thinned, and collapsed catastrophically. While change in the mass of floating ice shelves has only a modest steric impact on the rate of sea-level rise, their loss can affect the mass balance of the grounded ice-sheet by influencing the rate of ice flow inland, due to the buttressing effect. Here we use CryoSat-2 altimetry data to map the detailed pattern of ice shelf thickness change in Antarctica. We exploit the dense spatial sampling and repeat coverage provided by the CryoSat-2 synthetic aperture radar interferometric mode (SARIn) to investigate data acquired between 2010 to the present day. We find that ice shelf thinning rates can exhibit large fluctuations over short time periods, and that the improved spatial resolution of CryoSat-2 enables us to resolve the spatial pattern of thinning with ever greater detail in Antarctica. In the Amundsen Sea, ice shelves at the terminus of the Pine Island and Thwaites glaciers have thinned at rates in excess of 5 meters per year for more than two decades. We observe the highest rates of basal melting near to the ice sheet grounding line, reinforcing the importance of high resolution datasets. On the Antarctic Peninsula, in contrast to the 3.8 m per decade of thinning observed since 1992, we measure an increase in the surface elevation of the Larsen-C Ice-Shelf during the CryoSat-2 period.

Sensitivity of CryoSat-2 Arctic sea-ice freeboard and thickness on radar-waveform interpretation

DEFF Research Database (Denmark)

Ricker, R.; Hendricks, S.; Helm, V.

2014-01-01

In the context of quantifying Arctic ice-volume decrease at global scale, the CryoSat-2 satellite was launched in 2010 and is equipped with the K-u band synthetic aperture radar altimeter SIRAL (Synthetic Aperture Interferometric Radar Altimeter), which we use to derive sea-ice freeboard defined...... knowledge of ice and snow properties, the composition of radar backscatter and therefore the interpretation of radar echoes is crucial. This has consequences in the selection of retracker algorithms which are used to track the main scattering horizon and assign a range estimate to each CryoSat-2 measurement...... of sea-ice freeboard and higher-level products that arise from the choice of the retracker threshold only, independent of the uncertainties related to snow and ice properties. Our study shows that the choice of retracker thresholds does have a significant impact on magnitudes of estimates of sea...

The effect of sea ice on the solar energy budget in the astmosphere-sea ice-ocean system: A model study

Science.gov (United States)

Jin, Z.; Stamnes, Knut; Weeks, W. F.; Tsay, Si-Chee

1994-01-01

A coupled one-dimensional multilayer and multistream radiative transfer model has been developed and applied to the study of radiative interactions in the atmosphere, sea ice, and ocean system. The consistent solution of the radiative transfer equation in this coupled system automatically takes into account the refraction and reflection at the air-ice interface and allows flexibility in choice of stream numbers. The solar radiation spectrum (0.25 micron-4.0 micron) is divided into 24 spectral bands to account adequately for gaseous absorption in the atmosphere. The effects of ice property changes, including salinity and density variations, as well as of melt ponds and snow cover variations over the ice on the solar energy distribution in the entire system have been studied quantitatively. The results show that for bare ice it is the scattering, determined by air bubbles and brine pockets, in just a few centimeters of the top layer of ice that plays the most important role in the solar energy absorption and partitioning in the entire system. Ice thickness is important to the energy distribution only when the ice is thin, while the absorption in the atmosphere is not sensitive to ice thickness exceeds about 70 cm. The presence of clouds moderates all the sensitivities of the absorptive amounts in each layer to the variations in the ice properties and ice thickness. Comparisons with observational spectral albedo values for two simple ice types are also presented.

Climate change and ice hazards in the Beaufort Sea

DEFF Research Database (Denmark)

Barber, D. G.; McCullough, G.; Babb, D.

2014-01-01

Recent reductions in the summer extent of sea ice have focused the world’s attention on the effects of climate change. Increased CO2-derived global warming is rapidly shrinking the Arctic multi-year ice pack. This shift in ice regimes allows for increasing development opportunities for large oil...... will be a much more complex task than modeling average ice circulation. Given the observed reduction in sea ice extent and thickness this rather counterintuitive situation, associated with a warming climate, poses significant hazards to Arctic marine oil and gas development and marine transportation. Accurate...... forecasting of hazardous ice motion will require improved real-time surface wind and ocean current forecast models capable of ingesting local satellite-derived wind data and/or local, closely-spaced networks of anemometers and improved methods of determining high-frequency components of surface ocean current...

Contrasts in Sea Ice Formation and Production in the Arctic Seasonal and Perennial Ice Zones

Science.gov (United States)

Kwok, R.

2006-01-01

Four years (1997-2000) of RADARSAT Geophysical Processor System (RGPS) data are used to contrast the sea ice deformation and production regionally, and in the seasonal (SIZ) and perennial (PIZ) ice zones. Ice production is of seasonal ice in openings during the winter. 3-day estimates of these quantities are provided within Lagrangian elements initially 10 km on a side. A distinct seasonal cycle is seen in both zones with these estimates highest in the late fall and with seasonal minimums in the mid-winter. Regional divergence over the winter could be up to 30%. Spatially, the highest deformation is in the SIZ north of coastal Alaska. Both ice deformation and production are higher in the SIZ: deformation-related ice production in the SIZ (approx.0.5 m) is 1.5-2.3 times that of the PIZ (approx.0.3 m) - this is connected to ice strength and thickness. Atmospheric forcing and boundary layer structure contribute to only the seasonal and interannual variability. Seasonal ice growth in ice fractures accounts for approx.25-40% of the total ice production of the Arctic Ocean. By itself, this deformation-ice production relationship could be considered a negative feedback when thickness is perturbed. However, the overall effect on ice production in the face of increasing seasonal and thinner/weaker ice coverage could be modified by: local destabilization of the water column promoting overturning of warmer water due to increased brine rejection; and, the upwelling of the pynocline associated with increased occurrence of large shear motion in sea ice.

Measurement of spectral sea ice albedo at Qaanaaq fjord in northwest Greenland

Science.gov (United States)

Tanikawa, T.

2017-12-01

The spectral albedos of sea ice were measured at Qaanaaq fjord in northwest Greenland. Spectral measurements were conducted for sea ice covered with snow and sea ice without snow where snow was artificially removed around measurement point. Thickness of the sea ice was approximately 1.3 m with 5 cm of snow over the sea ice. The measurements show that the spectral albedos of the sea ice with snow were lower than those of natural pure snow especially in the visible regions though the spectral shapes were similar to each other. This is because the spectral albedos in the visible region have information of not only the snow but also the sea ice under the snow. The spectral albedos of the sea ice without the snow were approximately 0.4 - 0.5 in the visible region, 0.05-0.25 in the near-infrared region and almost constant of approximately 0.05 in the region of 1500 - 2500 nm. In the visible region, it would be due to multiple scattering by an air bubble within the sea ice. In contrast, in the near-infrared and shortwave infrared wavelengths, surface reflection at the sea ice surface would be dominant. Since a light absorption by the ice in these regions is relatively strong comparing to the visible region, the light could not be penetrated deeply within the sea ice, resulting that surface reflection based on Fresnel reflection would be dominant. In this presentation we also show the results of comparison between the radiative transfer calculation and spectral measurement data.

ASSESSMENT OF SEA ICE FREEBOARD AND THICKNESS IN MCMURDO SOUND, ANTARCTICA, DERIVED BY GROUND VALIDATED SATELLITE ALTIMETER DATA

Directory of Open Access Journals (Sweden)

D. Price

2012-07-01

Full Text Available This investigation employs the use of ICESat to derive freeboard measurements in McMurdo Sound in the western Ross Sea, Antarctica, for the time period 2003-2009. Methods closely follow those previously presented in the literature but are complemented by a good understanding of general sea ice characteristics in the study region from extensive temporal ground investigations but with limited spatial coverage. The aim of remote sensing applications in this area is to expand the good knowledge of sea ice characteristics within these limited areas to the wider McMurdo Sound and western Ross Sea region. The seven year Austral Spring (September, October, and November investigation is presented for sea ice freeboard alone. An interannual comparison of mean freeboard indicates an increase in multiyear sea ice freeboard from 1.08 m in 2003 to 1.15 m in 2009 with positive and negative variation in between. No significant trend was detected for first year sea ice freeboard. Further, an Envisat imagery investigation complements the freeboard assessment. The multiyear sea ice was observed to increase by 254 % of its original 2003 area, as firstyear sea ice persisted through the 2004 melt season into 2005. This maximum coverage then gradually diminished by 2009 to 20 % above the original 2003 value. The mid study period increase is likely attributed to the passage of iceberg B-15A minimising oceanic pressures and preventing sea ice breakout in the region.

SMOS sea ice product: Operational application and validation in the Barents Sea marginal ice zone

DEFF Research Database (Denmark)

Kaleschke, Lars; Tian-Kunze, Xiangshan; Maaß, Nina

2016-01-01

system for ship route optimisation has been developed and was tested during this field campaign with the ice-strengthened research vessel RV Lance. The ship cruise was complemented with coordinated measurements from a helicopter and the research aircraft Polar 5. Sea ice thickness was measured using...... an electromagnetic induction (EM) system from the bow of RV Lance and another EM-system towed below the helicopter. Polar 5 was equipped among others with the L-band radiometer EMIRAD-2. The experiment yielded a comprehensive data set allowing the evaluation of the operational forecast and route optimisation system...

Assessing, understanding, and conveying the state of the Arctic sea ice cover

Science.gov (United States)

Perovich, D. K.; Richter-Menge, J. A.; Rigor, I.; Parkinson, C. L.; Weatherly, J. W.; Nghiem, S. V.; Proshutinsky, A.; Overland, J. E.

2003-12-01

Recent studies indicate that the Arctic sea ice cover is undergoing significant climate-induced changes, affecting both its extent and thickness. Satellite-derived estimates of Arctic sea ice extent suggest a reduction of about 3% per decade since 1978. Ice thickness data from submarines suggest a net thinning of the sea ice cover since 1958. Changes (including oscillatory changes) in atmospheric circulation and the thermohaline properties of the upper ocean have also been observed. These changes impact not only the Arctic, but the global climate system and are likely accelerated by such processes as the ice-albedo feedback. It is important to continue and expand long-term observations of these changes to (a) improve the fundamental understanding of the role of the sea ice cover in the global climate system and (b) use the changes in the sea ice cover as an early indicator of climate change. This is a formidable task that spans a range of temporal and spatial scales. Fortunately, there are numerous tools that can be brought to bear on this task, including satellite remote sensing, autonomous buoys, ocean moorings, field campaigns and numerical models. We suggest the integrated and coordinated use of these tools during the International Polar Year to monitor the state of the Arctic sea ice cover and investigate its governing processes. For example, satellite remote sensing provides the large-scale snapshots of such basic parameters as ice distribution, melt zone, and cloud fraction at intervals of half a day to a week. Buoys and moorings can contribute high temporal resolution and can measure parameters currently unavailable from space including ice thickness, internal ice temperature, and ocean temperature and salinity. Field campaigns can be used to explore, in detail, the processes that govern the ice cover. Numerical models can be used to assess the character of the changes in the ice cover and predict their impacts on the rest of the climate system. This work

Arctic sea ice signatures: L-band brightness temperature sensitivity comparison using two radiation transfer models

Science.gov (United States)

Richter, Friedrich; Drusch, Matthias; Kaleschke, Lars; Maaß, Nina; Tian-Kunze, Xiangshan; Mecklenburg, Susanne

2018-03-01

Sea ice is a crucial component for short-, medium- and long-term numerical weather predictions. Most importantly, changes of sea ice coverage and areas covered by thin sea ice have a large impact on heat fluxes between the ocean and the atmosphere. L-band brightness temperatures from ESA's Earth Explorer SMOS (Soil Moisture and Ocean Salinity) have been proven to be a valuable tool to derive thin sea ice thickness. These retrieved estimates were already successfully assimilated in forecasting models to constrain the ice analysis, leading to more accurate initial conditions and subsequently more accurate forecasts. However, the brightness temperature measurements can potentially be assimilated directly in forecasting systems, reducing the data latency and providing a more consistent first guess. As a first step towards such a data assimilation system we studied the forward operator that translates geophysical parameters provided by a model into brightness temperatures. We use two different radiative transfer models to generate top of atmosphere brightness temperatures based on ORAP5 model output for the 2012/2013 winter season. The simulations are then compared against actual SMOS measurements. The results indicate that both models are able to capture the general variability of measured brightness temperatures over sea ice. The simulated brightness temperatures are dominated by sea ice coverage and thickness changes are most pronounced in the marginal ice zone where new sea ice is formed. There we observe the largest differences of more than 20 K over sea ice between simulated and observed brightness temperatures. We conclude that the assimilation of SMOS brightness temperatures yields high potential for forecasting models to correct for uncertainties in thin sea ice areas and suggest that information on sea ice fractional coverage from higher-frequency brightness temperatures should be used simultaneously.

Arctic sea ice signatures: L-band brightness temperature sensitivity comparison using two radiation transfer models

Directory of Open Access Journals (Sweden)

F. Richter

2018-03-01

Full Text Available Sea ice is a crucial component for short-, medium- and long-term numerical weather predictions. Most importantly, changes of sea ice coverage and areas covered by thin sea ice have a large impact on heat fluxes between the ocean and the atmosphere. L-band brightness temperatures from ESA's Earth Explorer SMOS (Soil Moisture and Ocean Salinity have been proven to be a valuable tool to derive thin sea ice thickness. These retrieved estimates were already successfully assimilated in forecasting models to constrain the ice analysis, leading to more accurate initial conditions and subsequently more accurate forecasts. However, the brightness temperature measurements can potentially be assimilated directly in forecasting systems, reducing the data latency and providing a more consistent first guess. As a first step towards such a data assimilation system we studied the forward operator that translates geophysical parameters provided by a model into brightness temperatures. We use two different radiative transfer models to generate top of atmosphere brightness temperatures based on ORAP5 model output for the 2012/2013 winter season. The simulations are then compared against actual SMOS measurements. The results indicate that both models are able to capture the general variability of measured brightness temperatures over sea ice. The simulated brightness temperatures are dominated by sea ice coverage and thickness changes are most pronounced in the marginal ice zone where new sea ice is formed. There we observe the largest differences of more than 20 K over sea ice between simulated and observed brightness temperatures. We conclude that the assimilation of SMOS brightness temperatures yields high potential for forecasting models to correct for uncertainties in thin sea ice areas and suggest that information on sea ice fractional coverage from higher-frequency brightness temperatures should be used simultaneously.

Tracing Atlantic Water Signature in the Arctic Sea Ice Cover East of Svalbard

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Vladimir V. Ivanov

2012-01-01

Full Text Available We focus on the Arctic Ocean between Svalbard and Franz Joseph Land in order to elucidate the possible role of Atlantic water (AW inflow in shaping ice conditions. Ice conditions substantially affect the temperature regime of the Spitsbergen archipelago, particularly in winter. We test the hypothesis that intensive vertical mixing at the upper AW boundary releases substantial heat upwards that eventually reaches the under-ice water layer, thinning the ice cover. We examine spatial and temporal variation of ice concentration against time series of wind, air temperature, and AW temperature. Analysis of 1979–2011 ice properties revealed a general tendency of decreasing ice concentration that commenced after the mid-1990s. AW temperature time series in Fram Strait feature a monotonic increase after the mid-1990s, consistent with shrinking ice cover. Ice thins due to increased sensible heat flux from AW; ice erosion from below allows wind and local currents to more effectively break ice. The winter spatial pattern of sea ice concentration is collocated with patterns of surface heat flux anomalies. Winter minimum sea ice thickness occurs in the ice pack interior above the AW path, clearly indicating AW influence on ice thickness. Our study indicates that in the AW inflow region heat flux from the ocean reduces the ice thickness.

Ikaite crystal distribution in Arctic winter sea ice and implications for CO2 system dynamics

Science.gov (United States)

Rysgaard, S.; Søgaard, D. H.; Cooper, M.; Pućko, M.; Lennert, K.; Papakyriakou, T. N.; Wang, F.; Geilfus, N. X.; Glud, R. N.; Ehn, J.; McGinnnis, D. F.; Attard, K.; Sievers, J.; Deming, J. W.; Barber, D.

2012-12-01

The precipitation of ikaite (CaCO3·6H2O) in polar sea ice is critical to the efficiency of the sea ice-driven carbon pump and potentially important to the global carbon cycle, yet the spatial and temporal occurrence of ikaite within the ice is poorly known. We report unique observations of ikaite in unmelted ice and vertical profiles of ikaite abundance and concentration in sea ice for the crucial season of winter. Ice was examined from two locations: a 1 m thick land-fast ice site and a 0.3 m thick polynya site, both in the Young Sound area (74° N, 20° W) of NE Greenland. Ikaite crystals, ranging in size from a few µm to 700 µm were observed to concentrate in the interstices between the ice platelets in both granular and columnar sea ice. In vertical sea-ice profiles from both locations, ikaite concentration determined from image analysis, decreased with depth from surfaceice values of 700-900 µmol kg-1 ice (~ 25 × 106 crystals kg-1) to bottom-layer values of 100-200 µmol kg-1 ice (1-7 × 106 kg-1), all of which are much higher (4-10 times) than those reported in the few previous studies. Direct measurements of total alkalinity (TA) in surface layers fell within the same range as ikaite concentration whereas TA concentrations in bottom layers were twice as high. This depth-related discrepancy suggests interior ice processes where ikaite crystals form in surface sea ice layers and partly dissolved in bottom layers. From these findings and model calculations we relate sea ice formation and melt to observed pCO2 conditions in polar surface waters, and hence, the air-sea CO2 flux.

Incorporation of a physically based melt pond scheme into the sea ice component of a climate model

OpenAIRE

Flocco, Daniela; Feltham, Danny; Turner, Adrian K.

2010-01-01

The extent and thickness of the Arctic sea ice cover has decreased dramatically in the past few decades with minima in sea ice extent in September 2005 and 2007. These minima have not been predicted in the IPCC AR4 report, suggesting that the sea ice component of climate models should more realistically represent the processes controlling the sea ice mass balance. One of the processes poorly represented in sea ice models is the formation and evolution of melt ponds. Melt ponds accumulate on t...

Ku-Band radar penetration into Snow over Arctic Sea Ice

DEFF Research Database (Denmark)

Hendricks, Stefan; Stenseng, Lars; Helm, Veit

is the snow/air interface, whereas radar waves interact with the variable physical properties of the snow cover on the Arctic sea ice. In addition, radar elevation measurements may vary for different retracker algorithms, which determine the track point of the scattered echo power distribution. Since accurate...... knowledge of the reflection horizon is critical for sea ice thickness retrieval, validation data is necessary to investigate the penetration of radar waves into the snow for the upcoming CryoSat-2 mission. Furthermore, the combination of both optical and RF wavelengths might be used to derive snow thickness......, if radar altimeters are capable of measuring the distance to the snow-ice interface reliably. We present the results of aircraft campaigns in the Arctic with a scanning laser altimeter and the Airborne SAR/Interferometric Radar Altimeter System (ASIRAS) of the European Space Agency. The elevation...

Carbon Dioxide Transfer Through Sea Ice: Modelling Flux in Brine Channels

Science.gov (United States)

Edwards, L.; Mitchelson-Jacob, G.; Hardman-Mountford, N.

2010-12-01

For many years sea ice was thought to act as a barrier to the flux of CO2 between the ocean and atmosphere. However, laboratory-based and in-situ observations suggest that while sea ice may in some circumstances reduce or prevent transfer (e.g. in regions of thick, superimposed multi-year ice), it may also be highly permeable (e.g. thin, first year ice) with some studies observing significant fluxes of CO2. Sea ice covered regions have been observed to act both as a sink and a source of atmospheric CO2 with the permeability of sea ice and direction of flux related to sea ice temperature and the presence of brine channels in the ice, as well as seasonal processes such as whether the ice is freezing or thawing. Brine channels concentrate dissolved inorganic carbon (DIC) as well as salinity and as these dense waters descend through both the sea ice and the surface ocean waters, they create a sink for CO2. Calcium carbonate (ikaite) precipitation in the sea ice is thought to enhance this process. Micro-organisms present within the sea ice will also contribute to the CO2 flux dynamics. Recent evidence of decreasing sea ice extent and the associated change from a multi-year ice to first-year ice dominated system suggest the potential for increased CO2 flux through regions of thinner, more porous sea ice. A full understanding of the processes and feedbacks controlling the flux in these regions is needed to determine their possible contribution to global CO2 levels in a future warming climate scenario. Despite the significance of these regions, the air-sea CO2 flux in sea ice covered regions is not currently included in global climate models. Incorporating this carbon flux system into Earth System models requires the development of a well-parameterised sea ice-air flux model. In our work we use the Los Alamos sea ice model, CICE, with a modification to incorporate the movement of CO2 through brine channels including the addition of DIC processes and ice algae production to

How accurate are estimates of glacier ice thickness? Results from ITMIX, the Ice Thickness Models Intercomparison eXperiment

DEFF Research Database (Denmark)

Farinotti, Daniel; Brinkerhoff, Douglas J.; Clarke, Garry K. C.

2017-01-01

Knowledge of the ice thickness distribution of glaciers and ice caps is an important prerequisite for many glaciological and hydrological investigations. A wealth of approaches has recently been presented for inferring ice thickness from characteristics of the surface. With the Ice Thickness Models...

Airborne Surveys of Snow Depth over Arctic Sea Ice

Science.gov (United States)

Kwok, R.; Panzer, B.; Leuschen, C.; Pang, S.; Markus, T.; Holt, B.; Gogineni, S.

2011-01-01

During the spring of 2009, an ultrawideband microwave radar was deployed as part of Operation IceBridge to provide the first cross-basin surveys of snow thickness over Arctic sea ice. In this paper, we analyze data from three approx 2000 km transects to examine detection issues, the limitations of the current instrument, and the regional variability of the retrieved snow depth. Snow depth is the vertical distance between the air \\snow and snow-ice interfaces detected in the radar echograms. Under ideal conditions, the per echogram uncertainty in snow depth retrieval is approx 4 - 5 cm. The finite range resolution of the radar (approx 5 cm) and the relative amplitude of backscatter from the two interfaces limit the direct retrieval of snow depths much below approx 8 cm. Well-defined interfaces are observed over only relatively smooth surfaces within the radar footprint of approx 6.5 m. Sampling is thus restricted to undeformed, level ice. In early April, mean snow depths are 28.5 +/- 16.6 cm and 41.0 +/- 22.2 cm over first-year and multiyear sea ice (MYI), respectively. Regionally, snow thickness is thinner and quite uniform over the large expanse of seasonal ice in the Beaufort Sea, and gets progressively thicker toward the MYI cover north of Ellesmere Island, Greenland, and the Fram Strait. Snow depth over MYI is comparable to that reported in the climatology by Warren et al. Ongoing improvements to the radar system and the utility of these snow depth measurements are discussed.

Arctic sea ice concentration observed with SMOS during summer

Science.gov (United States)

Gabarro, Carolina; Martinez, Justino; Turiel, Antonio

2017-04-01

The Arctic Ocean is under profound transformation. Observations and model predictions show dramatic decline in sea ice extent and volume [1]. A retreating Arctic ice cover has a marked impact on regional and global climate, and vice versa, through a large number of feedback mechanisms and interactions with the climate system [2]. The launch of the Soil Moisture and Ocean Salinity (SMOS) mission, in 2009, marked the dawn of a new type of space-based microwave observations. Although the mission was originally conceived for hydrological and oceanographic studies [3,4], SMOS is also making inroads in the cryospheric sciences by measuring the thin ice thickness [5,6]. SMOS carries an L-band (1.4 GHz), passive interferometric radiometer (the so-called MIRAS) that measures the electromagnetic radiation emitted by the Earth's surface, at about 50 km spatial resolution, continuous multi-angle viewing, large wide swath (1200-km), and with a 3-day revisit time at the equator, but more frequently at the poles. A novel radiometric method to determine sea ice concentration (SIC) from SMOS is presented. The method uses the Bayesian-based Maximum Likelihood Estimation (MLE) approach to retrieve SIC. The advantage of this approach with respect to the classical linear inversion is that the former takes into account the uncertainty of the tie-point measured data in addition to the mean value, while the latter only uses a mean value of the tie-point data. When thin ice is present, the SMOS algorithm underestimates the SIC due to the low opacity of the ice at this frequency. However, using a synergistic approach with data from other satellite sensors, it is possible to obtain accurate thin ice thickness estimations with the Bayesian-based method. Despite its lower spatial resolution relative to SSMI or AMSR-E, SMOS-derived SIC products are little affected by the atmosphere and the snow (almost transparent at L-band). Moreover L-band measurements are more robust in front of the

Sea-ice dynamics strongly promote Snowball Earth initiation and destabilize tropical sea-ice margins

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A. Voigt

2012-12-01

Full Text Available The Snowball Earth bifurcation, or runaway ice-albedo feedback, is defined for particular boundary conditions by a critical CO₂ and a critical sea-ice cover (SI, both of which are essential for evaluating hypotheses related to Neoproterozoic glaciations. Previous work has shown that the Snowball Earth bifurcation, denoted as (CO₂, SI^*, differs greatly among climate models. Here, we study the effect of bare sea-ice albedo, sea-ice dynamics and ocean heat transport on (CO₂, SI^* in the atmosphere–ocean general circulation model ECHAM5/MPI-OM with Marinoan (~ 635 Ma continents and solar insolation (94% of modern. In its standard setup, ECHAM5/MPI-OM initiates a~Snowball Earth much more easily than other climate models at (CO₂, SI^* ≈ (500 ppm, 55%. Replacing the model's standard bare sea-ice albedo of 0.75 by a much lower value of 0.45, we find (CO₂, SI^* ≈ (204 ppm, 70%. This is consistent with previous work and results from net evaporation and local melting near the sea-ice margin. When we additionally disable sea-ice dynamics, we find that the Snowball Earth bifurcation can be pushed even closer to the equator and occurs at a hundred times lower CO₂: (CO₂, SI^* ≈ (2 ppm, 85%. Therefore, the simulation of sea-ice dynamics in ECHAM5/MPI-OM is a dominant determinant of its high critical CO₂ for Snowball initiation relative to other models. Ocean heat transport has no effect on the critical sea-ice cover and only slightly decreases the critical CO₂. For disabled sea-ice dynamics, the state with 85% sea-ice cover is stabilized by the Jormungand mechanism and shares characteristics with the Jormungand climate states. However, there is no indication of the Jormungand bifurcation and hysteresis in ECHAM5/MPI-OM. The state with 85% sea-ice cover therefore is a soft Snowball state rather than a true

Influence of winter sea-ice motion on summer ice cover in the Arctic

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Noriaki Kimura

2013-11-01

Full Text Available Summer sea-ice cover in the Arctic varies largely from year to year owing to several factors. This study examines one such factor, the relationship between interannual difference in winter ice motion and ice area in the following summer. A daily-ice velocity product on a 37.5-km resolution grid is prepared using the satellite passive microwave sensor Advanced Microwave Scanning Radiometer—Earth Observing System data for the nine years of 2003–2011. Derived daily-ice motion reveals the dynamic modification of the winter ice cover. The winter ice divergence/convergence is strongly related to the summer ice cover in some regions; the correlation coefficient between the winter ice convergence and summer ice area ranges between 0.5 and 0.9 in areas with high interannual variability. This relation implies that the winter ice redistribution controls the spring ice thickness and the summer ice cover.

Quaternary Sea-ice history in the Arctic Ocean based on a new Ostracode sea-ice proxy

Science.gov (United States)

Cronin, T. M.; Gemery, L.; Briggs, W.M.; Jakobsson, M.; Polyak, L.; Brouwers, E.M.

2010-01-01

Paleo-sea-ice history in the Arctic Ocean was reconstructed using the sea-ice dwelling ostracode Acetabulastoma arcticum from late Quaternary sediments from the Mendeleyev, Lomonosov, and Gakkel Ridges, the Morris Jesup Rise and the Yermak Plateau. Results suggest intermittently high levels of perennial sea ice in the central Arctic Ocean during Marine Isotope Stage (MIS) 3 (25-45 ka), minimal sea ice during the last deglacial (16-11 ka) and early Holocene thermal maximum (11-5 ka) and increasing sea ice during the mid-to-late Holocene (5-0 ka). Sediment core records from the Iceland and Rockall Plateaus show that perennial sea ice existed in these regions only during glacial intervals MIS 2, 4, and 6. These results show that sea ice exhibits complex temporal and spatial variability during different climatic regimes and that the development of modern perennial sea ice may be a relatively recent phenomenon. ?? 2010.

New Tools for Sea Ice Data Analysis and Visualization: NSIDC's Arctic Sea Ice News and Analysis

Science.gov (United States)

Vizcarra, N.; Stroeve, J.; Beam, K.; Beitler, J.; Brandt, M.; Kovarik, J.; Savoie, M. H.; Skaug, M.; Stafford, T.

2017-12-01

Arctic sea ice has long been recognized as a sensitive climate indicator and has undergone a dramatic decline over the past thirty years. Antarctic sea ice continues to be an intriguing and active field of research. The National Snow and Ice Data Center's Arctic Sea Ice News & Analysis (ASINA) offers researchers and the public a transparent view of sea ice data and analysis. We have released a new set of tools for sea ice analysis and visualization. In addition to Charctic, our interactive sea ice extent graph, the new Sea Ice Data and Analysis Tools page provides access to Arctic and Antarctic sea ice data organized in seven different data workbooks, updated daily or monthly. An interactive tool lets scientists, or the public, quickly compare changes in ice extent and location. Another tool allows users to map trends, anomalies, and means for user-defined time periods. Animations of September Arctic and Antarctic monthly average sea ice extent and concentration may also be accessed from this page. Our tools help the NSIDC scientists monitor and understand sea ice conditions in near real time. They also allow the public to easily interact with and explore sea ice data. Technical innovations in our data center helped NSIDC quickly build these tools and more easily maintain them. The tools were made publicly accessible to meet the desire from the public and members of the media to access the numbers and calculations that power our visualizations and analysis. This poster explores these tools and how other researchers, the media, and the general public are using them.

Summer sea ice characteristics and morphology in the Pacific Arctic sector as observed during the CHINARE 2010 cruise

Directory of Open Access Journals (Sweden)

H. Xie

2013-07-01

Full Text Available In the summer of 2010, atmosphere–ice–ocean interaction was studied aboard the icebreaker R/V Xuelong during the Chinese National Arctic Research Expedition (CHINARE, in the sea ice zone of the Pacific Arctic sector between 150° W and 180° W up to 88.5° N. The expedition lasted from 21 July to 28 August and comprised of ice observations and measurements along the cruise track, 8 short-term stations and one 12-day drift station. Ship-based observations of ice thickness and concentration are compared with ice thickness measured by an electromagnetic induction device (EM31 mounted off the ship's side and ice concentrations obtained from AMSR-E. It is found that the modal thickness from ship-based visual observations matches well with the modal thickness from the mounted EM31. A grid of 8 profiles of ice thickness measurements (four repeats was conducted at the 12-day drift station in the central Arctic (~ 86°50´ N–87°20´ N and an average melt rate of 2 cm day−1, primarily bottom melt, was found. As compared with the 2005 data from the Healy/Oden Trans-Arctic Expedition (HOTRAX for the same sector but ~ 20 days later (9 August to 10 September, the summer 2010 was first-year ice dominant (vs. the multi-year ice dominant in 2005, 70% or less in mean ice concentration (vs. 90% in 2005, and 94–114 cm in mean ice thickness (vs. 150 cm in 2005. Those changes suggest the continuation of ice thinning, less concentration, and younger ice for the summer sea ice in the sector since 2007 when a record minimum sea ice extent was observed. Overall, the measurements provide a valuable dataset of sea ice morphological properties over the Arctic Pacific Sector in summer 2010 and can be used as a benchmark for measurements of future changes.

Bacterial Standing Stock, Activity, and Carbon Production during Formation and Growth of Sea Ice in the Weddell Sea, Antarctica.

Science.gov (United States)

Grossmann, S; Dieckmann, G S

1994-08-01

Bacterial response to formation and growth of sea ice was investigated during autumn in the northeastern Weddell Sea. Changes in standing stock, activity, and carbon production of bacteria were determined in successive stages of ice development. During initial ice formation, concentrations of bacterial cells, in the order of 1 x 10 to 3 x 10 liter, were not enhanced within the ice matrix. This suggests that physical enrichment of bacteria by ice crystals is not effective. Due to low concentrations of phytoplankton in the water column during freezing, incorporation of bacteria into newly formed ice via attachment to algal cells or aggregates was not recorded in this study. As soon as the ice had formed, the general metabolic activity of bacterial populations was strongly suppressed. Furthermore, the ratio of [H]leucine incorporation into proteins to [H]thymidine incorporation into DNA changed during ice growth. In thick pack ice, bacterial activity recovered and growth rates up to 0.6 day indicated actively dividing populations. However, biomass-specific utilization of organic compounds remained lower than in open water. Bacterial concentrations of up to 2.8 x 10 cells liter along with considerably enlarged cell volumes accumulated within thick pack ice, suggesting reduced mortality rates of bacteria within the small brine pores. In the course of ice development, bacterial carbon production increased from about 0.01 to 0.4 mug of C liter h. In thick ice, bacterial secondary production exceeded primary production of microalgae.

The impact of atmospheric mineral aerosol deposition on the albedo of snow & sea ice: are snow and sea ice optical properties more important than mineral aerosol optical properties?

Directory of Open Access Journals (Sweden)

M. L. Lamare

2016-01-01

Full Text Available Knowledge of the albedo of polar regions is crucial for understanding a range of climatic processes that have an impact on a global scale. Light-absorbing impurities in atmospheric aerosols deposited on snow and sea ice by aeolian transport absorb solar radiation, reducing albedo. Here, the effects of five mineral aerosol deposits reducing the albedo of polar snow and sea ice are considered. Calculations employing a coupled atmospheric and snow/sea ice radiative-transfer model (TUV-snow show that the effects of mineral aerosol deposits are strongly dependent on the snow or sea ice type rather than the differences between the aerosol optical characteristics. The change in albedo between five different mineral aerosol deposits with refractive indices varying by a factor of 2 reaches a maximum of 0.0788, whereas the difference between cold polar snow and melting sea ice is 0.8893 for the same mineral loading. Surprisingly, the thickness of a surface layer of snow or sea ice loaded with the same mass ratio of mineral dust has little effect on albedo. On the contrary, the surface albedo of two snowpacks of equal depth, containing the same mineral aerosol mass ratio, is similar, whether the loading is uniformly distributed or concentrated in multiple layers, regardless of their position or spacing. The impact of mineral aerosol deposits is much larger on melting sea ice than on other types of snow and sea ice. Therefore, the higher input of shortwave radiation during the summer melt cycle associated with melting sea ice accelerates the melt process.

Caisson structures in the Beaufort Sea 1982-1990 : characteristics, instrumentation and ice loads

Energy Technology Data Exchange (ETDEWEB)

Timco, G.W.; Johnston, M.E. [National Research Council of Canada, Ottawa, ON (Canada). Canadian Hydraulics Centre

2002-11-01

This report presents a comprehensive overview of the instrumentation, characteristics and measured ice loads on the caisson structures used for exploratory drilling in the Canadian Beaufort Sea during the 1970s and 1980s. The focus was placed on the Tarsiut Caissons, the Single Steel Drilling Caisson (SSDC), the Caisson Retained Island (CRI), and the Molikpaq. Details on the ice-load measuring instrumentation were provided for each of the drill sites featuring an ice-load measurement program. The results of global loads on the structures were presented as a Line Load (global load per width of the structure) and the Global Pressure (line load per ice thickness). The authors showed that global loads were a function of the ice macrostructure (level first-year sea ice, multi-year ice, first-year ridges, hummock fields, isolated floes). A general increase in the Line Load with increasing ice thickness was revealed through analysis. There was considerable scatter in the data, and the authors explained it by examining the failure mode of the ice during the interaction process. 36 refs., 4 tabs., 57 figs.

Arctic Sea Ice in Transformation: A Review of Recent Observed Changes and Impacts on Biology and Human Activity

Science.gov (United States)

Meier, Walter N.; Hovelsrud, Greta K.; van Oort, Bob E. H.; Key, Jeffrey R.; Kovacs, Kit M.; Michel, Christine; Haas, Christian; Granskog, Mats A.; Gerland, Sebastian; Perovich, Donald K.;

Do pelagic grazers benefit from sea ice? Insights from the Antarctic sea ice proxy IPSO25

Directory of Open Access Journals (Sweden)

K. Schmidt

2018-04-01

Full Text Available Sea ice affects primary production in polar regions in multiple ways. It can dampen water column productivity by reducing light or nutrient supply, provide a habitat for ice algae and condition the marginal ice zone (MIZ for phytoplankton blooms on its seasonal retreat. The relative importance of three different carbon sources (sea ice derived, sea ice conditioned, non-sea-ice associated for the polar food web is not well understood, partly due to the lack of methods that enable their unambiguous distinction. Here we analysed two highly branched isoprenoid (HBI biomarkers to trace sea-ice-derived and sea-ice-conditioned carbon in Antarctic krill (Euphausia superba and relate their concentrations to the grazers' body reserves, growth and recruitment. During our sampling in January–February 2003, the proxy for sea ice diatoms (a di-unsaturated HBI termed IPSO25, δ13C  =  −12.5 ± 3.3 ‰ occurred in open waters of the western Scotia Sea, where seasonal ice retreat was slow. In suspended matter from surface waters, IPSO25 was present at a few stations close to the ice edge, but in krill the marker was widespread. Even at stations that had been ice-free for several weeks, IPSO25 was found in krill stomachs, suggesting that they gathered the ice-derived algae from below the upper mixed layer. Peak abundances of the proxy for MIZ diatoms (a tri-unsaturated HBI termed HBI III, δ13C  =  −42.2 ± 2.4 ‰ occurred in regions of fast sea ice retreat and persistent salinity-driven stratification in the eastern Scotia Sea. Krill sampled in the area defined by the ice edge bloom likewise contained high amounts of HBI III. As indicators for the grazer's performance we used the mass–length ratio, size of digestive gland and growth rate for krill, and recruitment for the biomass-dominant calanoid copepods Calanoides acutus and Calanus propinquus. These indices consistently point to blooms in the MIZ as an important feeding

Do pelagic grazers benefit from sea ice? Insights from the Antarctic sea ice proxy IPSO25

Science.gov (United States)

Schmidt, Katrin; Brown, Thomas A.; Belt, Simon T.; Ireland, Louise C.; Taylor, Kyle W. R.; Thorpe, Sally E.; Ward, Peter; Atkinson, Angus

2018-04-01

Sea ice affects primary production in polar regions in multiple ways. It can dampen water column productivity by reducing light or nutrient supply, provide a habitat for ice algae and condition the marginal ice zone (MIZ) for phytoplankton blooms on its seasonal retreat. The relative importance of three different carbon sources (sea ice derived, sea ice conditioned, non-sea-ice associated) for the polar food web is not well understood, partly due to the lack of methods that enable their unambiguous distinction. Here we analysed two highly branched isoprenoid (HBI) biomarkers to trace sea-ice-derived and sea-ice-conditioned carbon in Antarctic krill (Euphausia superba) and relate their concentrations to the grazers' body reserves, growth and recruitment. During our sampling in January-February 2003, the proxy for sea ice diatoms (a di-unsaturated HBI termed IPSO25, δ13C = -12.5 ± 3.3 ‰) occurred in open waters of the western Scotia Sea, where seasonal ice retreat was slow. In suspended matter from surface waters, IPSO25 was present at a few stations close to the ice edge, but in krill the marker was widespread. Even at stations that had been ice-free for several weeks, IPSO25 was found in krill stomachs, suggesting that they gathered the ice-derived algae from below the upper mixed layer. Peak abundances of the proxy for MIZ diatoms (a tri-unsaturated HBI termed HBI III, δ13C = -42.2 ± 2.4 ‰) occurred in regions of fast sea ice retreat and persistent salinity-driven stratification in the eastern Scotia Sea. Krill sampled in the area defined by the ice edge bloom likewise contained high amounts of HBI III. As indicators for the grazer's performance we used the mass-length ratio, size of digestive gland and growth rate for krill, and recruitment for the biomass-dominant calanoid copepods Calanoides acutus and Calanus propinquus. These indices consistently point to blooms in the MIZ as an important feeding ground for pelagic grazers. Even though ice

Sea ice roughness: the key for predicting Arctic summer ice albedo

Science.gov (United States)

Landy, J.; Ehn, J. K.; Tsamados, M.; Stroeve, J.; Barber, D. G.

2017-12-01

Although melt ponds on Arctic sea ice evolve in stages, ice with smoother surface topography typically allows the pond water to spread over a wider area, reducing the ice-albedo and accelerating further melt. Building on this theory, we simulated the distribution of meltwater on a range of statistically-derived topographies to develop a quantitative relationship between premelt sea ice surface roughness and summer ice albedo. Our method, previously applied to ICESat observations of the end-of-winter sea ice roughness, could account for 85% of the variance in AVHRR observations of the summer ice-albedo [Landy et al., 2015]. Consequently, an Arctic-wide reduction in sea ice roughness over the ICESat operational period (from 2003 to 2008) explained a drop in ice-albedo that resulted in a 16% increase in solar heat input to the sea ice cover. Here we will review this work and present new research linking pre-melt sea ice surface roughness observations from Cryosat-2 to summer sea ice albedo over the past six years, examining the potential of winter roughness as a significant new source of sea ice predictability. We will further evaluate the possibility for high-resolution (kilometre-scale) forecasts of summer sea ice albedo from waveform-level Cryosat-2 roughness data in the landfast sea ice zone of the Canadian Arctic. Landy, J. C., J. K. Ehn, and D. G. Barber (2015), Albedo feedback enhanced by smoother Arctic sea ice, Geophys. Res. Lett., 42, 10,714-10,720, doi:10.1002/2015GL066712.

Estimates of ikaite export from sea ice to the underlying seawater in a sea ice-seawater mesocosm

Science.gov (United States)

Geilfus, Nicolas-Xavier; Galley, Ryan J.; Else, Brent G. T.; Campbell, Karley; Papakyriakou, Tim; Crabeck, Odile; Lemes, Marcos; Delille, Bruno; Rysgaard, Søren

2016-09-01

The precipitation of ikaite and its fate within sea ice is still poorly understood. We quantify temporal inorganic carbon dynamics in sea ice from initial formation to its melt in a sea ice-seawater mesocosm pool from 11 to 29 January 2013. Based on measurements of total alkalinity (TA) and total dissolved inorganic carbon (TCO2), the main processes affecting inorganic carbon dynamics within sea ice were ikaite precipitation and CO2 exchange with the atmosphere. In the underlying seawater, the dissolution of ikaite was the main process affecting inorganic carbon dynamics. Sea ice acted as an active layer, releasing CO2 to the atmosphere during the growth phase, taking up CO2 as it melted and exporting both ikaite and TCO2 into the underlying seawater during the whole experiment. Ikaite precipitation of up to 167 µmol kg-1 within sea ice was estimated, while its export and dissolution into the underlying seawater was responsible for a TA increase of 64-66 µmol kg-1 in the water column. The export of TCO2 from sea ice to the water column increased the underlying seawater TCO2 by 43.5 µmol kg-1, suggesting that almost all of the TCO2 that left the sea ice was exported to the underlying seawater. The export of ikaite from the ice to the underlying seawater was associated with brine rejection during sea ice growth, increased vertical connectivity in sea ice due to the upward percolation of seawater and meltwater flushing during sea ice melt. Based on the change in TA in the water column around the onset of sea ice melt, more than half of the total ikaite precipitated in the ice during sea ice growth was still contained in the ice when the sea ice began to melt. Ikaite crystal dissolution in the water column kept the seawater pCO2 undersaturated with respect to the atmosphere in spite of increased salinity, TA and TCO2 associated with sea ice growth. Results indicate that ikaite export from sea ice and its dissolution in the underlying seawater can potentially hamper

On the Arctic Ocean ice thickness response to changes in the external forcing

Energy Technology Data Exchange (ETDEWEB)

Stranne, Christian; Bjoerk, Goeran [University of Gothenburg, Department of Earth Sciences, Box 460, Goeteborg (Sweden)

2012-12-15

Submarine and satellite observations show that the Arctic Ocean ice cover has undergone a large thickness reduction and a decrease in the areal extent during the last decades. Here the response of the Arctic Ocean ice cover to changes in the poleward atmospheric energy transport, F{sub wall}, is investigated using coupled atmosphere-ice-ocean column models. Two models with highly different complexity are used in order to illustrate the importance of different internal processes and the results highlight the dramatic effects of the negative ice thickness - ice volume export feedback and the positive surface albedo feedback. The steady state ice thickness as a function of F{sub wall} is determined for various model setups and defines what we call ice thickness response curves. When a variable surface albedo and snow precipitation is included, a complex response curve appears with two distinct regimes: a perennial ice cover regime with a fairly linear response and a less responsive seasonal ice cover regime. The two regimes are separated by a steep transition associated with surface albedo feedback. The associated hysteresis is however small, indicating that the Arctic climate system does not have an irreversible tipping point behaviour related to the surface albedo feedback. The results are discussed in the context of the recent reduction of the Arctic sea ice cover. A new mechanism related to regional and temporal variations of the ice divergence within the Arctic Ocean is presented as an explanation for the observed regional variation of the ice thickness reduction. Our results further suggest that the recent reduction in areal ice extent and loss of multiyear ice is related to the albedo dependent transition between seasonal and perennial ice i.e. large areas of the Arctic Ocean that has previously been dominated by multiyear ice might have been pushed below a critical mean ice thickness, corresponding to the above mentioned transition, and into a state dominated

Modeling and analysis of Off-beam lidar returns from thick clouds, snow, and sea ice

International Nuclear Information System (INIS)

Varnai, T.; Cahalan, R. F.

2009-01-01

A group of recently developed lidar (laser ranging and detection) systems can detect signals returning from several wide field-of-views, allowing them to observe the way laser pulses spread in thick media. The new capability enabled accurate measurements of cloud geometrical thickness and promises improved measurements of internal cloud structure as well as snow and sea ice thickness. This paper presents a brief overview of radiation transport simulation techniques and data analysis methods that were developed for multi-view lidar applications and for and considering multiple scattering effects in single-view lidar data. In discussing methods for simulating the three-dimensional spread of lidar pulses, we present initial results from Phase 3 of the Intercomparison of 3-D Radiation Codes (I3RC) project. The results reveal some differences in the capabilities of participating models, while good agreement among several models provides consensus results suitable for testing future models. Detailed numerical results are available at the I3RC web site at http://i3rc.gsfc.nasa. gov. In considering data analysis methods, we focus on the Thickness from Off-beam Returns (THOR) lidar. THOR proved successful in measuring the geometrical thickness of optically thick clouds; here we focus on its potential for retrieving the vertical profile of scattering coefficient in clouds and for measuring snow thickness. Initial observations suggest considerable promise but also reveal some limitations, for example that the maximum retrievable snow thickness drops from about 0.5 m in pristine areas to about 0.15 m in polluted regions. (authors)

Parameters Comparsion of Leads Detection in Arctic Sea Ice Using CRYOSAT-2 Waveform Data

Science.gov (United States)

Li, J.; Zhang, S.; Xiao, F.; Zhu, C.; Zhang, Y.; Zhu, T.; Yuan, L.

2018-04-01

Leads are only a small part of the polar sea ice structure, but they play a dominant role on the turbulence exchange between the ocean and the atmosphere, they are also important factors about sea ice thickness inversion. Since the early 2000s, Satellite altimetry has been applied to monitor the Arctic sea ice thickness, Satellite altimetry data can be used to distinguish leads and sea ice. In this paper, four parameters including Pulse peakiness (PP), stack standard deviation (SSD), stack kurtosis (SKU) and stack skewness (SSK) are extracted from CryoSat-2 satellite altimetry waveform data. The four parameters are combined into five combinations (PP, PP&SSD, PP&SSD&SKU, PP&SSD&SSK, PP&SSD&SSK&SKU) with constrain conditions to detect the leads. The results of the five methods are compared with MODIS (moderate-resolution imagining spectroradiometer) images and show that, the combination of PP&SSD is better than the single PP, the rest of combinations are the same as the combination of PP&SSD. It turns out, there is no promotion when we add SSK and SKU, successively or simultaneously.

Quantifying Seasonal Skill In Coupled Sea Ice Models Using Freeboard Measurements From Spaceborne Laser Altimeters

Science.gov (United States)

2016-06-01

Data collection periods during the ICESat mission were influenced by the presence of atmospheric clouds and aerosols, and also LASER malfunctions. Upon...measurements after that satellite is launched next year. 14. subject terms Arctic, climate change, Regional Arctic System Model, altimetry...measurements, sea ice, sea ice thickness, freeboard, ICESat, ICESat-2, climate model, coupled model, Operation IceBridge 15. NUMBER OF PAGES 147 16

Arctic sea ice decline: Projected changes in timing and extent of sea ice in the Bering and Chukchi Seas

Science.gov (United States)

Douglas, David C.

2010-01-01

The Arctic region is warming faster than most regions of the world due in part to increasing greenhouse gases and positive feedbacks associated with the loss of snow and ice cover. One consequence has been a rapid decline in Arctic sea ice over the past 3 decades?a decline that is projected to continue by state-of-the-art models. Many stakeholders are therefore interested in how global warming may change the timing and extent of sea ice Arctic-wide, and for specific regions. To inform the public and decision makers of anticipated environmental changes, scientists are striving to better understand how sea ice influences ecosystem structure, local weather, and global climate. Here, projected changes in the Bering and Chukchi Seas are examined because sea ice influences the presence of, or accessibility to, a variety of local resources of commercial and cultural value. In this study, 21st century sea ice conditions in the Bering and Chukchi Seas are based on projections by 18 general circulation models (GCMs) prepared for the fourth reporting period by the Intergovernmental Panel on Climate Change (IPCC) in 2007. Sea ice projections are analyzed for each of two IPCC greenhouse gas forcing scenarios: the A1B `business as usual? scenario and the A2 scenario that is somewhat more aggressive in its CO2 emissions during the second half of the century. A large spread of uncertainty among projections by all 18 models was constrained by creating model subsets that excluded GCMs that poorly simulated the 1979-2008 satellite record of ice extent and seasonality. At the end of the 21st century (2090-2099), median sea ice projections among all combinations of model ensemble and forcing scenario were qualitatively similar. June is projected to experience the least amount of sea ice loss among all months. For the Chukchi Sea, projections show extensive ice melt during July and ice-free conditions during August, September, and October by the end of the century, with high agreement

Sea ice thermohaline dynamics and biogeochemistry in the Arctic Ocean: Empirical and model results

Science.gov (United States)

Duarte, Pedro; Meyer, Amelie; Olsen, Lasse M.; Kauko, Hanna M.; Assmy, Philipp; Rösel, Anja; Itkin, Polona; Hudson, Stephen R.; Granskog, Mats A.; Gerland, Sebastian; Sundfjord, Arild; Steen, Harald; Hop, Haakon; Cohen, Lana; Peterson, Algot K.; Jeffery, Nicole; Elliott, Scott M.; Hunke, Elizabeth C.; Turner, Adrian K.

2017-07-01

Large changes in the sea ice regime of the Arctic Ocean have occurred over the last decades justifying the development of models to forecast sea ice physics and biogeochemistry. The main goal of this study is to evaluate the performance of the Los Alamos Sea Ice Model (CICE) to simulate physical and biogeochemical properties at time scales of a few weeks and to use the model to analyze ice algal bloom dynamics in different types of ice. Ocean and atmospheric forcing data and observations of the evolution of the sea ice properties collected from 18 April to 4 June 2015, during the Norwegian young sea ICE expedition, were used to test the CICE model. Our results show the following: (i) model performance is reasonable for sea ice thickness and bulk salinity; good for vertically resolved temperature, vertically averaged Chl a concentrations, and standing stocks; and poor for vertically resolved Chl a concentrations. (ii) Improving current knowledge about nutrient exchanges, ice algal recruitment, and motion is critical to improve sea ice biogeochemical modeling. (iii) Ice algae may bloom despite some degree of basal melting. (iv) Ice algal motility driven by gradients in limiting factors is a plausible mechanism to explain their vertical distribution. (v) Different ice algal bloom and net primary production (NPP) patterns were identified in the ice types studied, suggesting that ice algal maximal growth rates will increase, while sea ice vertically integrated NPP and biomass will decrease as a result of the predictable increase in the area covered by refrozen leads in the Arctic Ocean.

On Sea Ice Characterisation By Multi-Frequency SAR

Science.gov (United States)

Grahn, Jakob; Brekke, Camilla; Eltoft, Torbjorn; Holt, Benjamin

2013-12-01

By means of polarimetric target decomposition, quad-pol SAR data of sea ice is analysed at two frequency bands. In particular, the non negative eigenvalue decomposition (NNED) is applied on L- and C-band NASA/JPL AIR- SAR data acquired over the Beaufort sea in 2004. The de- composition separates the scattered radar signal into three types, dominated by double, volume and single bounce scattering respectively. Using ground truth derived from RADARSAT-1 and meteorological data, we investigate how the different frequency bands compare in terms of these scattering types. The ground truth contains multi year ice and three types of first year ice of different age and thickness. We find that C-band yields a higher scattered intensity in most ice and scattering types, as well as a more homogeneous intensity. L-band on the other hand yields more pronounced deformation features, such as ridges. The mean intensity contrast between the two thinnest ice types is highest in the double scattering component of C- band, although the contrast of the total signal is greater in L-band. This may indicate that the choice of polarimetric parameters is important for discriminating thin ice types.

Pan-Arctic sea ice-algal chl a biomass and suitable habitat are largely underestimated for multiyear ice.

Science.gov (United States)

Lange, Benjamin A; Flores, Hauke; Michel, Christine; Beckers, Justin F; Bublitz, Anne; Casey, John Alec; Castellani, Giulia; Hatam, Ido; Reppchen, Anke; Rudolph, Svenja A; Haas, Christian

2017-11-01

There is mounting evidence that multiyear ice (MYI) is a unique component of the Arctic Ocean and may play a more important ecological role than previously assumed. This study improves our understanding of the potential of MYI as a suitable habitat for sea ice algae on a pan-Arctic scale. We sampled sea ice cores from MYI and first-year sea ice (FYI) within the Lincoln Sea during four consecutive spring seasons. This included four MYI hummocks with a mean chl a biomass of 2.0 mg/m 2 , a value significantly higher than FYI and MYI refrozen ponds. Our results support the hypothesis that MYI hummocks can host substantial ice-algal biomass and represent a reliable ice-algal habitat due to the (quasi-) permanent low-snow surface of these features. We identified an ice-algal habitat threshold value for calculated light transmittance of 0.014%. Ice classes and coverage of suitable ice-algal habitat were determined from snow and ice surveys. These ice classes and associated coverage of suitable habitat were applied to pan-Arctic CryoSat-2 snow and ice thickness data products. This habitat classification accounted for the variability of the snow and ice properties and showed an areal coverage of suitable ice-algal habitat within the MYI-covered region of 0.54 million km 2 (8.5% of total ice area). This is 27 times greater than the areal coverage of 0.02 million km 2 (0.3% of total ice area) determined using the conventional block-model classification, which assigns single-parameter values to each grid cell and does not account for subgrid cell variability. This emphasizes the importance of accounting for variable snow and ice conditions in all sea ice studies. Furthermore, our results indicate the loss of MYI will also mean the loss of reliable ice-algal habitat during spring when food is sparse and many organisms depend on ice-algae. © 2017 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

Extreme Low Light Requirement for Algae Growth Underneath Sea Ice: A Case Study From Station Nord, NE Greenland

Science.gov (United States)

Hancke, Kasper; Lund-Hansen, Lars C.; Lamare, Maxim L.; Højlund Pedersen, Stine; King, Martin D.; Andersen, Per; Sorrell, Brian K.

2018-02-01

Microalgae colonizing the underside of sea ice in spring are a key component of the Arctic foodweb as they drive early primary production and transport of carbon from the atmosphere to the ocean interior. Onset of the spring bloom of ice algae is typically limited by the availability of light, and the current consensus is that a few tens-of-centimeters of snow is enough to prevent sufficient solar radiation to reach underneath the sea ice. We challenge this consensus, and investigated the onset and the light requirement of an ice algae spring bloom, and the importance of snow optical properties for light penetration. Colonization by ice algae began in May under >1 m of first-year sea ice with ˜1 m thick snow cover on top, in NE Greenland. The initial growth of ice algae began at extremely low irradiance (automated high-frequency temperature profiles. We propose that changes in snow optical properties, caused by temperature-driven snow metamorphosis, was the primary driver for allowing sufficient light to penetrate through the thick snow and initiate algae growth below the sea ice. This was supported by radiative-transfer modeling of light attenuation. Implications are an earlier productivity by ice algae in Arctic sea ice than recognized previously.

Arctic landfast sea ice

Science.gov (United States)

Konig, Christof S.

Landfast ice is sea ice which forms and remains fixed along a coast, where it is attached either to the shore, or held between shoals or grounded icebergs. Landfast ice fundamentally modifies the momentum exchange between atmosphere and ocean, as compared to pack ice. It thus affects the heat and freshwater exchange between air and ocean and impacts on the location of ocean upwelling and downwelling zones. Further, the landfast ice edge is essential for numerous Arctic mammals and Inupiat who depend on them for their subsistence. The current generation of sea ice models is not capable of reproducing certain aspects of landfast ice formation, maintenance, and disintegration even when the spatial resolution would be sufficient to resolve such features. In my work I develop a new ice model that permits the existence of landfast sea ice even in the presence of offshore winds, as is observed in mature. Based on viscous-plastic as well as elastic-viscous-plastic ice dynamics I add tensile strength to the ice rheology and re-derive the equations as well as numerical methods to solve them. Through numerical experiments on simplified domains, the effects of those changes are demonstrated. It is found that the modifications enable landfast ice modeling, as desired. The elastic-viscous-plastic rheology leads to initial velocity fluctuations within the landfast ice that weaken the ice sheet and break it up much faster than theoretically predicted. Solving the viscous-plastic rheology using an implicit numerical method avoids those waves and comes much closer to theoretical predictions. Improvements in landfast ice modeling can only verified in comparison to observed data. I have extracted landfast sea ice data of several decades from several sources to create a landfast sea ice climatology that can be used for that purpose. Statistical analysis of the data shows several factors that significantly influence landfast ice distribution: distance from the coastline, ocean depth, as

Sea ice dynamics across the Mid-Pleistocene transition in the Bering Sea.

Science.gov (United States)

Detlef, H; Belt, S T; Sosdian, S M; Smik, L; Lear, C H; Hall, I R; Cabedo-Sanz, P; Husum, K; Kender, S

2018-03-05

Sea ice and associated feedback mechanisms play an important role for both long- and short-term climate change. Our ability to predict future sea ice extent, however, hinges on a greater understanding of past sea ice dynamics. Here we investigate sea ice changes in the eastern Bering Sea prior to, across, and after the Mid-Pleistocene transition (MPT). The sea ice record, based on the Arctic sea ice biomarker IP 25 and related open water proxies from the International Ocean Discovery Program Site U1343, shows a substantial increase in sea ice extent across the MPT. The occurrence of late-glacial/deglacial sea ice maxima are consistent with sea ice/land ice hysteresis and land-glacier retreat via the temperature-precipitation feedback. We also identify interactions of sea ice with phytoplankton growth and ocean circulation patterns, which have important implications for glacial North Pacific Intermediate Water formation and potentially North Pacific abyssal carbon storage.

Evaluation of the limit ice thickness for the hull of various Finnish-Swedish ice class vessels navigating in the Russian Arctic

Directory of Open Access Journals (Sweden)

Pentti Kujala

2018-05-01

Full Text Available Selection of suitable ice class for ships operation is an important but not simple task. The increased exploitation of the Polar waters, both seasonal periods and geographical areas, as well as the introduction of new international design standards such as Polar Code, reduces the relevancy of using existing experience as basis for the selection, and new methods and knowledge have to be developed. This paper will analyse what can be the limiting ice thickness for ships navigating in the Russian Arctic and designed according to the Finnish-Swedish ice class rules. The permanent deformations of ice-strengthened shell structures for various ice classes is determined using MT Uikku as the typical size of a vessel navigating in ice. The ice load in various conditions is determined using the ARCDEV data from the winter 1998 as the basic database. By comparing the measured load in various ice conditions with the serviceability limit state of the structures, the limiting ice thickness for various ice classes is determined. The database for maximum loads includes 3-weeks ice load measurements during April 1998 on the Kara Sea mainly by icebreaker assistance. Gumbel 1 distribution is fitted on the measured 20 min maximum values and the data is divided into various classes using ship speed, ice thickness and ice concentration as the main parameters. Results encouragingly show that present designs are safer than assumed in the Polar Code suggesting that assisted operation in Arctic conditions is feasible in rougher conditions than indicated in the Polar Code. Keywords: Loads, Serviceability, Limit ice thickness, Polar code

The Hamburg sea-ice model

International Nuclear Information System (INIS)

Stoessel, A.; Owens, W.B.

1992-10-01

The general purpose of the model is to simulate sea ice dynamically as well as thermodynamically. Pure sea-ice models are generally highly dependent on the specified atmospheric and oceanic forcing, especially on the winds and the vertical oceanic heat flux. In order to reduce these dependencies, the sea-ice [SI] model was extended to optionally include a prognostic oceanic mixed layer [OML], a diagnostic atmospheric surface layer [ASL] and/or a diagnostic atmospheric boundary layer [ABL], thus shifting the forcing levels further away from the surface (i.e. from the sea ice) and simultaneously providing a modification of the forcing considering boundary-layer adjustments to the instantaneous sea-ice conditions given by the SI model. A further major extension of the model is the (optional) employment of a prognostic snow layer. The special application characterising the present code was sea-ice simulation in the Southern Ocean, employing a spherical, circumpolar grid with a resolution of 2.5 in latitude and 5 in longitude, extending from 50 S to 80 S and using a daily time step. (orig.)

Sea-ice indicators of polar bear habitat

Science.gov (United States)

Stern, Harry L.; Laidre, Kristin L.

2016-09-01

Nineteen subpopulations of polar bears (Ursus maritimus) are found throughout the circumpolar Arctic, and in all regions they depend on sea ice as a platform for traveling, hunting, and breeding. Therefore polar bear phenology - the cycle of biological events - is linked to the timing of sea-ice retreat in spring and advance in fall. We analyzed the dates of sea-ice retreat and advance in all 19 polar bear subpopulation regions from 1979 to 2014, using daily sea-ice concentration data from satellite passive microwave instruments. We define the dates of sea-ice retreat and advance in a region as the dates when the area of sea ice drops below a certain threshold (retreat) on its way to the summer minimum or rises above the threshold (advance) on its way to the winter maximum. The threshold is chosen to be halfway between the historical (1979-2014) mean September and mean March sea-ice areas. In all 19 regions there is a trend toward earlier sea-ice retreat and later sea-ice advance. Trends generally range from -3 to -9 days decade-1 in spring and from +3 to +9 days decade-1 in fall, with larger trends in the Barents Sea and central Arctic Basin. The trends are not sensitive to the threshold. We also calculated the number of days per year that the sea-ice area exceeded the threshold (termed ice-covered days) and the average sea-ice concentration from 1 June through 31 October. The number of ice-covered days is declining in all regions at the rate of -7 to -19 days decade-1, with larger trends in the Barents Sea and central Arctic Basin. The June-October sea-ice concentration is declining in all regions at rates ranging from -1 to -9 percent decade-1. These sea-ice metrics (or indicators of habitat change) were designed to be useful for management agencies and for comparative purposes among subpopulations. We recommend that the National Climate Assessment include the timing of sea-ice retreat and advance in future reports.

Some Results on Sea Ice Rheology for the Seasonal Ice Zone, Obtained from the Deformation Field of Sea Ice Drift Pattern

Science.gov (United States)

Toyota, T.; Kimura, N.

2017-12-01

Sea ice rheology which relates sea ice stress to the large-scale deformation of the ice cover has been a big issue to numerical sea ice modelling. At present the treatment of internal stress within sea ice area is based mostly on the rheology formulated by Hibler (1979), where the whole sea ice area behaves like an isotropic and plastic matter under the ordinary stress with the yield curve given by an ellipse with an aspect ratio (e) of 2, irrespective of sea ice area and horizontal resolution of the model. However, this formulation was initially developed to reproduce the seasonal variation of the perennial ice in the Arctic Ocean. As for its applicability to the seasonal ice zones (SIZ), where various types of sea ice are present, it still needs validation from observational data. In this study, the validity of this rheology was examined for the Sea of Okhotsk ice, typical of the SIZ, based on the AMSR-derived ice drift pattern in comparison with the result obtained for the Beaufort Sea. To examine the dependence on a horizontal scale, the coastal radar data operated near the Hokkaido coast, Japan, were also used. Ice drift pattern was obtained by a maximum cross-correlation method with grid spacings of 37.5 km from the 89 GHz brightness temperature of AMSR-E for the entire Sea of Okhotsk and the Beaufort Sea and 1.3 km from the coastal radar for the near-shore Sea of Okhotsk. The validity of this rheology was investigated from a standpoint of work rate done by deformation field, following the theory of Rothrock (1975). In analysis, the relative rates of convergence were compared between theory and observation to check the shape of yield curve, and the strain ellipse at each grid cell was estimated to see the horizontal variation of deformation field. The result shows that the ellipse of e=1.7-2.0 as the yield curve represents the observed relative conversion rates well for all the ice areas. Since this result corresponds with the yield criterion by Tresca and

An Evaluation of Sea Ice Deformation and Its Spatial Characteristics from the Regional Arctic System Model

Science.gov (United States)

2012-12-01

Ice Thickness and Age It has long been recognized that many physical properties of sea ice depend upon the thickness ( Thorndike et al. 1975). Three...within the ice (Kovacs 1996). Thorndike et al. (1975) showed that the approximation, used in many ice models even today, for the compressive stress...in the wintertime geopotential height and temperature fields. Geophys. Res. Lett., 25, 1297–1300. Thorndike , A.S., D.A. Rothrock, G.A. Maykut, and

Deglacial climate modulated by the storage and release of Arctic sea ice

Science.gov (United States)

Condron, A.; Coletti, A. J.; Bradley, R. S.

2017-12-01

Periods of abrupt climate cooling during the last deglaciation (20 - 8 kyr ago) are often attributed to glacial outburst floods slowing the Atlantic meridional overturning circulation (AMOC). Here, we present results from a series of climate model simulations showing that the episodic break-up and mobilization of thick, perennial, Arctic sea ice during this time would have released considerable volumes of freshwater directly to the Nordic Seas, where processes regulating large-scale climate occur. Massive sea ice export events to the North Atlantic are generated whenever the transport of sea ice is enhanced, either by changes in atmospheric circulation, rising sea level submerging the Bering land bridge, or glacial outburst floods draining into the Arctic Ocean from the Mackenzie River. We find that the volumes of freshwater released to the Nordic Seas are similar to, or larger than, those estimated to have come from terrestrial outburst floods, including the discharge at the onset of the Younger Dryas. Our results provide the first evidence that the storage and release of Arctic sea ice helped drive deglacial climate change by modulating the strength of the AMOC.

PARAMETERS COMPARSION OF LEADS DETECTION IN ARCTIC SEA ICE USING CRYOSAT-2 WAVEFORM DATA

Directory of Open Access Journals (Sweden)

J. Li

2018-04-01

Full Text Available Leads are only a small part of the polar sea ice structure, but they play a dominant role on the turbulence exchange between the ocean and the atmosphere, they are also important factors about sea ice thickness inversion. Since the early 2000s, Satellite altimetry has been applied to monitor the Arctic sea ice thickness, Satellite altimetry data can be used to distinguish leads and sea ice. In this paper, four parameters including Pulse peakiness (PP, stack standard deviation (SSD, stack kurtosis (SKU and stack skewness (SSK are extracted from CryoSat-2 satellite altimetry waveform data. The four parameters are combined into five combinations (PP, PP&SSD, PP&SSD&SKU, PP&SSD&SSK, PP&SSD&SSK&SKU with constrain conditions to detect the leads. The results of the five methods are compared with MODIS (moderate-resolution imagining spectroradiometer images and show that, the combination of PP&SSD is better than the single PP, the rest of combinations are the same as the combination of PP&SSD. It turns out, there is no promotion when we add SSK and SKU, successively or simultaneously.

Sea-ice indicators of polar bear habitat

Directory of Open Access Journals (Sweden)

H. L. Stern

2016-09-01

Full Text Available Nineteen subpopulations of polar bears (Ursus maritimus are found throughout the circumpolar Arctic, and in all regions they depend on sea ice as a platform for traveling, hunting, and breeding. Therefore polar bear phenology – the cycle of biological events – is linked to the timing of sea-ice retreat in spring and advance in fall. We analyzed the dates of sea-ice retreat and advance in all 19 polar bear subpopulation regions from 1979 to 2014, using daily sea-ice concentration data from satellite passive microwave instruments. We define the dates of sea-ice retreat and advance in a region as the dates when the area of sea ice drops below a certain threshold (retreat on its way to the summer minimum or rises above the threshold (advance on its way to the winter maximum. The threshold is chosen to be halfway between the historical (1979–2014 mean September and mean March sea-ice areas. In all 19 regions there is a trend toward earlier sea-ice retreat and later sea-ice advance. Trends generally range from −3 to −9 days decade−1 in spring and from +3 to +9 days decade−1 in fall, with larger trends in the Barents Sea and central Arctic Basin. The trends are not sensitive to the threshold. We also calculated the number of days per year that the sea-ice area exceeded the threshold (termed ice-covered days and the average sea-ice concentration from 1 June through 31 October. The number of ice-covered days is declining in all regions at the rate of −7 to −19 days decade−1, with larger trends in the Barents Sea and central Arctic Basin. The June–October sea-ice concentration is declining in all regions at rates ranging from −1 to −9 percent decade−1. These sea-ice metrics (or indicators of habitat change were designed to be useful for management agencies and for comparative purposes among subpopulations. We recommend that the National Climate Assessment include the timing of sea-ice retreat and advance in

[Reflectance of sea ice in Liaodong Bay].

Science.gov (United States)

Xu, Zhan-tang; Yang, Yue-zhong; Wang, Gui-fen; Cao, Wen-xi; Kong, Xiang-peng

2010-07-01

In the present study, the relationships between sea ice albedo and the bidirectional reflectance distribution in Liaodong Bay were investigated. The results indicate that: (1) sea ice albedo alpha(lambda) is closely related to the components of sea ice, the higher the particulate concentration in sea ice surface is, the lower the sea ice albedo alpha(lambda) is. On the contrary, the higher the bubble concentration in sea ice is, the higher sea ice albedo alpha(lambda) is. (2) Sea ice albedo alpha(lambda) is similar to the bidirectional reflectance factor R(f) when the probe locates at nadir. The R(f) would increase with the increase in detector zenith theta, and the correlation between R(f) and the detector azimuth would gradually increase. When the theta is located at solar zenith 63 degrees, the R(f) would reach the maximum, and the strongest correlation is also shown between the R(f) and the detector azimuth. (3) Different types of sea ice would have the different anisotropic reflectance factors.

Propagation of Uncertainties in Sea Ice Thickness Calculations From Basin-Scale Operational Observations: A Report Prepared for the International Ice Charting Working Group and the National/Naval Ice Center

National Research Council Canada - National Science Library

Geiger, Cathleen A

2006-01-01

Sea ice serves as a natural flux monitor of the global heat balance. This capability is attributed to the unique location of sea ice at the interface of the world's two largest circulation systems the air and ocean...

Determination of Arctic sea ice variability modes on interannual timescales via nonhierarchical clustering

Science.gov (United States)

Fučkar, Neven-Stjepan; Guemas, Virginie; Massonnet, François; Doblas-Reyes, Francisco

2015-04-01

Over the modern observational era, the northern hemisphere sea ice concentration, age and thickness have experienced a sharp long-term decline superimposed with strong internal variability. Hence, there is a crucial need to identify robust patterns of Arctic sea ice variability on interannual timescales and disentangle them from the long-term trend in noisy datasets. The principal component analysis (PCA) is a versatile and broadly used method for the study of climate variability. However, the PCA has several limiting aspects because it assumes that all modes of variability have symmetry between positive and negative phases, and suppresses nonlinearities by using a linear covariance matrix. Clustering methods offer an alternative set of dimension reduction tools that are more robust and capable of taking into account possible nonlinear characteristics of a climate field. Cluster analysis aggregates data into groups or clusters based on their distance, to simultaneously minimize the distance between data points in a given cluster and maximize the distance between the centers of the clusters. We extract modes of Arctic interannual sea-ice variability with nonhierarchical K-means cluster analysis and investigate the mechanisms leading to these modes. Our focus is on the sea ice thickness (SIT) as the base variable for clustering because SIT holds most of the climate memory for variability and predictability on interannual timescales. We primarily use global reconstructions of sea ice fields with a state-of-the-art ocean-sea-ice model, but we also verify the robustness of determined clusters in other Arctic sea ice datasets. Applied cluster analysis over the 1958-2013 period shows that the optimal number of detrended SIT clusters is K=3. Determined SIT cluster patterns and their time series of occurrence are rather similar between different seasons and months. Two opposite thermodynamic modes are characterized with prevailing negative or positive SIT anomalies over the

Ice and AIS: ship speed data and sea ice forecasts in the Baltic Sea

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U. Löptien

2014-12-01

Full Text Available The Baltic Sea is a seasonally ice-covered marginal sea located in a densely populated area in northern Europe. Severe sea ice conditions have the potential to hinder the intense ship traffic considerably. Thus, sea ice fore- and nowcasts are regularly provided by the national weather services. Typically, the forecast comprises several ice properties that are distributed as prognostic variables, but their actual usefulness is difficult to measure, and the ship captains must determine their relative importance and relevance for optimal ship speed and safety ad hoc. The present study provides a more objective approach by comparing the ship speeds, obtained by the automatic identification system (AIS, with the respective forecasted ice conditions. We find that, despite an unavoidable random component, this information is useful to constrain and rate fore- and nowcasts. More precisely, 62–67% of ship speed variations can be explained by the forecasted ice properties when fitting a mixed-effect model. This statistical fit is based on a test region in the Bothnian Sea during the severe winter 2011 and employs 15 to 25 min averages of ship speed.

Relating C-band Microwave and Optical Satellite Observations as A Function of Snow Thickness on First-Year Sea Ice during the Winter to Summer Transition

Science.gov (United States)

Zheng, J.; Yackel, J.

2015-12-01

The Arctic sea ice and its snow cover have a direct impact on both the Arctic and global climate system through their ability to moderate heat exchange across the ocean-sea ice-atmosphere (OSA) interface. Snow cover plays a key role in the OSA interface radiation and energy exchange, as it controls the growth and decay of first-year sea ice (FYI). However, meteoric accumulation and redistribution of snow on FYI is highly stochastic over space and time, which makes it poorly understood. Previous studies have estimated local-scale snow thickness distributions using in-situ technique and modelling but it is spatially limited and challenging due to logistic difficulties. Moreover, snow albedo is also critical for determining the surface energy balance of the OSA during the critical summer ablation season. Even then, due to persistent and widespread cloud cover in the Arctic at various spatio-temporal scales, it is difficult and unreliable to remotely measure albedo of snow cover on FYI in the optical spectrum. Previous studies demonstrate that only large-scale sea ice albedo was successfully estimated using optical-satellite sensors. However, space-borne microwave sensors, with their capability of all-weather and 24-hour imaging, can provide enhanced information about snow cover on FYI. Daily spaceborne C-band scatterometer data (ASCAT) and MODIS data are used to investigate the the seasonal co-evolution of the microwave backscatter coefficient and optical albedo as a function of snow thickness on smooth FYI. The research focuses on snow-covered FYI near Cambridge Bay, Nunavut (Fig.1) during the winter to advanced-melt period (April-June, 2014). The ACSAT time series (Fig.2) show distinct increase in scattering at melt onset indicating the first occurrence of melt water in the snow cover. The corresponding albedo exhibits no decrease at this stage. We show how the standard deviation of ASCAT backscatter on FYI during winter can be used as a proxy for surface roughness

In-situ calibration and validation of Cryosat-2 observations over arctic sea ice north of Svalbard

DEFF Research Database (Denmark)

Gerland, Sebastian; Renner, Angelika H. H.; Spreen, Gunnar

CryoSat-2's radar altimeter allows to observe the panArctic sea ice thickness up to 88°N on a monthly basis. However, calibration and validation are crucial to assess limitations and accuracy of the altimeter, and to better quantify the uncertainties involved in converting sea ice freeboard to th...

Reflection and transmission of irradiance by snow and sea ice in the central Arctic Ocean in summer 2010

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Ruibo Lei

2012-03-01

Full Text Available Reflection and transmission of irradiance by the combined snow and sea ice layer were measured at an ice camp (ca. 10 days and several short-term stations (ca. 2 h established in the western sector of the Arctic Ocean above 80°N during the 2010 summer. These measurements were made with an intention to quantify the apparent optical properties of snow and sea ice, and to evaluate their roles in the mass balance of snow-covered sea ice in the High Arctic. The integrated 350–920 nm albedo ranged from 0.54 to 0.88, and was primarily dependent on the geophysical properties of snow, but not those of sea ice. This implies that all snow cover was still optically thick, even though snow melting had commenced at all measurement sites. For sea ice about 1.66 m thick and covered by 2.5–8.5 cm of snow at the ice camp, the integrated 350–920 nm transmittance ranged from 0.017 to 0.065. Rapid snow melting resulting from an event of slight drizzle doubled the available solar irradiance under the ice (from ca. 3.6 to 7.2 W·m−2, which further accelerated ice-bottom decay. During the measurement at the camp, the temporally averaged incident solar irradiance at 320–950 nm was 110.6±33.6 W·m−2, 29.2±2.9% of which was absorbed by snow and sea ice and utilized to melt snow and sea ice. The melting of snow and sea ice had a distinctly greater effect on the spectral reflection and transmission for the near-infrared spectrum than for the ultraviolet and visible spectra.

Integration of airborne altimetry and in situ radar measurements to estimate marine ice thickness beneath the Larsen C ice shelf, Antarctic Peninsula

Science.gov (United States)

McGrath, D.; Steffen, K.; Rodriguez Lagos, J.

2010-12-01

Observed atmospheric and oceanic warming is driving significant retreat and / or collapse of ice shelves along the Antarctic Peninsula totaling over 25,000 km2 in the past five decades. Basal melting of meteoric ice can occur near the grounding line of deep glacier inflows if the ocean water is above the pressure melting point. Buoyant meltwater will develop thermohaline circulation, rising beneath the ice shelf, where it may become supercooled and subsequently refreeze in ice draft minima. Marine ice, due to its warm and thus relatively viscous nature, is hypothesized to suture parallel flow bands, increasing ice shelf stability by arresting fracture propagation and controlling iceberg calving dimensions. Thus efforts to model ice shelf stability require accurate estimates of marine ice location and thickness. Ice thickness of a floating ice shelf can be determined in two manners: (1) from measurements of ice elevation above sea level and the calculation of ice thickness from assumptions of hydrostatic equilibrium, and (2) from radar echo measurements of the ice-water interface. Marine ice can confound the latter because its high dielectric constant and strong absorptive properties attenuate the radar energy, often preventing a return signal from the bottom of the ice shelf. These two methods are complementary for determining the marine ice component though because positive anomalies in (1) relative to (2) suggest regions of marine ice accretion. Nearly 350 km of ice penetrating radar (25 MHz) surveys were collected on the Larsen C ice shelf, in conjunction with kinematic GPS measurements and collocated with surface elevation data from the NASA Airborne Topographic Mapper (ATM) as part of the ICE Bridge mission in 2009. Basal ice topography and total ice thickness is accurately mapped along the survey lines and compared with calculated ice thickness from both the kinematic GPS and ATM elevation data. Positive anomalies are discussed in light of visible imagery and

The effects of additional black carbon on Arctic sea ice surface albedo: variation with sea ice type and snow cover

OpenAIRE

A. A. Marks; M. D. King

2013-01-01

Black carbon in sea ice will decrease sea ice surface albedo through increased absorption of incident solar radiation, exacerbating sea ice melting. Previous literature has reported different albedo responses to additions of black carbon in sea ice and has not considered how a snow cover may mitigate the effect of black carbon in sea ice. Sea ice is predominately snow covered. Visible light absorption and light scattering coefficients are calculated for a typical first year and multi-y...

Middle Range Sea Ice Prediction System of Voyage Environmental Information System in Arctic Sea Route

Science.gov (United States)

Lim, H. S.

2017-12-01

Due to global warming, the sea ice in the Arctic Ocean is melting dramatically in summer, which is providing a new opportunity to exploit the Northern Sea Route (NSR) connecting Asia and Europe ship route. Recent increases in logistics transportation through NSR and resource development reveal the possible threats of marine pollution and marine transportation accidents without real-time navigation system. To develop a safe Voyage Environmental Information System (VEIS) for vessels operating, the Korea Institute of Ocean Science and Technology (KIOST) which is supported by the Ministry of Oceans and Fisheries, Korea has initiated the development of short-term and middle range prediction system for the sea ice concentration (SIC) and sea ice thickness (SIT) in NSR since 2014. The sea ice prediction system of VEIS consists of AMSR2 satellite composite images (a day), short-term (a week) prediction system, and middle range (a month) prediction system using a statistical method with re-analysis data (TOPAZ) and short-term predicted model data. In this study, the middle range prediction system for the SIC and SIT in NSR is calibrated with another middle range predicted atmospheric and oceanic data (NOAA CFSv2). The system predicts one month SIC and SIT on a daily basis, as validated with dynamic composite SIC data extracted from AMSR2 L2 satellite images.

Variability and Anomalous Trends in the Global Sea Ice Cover

Science.gov (United States)

Comiso, Josefino C.

2012-01-01

The advent of satellite data came fortuitously at a time when the global sea ice cover has been changing rapidly and new techniques are needed to accurately assess the true state and characteristics of the global sea ice cover. The extent of the sea ice in the Northern Hemisphere has been declining by about -4% per decade for the period 1979 to 2011 but for the period from 1996 to 2010, the rate of decline became even more negative at -8% per decade, indicating an acceleration in the decline. More intriguing is the drastically declining perennial sea ice area, which is the ice that survives the summer melt and observed to be retreating at the rate of -14% per decade during the 1979 to 2012 period. Although a slight recovery occurred in the last three years from an abrupt decline in 2007, the perennial ice extent was almost as low as in 2007 in 2011. The multiyear ice, which is the thick component of the perennial ice and regarded as the mainstay of the Arctic sea ice cover is declining at an even higher rate of -19% per decade. The more rapid decline of the extent of this thicker ice type means that the volume of the ice is also declining making the survival of the Arctic ice in summer highly questionable. The slight recovery in 2008, 2009 and 2010 for the perennial ice in summer was likely associated with an apparent cycle in the time series with a period of about 8 years. Results of analysis of concurrent MODIS and AMSR-E data in summer also provide some evidence of more extensive summer melt and meltponding in 2007 and 2011 than in other years. Meanwhile, the Antarctic sea ice cover, as observed by the same set of satellite data, is showing an unexpected and counter intuitive increase of about 1 % per decade over the same period. Although a strong decline in ice extent is apparent in the Bellingshausen/ Amundsen Seas region, such decline is more than compensated by increases in the extent of the sea ice cover in the Ross Sea region. The results of analysis of

Optical properties of sea ice doped with black carbon - an experimental and radiative-transfer modelling comparison

Science.gov (United States)

Marks, Amelia A.; Lamare, Maxim L.; King, Martin D.

2017-12-01

Radiative-transfer calculations of the light reflectivity and extinction coefficient in laboratory-generated sea ice doped with and without black carbon demonstrate that the radiative-transfer model TUV-snow can be used to predict the light reflectance and extinction coefficient as a function of wavelength. The sea ice is representative of first-year sea ice containing typical amounts of black carbon and other light-absorbing impurities. The experiments give confidence in the application of the model to predict albedo of other sea ice fabrics. Sea ices, ˜ 30 cm thick, were generated in the Royal Holloway Sea Ice Simulator ( ˜ 2000 L tanks) with scattering cross sections measured between 0.012 and 0.032 m2 kg-1 for four ices. Sea ices were generated with and without ˜ 5 cm upper layers containing particulate black carbon. Nadir reflectances between 0.60 and 0.78 were measured along with extinction coefficients of 0.1 to 0.03 cm-1 (e-folding depths of 10-30 cm) at a wavelength of 500 nm. Values were measured between light wavelengths of 350 and 650 nm. The sea ices generated in the Royal Holloway Sea Ice Simulator were found to be representative of natural sea ices. Particulate black carbon at mass ratios of ˜ 75, ˜ 150 and ˜ 300 ng g-1 in a 5 cm ice layer lowers the albedo to 97, 90 and 79 % of the reflectivity of an undoped clean sea ice (at a wavelength of 500 nm).

Evidence for middle Eocene Arctic sea ice from diatoms and ice-rafted debris.

Science.gov (United States)

Stickley, Catherine E; St John, Kristen; Koç, Nalân; Jordan, Richard W; Passchier, Sandra; Pearce, Richard B; Kearns, Lance E

2009-07-16

Oceanic sediments from long cores drilled on the Lomonosov ridge, in the central Arctic, contain ice-rafted debris (IRD) back to the middle Eocene epoch, prompting recent suggestions that ice appeared in the Arctic about 46 million years (Myr) ago. However, because IRD can be transported by icebergs (derived from land-based ice) and also by sea ice, IRD records are restricted to providing a history of general ice-rafting only. It is critical to differentiate sea ice from glacial (land-based) ice as climate feedback mechanisms vary and global impacts differ between these systems: sea ice directly affects ocean-atmosphere exchanges, whereas land-based ice affects sea level and consequently ocean acidity. An earlier report assumed that sea ice was prevalent in the middle Eocene Arctic on the basis of IRD, and although somewhat preliminary supportive evidence exists, these data are neither comprehensive nor quantified. Here we show the presence of middle Eocene Arctic sea ice from an extraordinary abundance of a group of sea-ice-dependent fossil diatoms (Synedropsis spp.). Analysis of quartz grain textural characteristics further supports sea ice as the dominant transporter of IRD at this time. Together with new information on cosmopolitan diatoms and existing IRD records, our data strongly suggest a two-phase establishment of sea ice: initial episodic formation in marginal shelf areas approximately 47.5 Myr ago, followed approximately 0.5 Myr later by the onset of seasonally paced sea-ice formation in offshore areas of the central Arctic. Our data establish a 2-Myr record of sea ice, documenting the transition from a warm, ice-free environment to one dominated by winter sea ice at the start of the middle Eocene climatic cooling phase.

Ikaite crystals in melting sea ice - implications for pCO2 and pH levels in Arctic surface waters

Science.gov (United States)

Rysgaard, S.; Glud, R. N.; Lennert, K.; Cooper, M.; Halden, N.; Leakey, R. J. G.; Hawthorne, F. C.; Barber, D.

2012-08-01

A major issue of Arctic marine science is to understand whether the Arctic Ocean is, or will be, a source or sink for air-sea CO2 exchange. This has been complicated by the recent discoveries of ikaite (a polymorph of CaCO3·6H2O) in Arctic and Antarctic sea ice, which indicate that multiple chemical transformations occur in sea ice with a possible effect on CO2 and pH conditions in surface waters. Here, we report on biogeochemical conditions, microscopic examinations and x-ray diffraction analysis of single crystals from a melting 1.7 km2 (0.5-1 m thick) drifting ice floe in the Fram Strait during summer. Our findings show that ikaite crystals are present throughout the sea ice but with larger crystals appearing in the upper ice layers. Ikaite crystals placed at elevated temperatures disintegrated into smaller crystallites and dissolved. During our field campaign in late June, melt reduced the ice floe thickness by 0.2 m per week and resulted in an estimated 3.8 ppm decrease of pCO2 in the ocean surface mixed layer. This corresponds to an air-sea CO2 uptake of 10.6 mmol m-2 sea ice d-1 or to 3.3 ton km-2 ice floe week-1. This is markedly higher than the estimated primary production within the ice floe of 0.3-1.3 mmol m-2 sea ice d-1. Finally, the presence of ikaite in sea ice and the dissolution of the mineral during melting of the sea ice and mixing of the melt water into the surface oceanic mixed layer accounted for half of the estimated pCO2 uptake.

Inferring Ice Thickness from a Glacier Dynamics Model and Multiple Surface Datasets.

Science.gov (United States)

Guan, Y.; Haran, M.; Pollard, D.

2017-12-01

The future behavior of the West Antarctic Ice Sheet (WAIS) may have a major impact on future climate. For instance, ice sheet melt may contribute significantly to global sea level rise. Understanding the current state of WAIS is therefore of great interest. WAIS is drained by fast-flowing glaciers which are major contributors to ice loss. Hence, understanding the stability and dynamics of glaciers is critical for predicting the future of the ice sheet. Glacier dynamics are driven by the interplay between the topography, temperature and basal conditions beneath the ice. A glacier dynamics model describes the interactions between these processes. We develop a hierarchical Bayesian model that integrates multiple ice sheet surface data sets with a glacier dynamics model. Our approach allows us to (1) infer important parameters describing the glacier dynamics, (2) learn about ice sheet thickness, and (3) account for errors in the observations and the model. Because we have relatively dense and accurate ice thickness data from the Thwaites Glacier in West Antarctica, we use these data to validate the proposed approach. The long-term goal of this work is to have a general model that may be used to study multiple glaciers in the Antarctic.

Ice–ocean coupled computations for sea-ice prediction to support ice navigation in Arctic sea routes

Directory of Open Access Journals (Sweden)

Liyanarachchi Waruna Arampath De Silva

2015-11-01

Full Text Available With the recent rapid decrease in summer sea ice in the Arctic Ocean extending the navigation period in the Arctic sea routes (ASR, the precise prediction of ice distribution is crucial for safe and efficient navigation in the Arctic Ocean. In general, however, most of the available numerical models have exhibited significant uncertainties in short-term and narrow-area predictions, especially in marginal ice zones such as the ASR. In this study, we predict short-term sea-ice conditions in the ASR by using a mesoscale eddy-resolving ice–ocean coupled model that explicitly treats ice floe collisions in marginal ice zones. First, numerical issues associated with collision rheology in the ice–ocean coupled model (ice–Princeton Ocean Model [POM] are discussed and resolved. A model for the whole of the Arctic Ocean with a coarser resolution (about 25 km was developed to investigate the performance of the ice–POM model by examining the reproducibility of seasonal and interannual sea-ice variability. It was found that this coarser resolution model can reproduce seasonal and interannual sea-ice variations compared to observations, but it cannot be used to predict variations over the short-term, such as one to two weeks. Therefore, second, high-resolution (about 2.5 km regional models were set up along the ASR to investigate the accuracy of short-term sea-ice predictions. High-resolution computations were able to reasonably reproduce the sea-ice extent compared to Advanced Microwave Scanning Radiometer–Earth Observing System satellite observations because of the improved expression of the ice–albedo feedback process and the ice–eddy interaction process.

Modelling snow ice and superimposed ice on landfast sea ice in Kongsfjorden, Svalbard

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Caixin Wang

2015-08-01

Full Text Available Snow ice and superimposed ice formation on landfast sea ice in a Svalbard fjord, Kongsfjorden, was investigated with a high-resolution thermodynamic snow and sea-ice model, applying meteorological weather station data as external forcing. The model shows that sea-ice formation occurs both at the ice bottom and at the snow/ice interface. Modelling results indicated that the total snow ice and superimposed ice, which formed at the snow/ice interface, was about 14 cm during the simulation period, accounting for about 15% of the total ice mass and 35% of the total ice growth. Introducing a time-dependent snow density improved the modelled results, and a time-dependent oceanic heat flux parameterization yielded reasonable ice growth at the ice bottom. Model results suggest that weather conditions, in particular air temperature and precipitation, as well as snow thermal properties and surface albedo are the most critical factors for the development of snow ice and superimposed ice in Kongsfjorden. While both warming air and higher precipitation led to increased snow ice and superimposed ice forming in Kongsfjorden in the model runs, the processes were more sensitive to precipitation than to air temperature.

Collaborations for Arctic Sea Ice Information and Tools

Science.gov (United States)

Sheffield Guy, L.; Wiggins, H. V.; Turner-Bogren, E. J.; Rich, R. H.

2017-12-01

The dramatic and rapid changes in Arctic sea ice require collaboration across boundaries, including between disciplines, sectors, institutions, and between scientists and decision-makers. This poster will highlight several projects that provide knowledge to advance the development and use of sea ice knowledge. Sea Ice for Walrus Outlook (SIWO: https://www.arcus.org/search-program/siwo) - SIWO is a resource for Alaskan Native subsistence hunters and other interested stakeholders. SIWO provides weekly reports, during April-June, of sea ice conditions relevant to walrus in the northern Bering and southern Chukchi seas. Collaboration among scientists, Alaskan Native sea-ice experts, and the Eskimo Walrus Commission is fundamental to this project's success. Sea Ice Prediction Network (SIPN: https://www.arcus.org/sipn) - A collaborative, multi-agency-funded project focused on seasonal Arctic sea ice predictions. The goals of SIPN include: coordinate and evaluate Arctic sea ice predictions; integrate, assess, and guide observations; synthesize predictions and observations; and disseminate predictions and engage key stakeholders. The Sea Ice Outlook—a key activity of SIPN—is an open process to share and synthesize predictions of the September minimum Arctic sea ice extent and other variables. Other SIPN activities include workshops, webinars, and communications across the network. Directory of Sea Ice Experts (https://www.arcus.org/researchers) - ARCUS has undertaken a pilot project to develop a web-based directory of sea ice experts across institutions, countries, and sectors. The goal of the project is to catalyze networking between individual investigators, institutions, funding agencies, and other stakeholders interested in Arctic sea ice. Study of Environmental Arctic Change (SEARCH: https://www.arcus.org/search-program) - SEARCH is a collaborative program that advances research, synthesizes research findings, and broadly communicates the results to support

Wind-sea surface temperature-sea ice relationship in the Chukchi-Beaufort Seas during autumn

Science.gov (United States)

Zhang, Jing; Stegall, Steve T.; Zhang, Xiangdong

2018-03-01

Dramatic climate changes, especially the largest sea ice retreat during September and October, in the Chukchi-Beaufort Seas could be a consequence of, and further enhance, complex air-ice-sea interactions. To detect these interaction signals, statistical relationships between surface wind speed, sea surface temperature (SST), and sea ice concentration (SIC) were analyzed. The results show a negative correlation between wind speed and SIC. The relationships between wind speed and SST are complicated by the presence of sea ice, with a negative correlation over open water but a positive correlation in sea ice dominated areas. The examination of spatial structures indicates that wind speed tends to increase when approaching the ice edge from open water and the area fully covered by sea ice. The anomalous downward radiation and thermal advection, as well as their regional distribution, play important roles in shaping these relationships, though wind-driven sub-grid scale boundary layer processes may also have contributions. Considering the feedback loop involved in the wind-SST-SIC relationships, climate model experiments would be required to further untangle the underlying complex physical processes.

The interaction of ultraviolet light with Arctic sea ice during SHEBA

Science.gov (United States)

Perovich, Donald K.

The reflection, absorption and transmission of ultraviolet light by a sea-ice cover strongly impacts primary productivity, higher trophic components of the food web, and humans. Measurements of the incident irradiance at 305, 320, 340 and 380 nm and of the photosynthetically active radiation were made from April through September 1998 as part of the SHEBA (Surface Heat Budget of the Arctic Ocean program) field experiment in the Arctic Ocean. In addition, observations of snow depth and ice thickness were made at more than 100 sites encompassing a comprehensive range of conditions. The thickness observations were combined with a radiative transfer model to compute a time series of the ultraviolet light transmitted by the ice cover from April through September. Peak values of incident ultraviolet irradiance occurred in mid-June. Peak transmittance was later in the summer at the end of the melt season when the snow cover had completely melted, the ice had thinned and pond coverage was extensive. The fraction of the incident ultraviolet irradiance transmitted through the ice increased by several orders of magnitude as the melt season progressed. Ultraviolet transmittance was approximately a factor of ten greater for melt ponds than bare ice. Climate change has the potential to alter the amplitude and timing of the annual albedo cycle of sea ice. If the onset of melt occurs at increasingly earlier dates, ultraviolet transmittance will be significantly enhanced, with potentially deleterious biological impacts.

MODIS Snow and Sea Ice Products

Science.gov (United States)

Hall, Dorothy K.; Riggs, George A.; Salomonson, Vincent V.

2004-01-01

In this chapter, we describe the suite of Earth Observing System (EOS) Moderate-Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua snow and sea ice products. Global, daily products, developed at Goddard Space Flight Center, are archived and distributed through the National Snow and Ice Data Center at various resolutions and on different grids useful for different communities Snow products include binary snow cover, snow albedo, and in the near future, fraction of snow in a 5OO-m pixel. Sea ice products include ice extent determined with two different algorithms, and sea ice surface temperature. The algorithms used to develop these products are described. Both the snow and sea ice products, available since February 24,2000, are useful for modelers. Validation of the products is also discussed.

Sea-ice deformation in a coupled ocean–sea-ice model and in satellite remote sensing data

Directory of Open Access Journals (Sweden)

G. Spreen

2017-07-01

Full Text Available A realistic representation of sea-ice deformation in models is important for accurate simulation of the sea-ice mass balance. Simulated sea-ice deformation from numerical simulations with 4.5, 9, and 18 km horizontal grid spacing and a viscous–plastic (VP sea-ice rheology are compared with synthetic aperture radar (SAR satellite observations (RGPS, RADARSAT Geophysical Processor System for the time period 1996–2008. All three simulations can reproduce the large-scale ice deformation patterns, but small-scale sea-ice deformations and linear kinematic features (LKFs are not adequately reproduced. The mean sea-ice total deformation rate is about 40 % lower in all model solutions than in the satellite observations, especially in the seasonal sea-ice zone. A decrease in model grid spacing, however, produces a higher density and more localized ice deformation features. The 4.5 km simulation produces some linear kinematic features, but not with the right frequency. The dependence on length scale and probability density functions (PDFs of absolute divergence and shear for all three model solutions show a power-law scaling behavior similar to RGPS observations, contrary to what was found in some previous studies. Overall, the 4.5 km simulation produces the most realistic divergence, vorticity, and shear when compared with RGPS data. This study provides an evaluation of high and coarse-resolution viscous–plastic sea-ice simulations based on spatial distribution, time series, and power-law scaling metrics.

Sea ice algal biomass and physiology in the Amundsen Sea, Antarctica

Directory of Open Access Journals (Sweden)

Kevin R. Arrigo

2014-07-01

Full Text Available Abstract Sea ice covers approximately 5% of the ocean surface and is one of the most extensive ecosystems on the planet. The microbial communities that live in sea ice represent an important food source for numerous organisms at a time of year when phytoplankton in the water column are scarce. Here we describe the distributions and physiology of sea ice microalgae in the poorly studied Amundsen Sea sector of the Southern Ocean. Microalgal biomass was relatively high in sea ice in the Amundsen Sea, due primarily to well developed surface communities that would have been replenished with nutrients during seawater flooding of the surface as a result of heavy snow accumulation. Elevated biomass was also occasionally observed in slush, interior, and bottom ice microhabitats throughout the region. Sea ice microalgal photophysiology appeared to be controlled by the availability of both light and nutrients. Surface communities used an active xanthophyll cycle and effective pigment sunscreens to protect themselves from harmful ultraviolet and visible radiation. Acclimation to low light microhabitats in sea ice was facilitated by enhanced pigment content per cell, greater photosynthetic accessory pigments, and increased photosynthetic efficiency. Photoacclimation was especially effective in the bottom ice community, where ready access to nutrients would have allowed ice microalgae to synthesize a more efficient photosynthetic apparatus. Surprisingly, the pigment-detected prymnesiophyte Phaeocystis antarctica was an important component of surface communities (slush and surface ponds where its acclimation to high light may precondition it to seed phytoplankton blooms after the sea ice melts in spring.

Ikaite crystals in melting sea ice – implications for pCO2 and pH levels in Arctic surface waters

Directory of Open Access Journals (Sweden)

R. J. G. Leakey

2012-08-01

Full Text Available A major issue of Arctic marine science is to understand whether the Arctic Ocean is, or will be, a source or sink for air–sea CO2 exchange. This has been complicated by the recent discoveries of ikaite (a polymorph of CaCO3·6H2O in Arctic and Antarctic sea ice, which indicate that multiple chemical transformations occur in sea ice with a possible effect on CO2 and pH conditions in surface waters. Here, we report on biogeochemical conditions, microscopic examinations and x-ray diffraction analysis of single crystals from a melting 1.7 km2 (0.5–1 m thick drifting ice floe in the Fram Strait during summer. Our findings show that ikaite crystals are present throughout the sea ice but with larger crystals appearing in the upper ice layers. Ikaite crystals placed at elevated temperatures disintegrated into smaller crystallites and dissolved. During our field campaign in late June, melt reduced the ice floe thickness by 0.2 m per week and resulted in an estimated 3.8 ppm decrease of pCO2 in the ocean surface mixed layer. This corresponds to an air–sea CO2 uptake of 10.6 mmol m−2 sea ice d−1 or to 3.3 ton km−2 ice floe week−1. This is markedly higher than the estimated primary production within the ice floe of 0.3–1.3 mmol m−2 sea ice d−1. Finally, the presence of ikaite in sea ice and the dissolution of the mineral during melting of the sea ice and mixing of the melt water into the surface oceanic mixed layer accounted for half of the estimated pCO2 uptake.

Potential decadal predictability and its sensitivity to sea ice albedo parameterization in a global coupled model

Energy Technology Data Exchange (ETDEWEB)

Koenigk, Torben; Caian, Mihaela; Doescher, Ralf; Wyser, Klaus [Swedish Meteorological and Hydrological Institute, Rossby Centre, Norrkoeping (Sweden); Koenig Beatty, Christof [Universite Catholique de Louvain, Louvain-la-Neuve (Belgium)

2012-06-15

Decadal prediction is one focus of the upcoming 5th IPCC Assessment report. To be able to interpret the results and to further improve the decadal predictions it is important to investigate the potential predictability in the participating climate models. This study analyzes the upper limit of climate predictability on decadal time scales and its dependency on sea ice albedo parameterization by performing two perfect ensemble experiments with the global coupled climate model EC-Earth. In the first experiment, the standard albedo formulation of EC-Earth is used, in the second experiment sea ice albedo is reduced. The potential prognostic predictability is analyzed for a set of oceanic and atmospheric parameters. The decadal predictability of the atmospheric circulation is small. The highest potential predictability was found in air temperature at 2 m height over the northern North Atlantic and the southern South Atlantic. Over land, only a few areas are significantly predictable. The predictability for continental size averages of air temperature is relatively good in all northern hemisphere regions. Sea ice thickness is highly predictable along the ice edges in the North Atlantic Arctic Sector. The meridional overturning circulation is highly predictable in both experiments and governs most of the decadal climate predictability in the northern hemisphere. The experiments using reduced sea ice albedo show some important differences like a generally higher predictability of atmospheric variables in the Arctic or higher predictability of air temperature in Europe. Furthermore, decadal variations are substantially smaller in the simulations with reduced ice albedo, which can be explained by reduced sea ice thickness in these simulations. (orig.)

Broad-scale predictability of carbohydrates and exopolymers in Antarctic and Arctic sea ice

Science.gov (United States)

Underwood, Graham J. C.; Aslam, Shazia N.; Michel, Christine; Niemi, Andrea; Norman, Louiza; Meiners, Klaus M.; Laybourn-Parry, Johanna; Paterson, Harriet; Thomas, David N.

2013-01-01

Sea ice can contain high concentrations of dissolved organic carbon (DOC), much of which is carbohydrate-rich extracellular polymeric substances (EPS) produced by microalgae and bacteria inhabiting the ice. Here we report the concentrations of dissolved carbohydrates (dCHO) and dissolved EPS (dEPS) in relation to algal standing stock [estimated by chlorophyll (Chl) a concentrations] in sea ice from six locations in the Southern and Arctic Oceans. Concentrations varied substantially within and between sampling sites, reflecting local ice conditions and biological content. However, combining all data revealed robust statistical relationships between dCHO concentrations and the concentrations of different dEPS fractions, Chl a, and DOC. These relationships were true for whole ice cores, bottom ice (biomass rich) sections, and colder surface ice. The distribution of dEPS was strongly correlated to algal biomass, with the highest concentrations of both dEPS and non-EPS carbohydrates in the bottom horizons of the ice. Complex EPS was more prevalent in colder surface sea ice horizons. Predictive models (validated against independent data) were derived to enable the estimation of dCHO concentrations from data on ice thickness, salinity, and vertical position in core. When Chl a data were included a higher level of prediction was obtained. The consistent patterns reflected in these relationships provide a strong basis for including estimates of regional and seasonal carbohydrate and dEPS carbon budgets in coupled physical-biogeochemical models, across different types of sea ice from both polar regions. PMID:24019487

Broad-scale predictability of carbohydrates and exopolymers in Antarctic and Arctic sea ice.

Science.gov (United States)

Underwood, Graham J C; Aslam, Shazia N; Michel, Christine; Niemi, Andrea; Norman, Louiza; Meiners, Klaus M; Laybourn-Parry, Johanna; Paterson, Harriet; Thomas, David N

2013-09-24

Sea ice can contain high concentrations of dissolved organic carbon (DOC), much of which is carbohydrate-rich extracellular polymeric substances (EPS) produced by microalgae and bacteria inhabiting the ice. Here we report the concentrations of dissolved carbohydrates (dCHO) and dissolved EPS (dEPS) in relation to algal standing stock [estimated by chlorophyll (Chl) a concentrations] in sea ice from six locations in the Southern and Arctic Oceans. Concentrations varied substantially within and between sampling sites, reflecting local ice conditions and biological content. However, combining all data revealed robust statistical relationships between dCHO concentrations and the concentrations of different dEPS fractions, Chl a, and DOC. These relationships were true for whole ice cores, bottom ice (biomass rich) sections, and colder surface ice. The distribution of dEPS was strongly correlated to algal biomass, with the highest concentrations of both dEPS and non-EPS carbohydrates in the bottom horizons of the ice. Complex EPS was more prevalent in colder surface sea ice horizons. Predictive models (validated against independent data) were derived to enable the estimation of dCHO concentrations from data on ice thickness, salinity, and vertical position in core. When Chl a data were included a higher level of prediction was obtained. The consistent patterns reflected in these relationships provide a strong basis for including estimates of regional and seasonal carbohydrate and dEPS carbon budgets in coupled physical-biogeochemical models, across different types of sea ice from both polar regions.

Does a Relationship Between Arctic Low Clouds and Sea Ice Matter?

Science.gov (United States)

Taylor, Patrick C.

2016-01-01

Arctic low clouds strongly affect the Arctic surface energy budget. Through this impact Arctic low clouds influence important aspects of the Arctic climate system, namely surface and atmospheric temperature, sea ice extent and thickness, and atmospheric circulation. Arctic clouds are in turn influenced by these elements of the Arctic climate system, and these interactions create the potential for Arctic cloud-climate feedbacks. To further our understanding of potential Arctic cloudclimate feedbacks, the goal of this paper is to quantify the influence of atmospheric state on the surface cloud radiative effect (CRE) and its covariation with sea ice concentration (SIC). We build on previous research using instantaneous, active remote sensing satellite footprint data from the NASA A-Train. First, the results indicate significant differences in the surface CRE when stratified by atmospheric state. Second, there is a weak covariation between CRE and SIC for most atmospheric conditions. Third, the results show statistically significant differences in the average surface CRE under different SIC values in fall indicating a 3-5 W m(exp -2) larger LW CRE in 0% versus 100% SIC footprints. Because systematic changes on the order of 1 W m(exp -2) are sufficient to explain the observed long-term reductions in sea ice extent, our results indicate a potentially significant amplifying sea ice-cloud feedback, under certain meteorological conditions, that could delay the fall freeze-up and influence the variability in sea ice extent and volume. Lastly, a small change in the frequency of occurrence of atmosphere states may yield a larger Arctic cloud feedback than any cloud response to sea ice.

History of sea ice in the Arctic

DEFF Research Database (Denmark)

Polyak, Leonid; Alley, Richard B.; Andrews, John T.

2010-01-01

Arctic sea-ice extent and volume are declining rapidly. Several studies project that the Arctic Ocean may become seasonally ice-free by the year 2040 or even earlier. Putting this into perspective requires information on the history of Arctic sea-ice conditions through the geologic past. This inf......Arctic sea-ice extent and volume are declining rapidly. Several studies project that the Arctic Ocean may become seasonally ice-free by the year 2040 or even earlier. Putting this into perspective requires information on the history of Arctic sea-ice conditions through the geologic past...... Optimum, and consistently covered at least part of the Arctic Ocean for no less than the last 13–14 million years. Ice was apparently most widespread during the last 2–3 million years, in accordance with Earth’s overall cooler climate. Nevertheless, episodes of considerably reduced sea ice or even...

Sea ice classification using dual polarization SAR data

International Nuclear Information System (INIS)

Huiying, Liu; Huadong, Guo; Lu, Zhang

2014-01-01

Sea ice is an indicator of climate change and also a threat to the navigation security of ships. Polarimetric SAR images are useful in the sea ice detection and classification. In this paper, backscattering coefficients and texture features derived from dual polarization SAR images are used for sea ice classification. Firstly, the HH image is recalculated based on the angular dependences of sea ice types. Then the effective gray level co-occurrence matrix (GLCM) texture features are selected for the support vector machine (SVM) classification. In the end, because sea ice concentration can provide a better separation of pancake ice from old ice, it is used to improve the SVM result. This method provides a good classification result, compared with the sea ice chart from CIS

Wave inhibition by sea ice enables trans-Atlantic ice rafting of debris during Heinrich Events

Science.gov (United States)

Wagner, T. J. W.; Dell, R.; Eisenman, I.; Keeling, R. F.; Padman, L.; Severinghaus, J. P.

2017-12-01

The thickness of the ice-rafted debris (IRD) layers that signal Heinrich Events declines far more gradually with distance from the iceberg sources than would be expected based on present-day iceberg trajectories. Here we model icebergs as passive Lagrangian tracers driven by ocean currents, winds, and sea surface temperatures. The icebergs are released in a comprehensive climate model simulation of the last glacial maximum (LGM), as well as a simulation of the modern climate. The two simulated climates result in qualitatively similar distributions of iceberg meltwater and hence debris, with the colder temperatures of the LGM having only a relatively small effect on meltwater spread. In both scenarios, meltwater flux falls off rapidly with zonal distance from the source, in contrast with the more uniform spread of IRD in sediment cores. In order to address this discrepancy, we propose a physical mechanism that could have prolonged the lifetime of icebergs during Heinrich events. The mechanism involves a surface layer of cold and fresh meltwater formed from, and retained around, densely packed armadas of icebergs. This leads to wintertime sea ice formation even in relatively low latitudes. The sea ice in turn shields the icebergs from wave erosion, which is the main source of iceberg ablation. We find that allowing sea ice to form around all icebergs during four months each winter causes the model to approximately agree with the distribution of IRD in sediment cores.

Sea ice biogeochemistry: a guide for modellers.

Directory of Open Access Journals (Sweden)

Letizia Tedesco

Full Text Available Sea ice is a fundamental component of the climate system and plays a key role in polar trophic food webs. Nonetheless sea ice biogeochemical dynamics at large temporal and spatial scales are still rarely described. Numerical models may potentially contribute integrating among sparse observations, but available models of sea ice biogeochemistry are still scarce, whether their relevance for properly describing the current and future state of the polar oceans has been recently addressed. A general methodology to develop a sea ice biogeochemical model is presented, deriving it from an existing validated model application by extension of generic pelagic biogeochemistry model parameterizations. The described methodology is flexible and considers different levels of ecosystem complexity and vertical representation, while adopting a strategy of coupling that ensures mass conservation. We show how to apply this methodology step by step by building an intermediate complexity model from a published realistic application and applying it to analyze theoretically a typical season of first-year sea ice in the Arctic, the one currently needing the most urgent understanding. The aim is to (1 introduce sea ice biogeochemistry and address its relevance to ocean modelers of polar regions, supporting them in adding a new sea ice component to their modelling framework for a more adequate representation of the sea ice-covered ocean ecosystem as a whole, and (2 extend our knowledge on the relevant controlling factors of sea ice algal production, showing that beyond the light and nutrient availability, the duration of the sea ice season may play a key-role shaping the algal production during the on going and upcoming projected changes.

Sea ice and pollution-modulated changes in Greenland ice core methanesulfonate and bromine

Science.gov (United States)

Maselli, Olivia J.; Chellman, Nathan J.; Grieman, Mackenzie; Layman, Lawrence; McConnell, Joseph R.; Pasteris, Daniel; Rhodes, Rachael H.; Saltzman, Eric; Sigl, Michael

2017-01-01

Reconstruction of past changes in Arctic sea ice extent may be critical for understanding its future evolution. Methanesulfonate (MSA) and bromine concentrations preserved in ice cores have both been proposed as indicators of past sea ice conditions. In this study, two ice cores from central and north-eastern Greenland were analysed at sub-annual resolution for MSA (CH3SO3H) and bromine, covering the time period 1750-2010. We examine correlations between ice core MSA and the HadISST1 ICE sea ice dataset and consult back trajectories to infer the likely source regions. A strong correlation between the low-frequency MSA and bromine records during pre-industrial times indicates that both chemical species are likely linked to processes occurring on or near sea ice in the same source regions. The positive correlation between ice core MSA and bromine persists until the mid-20th century, when the acidity of Greenland ice begins to increase markedly due to increased fossil fuel emissions. After that time, MSA levels decrease as a result of declining sea ice extent but bromine levels increase. We consider several possible explanations and ultimately suggest that increased acidity, specifically nitric acid, of snow on sea ice stimulates the release of reactive Br from sea ice, resulting in increased transport and deposition on the Greenland ice sheet.

Variational Ridging in Sea Ice Models

Science.gov (United States)

Roberts, A.; Hunke, E. C.; Lipscomb, W. H.; Maslowski, W.; Kamal, S.

2017-12-01

This work presents the results of a new development to make basin-scale sea ice models aware of the shape, porosity and extent of individual ridges within the pack. We have derived an analytic solution for the Euler-Lagrange equation of individual ridges that accounts for non-conservative forces, and therefore the compressive strength of individual ridges. Because a region of the pack is simply a collection of paths of individual ridges, we are able to solve the Euler-Lagrange equation for a large-scale sea ice field also, and therefore the compressive strength of a region of the pack that explicitly accounts for the macro-porosity of ridged debris. We make a number of assumptions that have simplified the problem, such as treating sea ice as a granular material in ridges, and assuming that bending moments associated with ridging are perturbations around an isostatic state. Regardless of these simplifications, the ridge model is remarkably predictive of macro-porosity and ridge shape, and, because our equations are analytic, they do not require costly computations to solve the Euler-Lagrange equation of ridges on the large scale. The new ridge model is therefore applicable to large-scale sea ice models. We present results from this theoretical development, as well as plans to apply it to the Regional Arctic System Model and a community sea ice code. Most importantly, the new ridging model is particularly useful for pinpointing gaps in our observational record of sea ice ridges, and points to the need for improved measurements of the evolution of porosity of deformed ice in the Arctic and Antarctic. Such knowledge is not only useful for improving models, but also for improving estimates of sea ice volume derived from altimetric measurements of sea ice freeboard.

Observation and modeling of snow melt and superimposed ice formation on sea ice

OpenAIRE

Nicolaus, Marcel; Haas, Christian

2004-01-01

Sea ice plays a key role within the global climate system. It covers some 7% of earths surface and processes a strong seasonal cycle. Snow on sea ice even amplifies the importance of sea ice in the coupled atmosphere-ice-ocean system, because it dominates surface properties and energy balance (incl. albedo).Several quantitative observations of summer sea ice and its snow cover show the formation of superimposed ice and a gap layer underneath, which was found to be associated to high standing ...

The Antarctica component of postglacial rebound model ICE-6G_C (VM5a) based on GPS positioning, exposure age dating of ice thicknesses, and relative sea level histories

Science.gov (United States)

Argus, Donald F.; Peltier, W. R.; Drummond, R.; Moore, Angelyn W.

2014-07-01

A new model of the deglaciation history of Antarctica over the past 25 kyr has been developed, which we refer to herein as ICE-6G_C (VM5a). This revision of its predecessor ICE-5G (VM2) has been constrained to fit all available geological and geodetic observations, consisting of: (1) the present day uplift rates at 42 sites estimated from GPS measurements, (2) ice thickness change at 62 locations estimated from exposure-age dating, (3) Holocene relative sea level histories from 12 locations estimated on the basis of radiocarbon dating and (4) age of the onset of marine sedimentation at nine locations along the Antarctic shelf also estimated on the basis of 14C dating. Our new model fits the totality of these data well. An additional nine GPS-determined site velocities are also estimated for locations known to be influenced by modern ice loss from the Pine Island Bay and Northern Antarctic Peninsula regions. At the 42 locations not influenced by modern ice loss, the quality of the fit of postglacial rebound model ICE-6G_C (VM5A) is characterized by a weighted root mean square residual of 0.9 mm yr-1. The Southern Antarctic Peninsula is inferred to be rising at 2 mm yr-1, requiring there to be less Holocene ice loss there than in the prior model ICE-5G (VM2). The East Antarctica coast is rising at approximately 1 mm yr-1, requiring ice loss from this region to have been small since Last Glacial Maximum. The Ellsworth Mountains, at the base of the Antarctic Peninsula, are inferred to be rising at 5-8 mm yr-1, indicating large ice loss from this area during deglaciation that is poorly sampled by geological data. Horizontal deformation of the Antarctic Plate is minor with two exceptions. First, O'Higgins, at the tip of the Antarctic Peninsula, is moving southeast at a significant 2 mm yr-1 relative to the Antarctic Plate. Secondly, the margins of the Ronne and Ross Ice Shelves are moving horizontally away from the shelf centres at an approximate rate of 0.8 mm yr-1, in

Multiscale Models of Melting Arctic Sea Ice

Science.gov (United States)

2014-09-30

Sea ice reflectance or albedo , a key parameter in climate modeling, is primarily determined by melt pond and ice floe configurations. Ice - albedo ...determine their albedo - a key parameter in climate modeling. Here we explore the possibility of a conceptual sea ice climate model passing through a...bifurcation points. Ising model for melt ponds on Arctic sea ice Y. Ma, I. Sudakov, and K. M. Golden Abstract: The albedo of melting

Estimation of degree of sea ice ridging based on dual-polarized C-band SAR data

Science.gov (United States)

Gegiuc, Alexandru; Similä, Markku; Karvonen, Juha; Lensu, Mikko; Mäkynen, Marko; Vainio, Jouni

2018-01-01

For ship navigation in the Baltic Sea ice, parameters such as ice edge, ice concentration, ice thickness and degree of ridging are usually reported daily in manually prepared ice charts. These charts provide icebreakers with essential information for route optimization and fuel calculations. However, manual ice charting requires long analysis times, and detailed analysis of large areas (e.g. Arctic Ocean) is not feasible. Here, we propose a method for automatic estimation of the degree of ice ridging in the Baltic Sea region, based on RADARSAT-2 C-band dual-polarized (HH/HV channels) SAR texture features and sea ice concentration information extracted from Finnish ice charts. The SAR images were first segmented and then several texture features were extracted for each segment. Using the random forest method, we classified them into four classes of ridging intensity and compared them to the reference data extracted from the digitized ice charts. The overall agreement between the ice-chart-based degree of ice ridging and the automated results varied monthly, being 83, 63 and 81 % in January, February and March 2013, respectively. The correspondence between the degree of ice ridging reported in the ice charts and the actual ridge density was validated with data collected during a field campaign in March 2011. In principle the method can be applied to the seasonal sea ice regime in the Arctic Ocean.

How reversible is sea ice loss?

Directory of Open Access Journals (Sweden)

J. K. Ridley

2012-02-01

Full Text Available It is well accepted that increasing atmospheric CO₂ results in global warming, leading to a decline in polar sea ice area. Here, the specific question of whether there is a tipping point in the sea ice cover is investigated. The global climate model HadCM3 is used to map the trajectory of sea ice area under idealised scenarios. The atmospheric CO₂ is first ramped up to four times pre-industrial levels (4 × CO₂, then ramped down to pre-industrial levels. We also examine the impact of stabilising climate at 4 × CO₂ prior to ramping CO₂ down to pre-industrial levels. Against global mean temperature, Arctic sea ice area is reversible, while the Antarctic sea ice shows some asymmetric behaviour – its rate of change slower, with falling temperatures, than its rate of change with rising temperatures. However, we show that the asymmetric behaviour is driven by hemispherical differences in temperature change between transient and stabilisation periods. We find no irreversible behaviour in the sea ice cover.

Increased Surface Wind Speeds Follow Diminishing Arctic Sea Ice

Science.gov (United States)

Mioduszewski, J.; Vavrus, S. J.; Wang, M.; Holland, M. M.; Landrum, L.

2017-12-01

Projections of Arctic sea ice through the end of the 21st century indicate the likelihood of a strong reduction in ice area and thickness in all seasons, leading to a substantial thermodynamic influence on the overlying atmosphere. This is likely to have an effect on winds over the Arctic Basin, due to changes in atmospheric stability and/or baroclinicity. Prior research on future Arctic wind changes is limited and has focused mainly on the practical impacts on wave heights in certain seasons. Here we attempt to identify patterns and likely mechanisms responsible for surface wind changes in all seasons across the Arctic, particularly those associated with sea ice loss in the marginal ice zone. Sea level pressure, near-surface (10 m) and upper-air (850 hPa) wind speeds, and lower-level dynamic and thermodynamic variables from the Community Earth System Model Large Ensemble Project (CESM-LE) were analyzed for the periods 1971-2000 and 2071-2100 to facilitate comparison between a present-day and future climate. Mean near-surface wind speeds over the Arctic Ocean are projected to increase by late century in all seasons but especially during autumn and winter, when they strengthen by up to 50% locally. The most extreme wind speeds in the 90th percentile change even more, increasing in frequency by over 100%. The strengthened winds are closely linked to decreasing lower-tropospheric stability resulting from the loss of sea ice cover and consequent surface warming (locally over 20 ºC warmer in autumn and winter). A muted pattern of these future changes is simulated in CESM-LE historical runs from 1920-2005. The enhanced winds near the surface are mostly collocated with weaker winds above the boundary layer during autumn and winter, implying more vigorous vertical mixing and a drawdown of high-momentum air.The implications of stronger future winds include increased coastal hazards and the potential for a positive feedback with sea ice by generating higher winds and

Impact of melt ponds on Arctic sea ice in past and future climates as simulated by MPI-ESM

Directory of Open Access Journals (Sweden)

Erich Roeckner

2012-09-01

Full Text Available The impact of melt ponds on Arctic sea ice is estimated from model simulations of the historical and future climate. The simulations were performed with and without the effect of melt ponds on sea ice melt, respectively. In the last thirty years of the historical simulations, melt ponds develop predominantly in the continental shelf regions and in the Canadian archipelago. Accordingly, the ice albedo in these regions is systematically smaller than in the no-pond simulations, the sea ice melt is enhanced, and both the ice concentration and ice thickness during the September minimum are reduced. Open ponds decrease the ice albedo, resulting in enhanced ice melt, less sea ice and further pond growth. This positive feedback entails a more realistic representation of the seasonal cycle of Northern Hemisphere sea ice area. Under the premise that the observed decline of Arctic sea ice over the period of modern satellite observations is mainly externally driven and, therefore, potentially predictable, both model versions underestimate the decline in Arctic sea ice. This presupposition, however, is challenged by our model simulations which show a distinct modulation of the downward Arctic sea ice trends by multidecadal variability. At longer time scales, an impact of pond activation on Arctic sea ice trends is more evident: In the Representative Concentration Pathway scenario RCP45, the September sea ice is projected to vanish by the end of the 21st century. In the active-pond simulation, this happens up to two decades earlier than in the no-pond simulations.

Biologically-Oriented Processes in the Coastal Sea Ice Zone of the White Sea

Science.gov (United States)

Melnikov, I. A.

2002-12-01

The annual advance and retreat of sea ice is a major physical determinant of spatial and temporal changes in the structure and function of marine coastal biological communities. Sea ice biological data obtained in the tidal zone of Kandalaksha Gulf (White Sea) during 1996-2001 period will be presented. Previous observations in this area were mainly conducted during the ice-free summer season. However, there is little information on the ice-covered winter season (6-7 months duration), and, especially, on the sea-ice biology in the coastal zone within tidal regimes. During the January-May period time-series observations were conducted on transects along shorelines with coastal and fast ice. Trends in the annual extent of sea ice showed significant impacts on ice-associated biological communities. Three types of sea ice impact on kelps, balanoides, littorinas and amphipods are distinguished: (i) positive, when sea ice protects these populations from grinding (ii) negative, when ice grinds both fauna and flora, and (iii) a combined effect, when fast ice protects, but anchored ice grinds plant and animals. To understand the full spectrum of ecological problems caused by pollution on the coastal zone, as well as the problems of sea ice melting caused by global warming, an integrated, long-term study of the physical, chemical, and biological processes is needed.

Improving Arctic Sea Ice Edge Forecasts by Assimilating High Horizontal Resolution Sea Ice Concentration Data into the US Navy’s Ice Forecast Systems

Science.gov (United States)

2016-06-13

1735-2015 © Author(s) 2015. CC Attribution 3.0 License. Improving Arctic sea ice edge forecasts by assimilating high horizontal resolution sea ice...concentration data into the US Navy’s ice forecast systems P. G. Posey1, E. J. Metzger1, A. J. Wallcraft1, D. A. Hebert1, R. A. Allard1, O. M. Smedstad2...error within the US Navy’s operational sea ice forecast systems gained by assimilating high horizontal resolution satellite-derived ice concentration

Sea Ice, Climate and Fram Strait

Science.gov (United States)

Hunkins, K.

1984-01-01

When sea ice is formed the albedo of the ocean surface increases from its open water value of about 0.1 to a value as high as 0.8. This albedo change effects the radiation balance and thus has the potential to alter climate. Sea ice also partially seals off the ocean from the atmosphere, reducing the exchange of gases such as carbon dioxide. This is another possible mechanism by which climate might be affected. The Marginal Ice Zone Experiment (MIZEX 83 to 84) is an international, multidisciplinary study of processes controlling the edge of the ice pack in that area including the interactions between sea, air and ice.

Remotely Operated Vehicles under sea ice - Experiences and results from five years of polar operations

Science.gov (United States)

Katlein, Christian; Arndt, Stefanie; Lange, Benjamin; Belter, Hans Jakob; Schiller, Martin; Nicolaus, Marcel

2016-04-01

The availability of advanced robotic technologies to the Earth Science community has largely increased in the last decade. Remotely operated vehicles (ROV) enable spatially extensive scientific investigations underneath the sea ice of the polar oceans, covering a larger range and longer diving times than divers with significantly lower risks. Here we present our experiences and scientific results acquired from ROV operations during the last five years in the Arctic and Antarctic sea ice region. Working under the sea ice means to have all obstacles and investigated objects above the vehicle, and thus changes several paradigms of ROV operations as compared to blue water applications. Observations of downwelling spectral irradiance and radiance allow a characterization of the optical properties of sea ice and the spatial variability of the energy partitioning across the atmosphere-ice-ocean boundary. Our results show that the decreasing thickness and age of the sea ice have led to a significant increase in light transmission during summer over the last three decades. Spatially extensive measurements from ROV surveys generally provide more information on the light field variability than single spot measurements. The large number of sampled ice conditions during five cruises with the German research icebreaker RV Polarstern allows for the investigations of the seasonal evolution of light transmittance. Both, measurements of hyperspectral light transmittance through sea ice, as well as classification of upward-looking camera images were used to investigate the spatial distribution of ice-algal biomass. Buoyant ice-algal aggregates were found to be positioned in the stretches of level ice, rather than pressure ridges due to a physical interaction of aggregate-buoyancy and under-ice currents. Synchronous measurements of sea ice thickness by upward looking sonar provides crucial additional information to put light-transmittance and biological observations into context

Microwave emission measurements of sea surface roughness, soil moisture, and sea ice structure

Science.gov (United States)

Gloersen, P.; Wilheit, T. T.; Schmugge, T. J.

1972-01-01

In order to demonstrate the feasibility of the microwave radiometers to be carried aboard the Nimbus 5 and 6 satellites and proposed for one of the earth observatory satellites, remote measurements of microwave radiation at wavelengths ranging from 0.8 to 21 cm have been made of a variety of the earth's surfaces from the NASA CV-990 A/C. Brightness temperatures of sea water surfaces of varying roughness, of terrain with varying soil moisture, and of sea ice of varying structure were observed. In each case, around truth information was available for correlation with the microwave brightness temperature. The utility of passive microwave radiometry in determining ocean surface wind speeds, at least for values higher than 7 meters/second has been demonstrated. In addition, it was shown that radiometric signatures can be used to determine soil moisture in unvegetated terrain to within five percentage points by weight. Finally, it was demonstrated that first year thick, multi-year, and first year thin sea ice can be distinguished by observing their differing microwave emissivities at various wavelengths.

Radiative transfer in atmosphere-sea ice-ocean system

Energy Technology Data Exchange (ETDEWEB)

Jin, Z.; Stamnes, K.; Weeks, W.F. [Univ. of Alaska, Fairbanks, AK (United States); Tsay, S.C. [NASA Goddard Space Flight Center, Greenbelt, MD (United States)

1996-04-01

Radiative energy is critical in controlling the heat and mass balance of sea ice, which significantly affects the polar climate. In the polar oceans, light transmission through the atmosphere and sea ice is essential to the growth of plankton and algae and, consequently, to the microbial community both in the ice and in the ocean. Therefore, the study of radiative transfer in the polar atmosphere, sea ice, and ocean system is of particular importance. Lacking a properly coupled radiative transfer model for the atmosphere-sea ice-ocean system, a consistent study of the radiative transfer in the polar atmosphere, snow, sea ice, and ocean system has not been undertaken before. The radiative transfer processes in the atmosphere and in the ice and ocean have been treated separately. Because the radiation processes in the atmosphere, sea ice, and ocean depend on each other, this separate treatment is inconsistent. To study the radiative interaction between the atmosphere, clouds, snow, sea ice, and ocean, a radiative transfer model with consistent treatment of radiation in the coupled system is needed and is under development.

Intercomparison of passive microwave sea ice concentration retrievals over the high-concentration Arctic sea ice

DEFF Research Database (Denmark)

andersen, susanne; Tonboe, R.; Kaleschke, L.

2007-01-01

[1] Measurements of sea ice concentration from the Special Sensor Microwave Imager (SSM/I) using seven different algorithms are compared to ship observations, sea ice divergence estimates from the Radarsat Geophysical Processor System, and ice and water surface type classification of 59 wide...... with sensor noise between 1.3 and 1.8%. This is in accord with variability estimated from analysis of SSM/I time series. Algorithms, which primarily use 85 GHz information, consistently give the best agreement with both SAR ice concentrations and ship observations. Although the 85 GHz information is more...... sensitive to atmospheric influences, it was found that the atmospheric contribution is secondary to the influence of the surface emissivity variability. Analysis of the entire SSM/I time series shows that there are significant differences in trend between sea ice extent and area, using different algorithms...

Under the sea ice: Exploring the relationship between sea ice and the foraging behaviour of southern elephant seals in East Antarctica

Science.gov (United States)

Labrousse, Sara; Sallée, Jean-Baptiste; Fraser, Alexander D.; Massom, Robert A.; Reid, Phillip; Sumner, Michael; Guinet, Christophe; Harcourt, Robert; McMahon, Clive; Bailleul, Frédéric; Hindell, Mark A.; Charrassin, Jean-Benoit

2017-08-01

Investigating ecological relationships between predators and their environment is essential to understand the response of marine ecosystems to climate variability and change. This is particularly true in polar regions, where sea ice (a sensitive climate variable) plays a crucial yet highly dynamic and variable role in how it influences the whole marine ecosystem, from phytoplankton to top predators. For mesopredators such as seals, sea ice both supports a rich (under-ice) food resource, access to which depends on local to regional coverage and conditions. Here, we investigate sex-specific relationships between the foraging strategies of southern elephant seals (Mirounga leonina) in winter and spatio-temporal variability in sea ice concentration (SIC) and coverage in East Antarctica. We satellite-tracked 46 individuals undertaking post-moult trips in winter from Kerguelen Islands to the peri-Antarctic shelf between 2004 and 2014. These data indicate distinct general patterns of sea ice usage: while females tended to follow the sea ice edge as it extended northward, the males remained on the continental shelf despite increasing sea ice. Seal hunting time, a proxy of foraging activity inferred from the diving behaviour, was longer for females in late autumn in the outer part of the pack ice, ∼150-370 km south of the ice edge. Within persistent regions of compact sea ice, females had a longer foraging activity (i) in the highest sea ice concentration at their position, but (ii) their foraging activity was longer when there were more patches of low concentration sea ice around their position (either in time or in space; 30 days & 50 km). The high spatio-temporal variability of sea ice around female positions is probably a key factor allowing them to exploit these concentrated patches. Despite lack of information on prey availability, females may exploit mesopelagic finfishes and squids that concentrate near the ice-water interface or within the water column (from

Sea Ice Drift Monitoring in the Bohai Sea Based on GF4 Satellite

Science.gov (United States)

Zhao, Y.; Wei, P.; Zhu, H.; Xing, B.

2018-04-01

The Bohai Sea is the inland sea with the highest latitude in China. In winter, the phenomenon of freezing occurs in the Bohai Sea due to frequent cold wave influx. According to historical records, there have been three serious ice packs in the Bohai Sea in the past 50 years which caused heavy losses to our economy. Therefore, it is of great significance to monitor the drift of sea ice and sea ice in the Bohai Sea. The GF4 image has the advantages of short imaging time and high spatial resolution. Based on the GF4 satellite images, the three methods of SIFT (Scale invariant feature - the transform and Scale invariant feature transform), MCC (maximum cross-correlation method) and sift combined with MCC are used to monitor sea ice drift and calculate the speed and direction of sea ice drift, the three calculation results are compared and analyzed by using expert interpretation and historical statistical data to carry out remote sensing monitoring of sea ice drift results. The experimental results show that the experimental results of the three methods are in accordance with expert interpretation and historical statistics. Therefore, the GF4 remote sensing satellite images have the ability to monitor sea ice drift and can be used for drift monitoring of sea ice in the Bohai Sea.

Seasonal and interannual variability of fast ice extent in the southeastern Laptev Sea between 1999 and 2013

Science.gov (United States)

Selyuzhenok, V.; Krumpen, T.; Mahoney, A.; Janout, M.; Gerdes, R.

2015-12-01

Along with changes in sea ice extent, thickness, and drift speed, Arctic sea ice regime is characterized by a decrease of fast ice season and reduction of fast ice extent. The most extensive fast ice cover in the Arctic develops in the southeastern Laptev Sea. Using weekly operational sea ice charts produced by Arctic and Antarctic Research Institute (AARI, Russia) from 1999 to 2013, we identified five main key events that characterize the annual evolution of fast ice in the southeastern Laptev Sea. Linking the occurrence of the key events with the atmospheric forcing, bathymetry, freezeup, and melt onset, we examined the processes driving annual fast ice cycle. The analysis revealed that fast ice in the region is sensitive to thermodynamic processes throughout a season, while the wind has a strong influence only on the first stages of fast ice development. The maximal fast ice extent is closely linked to the bathymetry and local topography and is primarily defined by the location of shoals, where fast ice is likely grounded. The annual fast ice cycle shows significant changes over the period of investigation, with tendencies toward later fast ice formation and earlier breakup. These tendencies result in an overall decrease of the fast ice season by 2.8 d/yr, which is significantly higher than previously reported trends.

Optical properties of sea ice doped with black carbon – an experimental and radiative-transfer modelling comparison

Directory of Open Access Journals (Sweden)

A. A. Marks

2017-12-01

Full Text Available Radiative-transfer calculations of the light reflectivity and extinction coefficient in laboratory-generated sea ice doped with and without black carbon demonstrate that the radiative-transfer model TUV-snow can be used to predict the light reflectance and extinction coefficient as a function of wavelength. The sea ice is representative of first-year sea ice containing typical amounts of black carbon and other light-absorbing impurities. The experiments give confidence in the application of the model to predict albedo of other sea ice fabrics. Sea ices,  ∼  30 cm thick, were generated in the Royal Holloway Sea Ice Simulator ( ∼  2000 L tanks with scattering cross sections measured between 0.012 and 0.032 m2 kg−1 for four ices. Sea ices were generated with and without  ∼  5 cm upper layers containing particulate black carbon. Nadir reflectances between 0.60 and 0.78 were measured along with extinction coefficients of 0.1 to 0.03 cm−1 (e-folding depths of 10–30 cm at a wavelength of 500 nm. Values were measured between light wavelengths of 350 and 650 nm. The sea ices generated in the Royal Holloway Sea Ice Simulator were found to be representative of natural sea ices. Particulate black carbon at mass ratios of  ∼  75,  ∼  150 and  ∼  300 ng g−1 in a 5 cm ice layer lowers the albedo to 97, 90 and 79 % of the reflectivity of an undoped clean sea ice (at a wavelength of 500 nm.

The effects of additional black carbon on the albedo of Arctic sea ice: variation with sea ice type and snow cover

OpenAIRE

A. A. Marks; M. D. King

2013-01-01

The response of the albedo of bare sea ice and snow-covered sea ice to the addition of black carbon is calculated. Visible light absorption and light-scattering cross-sections are derived for a typical first-year and multi-year sea ice with both "dry" and "wet" snow types. The cross-sections are derived using data from a 1970s field study that recorded both reflectivity and light penetration in Arctic sea ice and snow overlying sea ice. The variation of absorption cross-section ov...

Inuit and Scientific Perspectives on the Relationship Between Sea Ice and Climate Change. The Ideal Complement?

Energy Technology Data Exchange (ETDEWEB)

Laidler, G.J. [Department of Geography, University of Toronto at Mississauga, 3359 Mississauga Road North, Mississauga, Ontario, L5L 1C6 (Canada)

2006-10-15

Sea ice is influential in regulating energy exchanges between the ocean and the atmosphere, and has figured prominently in scientific studies of climate change and climate feedbacks. However, sea ice is also a vital component of everyday life in Inuit communities of the circumpolar Arctic. Therefore, it is important to understand the links between the potential impacts of climate change on Arctic sea ice extent, distribution, and thickness as well as the related consequences for northern coastal populations. This paper explores the relationship between sea ice and climate change from both scientific and Inuit perspectives. Based on an overview of diverse literature the experiences, methods, and goals which differentiate local and scientific sea ice knowledge are examined. These efforts are considered essential background upon which to develop more accurate assessments of community vulnerability to climate, and resulting sea ice, change. Inuit and scientific perspectives may indeed be the ideal complement when investigating the links between sea ice and climate change, but effective and appropriate conceptual bridges need to be built between the two types of expertise. The complementary nature of these knowledge systems may only be realized, in a practical sense, if significant effort is expended to: (1) understand sea ice from both Inuit and scientific perspectives, along with their underlying differences; (2) investigate common interests or concerns; (3) establish meaningful and reciprocal research partnerships with Inuit communities; (4) engage in, and improve, collaborative research methods; and, (5) maintain ongoing dialogue.

Radar and infrared remote sensing of terrain, water resources, arctic sea ice, and agriculture

Science.gov (United States)

Biggs, A. W.

1983-01-01

Radar range measurements, basic waveforms of radar systems, and radar displays are initially described. These are followed by backscatter from several types of terrain and vegetation as a function of frequency and grazing angle. Analytical models for this backscatter include the facet models of radar return, with range-angle, velocity-range, velocity-angle, range, velocity, and angular only discriminations. Several side-looking airborne radar geometries are presented. Radar images of Arctic sea ice, fresh water lake ice, cloud-covered terrain, and related areas are presented to identify applications of radar imagery. Volume scatter models are applied to radar imagery from alpine snowfields. Short pulse ice thickness radar for subsurface probes is discussed in fresh-water ice and sea ice detection. Infrared scanners, including multispectral, are described. Diffusion of cold water into a river, Arctic sea ice, power plant discharges, volcanic heat, and related areas are presented in thermal imagery. Multispectral radar and infrared imagery are discussed, with comparisons of photographic, infrared, and radar imagery of the same terrain or subjects.

Minimum and Maximum Potential Contributions to Future Sea Level Rise from Polar Ice Sheets

Science.gov (United States)

Deconto, R. M.; Pollard, D.

2017-12-01

New climate and ice-sheet modeling, calibrated to past changes in sea-level, is painting a stark picture of the future fate of the great polar ice sheets if greenhouse gas emissions continue unabated. This is especially true for Antarctica, where a substantial fraction of the ice sheet rests on bedrock more than 500-meters below sea level. Here, we explore the sensitivity of the polar ice sheets to a warming atmosphere and ocean under a range of future greenhouse gas emissions scenarios. The ice sheet-climate-ocean model used here considers time-evolving changes in surface mass balance and sub-ice oceanic melting, ice deformation, grounding line retreat on reverse-sloped bedrock (Marine Ice Sheet Instability), and newly added processes including hydrofracturing of ice shelves in response to surface meltwater and rain, and structural collapse of thick, marine-terminating ice margins with tall ice-cliff faces (Marine Ice Cliff Instability). The simulations improve on previous work by using 1) improved atmospheric forcing from a Regional Climate Model and 2) a much wider range of model physical parameters within the bounds of modern observations of ice dynamical processes (particularly calving rates) and paleo constraints on past ice-sheet response to warming. Approaches to more precisely define the climatic thresholds capable of triggering rapid and potentially irreversible ice-sheet retreat are also discussed, as is the potential for aggressive mitigation strategies like those discussed at the 2015 Paris Climate Conference (COP21) to substantially reduce the risk of extreme sea-level rise. These results, including physics that consider both ice deformation (creep) and calving (mechanical failure of marine terminating ice) expand on previously estimated limits of maximum rates of future sea level rise based solely on kinematic constraints of glacier flow. At the high end, the new results show the potential for more than 2m of global mean sea level rise by 2100

Statistical Analyses of High-Resolution Aircraft and Satellite Observations of Sea Ice: Applications for Improving Model Simulations

Science.gov (United States)

Farrell, S. L.; Kurtz, N. T.; Richter-Menge, J.; Harbeck, J. P.; Onana, V.

2012-12-01

Satellite-derived estimates of ice thickness and observations of ice extent over the last decade point to a downward trend in the basin-scale ice volume of the Arctic Ocean. This loss has broad-ranging impacts on the regional climate and ecosystems, as well as implications for regional infrastructure, marine navigation, national security, and resource exploration. New observational datasets at small spatial and temporal scales are now required to improve our understanding of physical processes occurring within the ice pack and advance parameterizations in the next generation of numerical sea-ice models. High-resolution airborne and satellite observations of the sea ice are now available at meter-scale resolution or better that provide new details on the properties and morphology of the ice pack across basin scales. For example the NASA IceBridge airborne campaign routinely surveys the sea ice of the Arctic and Southern Oceans with an advanced sensor suite including laser and radar altimeters and digital cameras that together provide high-resolution measurements of sea ice freeboard, thickness, snow depth and lead distribution. Here we present statistical analyses of the ice pack primarily derived from the following IceBridge instruments: the Digital Mapping System (DMS), a nadir-looking, high-resolution digital camera; the Airborne Topographic Mapper, a scanning lidar; and the University of Kansas snow radar, a novel instrument designed to estimate snow depth on sea ice. Together these instruments provide data from which a wide range of sea ice properties may be derived. We provide statistics on lead distribution and spacing, lead width and area, floe size and distance between floes, as well as ridge height, frequency and distribution. The goals of this study are to (i) identify unique statistics that can be used to describe the characteristics of specific ice regions, for example first-year/multi-year ice, diffuse ice edge/consolidated ice pack, and convergent

Atmospheric forcing of sea ice leads in the Beaufort Sea

Science.gov (United States)

Lewis, B. J.; Hutchings, J.; Mahoney, A. R.; Shapiro, L. H.

2016-12-01

Leads in sea ice play an important role in the polar marine environment where they allow heat and moisture transfer between the oceans and atmosphere and act as travel pathways for both marine mammals and ships. Examining AVHRR thermal imagery of the Beaufort Sea, collected between 1994 and 2010, sea ice leads appear in repeating patterns and locations (Eicken et al 2005). The leads, resolved by AVHRR, are at least 250m wide (Mahoney et al 2012), thus the patterns described are for lead systems that extend up to hundreds of kilometers across the Beaufort Sea. We describe how these patterns are associated with the location of weather systems relative to the coastline. Mean sea level pressure and 10m wind fields from ECMWF ERA-Interim reanalysis are used to identify if particular lead patterns can be uniquely forecast based on the location of weather systems. Ice drift data from the NSIDC's Polar Pathfinder Daily 25km EASE-Grid Sea Ice Motion Vectors indicates the role shear along leads has on the motion of ice in the Beaufort Gyre. Lead formation is driven by 4 main factors: (i) coastal features such as promontories and islands influence the origin of leads by concentrating stresses within the ice pack; (ii) direction of the wind forcing on the ice pack determines the type of fracture, (iii) the location of the anticyclone (or cyclone) center determines the length of the fracture for certain patterns; and (iv) duration of weather conditions affects the width of the ice fracture zones. Movement of the ice pack on the leeward side of leads originating at promontories and islands increases, creating shear zones that control ice transport along the Alaska coast in winter. . Understanding how atmospheric conditions influence the large-scale motion of the ice pack is needed to design models that predict variability of the gyre and export of multi-year ice to lower latitudes.

Sea ice in the Baltic Sea - revisiting BASIS ice, a~historical data set covering the period 1960/1961-1978/1979

Science.gov (United States)

Löptien, U.; Dietze, H.

2014-06-01

The Baltic Sea is a seasonally ice-covered, marginal sea, situated in central northern Europe. It is an essential waterway connecting highly industrialised countries. Because ship traffic is intermittently hindered by sea ice, the local weather services have been monitoring sea ice conditions for decades. In the present study we revisit a historical monitoring data set, covering the winters 1960/1961. This data set, dubbed Data Bank for Baltic Sea Ice and Sea Surface Temperatures (BASIS) ice, is based on hand-drawn maps that were collected and then digitised 1981 in a joint project of the Finnish Institute of Marine Research (today Finish Meteorological Institute (FMI)) and the Swedish Meteorological and Hydrological Institute (SMHI). BASIS ice was designed for storage on punch cards and all ice information is encoded by five digits. This makes the data hard to access. Here we present a post-processed product based on the original five-digit code. Specifically, we convert to standard ice quantities (including information on ice types), which we distribute in the current and free Network Common Data Format (NetCDF). Our post-processed data set will help to assess numerical ice models and provide easy-to-access unique historical reference material for sea ice in the Baltic Sea. In addition we provide statistics showcasing the data quality. The website www.baltic-ocean.org hosts the post-prossed data and the conversion code. The data are also archived at the Data Publisher for Earth & Environmental Science PANGEA (doi:10.1594/PANGEA.832353).

Sea ice in the Baltic Sea - revisiting BASIS ice, a historical data set covering the period 1960/1961-1978/1979

Science.gov (United States)

Löptien, U.; Dietze, H.

2014-12-01

The Baltic Sea is a seasonally ice-covered, marginal sea in central northern Europe. It is an essential waterway connecting highly industrialised countries. Because ship traffic is intermittently hindered by sea ice, the local weather services have been monitoring sea ice conditions for decades. In the present study we revisit a historical monitoring data set, covering the winters 1960/1961 to 1978/1979. This data set, dubbed Data Bank for Baltic Sea Ice and Sea Surface Temperatures (BASIS) ice, is based on hand-drawn maps that were collected and then digitised in 1981 in a joint project of the Finnish Institute of Marine Research (today the Finnish Meteorological Institute (FMI)) and the Swedish Meteorological and Hydrological Institute (SMHI). BASIS ice was designed for storage on punch cards and all ice information is encoded by five digits. This makes the data hard to access. Here we present a post-processed product based on the original five-digit code. Specifically, we convert to standard ice quantities (including information on ice types), which we distribute in the current and free Network Common Data Format (NetCDF). Our post-processed data set will help to assess numerical ice models and provide easy-to-access unique historical reference material for sea ice in the Baltic Sea. In addition we provide statistics showcasing the data quality. The website http://www.baltic-ocean.org hosts the post-processed data and the conversion code. The data are also archived at the Data Publisher for Earth & Environmental Science, PANGAEA (doi:10.1594/PANGAEA.832353).

Sea ice dynamics influence halogen deposition to Svalbard

Directory of Open Access Journals (Sweden)

A. Spolaor

2013-10-01

Full Text Available Sea ice is an important parameter in the climate system and its changes impact upon the polar albedo and atmospheric and oceanic circulation. Iodine (I and bromine (Br have been measured in a shallow firn core drilled at the summit of the Holtedahlfonna glacier (Northwest Spitsbergen, Svalbard. Changing I concentrations can be linked to the March–May maximum sea ice extension. Bromine enrichment, indexed to the Br / Na sea water mass ratio, appears to be influenced by changes in the seasonal sea ice area. I is emitted from marine biota and so the retreat of March–May sea ice coincides with enlargement of the open-ocean surface which enhances marine primary production and consequent I emission. The observed Br enrichment could be explained by greater Br emissions during the Br explosions that have been observed to occur mainly above first year sea ice during the early springtime. In this work we present the first comparison between halogens in surface snow and Arctic sea ice extension. Although further investigation is required to characterize potential depositional and post-depositional processes, these preliminary findings suggest that I and Br can be linked to variability in the spring maximum sea ice extension and seasonal sea ice surface area.

Mapping Arctic Bottomfast Sea Ice Using SAR Interferometry

Directory of Open Access Journals (Sweden)

Dyre O. Dammann

2018-05-01

Full Text Available Bottomfast sea ice is an integral part of many near-coastal Arctic ecosystems with implications for subsea permafrost, coastal stability and morphology. Bottomfast sea ice is also of great relevance to over-ice travel by coastal communities, industrial ice roads, and marine habitats. There are currently large uncertainties around where and how much bottomfast ice is present in the Arctic due to the lack of effective approaches for detecting bottomfast sea ice on large spatial scales. Here, we suggest a robust method capable of detecting bottomfast sea ice using spaceborne synthetic aperture radar interferometry. This approach is used to discriminate between slowly deforming floating ice and completely stationary bottomfast ice based on the interferometric phase. We validate the approach over freshwater ice in the Mackenzie Delta, Canada, and over sea ice in the Colville Delta and Elson Lagoon, Alaska. For these areas, bottomfast ice, as interpreted from the interferometric phase, shows high correlation with local bathymetry and in-situ ice auger and ground penetrating radar measurements. The technique is further used to track the seasonal evolution of bottomfast ice in the Kasegaluk Lagoon, Alaska, by identifying freeze-up progression and areas of liquid water throughout winter.

Calcium carbonate as ikaite crystals in Antarctic sea ice

Science.gov (United States)

Dieckmann, Gerhard S.; Nehrke, Gernot; Papadimitriou, Stathys; Göttlicher, Jörg; Steininger, Ralph; Kennedy, Hilary; Wolf-Gladrow, Dieter; Thomas, David N.

2008-04-01

We report on the discovery of the mineral ikaite (CaCO3.6H2O) in sea-ice from the Southern Ocean. The precipitation of CaCO3 during the freezing of seawater has previously been predicted from thermodynamic modelling, indirect measurements, and has been documented in artificial sea ice during laboratory experiments but has not been reported for natural sea-ice. It is assumed that CaCO3 formation in sea ice may be important for a sea ice-driven carbon pump in ice-covered oceanic waters. Without direct evidence of CaCO3 precipitation in sea ice, its role in this and other processes has remained speculative. The discovery of CaCO3.6H2O crystals in natural sea ice provides the necessary evidence for the evaluation of previous assumptions and lays the foundation for further studies to help elucidate the role of ikaite in the carbon cycle of the seasonally sea ice-covered regions

Canadian Ice Service Arctic Regional Sea Ice Charts in SIGRID-3 Format

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Canadian Ice Service (CIS) produces digital Arctic regional sea ice charts for marine navigation, climate research, and input to the Global Digital Sea Ice Data...

Severnaya Zemlya, arctic Russia: a nucleation area for Kara Sea ice sheets during the Middle to Late Quaternary

DEFF Research Database (Denmark)

Möller, Per; Lubinski, David J.; Ingólfsson, Ólafur

2006-01-01

Quaternary glacial stratigraphy and relative sea-level changes reveal at least four expansions of the Kara Sea ice sheet over the Severnaya Zemlya Archipelago at 79°N in the Russian Arctic, as indicated from tills interbedded with marine sediments, exposed in stratigraphic superposition, and from...... of a large Kara Sea ice sheet, with exception of the Last Glacial Maximum (MIS 2), when Kara Sea ice did not impact Severnaya Zemlya and barely graced northernmost Taymyr Peninsula.......Quaternary glacial stratigraphy and relative sea-level changes reveal at least four expansions of the Kara Sea ice sheet over the Severnaya Zemlya Archipelago at 79°N in the Russian Arctic, as indicated from tills interbedded with marine sediments, exposed in stratigraphic superposition, and from......-5e and MIS 5d-3. The MIS 6-5e event, associated with the high marine limit, implies ice-sheet thickness of >2000 m only 200 km from the deep Arctic Ocean, consistent with published evidence of ice grounding at ~1000 m water depth in the central Arctic Ocean. Till fabrics and glacial tectonics record...

Synthesis of User Needs for Arctic Sea Ice Predictions

Science.gov (United States)

Wiggins, H. V.; Turner-Bogren, E. J.; Sheffield Guy, L.

2017-12-01

Forecasting Arctic sea ice on sub-seasonal to seasonal scales in a changing Arctic is of interest to a diverse range of stakeholders. However, sea ice forecasting is still challenging due to high variability in weather and ocean conditions and limits to prediction capabilities; the science needs for observations and modeling are extensive. At a time of challenged science funding, one way to prioritize sea ice prediction efforts is to examine the information needs of various stakeholder groups. This poster will present a summary and synthesis of existing surveys, reports, and other literature that examines user needs for sea ice predictions. The synthesis will include lessons learned from the Sea Ice Prediction Network (a collaborative, multi-agency-funded project focused on seasonal Arctic sea ice predictions), the Sea Ice for Walrus Outlook (a resource for Alaska Native subsistence hunters and coastal communities, that provides reports on weather and sea ice conditions), and other efforts. The poster will specifically compare the scales and variables of sea ice forecasts currently available, as compared to what information is requested by various user groups.

Late Quaternary Variability of Arctic Sea Ice: Insights From Biomarker Proxy Records and Model Simulations

Science.gov (United States)

Stein, R. H.; Fahl, K.; Gierz, P.; Niessen, F.; Lohmann, G.

2017-12-01

Over the last about four decades, coinciding with global warming and atmospheric CO2increase, the extent and thickness of Arctic sea ice has decreased dramatically, a decrease much more rapid than predicted by climate models. The driving forces of this change are still not fully understood. In this context, detailed paleoclimatic records going back beyond the timescale of direct observations, i.e., high-resolution Holocene records but also records representing more distant warm periods, may help to to distinguish and quantify more precisely the natural and anthropogenic greenhouse gas forcing of global climate change and related sea ice decrease. Here, we concentrate on sea ice biomarker records representing the penultimate glacial/last interglacial (MIS 6/MIS 5e) and the Holocene time intervals. Our proxy records are compared with climate model simulations using a coupled atmosphere-ocean general circulation model (AOGCM). Based on our data, polynya-type sea ice conditions probably occurred off the major ice sheets along the northern Barents and East Siberian continental margins during late MIS 6. Furthermore, we demonstrate that even during MIS 5e, i.e., a time interval when the high latitudes have been significantly warmer than today, sea ice existed in the central Arctic Ocean during summer, whereas sea ice was significantly reduced along the Barents Sea continental margin influenced by Atlantic Water inflow. Assuming a closed Bering Strait (no Pacific Water inflow) during early MIS 5, model simulations point to a significantly reduced sea ice cover in the central Arctic Ocean, a scenario that is however not supported by the proxy record and thus seems to be less realistic. Our Holocene biomarker proxy records from the Chukchi Sea indicate that main factors controlling the millennial Holocene variability in sea ice are probably changes in surface water and heat flow from the Pacific into the Arctic Ocean as well as the long-term decrease in summer insolation

IceBridge Radar L3 Tomographic Ice Thickness V001

Data.gov (United States)

National Aeronautics and Space Administration — This data set contains Level-3 tomographic ice thickness measurements derived from data captured by the Center for Remote Sensing of Ice Sheets (CReSIS) Multichannel...

Mechanisms causing reduced Arctic sea ice loss in a coupled climate model

Directory of Open Access Journals (Sweden)

A. E. West

2013-03-01

Full Text Available The fully coupled climate model HadGEM1 produces one of the most accurate simulations of the historical record of Arctic sea ice seen in the IPCC AR4 multi-model ensemble. In this study, we examine projections of sea ice decline out to 2030, produced by two ensembles of HadGEM1 with natural and anthropogenic forcings included. These ensembles project a significant slowing of the rate of ice loss to occur after 2010, with some integrations even simulating a small increase in ice area. We use an energy budget of the Arctic to examine the causes of this slowdown. A negative feedback effect by which rapid reductions in ice thickness north of Greenland reduce ice export is found to play a major role. A slight reduction in ocean-to-ice heat flux in the relevant period, caused by changes in the meridional overturning circulation (MOC and subpolar gyre in some integrations, as well as freshening of the mixed layer driven by causes other than ice melt, is also found to play a part. Finally, we assess the likelihood of a slowdown occurring in the real world due to these causes.

Greenland Radar Ice Sheet Thickness Measurements

Data.gov (United States)

National Aeronautics and Space Administration — Two 150-MHz coherent radar depth sounders were developed and flown over the Greenland ice sheet to obtain ice thickness measurements in support of PARCA...

Arctic and Antarctic Sea Ice Changes and Impacts (Invited)

Science.gov (United States)

Nghiem, S. V.

2013-12-01

The extent of springtime Arctic perennial sea ice, important to preconditioning summer melt and to polar sunrise photochemistry, continues its precipitous reduction in the last decade marked by a record low in 2012, as the Bromine, Ozone, and Mercury Experiment (BROMEX) was conducted around Barrow, Alaska, to investigate impacts of sea ice reduction on photochemical processes, transport, and distribution in the polar environment. In spring 2013, there was further loss of perennial sea ice, as it was not observed in the ocean region adjacent to the Alaskan north coast, where there was a stretch of perennial sea ice in 2012 in the Beaufort Sea and Chukchi Sea. In contrast to the rapid and extensive loss of sea ice in the Arctic, Antarctic sea ice has a trend of a slight increase in the past three decades. Given the significant variability in time and in space together with uncertainties in satellite observations, the increasing trend of Antarctic sea ice may arguably be considered as having a low confidence level; however, there was no overall reduction of Antarctic sea ice extent anywhere close to the decreasing rate of Arctic sea ice. There exist publications presenting various factors driving changes in Arctic and Antarctic sea ice. After a short review of these published factors, new observations and atmospheric, oceanic, hydrological, and geological mechanisms contributed to different behaviors of sea ice changes in the Arctic and Antarctic are presented. The contribution from of hydrologic factors may provide a linkage to and enhance thermal impacts from lower latitudes. While geological factors may affect the sensitivity of sea ice response to climate change, these factors can serve as the long-term memory in the system that should be exploited to improve future projections or predictions of sea ice changes. Furthermore, similarities and differences in chemical impacts of Arctic and Antarctic sea ice changes are discussed. Understanding sea ice changes and

Albedo of the ice covered Weddell and Bellingshausen Seas

OpenAIRE

A. I. Weiss; J. C. King; T. A. Lachlan-Cope; R. S. Ladkin

2012-01-01

This study investigates the surface albedo of the sea ice areas adjacent to the Antarctic Peninsula during the austral summer. Aircraft measurements of the surface albedo, which were conducted in the sea ice areas of the Weddell and Bellingshausen Seas show significant differences between these two regions. The averaged surface albedo varied between 0.13 and 0.81. The ice cover of the Bellingshausen Sea consisted mainly of first year ice and the sea surface showed an averaged sea ice albedo o...

Albedo of the ice-covered Weddell and Bellingshausen Sea

OpenAIRE

A. I. Weiss; J. C. King; T. A. Lachlan-Cope; R. S. Ladkin

2011-01-01

This study investigates the surface albedo of the sea ice areas adjacent to the Antarctic Peninsula during the austral summer. Aircraft measurements of the surface albedo which were conducted in the sea ice areas of the Weddell and Bellingshausen Sea show significant differences between these two regions. The averaged surface albedo varied between 0.13 and 0.81. The ice cover of the Bellingshausen Sea consisted mainly of first year ice and the sea surface showed an averaged sea ice albed...

Modelling the future of the arctic sea ice cover

OpenAIRE

Myklebust, Erik Bryhn

2017-01-01

Record lows in sea ice cover have recently sparked new interest in the small ice cap instability. The change in albedo when sea ice becomes open water introduces a nonlinearity called the ice-albedo feedback. Forcing a joint energy- balance and sea ice model can lead to unstable ice caps in certain parameter regimes. When the ice caps are unstable, a small perturbation will initiate a tipping point in the sea ice cover. For tipping points in general, a number of studies have pointed out that ...

Constraining the parameters of the EAP sea ice rheology from satellite observations and discrete element model

Science.gov (United States)

Tsamados, Michel; Heorton, Harry; Feltham, Daniel; Muir, Alan; Baker, Steven

2016-04-01

The new elastic-plastic anisotropic (EAP) rheology that explicitly accounts for the sub-continuum anisotropy of the sea ice cover has been implemented into the latest version of the Los Alamos sea ice model CICE. The EAP rheology is widely used in the climate modeling scientific community (i.e. CPOM stand alone, RASM high resolution regional ice-ocean model, MetOffice fully coupled model). Early results from sensitivity studies (Tsamados et al, 2013) have shown the potential for an improved representation of the observed main sea ice characteristics with a substantial change of the spatial distribution of ice thickness and ice drift relative to model runs with the reference visco-plastic (VP) rheology. The model contains one new prognostic variable, the local structure tensor, which quantifies the degree of anisotropy of the sea ice, and two parameters that set the time scale of the evolution of this tensor. Observations from high resolution satellite SAR imagery as well as numerical simulation results from a discrete element model (DEM, see Wilchinsky, 2010) have shown that these individual floes can organize under external wind and thermal forcing to form an emergent isotropic sea ice state (via thermodynamic healing, thermal cracking) or an anisotropic sea ice state (via Coulombic failure lines due to shear rupture). In this work we use for the first time in the context of sea ice research a mathematical metric, the Tensorial Minkowski functionals (Schroeder-Turk, 2010), to measure quantitatively the degree of anisotropy and alignment of the sea ice at different scales. We apply the methodology on the GlobICE Envisat satellite deformation product (www.globice.info), on a prototype modified version of GlobICE applied on Sentinel-1 Synthetic Aperture Radar (SAR) imagery and on the DEM ice floe aggregates. By comparing these independent measurements of the sea ice anisotropy as well as its temporal evolution against the EAP model we are able to constrain the