WorldWideScience

Sample records for sar sea ice

  1. Sea ice classification using dual polarization SAR data

    Science.gov (United States)

    Huiying, Liu; Huadong, Guo; Lu, Zhang

    2014-03-01

    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.

  2. 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)...

  3. Estimation of Snow Thickness on Sea Ice and Lake Ice Using Airborne SnowSAR Data

    Science.gov (United States)

    Veijola, Katriina; Makynen, Marko; Lemmetyinen, Juha; Praks, Jaan

    2016-08-01

    Currently, snow thickness on sea ice is operationally estimated using microwave radiometer data. However, the estimates are hampered by the inherent coarse spatial resolution of passive microwave sensors. Successful application of SAR imagery for snow thickness estimation has the potential of providing estimates of snow thickness with much finer spatial resolution.In this study, we concentrate on assessing the capability of X- and Ku-band SAR backscattering to estimate snow thickness on sea and lake ice. Co- and cross -polarized X- and Ku-band SAR backscattering data, acquired with the ESA airborne SnowSAR sensor, are applied. The SAR data acquisition and co-incident in-situ measurements were conducted in Finland in the winter of 2012 over sea ice and lake ice test sites.Our analysis shows which frequency and polarization combinations have best sensitivity to snow thickness on sea and lake ice and in deep discussion provides plausible ways to improve the results.

  4. Polarimetric C-Band SAR Observations of Sea Ice in the Greenland Sea

    DEFF Research Database (Denmark)

    Thomsen, Bjørn Bavnehøj; Nghiem, S.V.; Kwok, R.

    1998-01-01

    The fully polarimetric EMISAR acquired C-band radar signatures of sea ice in the Greenland Sea during a campaign in March 1995. The authors present maps of polarimetric signatures over an area containing various kinds of ice and discuss the use of polarimetric SAR for identification of ice types...

  5. Assimilation of ice and water observations from SAR imagery to improve estimates of sea ice concentration

    Directory of Open Access Journals (Sweden)

    K. Andrea Scott

    2015-09-01

    Full Text Available In this paper, the assimilation of binary observations calculated from synthetic aperture radar (SAR images of sea ice is investigated. Ice and water observations are obtained from a set of SAR images by thresholding ice and water probabilities calculated using a supervised maximum likelihood estimator (MLE. These ice and water observations are then assimilated in combination with ice concentration from passive microwave imagery for the purpose of estimating sea ice concentration. Due to the fact that the observations are binary, consisting of zeros and ones, while the state vector is a continuous variable (ice concentration, the forward model used to map the state vector to the observation space requires special consideration. Both linear and non-linear forward models were investigated. In both cases, the assimilation of SAR data was able to produce ice concentration analyses in closer agreement with image analysis charts than when assimilating passive microwave data only. When both passive microwave and SAR data are assimilated, the bias between the ice concentration analyses and the ice concentration from ice charts is 19.78%, as compared to 26.72% when only passive microwave data are assimilated. The method presented here for the assimilation of SAR data could be applied to other binary observations, such as ice/water information from visual/infrared sensors.

  6. Sea ice concentration and sea ice drift for the Arctic summer using C- and L-band SAR

    Science.gov (United States)

    Johansson, Malin; Berg, Anders; Eriksson, Leif

    2014-05-01

    The decreasing amount of sea ice and changes from multi-year ice to first year ice within the Arctic Ocean opens up for increased maritime activities. These activities include transportation, fishing and tourism. One of the major threats for the shipping is the presence of sea ice. Should an oil spill occur, the search and rescue is heavily dependent on constant updates of sea ice movements, both to enable a safer working environment and to potentially prevent the oil from reaching the sea ice. It is therefore necessary to have accurate and updated sea ice charts for the Arctic Ocean during the entire year. During the melt season that ice is subject to melting conditions making satellite observations of sea ice more difficult. This period coincides with the peak in marine shipping activities and therefore requires highly accurate sea ice concentration estimates. Synthetic Aperture Radar (SAR) are not hindered by clouds and do not require daylight. The continuous record and high temporal resolution makes C-band data preferable as input data for operational sea ice mapping. However, with C-band SAR it is sometimes difficult to distinguish between a wet sea ice surface and surrounding open water. L-band SAR has a larger penetration depth and has been shown to be less sensitive to less sensitive than C-band to the melt season. Inclusion of L-band data into sea chart estimates during the melt season in particular could therefore improve sea ice monitoring. We compare sea ice concentration melt season observations using Advanced Land Observing Satellite (ALOS) L-band images with Envisat ASAR C-band images. We evaluate if L-band images can be used to improve separation of wet surface ice from open water and compare with results for C-band.

  7. Analysis of multi-dimensional SAR for determining the thickness of thin sea ice in the Bohai Sea

    Institute of Scientific and Technical Information of China (English)

    ZHANG Xi; ZHANG Jie; MENG Junmin; SU Tengfei

    2013-01-01

    Flat thin ice(30 cm thick) is a common ice type in the Bohai Sea, China. Ice thickness detection is important to offshore exploration and marine transport in winter. Synthetic aperture radar (SAR) can be used to acquire sea ice data in all weather conditions, and it is a useful tool for monitoring sea ice conditions. In this paper, we combine a multi-layered sea ice electromagnetic (EM) scattering model with a sea ice thermodynamic model to assess the determination of the thickness of flat thin ice in the Bohai Sea using SAR at different frequencies, polarization, and incidence angles. Our modeling studies suggest that co-polarization backscattering coefficients and the co-polarized ratio can be used to retrieve the thickness of flat thin ice from C- and X-band SAR, while the co-polarized correlation coefficient can be used to retrieve flat thin ice thickness from L-, C-, and X-band SAR. Importantly, small or moderate incidence angles should be chosen to avoid the effect of speckle noise.

  8. Comparing C- and L-band SAR images for sea ice motion estimation

    Science.gov (United States)

    Lehtiranta, J.; Siiriä, S.; Karvonen, J.

    2015-02-01

    Pairs of consecutive C-band synthetic-aperture radar (SAR) images are routinely used for sea ice motion estimation. The L-band radar has a fundamentally different character, as its longer wavelength penetrates deeper into sea ice. L-band SAR provides information on the seasonal sea ice inner structure in addition to the surface roughness that dominates C-band images. This is especially useful in the Baltic Sea, which lacks multiyear ice and icebergs, known to be confusing targets for L-band sea ice classification. In this work, L-band SAR images are investigated for sea ice motion estimation using the well-established maximal cross-correlation (MCC) approach. This work provides the first comparison of L-band and C-band SAR images for the purpose of motion estimation. The cross-correlation calculations are hardware accelerated using new OpenCL-based source code, which is made available through the author's web site. It is found that L-band images are preferable for motion estimation over C-band images. It is also shown that motion estimation is possible between a C-band and an L-band image using the maximal cross-correlation technique.

  9. Geostatistical and Statistical Classification of Sea-Ice Properties and Provinces from SAR Data

    Directory of Open Access Journals (Sweden)

    Ute C. Herzfeld

    2016-07-01

    Full Text Available Recent drastic reductions in the Arctic sea-ice cover have raised an interest in understanding the role of sea ice in the global system as well as pointed out a need to understand the physical processes that lead to such changes. Satellite remote-sensing data provide important information about remote ice areas, and Synthetic Aperture Radar (SAR data have the advantages of penetration of the omnipresent cloud cover and of high spatial resolution. A challenge addressed in this paper is how to extract information on sea-ice types and sea-ice processes from SAR data. We introduce, validate and apply geostatistical and statistical approaches to automated classification of sea ice from SAR data, to be used as individual tools for mapping sea-ice properties and provinces or in combination. A key concept of the geostatistical classification method is the analysis of spatial surface structures and their anisotropies, more generally, of spatial surface roughness, at variable, intermediate-sized scales. The geostatistical approach utilizes vario parameters extracted from directional vario functions, the parameters can be mapped or combined into feature vectors for classification. The method is flexible with respect to window sizes and parameter types and detects anisotropies. In two applications to RADARSAT and ERS-2 SAR data from the area near Point Barrow, Alaska, it is demonstrated that vario-parameter maps may be utilized to distinguish regions of different sea-ice characteristics in the Beaufort Sea, the Chukchi Sea and in Elson Lagoon. In a third and a fourth case study the analysis is taken further by utilizing multi-parameter feature vectors as inputs for unsupervised and supervised statistical classification. Field measurements and high-resolution aerial observations serve as basis for validation of the geostatistical-statistical classification methods. A combination of supervised classification and vario-parameter mapping yields best results

  10. Assessment of C-band compact polarimetry SAR for sea ice classification

    Institute of Scientific and Technical Information of China (English)

    ZHANG Xi; ZHANG Jie; LIU Meijie; MENG Junmin

    2016-01-01

    0HH 0V V 0 HV The C-band synthetic aperture radar (SAR) data from the Bohai Sea of China, the Labrador Sea in the Arctic and the Weddell Sea in the Antarctic are used to analyze and discuss the sea ice full polarimetric information reconstruction ability under compact polarimetric modes. The type of compact polarimetric mode which has the highest reconstructed accuracy is analyzed, along with the performance impact of the reconstructed pseudo quad-pol SAR data on the sea ice detection and sea ice classification. According to the assessment and analysis, it is recommended to adopt the CTLR mode for reconstructing the polarimetric parameters , ,H andα, while for reconstructing the polarimetric parameters ,ρH-V,λ1 andλ2, it is recommended to use the π/4 mode. Moreover, it is recommended to use the π/4 mode in studying the action effects between the electromagnetic waves and sea ice, but it is recommended to use the CTLR mode for studying the sea ice classification.

  11. Late summer sea ice segmentation with multi-polarisation SAR features in C- and X-band

    Directory of Open Access Journals (Sweden)

    A. S. Fors

    2015-09-01

    Full Text Available In this study we investigate the potential of sea ice segmentation by C- and X-band multi-polarisation synthetic aperture radar (SAR features during late summer. Five high-resolution satellite SAR scenes were recorded in the Fram Strait covering iceberg-fast first-year and old sea ice during a week with air temperatures varying around zero degrees Celsius. In situ data consisting of sea ice thickness, surface roughness and aerial photographs were collected during a helicopter flight at the site. Six polarimetric SAR features were extracted for each of the scenes. The ability of the individual SAR features to discriminate between sea ice types and their temporally consistency were examined. All SAR features were found to add value to sea ice type discrimination. Relative kurtosis, geometric brightness, cross-polarisation ratio and co-polarisation correlation angle were found to be temporally consistent in the investigated period, while co-polarisation ratio and co-polarisation correlation magnitude were found to be temporally inconsistent. An automatic feature-based segmentation algorithm was tested both for a full SAR feature set, and for a reduced SAR feature set limited to temporally consistent features. In general, the algorithm produces a good late summer sea ice segmentation. Excluding temporally inconsistent SAR features improved the segmentation at air temperatures above zero degrees Celcius.

  12. PCA-based sea-ice image fusion of optical data by HIS transform and SAR data by wavelet transform

    Institute of Scientific and Technical Information of China (English)

    LIU Meijie; DAI Yongshou; ZHANG Jie; ZHANG Xi; MENG Junmin; XIE Qinchuan

    2015-01-01

    Sea ice as a disaster has recently attracted a great deal of attention in China. Its monitoring has become a routine task for the maritime sector. Remote sensing, which depends mainly on SAR and optical sensors, has become the primary means for sea-ice research. Optical images contain abundant sea-ice multi-spectral in-formation, whereas SAR images contain rich sea-ice texture information. If the characteristic advantages of SAR and optical images could be combined for sea-ice study, the ability of sea-ice monitoring would be im-proved. In this study, in accordance with the characteristics of sea-ice SAR and optical images, the transfor-mation and fusion methods for these images were chosen. Also, a fusion method of optical and SAR images was proposed in order to improve sea-ice identification. Texture information can play an important role in sea-ice classification. Haar wavelet transformation was found to be suitable for the sea-ice SAR images, and the texture information of the sea-ice SAR image from Advanced Synthetic Aperture Radar (ASAR) loaded on ENVISAT was documented. The results of our studies showed that, the optical images in the hue-intensi-ty-saturation (HIS) space could reflect the spectral characteristics of the sea-ice types more efficiently than in the red-green-blue (RGB) space, and the optical image from the China-Brazil Earth Resources Satellite (CBERS-02B) was transferred from the RGB space to the HIS space. The principal component analysis (PCA) method could potentially contain the maximum information of the sea-ice images by fusing the HIS and texture images. The fusion image was obtained by a PCA method, which included the advantages of both the sea-ice SAR image and the optical image. To validate the fusion method, three methods were used to evaluate the fused image, i.e., objective, subjective, and comprehensive evaluations. It was concluded that the fusion method proposed could improve the ability of image interpretation and sea-ice

  13. SAR ice thickness mapping in the Beaufort Sea during autumn 2015 using wave dispersion in pancake ice

    Science.gov (United States)

    Wadhams, Peter; Aulicino, Giuseppe; Parmiggiani, Flavio

    2017-04-01

    Pancake and frazil ice represent an important component of the Arctic and Antarctic cryosphere, especially in the Marginal Ice Zones. In particular, pancake ice is the result of a freezing process that takes place in turbulent surface conditions, typically associated with wind and wave fields. The retrieval of its thickness by remote sensing is, in general, a very difficult task. This study presents our ongoing work in the EU SPICES project, in which we aim to use the results of theory and observations developed so far in order to refine a processing system for routinely deriving ice thicknesses in frazil-pancake regions of the Arctic and Antarctic. The change in dispersion of ocean waves as they penetrate into pancake icefield is analyzed in order to derive ice thickness estimation. The spectral changes in wave spectra from imagery provided by space-borne SAR systems (mainly Cosmo-SkyMed and Sentinel-1 satellites) is used to retrieve pancake ice thickness run trough by the R/V Sikuliaq research cruise in the Beaufort Sea (October-November 2015). During several experiments, a line of wave buoys was deployed along a pre-declared line, which could thus be covered by simultaneous overhead Cosmo-SkyMed images. The inversion procedures was then applied to SAR images, the final goal being the comparison between the ice thicknesses measured in situ and those inferred from SAR wave number analysis with the application of a viscous theory. Results show a broad agreement between observed thicknesses and those retrieved from the SAR, the latter slightly overestimating the former in several case studies. In the case of November 1, for example, the agreement is excellent (SAR retrievals 4.9, 5.0, 6.5 cm; observed mean 6.7 cm); on October 11 the agreement is also very good between the SAR retriveal (21 cm) and the output from an along-track EM-sounder; on October 23-24 the SAR retrieval of 18.1 cm is double the observed pancake thickness of 8.7 cm, but this difference can be

  14. Feasibility of sea ice typing with synthetic aperture radar (SAR): Merging of Landsat thematic mapper and ERS 1 SAR satellite imagery

    Science.gov (United States)

    Steffen, Konrad; Heinrichs, John

    1994-01-01

    Earth Remote-Sensing Satellite (ERS) 1 synthetic aperture radar (SAR) and Landsat thematic mapper (TM) images were acquired for the same area in the Beaufort Sea, April 16 and 18, 1992. The two image pairs were colocated to the same grid (25-m resolution), and a supervised ice type classification was performed on the TM images in order to classify ice free, nilas, gray ice, gray-white ice, thin first-year ice, medium and thick first-year ice, and old ice. Comparison of the collocated SAR pixels showed that ice-free areas can only be classified under calm wind conditions (less than 3 m/s) and for surface winds greater than 10 m/s based on the backscattering coefficient alone. This is true for pack ice regions during the cold months of the year where ice-free areas are spatially limited and where the capillary waves that cause SAR backscatter are dampened by entrained ice crystals. For nilas, two distinct backscatter classes were found at -17 dB and at -10 dB. The higher backscattering coefficient is attributed to the presence of frost flowers on light nilas. Gray and gray-white ice have a backscatter signature similar to first-year ice and therefore cannot be distinguished by SAR alone. First-year and old ice can be clearly separated based on their backscattering coefficient. The performance of the Geophysical Processor System ice classifier was tested against the Landsat derived ice products. It was found that smooth first-year ice and rough first-year ice were not significantly different in the backscatter domain. Ice concentration estimates based on ERS 1 C band SAR showed an error range of 5 to 8% for high ice concentration regions, mainly due to misclassified ice-free and smooth first-year ice areas. This error is expected to increase for areas of lower ice concentration. The combination of C band SAR and TM channels 2, 4, and 6 resulted in ice typing performance with an estimated accuracy of 90% for all seven ice classes.

  15. Sea Ice Detection with Sentinel-1A Dual Polarization SAR Data

    Science.gov (United States)

    Zhang, Yi; Zhang, Ming; Ji, Yonggang

    2016-08-01

    Sentinel-1A satellite was launched in the 3rd of April 2014. It is the first mission of the Copernicus family of Sentinels is designed to provide continuous routine data for the operational monitoring of oceans and land, and to support coordinated and rapid response operations to disasters (e.g. landslides and floods) as well as humanitarian aid missions. In this paper an approach to sea ice detection with dual polarization Sentinel-1A SAR data was presented. Firstly, the backscatter coefficients and texture features are achieved, in this step we found the best set of parameters including the window size, orientation, displacement and quantization levels, and the most useful texture characteristics to be used for detection, the effective GLCM texture features are mean and variance in HH polarization as well as mean, variance and correlation in HV polarization. In the end, the SVM classification was carried out with a series of bands, which including the texture characteristics and the backscatter information as the inputs. The final result shows good between sea ice and open water discrimination, which is important to the sea ice monitoring.

  16. Sea ice drift from Sentinel-1 SAR imagery using open source feature tracking

    Science.gov (United States)

    Muckenhuber, Stefan; Korosov, Anton; Sandven, Stein

    2016-04-01

    A computational efficient, open source feature tracking algorithm, called ORB, is adopted and tuned for sea ice drift retrieval from Sentinel-1 SAR images. The best suitable setting and parameter values have been found using four representative Sentinel-1 image pairs. A new quality measure for feature tracking algorithms is introduced utilising the distribution of the resulting vector field. The performance of the algorithm is compared with two other feature tracking algorithms (SIFT and SURF). Applied on a test image pair acquired over Fram Strait, the tuned ORB algorithm produces the highest number of vectors (6920, SIFT: 1585 and SURF: 518) while being computational most efficient (66 s, SIFT: 182 s and SURF: 99 s using a 2,7 GHz processor with 8 GB memory). For validation purpose, 350 manually drawn vectors have been compared with the closest calculated vectors and the resulting root mean square distance is 609.9 m (equivalent to 7.5 pixel). All test image pairs show a significant better performance of the HV channel. On average, around 4 times more vectors have been found using HV polarisation. All software requirements necessary for applying the presented feature tracking algorithm are open source to ensure a free and easy implementation.

  17. Estimates of ocean wave heights and attenuation in sea ice using the SAR wave mode on Sentinel-1A

    Science.gov (United States)

    Ardhuin, Fabrice; Collard, Fabrice; Chapron, Bertrand; Girard-Ardhuin, Fanny; Guitton, Gilles; Mouche, Alexis; Stopa, Justin E.

    2015-04-01

    Swell evolution from the open ocean into sea ice is poorly understood, in particular the amplitude attenuation expected from scattering and dissipation. New synthetic aperture radar (SAR) data from Sentinel-1A wave mode reveal intriguing patterns of bright oscillating lines shaped like instant noodles. We investigate cases in which the oscillations are in the azimuth direction, around a straight line in the range direction. This observation is interpreted as the distortion by the SAR processing of crests from a first swell, due to the presence of a second swell. Since deviations from a straight line should be proportional to the orbital velocity toward the satellite, swell height can be estimated, from 1.5 to 5 m in the present case. The evolution of this 13 s period swell across the ice pack is consistent with an exponential attenuation on a length scale of 200 km.

  18. In situ validation of segmented SAR satellite scenes of young Arctic thin landfast sea ice

    Science.gov (United States)

    Gerland, S.; Negrel, J.; Doulgeris, A. P.; Akbari, V.; Lauknes, T. R.; Rouyet, L.; Storvold, R.

    2016-12-01

    The use of satellite remote sensing techniques for the observation and monitoring of the polar regions has increased in recent years due to the ability to cover larger areas than can be covered by ground measurements, However, in situ data remain mandatory for the validation of such data. In April 2016 an Arctic fieldwork campaign was conducted at Kongsfjorden, Svalbard. Ground measurements from this campaign are used together with satellite data acquisitions to improve identification of young sea ice types from satellite data. This work was carried out in combination with Norwegian Polar Institute's long-term monitoring of Svalbard fast ice, and with partner institutes in the Center for Integrated Remote Sensing and Forecasting for Arctic operations (CIRFA). Thin ice types are generally more difficult to investigate than thicker ice, because ice of only a few centimetres thickness does not allow scientists to stand and work on it. Identifying it on radar scenes will make it easier to study and monitor. Four high resolution 25 km x 25 km Radarsat-2 quad-pol scenes were obtained, coincident in space and time with the in situ measurements. The field teams used a variety of methods, including ice thickness transects, ice salinity measurements, ground-based radar imaging from the coast and UAV-based photography, to identify the different thin ice types, their location and evolution in time. Sampling of the thinnest ice types was managed from a small boat. In addition, iceberg positions were recorded with GPS and photographed to enable us to quantify their contribution to the radar response. Thin ice from 0.02 to 0.18 m thickness was sampled on in a total nine ice stations. The ice had no or only a thin snow layer. The GPS positions and tracks and ice characteristics are then compared to the Radarsat-2 scenes, and the radar responses of the different thin ice types in the quad-pol scenes are identified. The first segmentation results of the scenes present a good

  19. Polarimetric signatures of sea ice in the Greenland Sea

    DEFF Research Database (Denmark)

    Skriver, Henning; Pedersen, Leif Toudal

    1995-01-01

    Polarimetric SAR data of sea ice have been acquired by the Danish polarimetric SAR (EMISAR) during a mission at the Greenland Sea in August 1994. Video recordings from a low-altitude acquisition have been used for interpretation of the SAR data. Also, ERS-1 SAR data and NOAA AVHRR-data have been...

  20. 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.

  1. Open-source feature-tracking algorithm for sea ice drift retrieval from Sentinel-1 SAR imagery

    Science.gov (United States)

    Muckenhuber, Stefan; Andreevich Korosov, Anton; Sandven, Stein

    2016-04-01

    A computationally efficient, open-source feature-tracking algorithm, called ORB, is adopted and tuned for sea ice drift retrieval from Sentinel-1 SAR (Synthetic Aperture Radar) images. The most suitable setting and parameter values have been found using four Sentinel-1 image pairs representative of sea ice conditions between Greenland and Severnaya Zemlya during winter and spring. The performance of the algorithm is compared to two other feature-tracking algorithms, namely SIFT (Scale-Invariant Feature Transform) and SURF (Speeded-Up Robust Features). Having been applied to 43 test image pairs acquired over Fram Strait and the north-east of Greenland, the tuned ORB (Oriented FAST and Rotated BRIEF) algorithm produces the highest number of vectors (177 513, SIFT: 43 260 and SURF: 25 113), while being computationally most efficient (66 s, SIFT: 182 s and SURF: 99 s per image pair using a 2.7 GHz processor with 8 GB memory). For validation purposes, 314 manually drawn vectors have been compared with the closest calculated vectors, and the resulting root mean square error of ice drift is 563 m. All test image pairs show a significantly better performance of the HV (horizontal transmit, vertical receive) channel due to higher informativeness. On average, around four times as many vectors have been found using HV polarization. All software requirements necessary for applying the presented feature-tracking algorithm are open source to ensure a free and easy implementation.

  2. SAR Ice Classification Using Fuzzy Screening Method

    Science.gov (United States)

    Gill, R. S.

    2003-04-01

    A semi-automatic SAR sea ice classification algorithm is described. It is based on combining the information in the original SAR data with those in the three 'image' products derived from it, namely Power-to-Mean Ratio (PMR), the Gamma distribution and the second order texture parameter entropy, respectively. The latter products contain information which is often useful during the manual interpretation of the images. The technique used to fuse the information in these products is based on a method c lled Multi Experts Multi Criteria Decision Making fuzzy a screening. The Multiple Experts in this case are the above four 'image' products. The two criteria used currently for making decisions are the Kolmogorov-Smirnov distribution matching and the statistical mean of different surface classes. The algorithm classifies an image into any number of predefined classes of sea ice and open water. The representative classes of these surface types are manually identified by the user. Further, as SAR signals from sea ice covered regions and open water are ambiguous, it was found that a minimum of 4 pre-identified surface classes (calm and turbulent water and sea ice with low and high backscatter values) are required to accurately classify an image. Best results are obtained when a total of 8 surface classes (2 each of sea ice and open water in the near range and a similar number in the far range of the SAR image) are used. The main advantage of using this image classification scheme is that, like neural networks, no prior knowledge is required of the statistical distribution of the different surface types. Furthermore, unlike the methods based on neural networks, no prior data sets are required to train the algorithm. All the information needed for image classification by the method is contained in the individual SAR images and associated products. Initial results illustrating the potential of this ice classification algorithm using the RADARSAT ScanSAR Wide data are presented

  3. Effects of surface roughness on sea ice freeboard retrieval with an Airborne Ku-Band SAR radar altimeter

    DEFF Research Database (Denmark)

    Hendricks, Stefan; Stenseng, Lars; Helm, Veit

    2010-01-01

    Results from two years of the CryoSat Validation Experiment (CryoVEx) over sea ice in the western Arctic Ocean are presented. The estimation of freeboard, the height of sea ice floating above the water level, is one the main goals of the CryoSat-2 mission of the European Space Agency (ESA) in order...... to investigate sea ice volume changes on an Arctic wide scale. Freeboard retrieval requires precise radar range measurements to the ice surface, therefore we investigate the penetration of the Ku-Band radar waves into the overlying snow cover as well as the effects of sub-footprint-scale surface roughness using...... of the airborne validation dataset, since the radar overestimates the amount of open water and thin ice as well the freeboard of heavy ice deformation zones....

  4. Sea ice melt pond fraction estimation from dual-polarisation C-band SAR – Part 2: Scaling in situ to Radarsat-2

    Directory of Open Access Journals (Sweden)

    R. K. Scharien

    2014-01-01

    Full Text Available Observed changes in the Arctic have motivated efforts to understand and model its components as an integrated and adaptive system at increasingly finer scales. Sea ice melt pond fraction, an important summer sea ice component affecting surface albedo and light transmittance across the ocean-sea ice–atmosphere interface, is inadequately parameterized in models due to a lack of large scale observations. In this paper, results from a multi-scale remote sensing program dedicated to the retrieval of pond fraction from satellite C-band synthetic aperture radar (SAR are detailed. The study was conducted on first-year sea (FY ice in the Canadian Arctic Archipelago during the summer melt period in June 2012. Approaches to retrieve the subscale FY ice pond fraction from mixed pixels in RADARSAT-2 imagery, using in situ, surface scattering theory, and image data are assessed. Each algorithm exploits the dominant effect of high dielectric free-water ponds on the VV/HH polarisation ratio (PR at moderate to high incidence angles (about 40° and above. Algorithms are applied to four images corresponding to discrete stages of the seasonal pond evolutionary cycle, and model performance is assessed using coincident pond fraction measurements from partitioned aerial photos. A RMSE of 0.07, across a pond fraction range of 0.10 to 0.70, is achieved during intermediate and late seasonal stages. Weak model performance is attributed to wet snow (pond formation and synoptically driven pond freezing events (all stages, though PR has utility for identification of these events when considered in time series context. Results demonstrate the potential of wide-swath, dual-polarisation, SAR for large-scale observations of pond fraction with temporal frequency suitable for process-scale studies and improvements to model parameterizations.

  5. SENTINEL-1 RESULTS: SEA ICE OPERATIONAL MONITORING

    DEFF Research Database (Denmark)

    Toudal Pedersen, Leif; Saldo, Roberto; Fenger-Nielsen, Rasmus

    2015-01-01

    In the present paper we demonstrate the capabilities of the Sentinel-1 SAR data for operational sea-ice and iceberg monitoring. Most of the examples are drawn from the Copernicus Marine Environmental Monitoring Service (CMEMS) production.......In the present paper we demonstrate the capabilities of the Sentinel-1 SAR data for operational sea-ice and iceberg monitoring. Most of the examples are drawn from the Copernicus Marine Environmental Monitoring Service (CMEMS) production....

  6. Open-source sea ice drift algorithm for Sentinel-1 SAR imagery using a combination of feature tracking and pattern matching

    Science.gov (United States)

    Muckenhuber, Stefan; Sandven, Stein

    2017-08-01

    An open-source sea ice drift algorithm for Sentinel-1 SAR imagery is introduced based on the combination of feature tracking and pattern matching. Feature tracking produces an initial drift estimate and limits the search area for the consecutive pattern matching, which provides small- to medium-scale drift adjustments and normalised cross-correlation values. The algorithm is designed to combine the two approaches in order to benefit from the respective advantages. The considered feature-tracking method allows for an efficient computation of the drift field and the resulting vectors show a high degree of independence in terms of position, length, direction and rotation. The considered pattern-matching method, on the other hand, allows better control over vector positioning and resolution. The preprocessing of the Sentinel-1 data has been adjusted to retrieve a feature distribution that depends less on SAR backscatter peak values. Applying the algorithm with the recommended parameter setting, sea ice drift retrieval with a vector spacing of 4 km on Sentinel-1 images covering 400 km × 400 km, takes about 4 min on a standard 2.7 GHz processor with 8 GB memory. The corresponding recommended patch size for the pattern-matching step that defines the final resolution of each drift vector is 34 × 34 pixels (2.7 × 2.7 km). To assess the potential performance after finding suitable search restrictions, calculated drift results from 246 Sentinel-1 image pairs have been compared to buoy GPS data, collected in 2015 between 15 January and 22 April and covering an area from 80.5 to 83.5° N and 12 to 27° E. We found a logarithmic normal distribution of the displacement difference with a median at 352.9 m using HV polarisation and 535.7 m using HH polarisation. All software requirements necessary for applying the presented sea ice drift algorithm are open-source to ensure free implementation and easy distribution.

  7. Retrieval of Melt Ponds on Arctic Multiyear Sea Ice in Summer from TerraSAR-X Dual-Polarization Data Using Machine Learning Approaches: A Case Study in the Chukchi Sea with Mid-Incidence Angle Data

    Directory of Open Access Journals (Sweden)

    Hyangsun Han

    2016-01-01

    Full Text Available Melt ponds, a common feature on Arctic sea ice, absorb most of the incoming solar radiation and have a large effect on the melting rate of sea ice, which significantly influences climate change. Therefore, it is very important to monitor melt ponds in order to better understand the sea ice-climate interaction. In this study, melt pond retrieval models were developed using the TerraSAR-X dual-polarization synthetic aperture radar (SAR data with mid-incidence angle obtained in a summer multiyear sea ice area in the Chukchi Sea, the Western Arctic, based on two rule-based machine learning approaches—decision trees (DT and random forest (RF—in order to derive melt pond statistics at high spatial resolution and to identify key polarimetric parameters for melt pond detection. Melt ponds, sea ice and open water were delineated from the airborne SAR images (0.3-m resolution, which were used as a reference dataset. A total of eight polarimetric parameters (HH and VV backscattering coefficients, co-polarization ratio, co-polarization phase difference, co-polarization correlation coefficient, alpha angle, entropy and anisotropy were derived from the TerraSAR-X dual-polarization data and then used as input variables for the machine learning models. The DT and RF models could not effectively discriminate melt ponds from open water when using only the polarimetric parameters. This is because melt ponds showed similar polarimetric signatures to open water. The average and standard deviation of the polarimetric parameters based on a 15 × 15 pixel window were supplemented to the input variables in order to consider the difference between the spatial texture of melt ponds and open water. Both the DT and RF models using the polarimetric parameters and their texture features produced improved performance for the retrieval of melt ponds, and RF was superior to DT. The HH backscattering coefficient was identified as the variable contributing the most, and its

  8. IOMASA SEA ICE DEVELOPMENTS

    DEFF Research Database (Denmark)

    Andersen, Søren; Tonboe, Rasmus; Heygster, Georg

    2005-01-01

    Sensitivity studies show that the radiometer ice concentration estimate can be biased by +10% by anomalous atmospheric emissivity and -20% by anomalous ice surface emissivity. The aim of the sea ice activities in EU 5th FP project IOMASA is to improve sea ice concentration estimates at higher...... spatial resolution. The project is in the process of facilitating an ice concentration observing system through validation and a better understanding of the microwave radiative transfer of the sea ice and overlying snow layers. By use of a novel modelling approach, it is possible to better detect...... and determine the circumstances that may lead to anomalous sea ice concentration retrieval as well as to assess and possibly minimize the sensitivities of the retrieval system. Through an active partnership with the SAF on Ocean and Sea Ice, a prototype system will be implemented as an experimental product...

  9. IOMASA SEA ICE DEVELOPMENTS

    DEFF Research Database (Denmark)

    Andersen, Søren; Tonboe, Rasmus; Heygster, Georg

    2005-01-01

    Sensitivity studies show that the radiometer ice concentration estimate can be biased by +10% by anomalous atmospheric emissivity and -20% by anomalous ice surface emissivity. The aim of the sea ice activities in EU 5th FP project IOMASA is to improve sea ice concentration estimates at higher...... spatial resolution. The project is in the process of facilitating an ice concentration observing system through validation and a better understanding of the microwave radiative transfer of the sea ice and overlying snow layers. By use of a novel modelling approach, it is possible to better detect...... and determine the circumstances that may lead to anomalous sea ice concentration retrieval as well as to assess and possibly minimize the sensitivities of the retrieval system. Through an active partnership with the SAF on Ocean and Sea Ice, a prototype system will be implemented as an experimental product...

  10. 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......-swath synthetic aperture radar (SAR) scenes. The analysis is confined to the high-concentration Arctic sea ice, where the ice cover is near 100%. During winter the results indicate that the variability of the SSM/I concentration estimates is larger than the true variability of ice concentration. Results from...... a trusted subset of the SAR scenes across the central Arctic allow the separation of the ice concentration uncertainty due to emissivity variations and sensor noise from other error sources during the winter of 2003-2004. Depending on the algorithm, error standard deviations from 2.5 to 5.0% are found...

  11. Automatic Detection of the Ice Edge in SAR Imagery Using Curvelet Transform and Active Contour

    Directory of Open Access Journals (Sweden)

    Jiange Liu

    2016-06-01

    Full Text Available A novel method based on the curvelet transform and active contour method to automatically detect the ice edge in Synthetic Aperture Radar (SAR imagery is proposed. The method utilizes the location of high curvelet coefficients to determine regions in the image likely to contain the ice edge. Using an ice edge from passive microwave sea ice concentration for initialization, these regions are then joined using the active contour method to obtain the final ice edge. The method is evaluated on four dual polarization SAR scenes of the Labrador sea. Through comparison of the ice edge with that from image analysis charts, it is demonstrated that the proposed method can detect the ice edge effectively in SAR images. This is particularly relevant when the marginal ice zone is diffuse or the ice is thin, and using the definition of ice edge from the passive microwave ice concentration would underestimate the ice edge location. It is expected that the method may be useful for operations in marginal ice zones, such as offshore drilling, where a high resolution estimate of the ice edge location is required. It could also be useful as a first guess for an ice analyst, or for the assimilation of SAR data.

  12. Arctic Sea Ice

    Science.gov (United States)

    Stroeve, J. C.; Fetterer, F.; Knowles, K.; Meier, W.; Serreze, M.; Arbetter, T.

    2004-12-01

    Of all the recent observed changes in the Arctic environment, the reduction of sea ice cover stands out most prominantly. Several independent analysis have established a trend in Arctic ice extent of -3% per decade from the late 1970s to the late 1990s, with a more pronounced trend in summer. The overall downward trend in ice cover is characterized by strong interannual variability, with a low September ice extent in one year typically followed by recovery the next September. Having two extreme minimum years, such as what was observed in 2002 and 2003 is unusual. 2004 marks the third year in a row of substantially below normal sea ice cover in the Arctic. Early summer 2004 appeared unusual in terms of ice extent, with May a record low for the satellite period (1979-present) and June also exhibiting below normal ice extent. August 2004 extent is below that of 2003 and large reductions in ice cover are observed once again off the coasts of Siberia and Alaska and the Greenland Sea. Neither the 2002 or 2003 anomaly appeared to be strongly linked to the positive phase of the Arctic Oscillation (AO) during the preceding winter. Similarly, the AO was negative during winter 2003/2004. In the previous AO framework of Rigor et al (2002), a positive winter AO implied preconditioning of the ice cover to extensive summer decay. In this hypothesis, the AO does not explain all aspects of the recent decline in Arctic ice cover, such as the extreme minima of 2002, 2003 and 2004. New analysis by Rigor and Wallace (2004) suggest that the very positive AO state from 1989-1995 can explain the recent sea ice minima in terms of changes in the Arctic surface wind field associated with the previous high AO state. However, it is also reasonable to expect that a general decrease in ice thickness accompanying warming would manifest itself as greater sensitivity of the ice pack to wind forcings and albedo feedbacks. The decrease in multiyear ice and attendant changes in ice thickness

  13. Sea-Ice Feature Mapping using JERS-1 Imagery

    Science.gov (United States)

    Maslanik, James; Heinrichs, John

    1994-01-01

    JERS-1 SAR and OPS imagery are examined in combination with other data sets to investigate the utility of the JERS-1 sensors for mapping fine-scale sea ice conditions. Combining ERS-1 C band and JERS-1 L band SAR aids in discriminating multiyear and first-year ice. Analysis of OPS imagery for a field site in the Canadian Archipelago highlights the advantages of OPS's high spatial and spectral resolution for mapping ice structure, melt pond distribution, and surface albedo.

  14. Global Sea Ice Charting at the National Ice Center

    Science.gov (United States)

    Clemente-Colon, P.

    2006-12-01

    The National Ice Center (NIC) is a U.S. government tri-agency operational center comprised of components from the United States Navy, the National Oceanic and Atmospheric Administration (NOAA), and the U. S. Coast Guard (USCG). The mission of the NIC is to provide the highest quality strategic and tactical ice services tailored to meet operational requirements of U.S. national interests. This includes broad responsibilities to monitor all frozen ocean regions of the world in support of coastal and marine sea ice operations and research. Sea ice conditions are routinely monitored and mapped using satellite imagery along with ancillary model and in-situ data. Active microwave images from Synthetic Aperture Radar (SAR) sensors are the data of choice for NIC analysts because of their high spatial resolution (~100 m). SAR is in fact the primary data source for ice analysis when available. The high spatial resolution of available SAR data and the reliability shown by the RADARSAT- 1 mission in particular have made the use of these data critical for vessels operating in or near the ice. Limited data from the ESA Envisat Advanced SAR (ASAR) are also used in the analyses when available. Preparations for the use of the Phased Array type L-band SAR (PALSAR) aboard the soon to be launched Japanese ALOS satellite are also underway. Scatterometer backscatter imagery from QuikSCAT is also routinely used for basin-scale and circumpolar ice edge mapping. Automated algorithms for ice type and melt ponds detection as well as the synergy between these observations and the QuikSCAT wind vectors off the marginal ice zone (MIZ) are been explored. ESA Envisat Advanced SAR (ASAR) Global Monitoring Mode (GMM) mosaics of the Arctic and Antarctic regions are becoming an important tool for sea ice edge delineation too. Although SAR observations are the choice for NIC analysts to produce high spatial resolution products gear toward tactical support, passive microwave data such as those from the

  15. Pixel Classification of SAR ice images using ANFIS-PSO Classifier

    Directory of Open Access Journals (Sweden)

    G. Vasumathi

    2016-12-01

    Full Text Available Synthetic Aperture Radar (SAR is playing a vital role in taking extremely high resolution radar images. It is greatly used to monitor the ice covered ocean regions. Sea monitoring is important for various purposes which includes global climate systems and ship navigation. Classification on the ice infested area gives important features which will be further useful for various monitoring process around the ice regions. Main objective of this paper is to classify the SAR ice image that helps in identifying the regions around the ice infested areas. In this paper three stages are considered in classification of SAR ice images. It starts with preprocessing in which the speckled SAR ice images are denoised using various speckle removal filters; comparison is made on all these filters to find the best filter in speckle removal. Second stage includes segmentation in which different regions are segmented using K-means and watershed segmentation algorithms; comparison is made between these two algorithms to find the best in segmenting SAR ice images. The last stage includes pixel based classification which identifies and classifies the segmented regions using various supervised learning classifiers. The algorithms includes Back propagation neural networks (BPN, Fuzzy Classifier, Adaptive Neuro Fuzzy Inference Classifier (ANFIS classifier and proposed ANFIS with Particle Swarm Optimization (PSO classifier; comparison is made on all these classifiers to propose which classifier is best suitable for classifying the SAR ice image. Various evaluation metrics are performed separately at all these three stages.

  16. Automatic polar ice thickness estimation from SAR imagery

    Science.gov (United States)

    Rahnemoonfar, Maryam; Yari, Masoud; Fox, Geoffrey C.

    2016-05-01

    Global warming has caused serious damage to our environment in recent years. Accelerated loss of ice from Greenland and Antarctica has been observed in recent decades. The melting of polar ice sheets and mountain glaciers has a considerable influence on sea level rise and altering ocean currents, potentially leading to the flooding of the coastal regions and putting millions of people around the world at risk. Synthetic aperture radar (SAR) systems are able to provide relevant information about subsurface structure of polar ice sheets. Manual layer identification is prohibitively tedious and expensive and is not practical for regular, longterm ice-sheet monitoring. Automatic layer finding in noisy radar images is quite challenging due to huge amount of noise, limited resolution and variations in ice layers and bedrock. Here we propose an approach which automatically detects ice surface and bedrock boundaries using distance regularized level set evolution. In this approach the complex topology of ice and bedrock boundary layers can be detected simultaneously by evolving an initial curve in radar imagery. Using a distance regularized term, the regularity of the level set function is intrinsically maintained that solves the reinitialization issues arising from conventional level set approaches. The results are evaluated on a large dataset of airborne radar imagery collected during IceBridge mission over Antarctica and Greenland and show promising results in respect to hand-labeled ground truth.

  17. Polar Sea Ice Monitoring Using HY-2A Scatterometer Measurements

    Directory of Open Access Journals (Sweden)

    Mingming Li

    2016-08-01

    Full Text Available A sea ice detection algorithm based on Fisher’s linear discriminant analysis is developed to segment sea ice and open water for the Ku-band scatterometer onboard the China’s Hai Yang 2A Satellite (HY-2A/SCAT. Residual classification errors are reduced through image erosion/dilation techniques and sea ice growth/retreat constraint methods. The arctic sea-ice-type classification is estimated via a time-dependent threshold derived from the annual backscatter trends based on previous HY-2A/SCAT derived sea ice extent. The extent and edge of the sea ice obtained in this study is compared with the Special Sensor Microwave Imager/Sounder (SSMIS sea ice concentration data and the Sentinel-1 SAR imagery for verification, respectively. Meanwhile, the classified sea ice type is compared with a multi-sensor sea ice type product based on data from the Advanced Scatterometer (ASCAT and SSMIS. Results show that HY-2A/SCAT is powerful in providing sea ice extent and type information, while differences in the sensitivities of active/passive products are found. In addition, HY-2A/SCAT derived sea ice products are also proved to be valuable complements for existing polar sea ice data products.

  18. Seafloor Control on Sea Ice

    Science.gov (United States)

    Nghiem, S. V.; Clemente-Colon, P.; Rigor, I. G.; Hall, D. K.; Neumann, G.

    2011-01-01

    The seafloor has a profound role in Arctic sea ice formation and seasonal evolution. Ocean bathymetry controls the distribution and mixing of warm and cold waters, which may originate from different sources, thereby dictating the pattern of sea ice on the ocean surface. Sea ice dynamics, forced by surface winds, are also guided by seafloor features in preferential directions. Here, satellite mapping of sea ice together with buoy measurements are used to reveal the bathymetric control on sea ice growth and dynamics. Bathymetric effects on sea ice formation are clearly observed in the conformation between sea ice patterns and bathymetric characteristics in the peripheral seas. Beyond local features, bathymetric control appears over extensive ice-prone regions across the Arctic Ocean. The large-scale conformation between bathymetry and patterns of different synoptic sea ice classes, including seasonal and perennial sea ice, is identified. An implication of the bathymetric influence is that the maximum extent of the total sea ice cover is relatively stable, as observed by scatterometer data in the decade of the 2000s, while the minimum ice extent has decreased drastically. Because of the geologic control, the sea ice cover can expand only as far as it reaches the seashore, the continental shelf break, or other pronounced bathymetric features in the peripheral seas. Since the seafloor does not change significantly for decades or centuries, sea ice patterns can be recurrent around certain bathymetric features, which, once identified, may help improve short-term forecast and seasonal outlook of the sea ice cover. Moreover, the seafloor can indirectly influence cloud cover by its control on sea ice distribution, which differentially modulates the latent heat flux through ice covered and open water areas.

  19. Modelling sea ice dynamics

    Science.gov (United States)

    Murawski, Jens; Kleine, Eckhard

    2017-04-01

    Sea ice remains one of the frontiers of ocean modelling and is of vital importance for the correct forecasts of the northern oceans. At large scale, it is commonly considered a continuous medium whose dynamics is modelled in terms of continuum mechanics. Its specifics are a matter of constitutive behaviour which may be characterised as rigid-plastic. The new developed sea ice dynamic module bases on general principles and follows a systematic approach to the problem. Both drift field and stress field are modelled by a variational property. Rigidity is treated by Lagrangian relaxation. Thus one is led to a sensible numerical method. Modelling fast ice remains to be a challenge. It is understood that ridging and the formation of grounded ice keels plays a role in the process. The ice dynamic model includes a parameterisation of the stress associated with grounded ice keels. Shear against the grounded bottom contact might lead to plastic deformation and the loss of integrity. The numerical scheme involves a potentially large system of linear equations which is solved by pre-conditioned iteration. The entire algorithm consists of several components which result from decomposing the problem. The algorithm has been implemented and tested in practice.

  20. Progress Toward Demonstrating SAR Monitoring of Chinese Seas

    Science.gov (United States)

    Huang, Weigen; Johannessen, Johnny; Alpers, Werner; Yang, Jingsong

    2010-12-01

    "Demonstrating SAR monitoring of Chinese seas" is a project of the ESA-MOST Dragon 2 program. This paper presents the progress of the project. Retrieval algorithms for SAR monitoring of sea surface currents, oceanic internal waves, sea surface winds, oil spills and ships have been advanced. SAR monitoring of Chinese seas in near-real-time is now in demonstration phase.

  1. Polarimetric SAR interferometry applied to land ice: modeling

    DEFF Research Database (Denmark)

    Dall, Jørgen; Papathanassiou, Konstantinos; Skriver, Henning

    2004-01-01

    This paper introduces a few simple scattering models intended for the application of polarimetric SAR interfer-ometry to land ice. The principal aim is to eliminate the penetration bias hampering ice sheet elevation maps generated with single-channel SAR interferometry. The polarimetric coherent...

  2. EASE-Grid Sea Ice Age

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set provides weekly estimates of sea ice age for the Arctic Ocean from remotely sensed sea ice motion and sea ice extent. The ice age data are derived from...

  3. Measurement of sea ice and icebergs topography using satellite imagery

    Science.gov (United States)

    Zakharov, I.; Power, D.; Prasad, S.

    2016-12-01

    Sea ice topography represents geospatial information on the three-dimensional geometrical attributes of the ice surface including height and shape of various ice features. The features interest consist of deformed (pressure ridges, rubbles and hummocks) and level sea ice as well as glacial ice. Sea ice topography is important for scientific research and climate studies because it helps characterise ice volume and thickness and it influences the near-surface atmospheric transport by impacting the drag coefficients. It also represents critical information to marine operational applications, such as ships navigation and risks assessment for offshore infrastructures. The several methods were used to measure sea ice topography from a single satellite image as well as multiple images. The techniques based on the single image, acquired by optical or synthetic aperture radar (SAR) satellites, derive the height and shape information from shadow and shading. Optical stereo images acquired by very high resolution (0.5 m) satellites were used to extract highly detailed digital elevation model (DEM). SAR imagery allowed extraction of DEM using stereo-radargrammetry and interferometry. The images from optical satellites WorldView, Pleiades, GeoEye, Spot, and Landsat-8 were used to measure topography of sea ice deformation features and glacial ice including icebergs and ice islands. These features were mapped in regions of the Central Arctic, Baffin Bay and the coast of Greenland. SAR imagery including interferometric TanDEM-X data and full polarimetric Radarsat-2 were used to extract ridge frequency and measure spatial parameters of glacial features. The accuracy was evaluated by comparison of the results from different methods demonstrating their strengths and limitations. Ridge height and frequency were also compared with the high resolution results from the Los Alamos sea ice model (CICE), regionally implemented for Baffin Bay and the Labrador Sea.

  4. Spatial and Temporal Observations of Summer Ice Melt Using ERS-1 SAR Imagery

    Science.gov (United States)

    Holt, B.; Martin, S.

    1995-01-01

    The complete understanding of the heat and mass balance of the polar oceans includes the melting of sea ice in the summer and the reinjection of fresh water into the upper ocean. This study examines the spatial and temporal character of ice melt. Using ERS-1 SAR imagery, the development of small floes formed by melt and deforma- tion, and changes in the fraction of open water and floes is examined.

  5. Spatial and Temporal Observations of Summer Ice Melt Using ERS-1 SAR Imagery

    Science.gov (United States)

    Holt, B.; Martin, S.

    1995-01-01

    The complete understanding of the heat and mass balance of the polar oceans includes the melting of sea ice in the summer and the reinjection of fresh water into the upper ocean. This study examines the spatial and temporal character of ice melt. Using ERS-1 SAR imagery, the development of small floes formed by melt and deforma- tion, and changes in the fraction of open water and floes is examined.

  6. Ice flow mapping with P-band SAR

    DEFF Research Database (Denmark)

    Dall, Jørgen; Nielsen, Ulrik; Kusk, Anders

    2013-01-01

    -band SAR data have been acquired in Greenland, and both offset tracking and DInSAR have been applied to the full resolution data as well as to data degraded to the resolution of Biomass. Generally, ice velocity maps are successfully generated, but in the ablation zone, DInSAR fails in the melt season......Glacier and ice sheet dynamics are currently mapped with X-, C-, and L-band SAR. With the prospect of a P-band SAR, Biomass, to be launched within the next decade it is interesting to look into the potential of P-band for ice velocity mapping. In this paper first results are presented. Airborne P...

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

    Science.gov (United States)

    Spreen, Gunnar; Kwok, Ron; Menemenlis, Dimitris; Nguyen, An T.

    2017-07-01

    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.

  8. Arctic Sea Ice Predictability and the Sea Ice Prediction Network

    Science.gov (United States)

    Wiggins, H. V.; Stroeve, J. C.

    2014-12-01

    Drastic reductions in Arctic sea ice cover have increased the demand for Arctic sea ice predictions by a range of stakeholders, including local communities, resource managers, industry and the public. The science of sea-ice prediction has been challenged to keep up with these developments. Efforts such as the SEARCH Sea Ice Outlook (SIO; http://www.arcus.org/sipn/sea-ice-outlook) and the Sea Ice for Walrus Outlook have provided a forum for the international sea-ice prediction and observing community to explore and compare different approaches. The SIO, originally organized by the Study of Environmental Change (SEARCH), is now managed by the new Sea Ice Prediction Network (SIPN), which is building a collaborative network of scientists and stakeholders to improve arctic sea ice prediction. The SIO synthesizes predictions from a variety of methods, including heuristic and from a statistical and/or dynamical model. In a recent study, SIO data from 2008 to 2013 were analyzed. The analysis revealed that in some years the predictions were very successful, in other years they were not. Years that were anomalous compared to the long-term trend have proven more difficult to predict, regardless of which method was employed. This year, in response to feedback from users and contributors to the SIO, several enhancements have been made to the SIO reports. One is to encourage contributors to provide spatial probability maps of sea ice cover in September and the first day each location becomes ice-free; these are an example of subseasonal to seasonal, local-scale predictions. Another enhancement is a separate analysis of the modeling contributions. In the June 2014 SIO report, 10 of 28 outlooks were produced from models that explicitly simulate sea ice from dynamic-thermodynamic sea ice models. Half of the models included fully-coupled (atmosphere, ice, and ocean) models that additionally employ data assimilation. Both of these subsets (models and coupled models with data

  9. Sunlight, Sea Ice, and the Ice Albedo Feedback in a Changing Arctic Sea Ice Cover

    Science.gov (United States)

    2015-09-30

    the Arctic Ocean and surrounding seas, with particular emphasis on the Chukchi and Beaufort Seas. Some of the largest changes to the sea ice cover are...Changing Arctic Sea Ice Cover Don Perovich ERDC – CRREL 72 Lyme Road Hanover, NH 03755 Phone: 603-646-4255 Email: donald.k.perovich...quantitative understanding of the partitioning of solar radiation by the Arctic sea ice cover and its impact on the heat and mass balance of the ice and upper

  10. Seasonal Changes of Arctic Sea Ice Physical Properties Observed During N-ICE2015: An Overview

    Science.gov (United States)

    Gerland, S.; Spreen, G.; Granskog, M. A.; Divine, D.; Ehn, J. K.; Eltoft, T.; Gallet, J. C.; Haapala, J. J.; Hudson, S. R.; Hughes, N. E.; Itkin, P.; King, J.; Krumpen, T.; Kustov, V. Y.; Liston, G. E.; Mundy, C. J.; Nicolaus, M.; Pavlov, A.; Polashenski, C.; Provost, C.; Richter-Menge, J.; Rösel, A.; Sennechael, N.; Shestov, A.; Taskjelle, T.; Wilkinson, J.; Steen, H.

    2015-12-01

    Arctic sea ice is changing, and for improving the understanding of the cryosphere, data is needed to describe the status and processes controlling current seasonal sea ice growth, change and decay. We present preliminary results from in-situ observations on sea ice in the Arctic Basin north of Svalbard from January to June 2015. Over that time, the Norwegian research vessel «Lance» was moored to in total four ice floes, drifting with the sea ice and allowing an international group of scientists to conduct detailed research. Each drift lasted until the ship reached the marginal ice zone and ice started to break up, before moving further north and starting the next drift. The ship stayed within the area approximately 80°-83° N and 5°-25° E. While the expedition covered measurements in the atmosphere, the snow and sea ice system, and in the ocean, as well as biological studies, in this presentation we focus on physics of snow and sea ice. Different ice types could be investigated: young ice in refrozen leads, first year ice, and old ice. Snow surveys included regular snow pits with standardized measurements of physical properties and sampling. Snow and ice thickness were measured at stake fields, along transects with electromagnetics, and in drillholes. For quantifying ice physical properties and texture, ice cores were obtained regularly and analyzed. Optical properties of snow and ice were measured both with fixed installed radiometers, and from mobile systems, a sledge and an ROV. For six weeks, the surface topography was scanned with a ground LIDAR system. Spatial scales of surveys ranged from spot measurements to regional surveys from helicopter (ice thickness, photography) during two months of the expedition, and by means of an array of autonomous buoys in the region. Other regional information was obtained from SAR satellite imagery and from satellite based radar altimetry. The analysis of the data collected has started, and first results will be

  11. Sunlight, Sea Ice, and the Ice Albedo Feedback in a Changing Artic Sea Ice Cover

    Science.gov (United States)

    2015-11-30

    Arctic sea ice cover and its impact on the heat and mass balance of the ice and upper ocean ... Arctic Ocean and surrounding seas, with particular emphasis on the Chukchi and Beaufort Seas. Some of the largest changes to the sea ice cover are...other parts of the Arctic ice cover appear to now be accelerating. Figure 6. Maps of the linear trend of annual solar heat input to the ocean

  12. USGS Sea Ice Email Script

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Daily sea ice imagery and charting benefits logistics and navigational planning in the Alaskan Arctic waters, yet access to these data often requires high bandwidth...

  13. Sea-Ice Deformation in a Coupled Ocean-Sea Ice Model and in Satellite Remote Sensing Data

    Science.gov (United States)

    Spreen, G.; Kwok, R.; Menemenlis, D.; Nguyen, A. T.

    2016-12-01

    A realistic representation of sea-ice deformation in models is important for accurate simulation of the sea ice mass balance. Simulated sea-ice deformation strain rates from model simulations with 4.5, 9, and 18-km horizontal grid spacing are compared with Synthetic Aperture Radar (SAR) satellite observations (RGPS). The used MITgcm model employs a viscous-plastic sea ice rheology. The figure below shows the ice thickness distributions for the three simulations on 15 November 1999. More ice fracturing and leads are visible in the 4.5 km solution. All three simulations can reproduce the large-scale ice deformation patterns, but small-scale sea-ice deformations and linear kinematic features are not adequately reproduced. The mean sea-ice total deformation rate is about 50% 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 spatial scaling and probability density functions of all three model solutions follow a power-law similar to the RGPS observations, and contrary to what is found in other studies. Overall, the 4.5-km simulation produces the lowest misfits in divergence, vorticity, and shear when compared with RGPS data. Model sensitivity experiments show a strong impact of the ice strength parametrization on the Arctic Basin sea ice volume, which increased by 7% and 35% for a decrease in ice strength of, respectively, 30% and 70%, after 8 years of model integration. This volume increase is caused by a combination of dynamic and thermodynamic processes: the ice thickness increased by enhanced deformation and ice growth in leads, which is followed by a decrease in ice export. The balance of these processes leads to a new equilibrium Arctic Basin ice volume. Not addressed in this study is whether the differences between simulated and observed deformation rates are an intrinsic limitation of the

  14. Jet formation at the sea ice edge

    Science.gov (United States)

    Feltham, D. L.; Heorton, H. D.

    2014-12-01

    The sea ice edge presents a region of many feedback processes between the atmosphere, ocean and sea ice, which are inadequately represented in current climate models. Here we focus on on-ice atmospheric and oceanic flows at the sea ice edge. Mesoscale jet formation due to the Coriolis effect is well understood over sharp changes in surface roughness such as coastlines. This sharp change in surface roughness is experienced by the atmosphere flowing over, and ocean flowing under, a compacted sea ice edge. We have studied a dynamic sea ice edge responding to atmospheric and oceanic jet formation. The shape and strength of atmospheric and oceanic jets during on-ice flows is calculated from existing studies of the sea ice edge and prescribed to idealised models of the sea ice edge. An idealised analytical model of sea ice drift is developed and compared to a sea ice climate model (the CICE model) run on an idealised domain. The response of the CICE model to jet formation is tested at various resolutions. We find that the formation of atmospheric jets during on-ice winds at the sea ice edge increases the wind speed parallel to the sea ice edge and results in the formation of a sea ice edge jet. The modelled sea ice edge jet is in agreement with an observed jet although more observations are needed for validation. The increase in ice drift speed is dependent upon the angle between the ice edge and wind and can result in a 40% increase in ice transport along the sea ice edge. The possibility of oceanic jet formation during on-ice currents and the resultant effect upon the sea ice edge is less conclusive. Observations and climate model data of the polar oceans has been analysed to show areas of likely atmospheric jet formation, with the Fram Strait being of particular interest.

  15. Science requirements for free-flying imaging radar (FIREX) experiment for sea ice, renewable resources, nonrenewable resources and oceanography

    Science.gov (United States)

    Carsey, F.

    1982-01-01

    A future bilateral SAR program was studied. The requirements supporting a SAR mission posed by science and operations in sea-ice-covered waters, oceanography, renewable resources, and nonrenewable resources are addressed. The instrument, mission, and program parameters were discussed. Research investigations supporting a SAR flight and the subsequent overall mission requirements and tradeoffs are summarized.

  16. Sea Ice Concentration and Extent

    Science.gov (United States)

    Comiso, Josefino C.

    2014-01-01

    Among the most seasonal and most dynamic parameters on the surface of the Earth is sea ice which at any one time covers about 3-6% of the planet. In the Northern Hemisphere, sea ice grows in extent from about 6 x 10(exp 6) sq km to 16 x 10(exp 6) sq km, while in the Southern Hemisphere, it grows from about 3 x 10(exp 6) sq km to about 19 x 10(exp 6) sq km (Comiso, 2010; Gloersen et al., 1992). Sea ice is up to about 2-3 m thick in the Northern Hemisphere and about 1 m thick in the Southern Hemisphere (Wadhams, 2002), and compared to the average ocean depth of about 3 km, it is a relatively thin, fragile sheet that can break due to waves and winds or melt due to upwelling of warm water. Being constantly advected by winds, waves, and currents, sea ice is very dynamic and usually follows the directions of the many gyres in the polar regions. Despite its vast expanse, the sea ice cover was previously left largely unstudied and it was only in recent years that we have understood its true impact and significance as related to the Earths climate, the oceans, and marine life.

  17. Sea Ice Concentration and Extent

    Science.gov (United States)

    Comiso, Josefino C.

    2014-01-01

    Among the most seasonal and most dynamic parameters on the surface of the Earth is sea ice which at any one time covers about 3-6% of the planet. In the Northern Hemisphere, sea ice grows in extent from about 6 x 10(exp 6) sq km to 16 x 10(exp 6) sq km, while in the Southern Hemisphere, it grows from about 3 x 10(exp 6) sq km to about 19 x 10(exp 6) sq km (Comiso, 2010; Gloersen et al., 1992). Sea ice is up to about 2-3 m thick in the Northern Hemisphere and about 1 m thick in the Southern Hemisphere (Wadhams, 2002), and compared to the average ocean depth of about 3 km, it is a relatively thin, fragile sheet that can break due to waves and winds or melt due to upwelling of warm water. Being constantly advected by winds, waves, and currents, sea ice is very dynamic and usually follows the directions of the many gyres in the polar regions. Despite its vast expanse, the sea ice cover was previously left largely unstudied and it was only in recent years that we have understood its true impact and significance as related to the Earths climate, the oceans, and marine life.

  18. Sea ice thickness and recent Arctic warming

    Science.gov (United States)

    Lang, Andreas; Yang, Shuting; Kaas, Eigil

    2017-01-01

    The climatic impact of increased Arctic sea ice loss has received growing attention in the last years. However, little focus has been set on the role of sea ice thickness, although it strongly determines surface heat fluxes. Here ensembles of simulations using the EC-Earth atmospheric model (Integrated Forecast System) are performed and analyzed to quantify the atmospheric impacts of Arctic sea ice thickness change since 1982 as revealed by the sea ice model assimilation Global Ice-Ocean Modeling and Assimilation System. Results show that the recent sea ice thinning has significantly affected the Arctic climate, while remote atmospheric responses are less pronounced owing to a high internal atmospheric variability. Locally, the sea ice thinning results in enhancement of near-surface warming of about 1°C per decade in winter, which is most pronounced over marginal sea ice areas with thin ice. This leads to an increase of the Arctic amplification factor by 37%.

  19. Ice Tank Experiments Highlight Changes in Sea Ice Types

    Science.gov (United States)

    Wilkinson, Jeremy P.; DeCarolis, Giacomo; Ehlert, Iris; Notz, Dirk; Evers, Karl-Ulrich; Jochmann, Peter; Gerland, Sebastian; Nicolaus, Marcel; Hughes, Nick; Kern, Stefan; de la Rosa, Sara; Smedsrud, Lars; Sakai, Shigeki; Shen, Hayley; Wadhams, Peter

    2009-03-01

    With the current and likely continuing reduction of summer sea ice extent in the Arctic Ocean, the predominant mechanism of sea ice formation in the Arctic is likely to change in the future. Although substantial new ice formation occurred under preexisting ice in the past, the fraction of sea ice formation in open water likely will increase significantly. In open water, sea ice formation starts with the development of small ice crystals, called frazil ice, which are suspended in the water column [World Meteorological Organization, 1985]. Under quiescent conditions, these crystals accumulate at the surface to form an unbroken ice sheet known in its early stage as nilas. Under turbulent conditions, caused by wind and waves, frazil ice continues to grow and forms into a thick, soupy mixture called grease ice. Eventually the frazil ice will coalesce into small, rounded pieces known as pancake ice, which finally consolidate into an ice sheet with the return of calm conditions. This frazil/pancake/ice sheet cycle is currently frequently observed in the Antarctic [Lange et al., 1989]. The cycle normally occurs in regions that have a significant stretch of open water, because this allows for the formation of larger waves and hence increased turbulence. Given the increase of such open water in the Arctic Ocean caused by retreating summer sea ice, the frazil/pancake/ice sheet cycle may also become the dominant ice formation process during freezeup in the Arctic.

  20. Summer sea ice characteristics of the Chukchi Sea

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    During August 1999, we investigated sea ice characteristics; its distribution, surface feature, thickness, ice floe movement, and the temperature field around inter-borders of air/ice/seawater in the Chukchi Sea. Thirteen ice cores were drilled at 11 floe stations in the area of 72°24′ 77°18′N, 153°34′ 163°28′W and the ice core structure was observed. From field observation, three melting processes of ice were observed; surface layer melting, surface and bottom layers melting, and all of ice melting. The observation of temperature fields around sea ice floes showed that the bottom melting under the ice floes were important process. As ice floes and open water areas were alternately distributed in summer Arctic Ocean; the water under ice was colder than the open water by 0.4 2.8℃. The sun radiation heated seawater in open sea areas so that the warmer water went to the bottom when the ice floes move to those areas. This causes ice melting to start at the bottom of the ice floes. This process can balance effectively the temperature fluctuating in the sea in summer. From the crystalline structure of sea ice observed from the cores, it was concluded that the ice was composed of ice crystals and brine-ice films. During the sea ice melting, the brine-ice films between ice crystals melted firstly; then the ice crystals were encircled by brine films; the sea ice became the mixture of ice and liquid brine. At the end of melting, the ice crystals would be separated each other, the bond between ice crystals weakens and this leads to the collapse of the ice sheet.

  1. Ionospheric Correction of InSAR for Accurate Ice Motion Mapping at High Latitudes

    Science.gov (United States)

    Liao, H.; Meyer, F. J.

    2016-12-01

    Monitoring the motion of the large ice sheets is of great importance for determining ice mass balance and its contribution to sea level rise. Recently the first comprehensive ice motion of the Greenland and the Antarctica have been generated with InSAR. However, these studies have indicated that the performance of InSAR-based ice motion mapping is limited by the presence of the ionosphere. This is particularly true at high latitudes and for low-frequency SAR data. Filter-based and empirical methods (e.g., removing polynomials), which have often been used to mitigate ionospheric effects, are often ineffective in these areas due to the typically strong spatial variability of ionospheric phase delay in high latitudes and due to the risk of removing true deformation signals from the observations. In this study, we will first present an outline of our split-spectrum InSAR-based ionospheric correction approach and particularly highlight how our method improves upon published techniques, such as the multiple sub-band approach to boost estimation accuracy as well as advanced error correction and filtering algorithms. We applied our work flow to a large number of ionosphere-affected dataset over the large ice sheets to estimate the benefit of ionospheric correction on ice motion mapping accuracy. Appropriate test sites over Greenland and the Antarctic have been chosen through cooperation with authors (UW, Ian Joughin) of previous ice motion studies. To demonstrate the magnitude of ionospheric noise and to showcase the performance of ionospheric correction, we will show examples of ionospheric-affected InSAR data and our ionosphere corrected result for comparison in visual. We also compared the corrected phase data to known ice velocity fields quantitatively for the analyzed areas from experts in ice velocity mapping. From our studies we found that ionospheric correction significantly reduces biases in ice velocity estimates and boosts accuracy by a factor that depends on a

  2. EXPERIMENTS OF SEA ICE SIMULATION

    Institute of Scientific and Technical Information of China (English)

    LIU Xi-ying; ZHANG Xue-hong; YU Ru-cong; LIU Hai-long; YU Yong-qiang

    2005-01-01

    As a substitute for the original displaced pole grids, a simple rotated spherical coordinate system was introduced into the Community Sea Ice Model version 4(CSIM4), which is a component of the Community Climate System Model(CCSM) of the American National Center of Atmospheric Research(NCAR), to deal with the "pole problems".In the new coordinates, both the geographical North Pole and South Pole lie in the model equator and grid sizes near the polar region are more uniform.With reanalysis dataset of American National Centers for Environment Prediction(NCEP) and Levitus dataset without considering sub-mixed layer heat flux, the model was integrated for 100 years with thermodynamics process involved only in the former 49 years and both dynamic and thermodynamic processes involved in the left time.Inner consistency of model results was checked with no contradiction found.The results of last 10 years' model output were analyzed and it is shown that the simulated sea ice seasonal variation is rational whereas sea ice extent in the Barents Sea in winter is larger than that of observation.Numerical experiment on influence of sub-mixed layer heat flux was also carried out and it is shown that the sub-mixed layer heat flux can modulate seasonal variation of sea ice greatly.As a model component, the sea ice model with rotated spherical coordinates was coupled with other models (the oceanic general circulation model is the LASG/IAP Climate System Ocean Model(LICOM) with reduced grid, other models are components of NCAR CCSM2) forming a climate system model and its preliminary results were also given briefly.

  3. 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.

  4. Radar for Mapping Sea Ice

    Science.gov (United States)

    Barath, F. T.; Jordan, R. L.

    1983-01-01

    X-band system has 100-m2 resolution. Wide swath imaging radar of synthetic aperature type transmits signal to ground station for subsequent processing into imagery. Concept meets functional requirements for continuously mapping sea ice in north and south polar regions.

  5. The Sea Ice Board Game

    Science.gov (United States)

    Bertram, Kathryn Berry

    2008-01-01

    The National Science Foundation-funded Arctic Climate Modeling Program (ACMP) provides "curriculum resource-based professional development" materials that combine current science information with practical classroom instruction embedded with "best practice" techniques for teaching science to diverse students. The Sea Ice Board…

  6. The Sea Ice Board Game

    Science.gov (United States)

    Bertram, Kathryn Berry

    2008-01-01

    The National Science Foundation-funded Arctic Climate Modeling Program (ACMP) provides "curriculum resource-based professional development" materials that combine current science information with practical classroom instruction embedded with "best practice" techniques for teaching science to diverse students. The Sea Ice Board…

  7. SAR observations of the Nansen Ice Shelf fracture

    Science.gov (United States)

    Moctezuma-Flores, M.; Parmiggiani, F.

    2016-11-01

    This paper presents a study, by means of of Synthetic Aperture Radar (SAR) images, of the fracture of the Nansen Ice Shelf, from its first appearance in SAR images to the final collapse on 7 April 2016. Both Sentinel-1 and Cosmo-SkyMed images have been used. First, the images were remapped onto an equidistant cylindrical projection; from these a subset, or imagette, only covering the fracture was extracted. A segmentation scheme was then applied to the sequence of imagettes in order to produce a sequence of binary imagettes with only the fracture area enhanced; from these, the computation of fracture area became a trivial task.

  8. An overview on SAR measurements of sea surface wind

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    Studies show that synthetic aperture radar (SAR) has the capability of providing high-resolution (sub-kilometer) sea surface wind fields. This is very useful for applications where knowledge of the sea surface wind at fine scales is crucial. This paper aims to review the latest work on sea surface wind field retrieval using SAR images. As shown, many different approaches have been developed for retrieving wind speed and wind direction. However, much more work will be required to fully exploit the SAR data for improving the retrieval accuracy of high-resolution winds and for producing wind products in an operational sense.

  9. Satellite altimetry in sea ice regions - detecting open water for estimating sea surface heights

    Science.gov (United States)

    Müller, Felix L.; Dettmering, Denise; Bosch, Wolfgang

    2017-04-01

    The Greenland Sea and the Farm Strait are transporting sea ice from the central Arctic ocean southwards. They are covered by a dynamic changing sea ice layer with significant influences on the Earth climate system. Between the sea ice there exist various sized open water areas known as leads, straight lined open water areas, and polynyas exhibiting a circular shape. Identifying these leads by satellite altimetry enables the extraction of sea surface height information. Analyzing the radar echoes, also called waveforms, provides information on the surface backscatter characteristics. For example waveforms reflected by calm water have a very narrow and single-peaked shape. Waveforms reflected by sea ice show more variability due to diffuse scattering. Here we analyze altimeter waveforms from different conventional pulse-limited satellite altimeters to separate open water and sea ice waveforms. An unsupervised classification approach employing partitional clustering algorithms such as K-medoids and memory-based classification methods such as K-nearest neighbor is used. The classification is based on six parameters derived from the waveform's shape, for example the maximum power or the peak's width. The open-water detection is quantitatively compared to SAR images processed while accounting for sea ice motion. The classification results are used to derive information about the temporal evolution of sea ice extent and sea surface heights. They allow to provide evidence on climate change relevant influences as for example Arctic sea level rise due to enhanced melting rates of Greenland's glaciers and an increasing fresh water influx into the Arctic ocean. Additionally, the sea ice cover extent analyzed over a long-time period provides an important indicator for a globally changing climate system.

  10. Ecological consequences of sea-ice decline.

    Science.gov (United States)

    Post, Eric; Bhatt, Uma S; Bitz, Cecilia M; Brodie, Jedediah F; Fulton, Tara L; Hebblewhite, Mark; Kerby, Jeffrey; Kutz, Susan J; Stirling, Ian; Walker, Donald A

    2013-08-02

    After a decade with nine of the lowest arctic sea-ice minima on record, including the historically low minimum in 2012, we synthesize recent developments in the study of ecological responses to sea-ice decline. Sea-ice loss emerges as an important driver of marine and terrestrial ecological dynamics, influencing productivity, species interactions, population mixing, gene flow, and pathogen and disease transmission. Major challenges in the near future include assigning clearer attribution to sea ice as a primary driver of such dynamics, especially in terrestrial systems, and addressing pressures arising from human use of arctic coastal and near-shore areas as sea ice diminishes.

  11. Sea Ice Processes

    Science.gov (United States)

    1988-01-01

    aq pnoiqs suol)0!pOid AixoolQA 00! 191100 (1I ’uoTow poAlosqo aql jo lqlgti 04) ol a~xe juqp suotioaJip 4)!A% parto s~t S stqi pule ’spoods 001 a)tUJT...to provide information as ating characteristics of PIPS. These factors in- to processes and their scales (as ascertained by elude the vertical grid...warranted horizontal compression being compensated by at this time. Further investigation is needed. vertical motion. In the case of ice, upward The space

  12. 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.

  13. Ross sea ice motion, area flux, and deformation

    Science.gov (United States)

    kwok, Ron

    2005-01-01

    The sea ice motion, area export, and deformation of the Ross Sea ice cover are examined with satellite passive microwave and RADARSAT observations. The record of high-resolution synthetic aperture radar (SAR) data, from 1998 and 2000, allows the estimation of the variability of ice deformation at the small scale (10 km) and to assess the quality of the longer record of passive microwave ice motion. Daily and subdaily deformation fields and RADARSAT imagery highlight the variability of motion and deformation in the Ross Sea. With the passive microwave ice motion, the area export at a flux gate positioned between Cape Adare and Land Bay is estimated. Between 1992 and 2003, a positive trend can be seen in the winter (March-November) ice area flux that has a mean of 990 x 103 km2 and ranges from a low of 600 x 103 km2 in 1992 to a peak of 1600 x 103 km2 in 2001. In the mean, the southern Ross Sea produces almost twice its own area of sea ice during the winter. Cross-gate sea level pressure (SLP) gradients explain 60% of the variance in the ice area flux. A positive trend in this gradient, from reanalysis products, suggests a 'spinup' of the Ross Sea Gyre over the past 12 yr. In both the NCEP-NCAR and ERA-40 surface pressure fields, longer-term trends in this gradient and mean SLP between 1979 and 2002 are explored along with positive anomalies in the monthly cross-gate SLP gradient associated with the positive phase of the Southern Hemisphere annular mode and the extrapolar Southern Oscillation.

  14. Multiscale Models of Melting Arctic Sea Ice

    Science.gov (United States)

    2014-09-30

    1 Multiscale Models of Melting Arctic Sea Ice Kenneth M. Golden University of Utah, Department of Mathematics phone: (801) 581-6851...feedback has played a major role in the recent declines of the summer Arctic sea ice pack. However, understanding the evolution of melt ponds and sea...Models of Melting Arctic Sea Ice 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER

  15. Sea ice, climate, and multiscale composites

    Science.gov (United States)

    Golden, Kenneth

    2014-03-01

    In September of 2012, the area of the Arctic Ocean covered by sea ice reached its lowest level ever recorded in more than three decades of satellite measurements. In fact, compared to the 1980's and 1990's, this represents a loss of more than half of the summer Arctic sea ice pack. While global climate models generally predict sea ice declines over the 21st century, the precipitous losses observed so far have significantly outpaced most projections. I will discuss how mathematical models of composite materials and statistical physics are being used to study key sea ice processes and advance how sea ice is represented in climate models. This work is helping to improve projections of the fate of Earth's ice packs, and the response of polar ecosystems. A brief video of a recent Antarctic expedition where sea ice properties were measured will be shown. Supported by NSF and ONR.

  16. Albedo evolution of seasonal Arctic sea ice

    Science.gov (United States)

    Perovich, Donald K.; Polashenski, Christopher

    2012-04-01

    There is an ongoing shift in the Arctic sea ice cover from multiyear ice to seasonal ice. Here we examine the impact of this shift on sea ice albedo. Our analysis of observations from four years of field experiments indicates that seasonal ice undergoes an albedo evolution with seven phases; cold snow, melting snow, pond formation, pond drainage, pond evolution, open water, and freezeup. Once surface ice melt begins, seasonal ice albedos are consistently less than albedos for multiyear ice resulting in more solar heat absorbed in the ice and transmitted to the ocean. The shift from a multiyear to seasonal ice cover has significant implications for the heat and mass budget of the ice and for primary productivity in the upper ocean. There will be enhanced melting of the ice cover and an increase in the amount of sunlight available in the upper ocean.

  17. Better constraints on the sea-ice state using global sea-ice data assimilation

    Directory of Open Access Journals (Sweden)

    P. Mathiot

    2012-06-01

    Full Text Available Short-term and decadal sea-ice prediction systems need a realistic initial state, generally obtained using ice-ocean model simulations with data assimilation. However, only sea-ice concentration and velocity data are currently assimilated. In this work, an Ensemble Kalman Filter system is used to assimilate observed ice concentration and freeboard (i.e. thickness of emerged sea ice data into a global coupled ocean–sea-ice model. The impact and effectiveness of our data assimilation system is assessed in two steps: firstly, through the assimilation of synthetic data (i.e., model-generated data and, secondly, through the assimilation of satellite data. While ice concentrations are available daily, freeboard data used in this study are only available during six one-month periods spread over 2005–2007. Our results show that the simulated Arctic and Antarctic sea-ice extents are improved by the assimilation of synthetic ice concentration data. Assimilation of synthetic ice freeboard data improves the simulated sea-ice thickness field. Using real ice concentration data enhances the model realism in both hemispheres. Assimilation of ice concentration data significantly improves the total hemispheric sea-ice extent all year long, especially in summer. Combining the assimilation of ice freeboard and concentration data leads to better ice thickness, but does not further improve the ice extent. Moreover, the improvements in sea-ice thickness due to the assimilation of ice freeboard remain visible well beyond the assimilation periods.

  18. 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...

  19. Snow on Antarctic sea ice

    Science.gov (United States)

    Massom, Robert A.; Eicken, Hajo; Hass, Christian; Jeffries, Martin O.; Drinkwater, Mark R.; Sturm, Matthew; Worby, Anthony P.; Wu, Xingren; Lytle, Victoria I.; Ushio, Shuki; Morris, Kim; Reid, Phillip A.; Warren, Stephen G.; Allison, Ian

    2001-08-01

    Snow on Antarctic sea ice plays a complex and highly variable role in air-sea-ice interaction processes and the Earth's climate system. Using data collected mostly during the past 10 years, this paper reviews the following topics: snow thickness and snow type and their geographical and seasonal variations; snow grain size, density, and salinity; frequency of occurrence of slush; thermal conductivity, snow surface temperature, and temperature gradients within snow; and the effect of snow thickness on albedo. Major findings include large regional and seasonal differences in snow properties and thicknesses; the consequences of thicker snow and thinner ice in the Antarctic relative to the Arctic (e.g., the importance of flooding and snow-ice formation); the potential impact of increasing snowfall resulting from global climate change; lower observed values of snow thermal conductivity than those typically used in models; periodic large-scale melt in winter; and the contrast in summer melt processes between the Arctic and the Antarctic. Both climate modeling and remote sensing would benefit by taking account of the differences between the two polar regions.

  20. Multiyear ice transport and small scale sea ice deformation near the Alaska coast measured by air-deployable Ice Trackers

    Science.gov (United States)

    Mahoney, A. R.; Kasper, J.; Winsor, P.

    2015-12-01

    Highly complex patterns of ice motion and deformation were captured by fifteen satellite-telemetered GPS buoys (known as Ice Trackers) deployed near Barrow, Alaska, in spring 2015. Two pentagonal clusters of buoys were deployed on pack ice by helicopter in the Beaufort Sea between 20 and 80 km offshore. During deployment, ice motion in the study region was effectively zero, but two days later the buoys captured a rapid transport event in which multiyear ice from the Beaufort Sea was flushed into the Chukchi Sea. During this event, westward ice motion began in the Chukchi Sea and propagated eastward. This created new openings in the ice and led to rapid elongation of the clusters as the westernmost buoys accelerated away from their neighbors to the east. The buoys tracked ice velocities of over 1.5 ms-1, with fastest motion occurring closest to the coast indicating strong current shear. Three days later, ice motion reversed and the two clusters became intermingled, rendering divergence calculations based on the area enclosed by clusters invalid. The data show no detectable difference in velocity between first year and multiyear ice floes, but Lagrangian timeseries of SAR imagery centered on each buoy show that first year ice underwent significant small-scale deformation during the event. The five remaining buoys were deployed by local residents on prominent ridges embedded in the landfast ice within 16 km of Barrow in order to track the fate of such features after they detached from the coast. Break-up of the landfast ice took place over a period of several days and, although the buoys each initially followed a similar eastward trajectory around Point Barrow into the Beaufort Sea, they rapidly dispersed over an area more than 50 km across. With rapid environmental and socio-economic change in the Arctic, understanding the complexity of nearshore ice motion is increasingly important for predict future changes in the ice and the tracking ice-related hazards

  1. Persistence of bacterial and archaeal communities in sea ice through an Arctic winter.

    Science.gov (United States)

    Collins, R Eric; Rocap, Gabrielle; Deming, Jody W

    2010-07-01

    The structure of bacterial communities in first-year spring and summer sea ice differs from that in source seawaters, suggesting selection during ice formation in autumn or taxon-specific mortality in the ice during winter. We tested these hypotheses by weekly sampling (January-March 2004) of first-year winter sea ice (Franklin Bay, Western Arctic) that experienced temperatures from -9 degrees C to -26 degrees C, generating community fingerprints and clone libraries for Bacteria and Archaea. Despite severe conditions and significant decreases in microbial abundance, no significant changes in richness or community structure were detected in the ice. Communities of Bacteria and Archaea in the ice, as in under-ice seawater, were dominated by SAR11 clade Alphaproteobacteria and Marine Group I Crenarchaeota, neither of which is known from later season sea ice. The bacterial ice library contained clones of Gammaproteobacteria from oligotrophic seawater clades (e.g. OM60, OM182) but no clones from gammaproteobacterial genera commonly detected in later season sea ice by similar methods (e.g. Colwellia, Psychrobacter). The only common sea ice bacterial genus detected in winter ice was Polaribacter. Overall, selection during ice formation and mortality during winter appear to play minor roles in the process of microbial succession that leads to distinctive spring and summer sea ice communities.

  2. Sea Ice Mapping using Unmanned Aerial Systems

    Science.gov (United States)

    Solbø, S.; Storvold, R.

    2011-12-01

    Mapping of sea ice extent and sea ice features is an important task in climate research. Since the arctic coastal and oceanic areas have a high probability of cloud coverage, aerial platforms are superior to satellite measurements for high-resolution optical measurements. However, routine observations of sea ice conditions present a variety of problems using conventional piloted aircrafts. Specially, the availability of suitable aircrafts for lease does not cover the demand in major parts of the arctic. With the recent advances in unmanned aerial systems (UAS), there is a high possibility of establishing routine, cost effective aerial observations of sea ice conditions in the near future. Unmanned aerial systems can carry a wide variety of sensors useful for characterizing sea-ice features. For instance, the CryoWing UAS, a system initially designed for measurements of the cryosphere, can be equipped with digital cameras, surface thermometers and laser altimeters for measuring freeboard of ice flows. In this work we will present results from recent CryoWing sea ice flights on Svalbard, Norway. The emphasis will be on data processing for stitching together images acquired with the non-stabilized camera payload, to form high-resolution mosaics covering large spatial areas. These data are being employed to map ice conditions; including ice and lead features and melt ponds. These high-resolution mosaics are also well suited for sea-ice mechanics, classification studies and for validation of satellite sea-ice products.

  3. Improved method for sea ice age computation based on combination of sea ice drift and concentration

    Science.gov (United States)

    Korosov, Anton; Rampal, Pierre; Lavergne, Thomas; Aaboe, Signe

    2017-04-01

    Sea Ice Age is one of the components of the Sea Ice ECV as defined by the Global Climate Observing System (GCOS) [WMO, 2015]. It is an important climate indicator describing the sea ice state in addition to sea ice concentration (SIC) and thickness (SIT). The amount of old/thick ice in the Arctic Ocean has been decreasing dramatically [Perovich et al. 2015]. Kwok et al. [2009] reported significant decline in the MYI share and consequent loss of thickness and therefore volume. Today, there is only one acknowledged sea ice age climate data record [Tschudi, et al. 2015], based on Maslanik et al. [2011] provided by National Snow and Ice Data Center (NSIDC) [http://nsidc.org/data/docs/daac/nsidc0611-sea-ice-age/]. The sea ice age algorithm [Fowler et al., 2004] is using satellite-derived ice drift for Lagrangian tracking of individual ice parcels (12-km grid cells) defined by areas of sea ice concentration > 15% [Maslanik et al., 2011], i.e. sea ice extent, according to the NASA Team algorithm [Cavalieri et al., 1984]. This approach has several drawbacks. (1) Using sea ice extent instead of sea ice concentration leads to overestimation of the amount of older ice. (2) The individual ice parcels are not advected uniformly over (long) time. This leads to undersampling in areas of consistent ice divergence. (3) The end product grid cells are assigned the age of the oldest ice parcel within that cell, and the frequency distribution of the ice age is not taken into account. In addition, the base sea ice drift product (https://nsidc.org/data/docs/daac/nsidc0116_icemotion.gd.html) is known to exhibit greatly reduced accuracy during the summer season [Sumata et al 2014, Szanyi, 2016] as it only relies on a combination of sea ice drifter trajectories and wind-driven "free-drift" motion during summer. This results in a significant overestimate of old-ice content, incorrect shape of the old-ice pack, and lack of information about the ice age distribution within the grid cells. We

  4. Quantification of ikaite in Antarctic sea ice

    Directory of Open Access Journals (Sweden)

    M. Fischer

    2012-02-01

    Full Text Available Calcium carbonate precipitation in sea ice can increase pCO2 during precipitation in winter and decrease pCO2 during dissolution in spring. CaCO3 precipitation in sea ice is thought to potentially drive significant CO2 uptake by the ocean. However, little is known about the quantitative spatial and temporal distribution of CaCO3 within sea ice. This is the first quantitative study of hydrous calcium carbonate, as ikaite, in sea ice and discusses its potential significance for the carbon cycle in polar oceans. Ice cores and brine samples were collected from pack and land fast sea ice between September and December 2007 during an expedition in the East Antarctic and another off Terre Adélie, Antarctica. Samples were analysed for CaCO3, Salinity, DOC, DON, Phosphate, and total alkalinity. A relationship between the measured parameters and CaCO3 precipitation could not be observed. We found calcium carbonate, as ikaite, mostly in the top layer of sea ice with values up to 126 mg ikaite per liter melted sea ice. This potentially represents a contribution between 0.12 and 9 Tg C to the annual carbon flux in polar oceans. The horizontal distribution of ikaite in sea ice was heterogenous. We also found the precipitate in the snow on top of the sea ice.

  5. Predictability of the Arctic sea ice edge

    Science.gov (United States)

    Goessling, H. F.; Tietsche, S.; Day, J. J.; Hawkins, E.; Jung, T.

    2016-02-01

    Skillful sea ice forecasts from days to years ahead are becoming increasingly important for the operation and planning of human activities in the Arctic. Here we analyze the potential predictability of the Arctic sea ice edge in six climate models. We introduce the integrated ice-edge error (IIEE), a user-relevant verification metric defined as the area where the forecast and the "truth" disagree on the ice concentration being above or below 15%. The IIEE lends itself to decomposition into an absolute extent error, corresponding to the common sea ice extent error, and a misplacement error. We find that the often-neglected misplacement error makes up more than half of the climatological IIEE. In idealized forecast ensembles initialized on 1 July, the IIEE grows faster than the absolute extent error. This means that the Arctic sea ice edge is less predictable than sea ice extent, particularly in September, with implications for the potential skill of end-user relevant forecasts.

  6. Arctic Landfast Sea Ice 1953-1998

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The files in this data set contain landfast sea ice data (monthly means) gathered from both Russian Arctic and Antarctic Research Institute (AARI) and Canadian Ice...

  7. Ice classification algorithm development and verification for the Alaska SAR Facility using aircraft imagery

    Science.gov (United States)

    Holt, Benjamin; Kwok, Ronald; Rignot, Eric

    1989-01-01

    The Alaska SAR Facility (ASF) at the University of Alaska, Fairbanks is a NASA program designed to receive, process, and archive SAR data from ERS-1 and to support investigations that will use this regional data. As part of ASF, specialized subsystems and algorithms to produce certain geophysical products from the SAR data are under development. Of particular interest are ice motion, ice classification, and ice concentration. This work focuses on the algorithm under development for ice classification, and the verification of the algorithm using C-band aircraft SAR imagery recently acquired over the Alaskan arctic.

  8. Impact of sea ice initialization on sea ice and atmosphere prediction skill on seasonal timescales

    Science.gov (United States)

    Guemas, V.; Chevallier, M.; Déqué, M.; Bellprat, O.; Doblas-Reyes, F.

    2016-04-01

    We present a robust assessment of the impact of sea ice initialization from reconstructions of the real state on the sea ice and atmosphere prediction skill. We ran two ensemble seasonal prediction experiments from 1979 to 2012 : one using realistic sea ice initial conditions and another where sea ice is initialized from a climatology, with two forecast systems. During the melting season in the Arctic Ocean, sea ice forecasts become skilful with sea ice initialization until 3-5 months ahead, thanks to the memory held by sea ice thickness. During the freezing season in both the Arctic and Antarctic Oceans, sea ice forecasts are skilful for 7 and 2 months, respectively, with negligible differences between the two experiments, the memory being held by the ocean heat content. A weak impact on the atmosphere prediction skill is obtained.

  9. Estimation of Arctic Sea Ice Freeboard and Thickness Using CryoSat-2

    Science.gov (United States)

    Lee, S.; Im, J.; Kim, J. W.; Kim, M.; Shin, M.

    2014-12-01

    Arctic sea ice is one of the significant components of the global climate system as it plays a significant role in driving global ocean circulation. Sea ice extent has constantly declined since 1980s. Arctic sea ice thickness has also been diminishing along with the decreasing sea ice extent. Because extent and thickness, two main characteristics of sea ice, are important indicators of the polar response to on-going climate change. Sea ice thickness has been measured with numerous field techniques such as surface drilling and deploying buoys. These techniques provide sparse and discontinuous data in spatiotemporal domain. Spaceborne radar and laser altimeters can overcome these limitations and have been used to estimate sea ice thickness. Ice Cloud and land Elevation Satellite (ICEsat), a laser altimeter provided data to detect polar area elevation change between 2003 and 2009. CryoSat-2 launched with Synthetic Aperture Radar (SAR)/Interferometric Radar Altimeter (SIRAL) in April 2010 can provide data to estimate time-series of Arctic sea ice thickness. In this study, Arctic sea ice freeboard and thickness between 2011 and 2014 were estimated using CryoSat-2 SAR and SARIn mode data that have sea ice surface height relative to the reference ellipsoid WGS84. In order to estimate sea ice thickness, freeboard, i.e., elevation difference between the top of sea ice surface should be calculated. Freeboard can be estimated through detecting leads. We proposed a novel lead detection approach. CryoSat-2 profiles such as pulse peakiness, backscatter sigma-0, stack standard deviation, skewness and kurtosis were examined to distinguish leads from sea ice. Near-real time cloud-free MODIS images corresponding to CryoSat-2 data measured were used to visually identify leads. Rule-based machine learning approaches such as See5.0 and random forest were used to identify leads. The proposed lead detection approach better distinguished leads from sea ice than the existing approaches

  10. The Last Arctic Sea Ice Refuge

    Science.gov (United States)

    Pfirman, S. L.; Tremblay, B.; Newton, R.; Fowler, C.

    2010-12-01

    Summer sea ice may persist along the northern flank of Canada and Greenland for decades longer than the rest of the Arctic, raising the possibility of a naturally formed refugium for ice-associated species. Observations and models indicate that some ice in this region forms locally, while some is transported to the area by winds and ocean currents. Depending on future changes in melt patterns and sea ice transport rates, both the central Arctic and Siberian shelf seas may be sources of ice to the region. An international system of monitoring and management of the sea ice refuge, along with the ice source regions, has the potential to maintain viable habitat for ice-associated species, including polar bears, for decades into the future. Issues to consider in developing a strategy include: + the likely duration and extent of summer sea ice in this region based on observations, models and paleoenvironmental information + the extent and characteristics of the “ice shed” contributing sea ice to the refuge, including its dynamics, physical and biological characteristics as well as potential for contamination from local or long-range sources + likely assemblages of ice-associated species and their habitats + potential stressors such as transportation, tourism, resource extraction, contamination + policy, governance, and development issues including management strategies that could maintain the viability of the refuge.

  11. 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.

  12. Seasonal thickness changes of Arctic sea ice north of Svalbard and implications for satellite remote sensing, ecosystem, and environmental management

    Science.gov (United States)

    Gerland, S.; Rösel, A.; King, J.; Spreen, G.; Divine, D.; Eltoft, T.; Gallet, J. C.; Hudson, S. R.; Itkin, P.; Krumpen, T.; Liston, G. E.; Merkouriadi, I.; Negrel, J.; Nicolaus, M.; Polashenski, C.; Assmy, P.; Barber, D. G.; Duarte, P.; Doulgeris, A. P.; Haas, C.; Hughes, N.; Johansson, M.; Meier, W.; Perovich, D. K.; Provost, C.; Richter-Menge, J.; Skourup, H.; Wagner, P.; Wilkinson, J.; Granskog, M. A.; Steen, H.

    2016-12-01

    Sea-ice thickness is a crucial parameter to consider when assessing the status of Arctic sea ice, whether for environmental management, monitoring projects, or regional or pan-arctic assessments. Modern satellite remote sensing techniques allow us to monitor ice extent and to estimate sea-ice thickness changes; but accurate quantifications of sea-ice thickness distribution rely on in situ and airborne surveys. From January to June 2015, an international expedition (N-ICE2015) took place in the Arctic Ocean north of Svalbard, with the Norwegian research vessel RV Lance frozen into drifting sea ice. In total, four drifts, with four different floes were made during that time. Sea-ice and snow thickness measurements were conducted on all main ice types present in the region, first year ice, multiyear ice, and young ice. Measurement methods included ground and helicopter based electromagnetic surveys, drillings, hot-wire installations, snow-sonde transects, snow stakes, and ice mass balance and snow buoys. Ice thickness distributions revealed modal thicknesses in spring between 1.6 and 1.7 m, which is lower than reported for the region from comparable studies in 2009 (2.4 m) and 2011 (1.8 m). Knowledge about the ice thickness distribution in a region is crucial to the understanding of climate processes, and also relevant to other disciplines. Sea-ice thickness data collected during N-ICE2015 can also give us insights into how ice and snow thicknesses affect ecosystem processes. In this presentation, we will explore the influence of snow cover and ocean properties on ice thickness, and the role of sea-ice thickness in air-ice-ocean interactions. We will also demonstrate how information about ice thickness aids classification of different sea ice types from SAR satellite remote sensing, which has real-world applications for shipping and ice forecasting, and how sea ice thickness data contributes to climate assessments.

  13. Fracture Networks in Sea Ice

    Directory of Open Access Journals (Sweden)

    Jonas Nesland Vevatne

    2014-04-01

    Full Text Available Fracturing and refreezing of sea ice in the Kara sea are investigated using complex networkanalysis. By going to the dual network, where the fractures are nodes and their intersectionslinks, we gain access to topological features which are easy to measure and hence comparewith modeled networks. Resulting network reveal statistical properties of the fracturing process.The dual networks have a broad degree distribution, with a scale-free tail, high clusteringand efficiency. The degree-degree correlation profile shows disassortative behavior, indicatingpreferential growth. This implies that long, dominating fractures appear earlier than shorterfractures, and that the short fractures which are created later tend to connect to the longfractures.The knowledge of the fracturing process is used to construct growing fracture network (GFNmodel which provides insight into the generation of fracture networks. The GFN model isprimarily based on the observation that fractures in sea ice are likely to end when hitting existingfractures. Based on an investigation of which fractures survive over time, a simple model forrefreezing is also added to the GFN model, and the model is analyzed and compared to the realnetworks.

  14. Modified PIC Method for Sea Ice Dynamics

    Institute of Scientific and Technical Information of China (English)

    WANG Rui-xue; JI Shun-ying; SHEN Hung-tao; YUE Qian-jin

    2005-01-01

    The sea ice cover displays various dynamical characteristics such as breakup, rafting, and ridging under external forces. To model the ice dynamic process accurately, the effective numerical modeling method should be established. In this paper, a modified particle-in-cell (PIC) method for sea ice dynamics is developed coupling the finite difference (FD) method and smoothed particle hydrodynamics (SPH). In this method, the ice cover is first discretized into a series of Lagrangian ice particles which have their own sizes, thicknesses, concentrations and velocities. The ice thickness and concentration at Eulerian grid positions are obtained by interpolation with the Gaussian function from their surrounding ice particles. The momentum of ice cover is solved with FD approach to obtain the Eulerian cell velocity, which is used to estimate the ice particle velocity with the Gaussian function also. The thickness and concentration of ice particles are adjusted with particle mass density and smooth length, which are adjusted with the redistribution of ice particles. With the above modified PIC method, numerical simulations for ice motion in an idealized rectangular basin and the ice dynamics in the Bohai Sea are carried out. These simulations show that this modified PIC method is applicable to sea ice dynamics simulation.

  15. Investigation of the effects of summer melt on the calculation of sea ice concentration using active and passive microwave data

    Science.gov (United States)

    Cavalieri, Donald J.; Burns, Barbara A.; Onstott, Robert G.

    1990-01-01

    The effects of ice surface melt on microwave signatures and errors in the calculation of sea ice concentration are examined, using active and passive microwave data sets from the Marginal Ice Zone Experiment aircraft flights in the Fram Strait region. Consideration is given to the possibility of using SAR to supplement passive microwave data to unambiguously discriminate between open water areas and ponded floes. Coincident active multichannel microwave radiometer and SAR measurements of individual floes are used to describe the effects of surface melt on sea ice concentration calculations.

  16. 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

    Brightness temperatures at 1.4. GHz (L-band) measured by the Soil Moisture and Ocean Salinity (SMOS) Mission have been used to derive the thickness of sea ice. The retrieval method is applicable only for relatively thin ice and not during the melting period. Hitherto, the availability of ground...... truth sea ice thickness measurements for validation of SMOS sea ice products was mainly limited to relatively thick ice. The situation has improved with an extensive field campaign in the Barents Sea during an anomalous ice edge retreat and subsequent freeze-up event in March 2014. A sea ice forecast...... 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...

  17. The consolidation of rafted sea ice

    Science.gov (United States)

    Bailey, E.; Feltham, D.; Sammonds, P.

    2009-04-01

    Rafting is an important process in the deformation of sea ice that occurs when two ice sheets collide. This process is particularly common in the North Caspian Sea, where ice floes override one another multiple times to produce thick sea ice features. To date, rafting has received little attention in the literature perhaps because in most regions pressure ridges produce the greatest loads on offshore structures. In the North Caspian Sea the shallow waters constrain the size to which pressure ridges can grow and the low salinity seems to favor rafting over ridging. Therefore it is likely that multiply-rafted sea ice may be the governing design feature for ice loads in the Caspian Sea. Here we present a one-dimensional, thermal-consolidation model for rafted sea ice. This is of interest because the degree of consolidation will affect the strength of a rafted structure, and therefore may be of value for modeling rafted ice loads. Results show that the thickness of the liquid layers reduces asymptotically with time, such that there always remains a thin liquid layer. We propose that when the liquid layer is equal to the surface roughness the adjacent layers can be considered consolidated. Using parameters specific to the North Caspian Sea, calculations show that it took 1hr, 14mins for the ice sheets to consolidate. To test the accuracy of the model concurrent experiments were carried out in the HSVA ice basin. During an experiment, equally sized portions of level ice were manually piled on top of one another to produce a rafted section. The rate of consolidation or bonding of the layers was then monitored by coring and using thermistors that were frozen into the level ice prior to rafting. Once consolidated, strength tests were carried out on the rafted ice and compared with those of level ice.

  18. Biogeochemical Coupling between Ocean and Sea Ice

    Science.gov (United States)

    Wang, S.; Jeffery, N.; Maltrud, M. E.; Elliott, S.; Wolfe, J.

    2016-12-01

    Biogeochemical processes in ocean and sea ice are tightly coupled at high latitudes. Ongoing changes in Arctic and Antarctic sea ice domain likely influence the coupled system, not only through physical fields but also biogeochemical properties. Investigating the system and its changes requires representation of ocean and sea ice biogeochemical cycles, as well as their coupling in Earth System Models. Our work is based on ACME-HiLAT, a new offshoot of the Community Earth System Model (CESM), including a comprehensive representation of marine ecosystems in the form of the Biogeochemical Elemental Cycling Module (BEC). A full vertical column sea ice biogeochemical module has recently been incorporated into the sea ice component. We have further introduced code modifications to couple key growth-limiting nutrients (N, Si, Fe), dissolved and particulate organic matter, and phytoplankton classes that are important in polar regions between ocean and sea ice. The coupling of ocean and sea ice biology-chemistry will enable representation of key processes such as the release of important climate active constituents or seeding algae from melting sea ice into surface waters. Sensitivity tests suggest sea ice and ocean biogeochemical coupling influences phytoplankton competition, biological production, and the CO2 flux. Sea ice algal seeding plays an important role in determining phytoplankton composition of Arctic early spring blooms, since different groups show various responses to the seeding biomass. Iron coupling leads to increased phytoplankton biomass in the Southern Ocean, which also affects carbon uptake via the biological pump. The coupling of macronutrients and organic matter may have weaker influences on the marine ecosystem. Our developments will allow climate scientists to investigate the fully coupled responses of the sea ice-ocean BGC system to physical changes in polar climate.

  19. Multisensor Analyzed Sea Ice Extent - Northern Hemisphere (MASIE-NH)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Multisensor Analyzed Sea Ice Extent Northern Hemisphere (MASIE-NH) products provide measurements of daily sea ice extent and sea ice edge boundary for the...

  20. Fram Strait Spring Ice Export and September Arctic Sea Ice

    Science.gov (United States)

    Smedsrud, Lars H.; Halvorsen, Mari H.; Stroeve, Julienne; Zhang, Rong; Kloster, Kjell

    2016-04-01

    The Arctic Basin exports between 600 000 - 1 million km² of it's sea ice cover southwards through Fram Strait each year, comparing to about 10% of the ice covered area inside the basin. During winter ice export results in growth of new and relatively thin ice inside the basin, while during summer or spring export contributes directly to open water further north. A new updated time series from 1935 to 2014 of Fram Strait sea ice area export shows that the long-term annual mean export is about 880,000 km², with large annual and decadal variability and no long-term trend over the past 80 years. Nevertheless, the last decade has witnessed increased annual ice export, with several years having annual ice export exceed 1 million km². Evaluating the trend onwards from 1979, when satellite based sea ice coverage became more readily available, reveals an increase in annual export of about +6% per decade. This increase is caused by higher southward ice drift speeds due to stronger southward geostrophic winds, largely explained by increasing surface pressure over Greenland. Spring and summer area export increased more (+11% per decade) than in autumn and winter. Contrary to the last decade the 1950 - 1970 period had low export during spring and summer, and mid-September sea ice extent was consistently higher than both before and after these decades. We thus find that export anomalies during spring have a clear influence on the following September sea ice extent in general, and that for the recent decade the export may be partially responsible for the accelerating decline in Arctic sea ice extent.

  1. On the measure of sea ice area from sea ice concentration data sets

    Science.gov (United States)

    Boccolari, Mauro; Parmiggiani, Flavio

    2015-10-01

    The measure of sea ice surface variability provides a fundamental information on the climatology of the Arctic region. Sea ice extension is conventionally measured by two parameters, i.e. Sea Ice Extent (SIE) and Sea Ice Area (SIA), both parameters being derived from Sea Ice Concentration (SIC) data sets. In this work a new parameter (CSIA) is introduced, which takes into account only the compact sea-ice, which is defined as the sea-ice having concentration at least equal the 70%. Aim of this study is to compare the performances of the two parameters, SIA and CSIA, in analyzing the trends of three monthly time-series of the whole Arctic region. The SIC data set used in this study was produced by the Institute of Environmental Physics of the University of Bremen and covers the period January 2003 - December 2014, i.e. the period in which the data set is built using the new AMSR passive microwave sensor.

  2. 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.

  3. 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

  4. Massive phytoplankton blooms under Arctic sea ice.

    Science.gov (United States)

    Arrigo, Kevin R; Perovich, Donald K; Pickart, Robert S; Brown, Zachary W; van Dijken, Gert L; Lowry, Kate E; Mills, Matthew M; Palmer, Molly A; Balch, William M; Bahr, Frank; Bates, Nicholas R; Benitez-Nelson, Claudia; Bowler, Bruce; Brownlee, Emily; Ehn, Jens K; Frey, Karen E; Garley, Rebecca; Laney, Samuel R; Lubelczyk, Laura; Mathis, Jeremy; Matsuoka, Atsushi; Mitchell, B Greg; Moore, G W K; Ortega-Retuerta, Eva; Pal, Sharmila; Polashenski, Chris M; Reynolds, Rick A; Schieber, Brian; Sosik, Heidi M; Stephens, Michael; Swift, James H

    2012-06-15

    Phytoplankton blooms over Arctic Ocean continental shelves are thought to be restricted to waters free of sea ice. Here, we document a massive phytoplankton bloom beneath fully consolidated pack ice far from the ice edge in the Chukchi Sea, where light transmission has increased in recent decades because of thinning ice cover and proliferation of melt ponds. The bloom was characterized by high diatom biomass and rates of growth and primary production. Evidence suggests that under-ice phytoplankton blooms may be more widespread over nutrient-rich Arctic continental shelves and that satellite-based estimates of annual primary production in these waters may be underestimated by up to 10-fold.

  5. Record Arctic Sea Ice Loss in 2007

    Science.gov (United States)

    2007-01-01

    This image of the Arctic was produced from sea ice observations collected by the Advanced Microwave Scanning Radiometer (AMSR-E) Instrument on NASA's Aqua satellite on September 16, overlaid on the NASA Blue Marble. The image captures ice conditions at the end of the melt season. Sea ice (white, image center) stretches across the Arctic Ocean from Greenland to Russia, but large areas of open water were apparent as well. In addition to record melt, the summer of 2007 brought an ice-free opening though the Northwest Passage that lasted several weeks. The Northeast Passage did not open during the summer of 2007, however, as a substantial tongue of ice remained in place north of the Russian coast. According to the National Snow and Ice Data Center (NSIDC), on September 16, 2007, sea ice extent dropped to 4.13 million square kilometers (1.59 million square miles)--38 percent below average and 24 percent below the 2005 record.

  6. A toy model of sea ice growth

    Science.gov (United States)

    Thorndike, Alan S.

    1992-01-01

    My purpose here is to present a simplified treatment of the growth of sea ice. By ignoring many details, it is possible to obtain several results that help to clarify the ways in which the sea ice cover will respond to climate change. Three models are discussed. The first deals with the growth of sea ice during the cold season. The second describes the cycle of growth and melting for perennial ice. The third model extends the second to account for the possibility that the ice melts away entirely in the summer. In each case, the objective is to understand what physical processes are most important, what ice properties determine the ice behavior, and to which climate variables the system is most sensitive.

  7. SAR imagery of the Grand Banks (Newfoundland) pack ice pack and its relationship to surface features

    Science.gov (United States)

    Argus, S. D.; Carsey, F. D.

    1988-01-01

    Synthetic Aperture Radar (SAR) data and aerial photographs were obtained over pack ice off the East Coast of Canada in March 1987 as part of the Labrador Ice Margin Experiment (LIMEX) pilot project. Examination of this data shows that although the pack ice off the Canadian East Coast appears essentially homogeneous to visible light imagery, two clearly defined zones of ice are apparent on C-band SAR imagery. To identify factors that create the zones seen on the radar image, aerial photographs were compared to the SAR imagery. Floe size data from the aerial photographs was compared to digital number values taken from SAR imagery of the same ice. The SAR data of the inner zone acquired three days apart over the melt period was also examined. The studies indicate that the radar response is governed by floe size and meltwater distribution.

  8. Arctic tides from GPS on sea ice

    DEFF Research Database (Denmark)

    Kildegaard Rose, Stine; Skourup, Henriette; Forsberg, René

    The presence of sea-ice in the Arctic Ocean plays a significant role in the Arctic climate. Sea ice dampens the ocean tide amplitude with the result that global tidal models which use only astronomical data perform less accurately in the polar regions. This study presents a kinematic processing...... of Global Positioning System (GPS) buoys placed on sea-ice at five different sites north of Greenland for the study of sea level height and tidal analysis to improve tidal models in the Central Arctic. The GPS measurements are compared with the Arctic tidal model AOTIM-5, which assimilates tide...

  9. On sea level - ice sheet interactions

    Science.gov (United States)

    Gomez, Natalya Alissa

    This thesis focuses on the physics of static sea-level changes following variations in the distribution of grounded ice and the influence of these changes on the stability and dynamics of marine ice sheets. Gravitational, deformational and rotational effects associated with changes in grounded ice mass lead to markedly non-uniform spatial patterns of sea-level change. I outline a revised theory for computing post-glacial sea-level predictions and discuss the dominant physical effects that contribute to the patterns of sea-level change associated with surface loading on different timescales. I show, in particular, that a large sea-level fall (rise) occurs in the vicinity of a retreating (advancing) ice sheet on both short and long timescales. I also present an application of the sea-level theory in which I predict the sea-level changes associated with a new model of North American ice sheet evolution and consider the implications of the results for efforts to establish the sources of Meltwater Pulse 1A. These results demonstrate that viscous deformational effects can influence the amplitude of sea-level changes observed at far-field sea-level sites, even when the time window being considered is relatively short (≤ 500 years). Subsequently, I investigate the feedback of sea-level changes on marine ice-sheet stability and dynamics by coupling a global sea-level model to ice-sheet models of increasing complexity. To begin, I incorporate gravitationally self-consistent sea-level changes into an equilibrium marine ice-sheet stability theory to show that the sea-level changes have a stabilizing influence on ice-sheet retreat. Next, I consider the impact of the stabilizing mechanism on the timescale of ice-sheet retreat using a 1D dynamic coupled ice sheet - sea level model. Simulations with the coupled model, which incorporate viscoelastic deformation of the solid Earth, show that local sea-level changes at the grounding line act to slow, and in some cases, halt

  10. 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.

  11. Sea Ice Biogeochemistry: A Guide for Modellers

    Science.gov (United States)

    Tedesco, Letizia; Vichi, Marcello

    2014-01-01

    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. PMID:24586604

  12. Sea ice biogeochemistry: a guide for modellers.

    Science.gov (United States)

    Tedesco, Letizia; Vichi, Marcello

    2014-01-01

    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.

  13. Mapping wave heights in sea ice with Sentinel 1

    Science.gov (United States)

    Stopa, Justin; Ardhuin, Fabrice; Collard, Fabrice; Mouche, Alexis; Guitton, Gilles; Sutherland, Peter

    2016-04-01

    Sea ice plays an important role in the Earth system by regulating air-sea fluxes. These fluxes can be enhanced by the breaking of ice into floes which critically depends on wave heights propagating across the ice. Remote sensing with SAR provides a unique coverage of the polar regions but so far the measurement of wave heights has been performed routinely only for open water. The presence of ice completely changes the mechanisms by which waves make patterns in radar images. Namely, in the open ocean, the constructed images appear blurred due to the fact that the high frequency waves are unresolved by the sensor. Instead, in ice-covered seas, high frequency waves have been dissipated or scattered away, and only the low-frequency swell components are observed. Two new algorithms have been proposed by Ardhuin et al. (2015). Refining these algorithms, we analyze the intricate wave patterns captured over sea ice by Sentinel 1-A, and measure both the wave heights and directional spreading of the wave spectrum. The procedure is a two-step process which uses an estimation of the orbital vertical velocities that produce the observed image intensity. The first step is implemented when wiggly lines are present. Wiggly lines are created by the presence of two swell systems and are removed by estimating the wave orbital velocity that causes the amplitude in the wiggly line. The second step uses Fourier analysis to invert the straightened image into a velocity field. As a result we obtain a full non-linear inversion the mapping from the velocity field to the SAR intensity image. The inverted velocities can be used to obtain the wavenumber-direction spectrum. Our algorithm is applied to S1A images from the Arctic and Antarctic and discussions follow in terms of wave-ice interaction. These data will be validated using in situ measurements from the ONR Sea State DRI (Beaufort sea, 2016), and combined with numerical modeling using the WAVEWATCH III model to adjust parameterization

  14. Correlated Energy Exchange in Drifting Sea Ice

    Directory of Open Access Journals (Sweden)

    A. Chmel

    2011-01-01

    Full Text Available The ice floe speed variations were monitored at the research camp North Pole 35 established on the Arctic ice pack in 2008. A three-month time series of measured speed values was used for determining changes in the kinetic energy of the drifting ice floe. The constructed energy distributions were analyzed by methods of nonextensive statistical mechanics based on the Tsallis statistics for open nonequilibrium systems, such as tectonic formations and drifting sea ice. The nonextensivity means the nonadditivity of externally induced energy changes in multicomponent systems due to dynamic interrelation of components having no structural links. The Tsallis formalism gives one an opportunity to assess the correlation between ice floe motions through a specific parameter, the so-called parameter of nonextensivity. This formalistic assessment of the actual state of drifting pack allows one to forecast some important trends in sea ice behavior, because the level of correlated dynamics determines conditions for extended mechanical perturbations in ice pack. In this work, we revealed temporal fluctuations of the parameter of nonextensivity and observed its maximum value before a large-scale sea ice fragmentation (faulting of consolidated sea ice. The correlation was not detected in fragmented sea ice where long-range interactions are weakened.

  15. 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 (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 enhanced summer ice melt. Previous estimates of Arctic sea ice meiofauna and under-ice amphipods on regional and pan-Arctic scales likely underestimate abundances at least in summer because they typically do not include pressure ridges.

  16. Operational multisensor sea ice concentration algorithm utilizing Sentinel-1 and AMSR2 data

    Science.gov (United States)

    Dinessen, Frode

    2017-04-01

    The Norwegian Ice Service provide ice charts of the European part of the Arctic every weekday. The charts are produced from a manually interpretation of satellite data where SAR (Synthetic Aperture Radar) data plays a central role because of its high spatial resolution and Independence of cloud cover. A new chart is produced every weekday and the charts are distributed through the CMEMS portal. After the launch of Sentinel-1A and B the number of available SAR data have significant increased making it difficult to utilize all the data in a manually process. This in combination with a user demand for a more frequent update of the ice conditions, also during the weekends, have made it important to focus the development on utilizing the high resolution Sentinel-1 data in an automatic sea ice concentration analysis. The algorithm developed here is based on a multi sensor approach using an optimal interpolation to combine sea ice concentration products derived from Sentinel-1 and passive microwave data from AMSR2. The Sentinel-1 data is classified with a Bayesian SAR classification algorithm using data in extra wide mode dual polarization (HH/HV) to separate ice and water in the full 40x40 meter spatial resolution. From the classification of ice/water the sea ice concentration is estimated by calculating amount of ice within an area of 1x1 km. The AMSR2 sea ice concentration are produced as part of the EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI SAF) project and utilize the 89 GHz channel to produce a concentration product with a 3km spatial resolution. Results from the automatic classification will be presented.

  17. Stress and deformation characteristics of sea ice in a high resolution numerical sea ice model.

    Science.gov (United States)

    Heorton, Harry; Feltham, Daniel; Tsamados, Michel

    2017-04-01

    The drift and deformation of sea ice floating on the polar oceans is due to the applied wind and ocean currents. The deformations of sea ice over ocean basin length scales have observable patterns; cracks and leads in satellite images and within the velocity fields generated from floe tracking. In a climate sea ice model the deformation of sea ice over ocean basin length scales is modelled using a rheology that represents the relationship between stresses and deformation within the sea ice cover. Here we investigate the link between observable deformation characteristics and the underlying internal sea ice stresses and force balance using the Los Alamos numerical sea ice climate model. In order to mimic laboratory experiments on the deformation of small cubes of sea ice we have developed an idealised square domain that tests the model response at spatial resolutions of up to 500m. We use the Elastic Anisotropic Plastic and Elastic Viscous Plastic rheologies, comparing their stability over varying resolutions and time scales. Sea ice within the domain is forced by idealised winds in order to compare the confinement of wind stresses and internal sea ice stresses. We document the characteristic deformation patterns of convergent, divergent and rotating stress states.

  18. Linking scales in sea ice mechanics

    Science.gov (United States)

    Weiss, Jérôme; Dansereau, Véronique

    2017-02-01

    Mechanics plays a key role in the evolution of the sea ice cover through its control on drift, on momentum and thermal energy exchanges between the polar oceans and the atmosphere along cracks and faults, and on ice thickness distribution through opening and ridging processes. At the local scale, a significant variability of the mechanical strength is associated with the microstructural heterogeneity of saline ice, however characterized by a small correlation length, below the ice thickness scale. Conversely, the sea ice mechanical fields (velocity, strain and stress) are characterized by long-ranged (more than 1000 km) and long-lasting (approx. few months) correlations. The associated space and time scaling laws are the signature of the brittle character of sea ice mechanics, with deformation resulting from a multi-scale accumulation of episodic fracturing and faulting events. To translate the short-range-correlated disorder on strength into long-range-correlated mechanical fields, several key ingredients are identified: long-ranged elastic interactions, slow driving conditions, a slow viscous-like relaxation of elastic stresses and a restoring/healing mechanism. These ingredients constrained the development of a new continuum mechanics modelling framework for the sea ice cover, called Maxwell-elasto-brittle. Idealized simulations without advection demonstrate that this rheological framework reproduces the main characteristics of sea ice mechanics, including anisotropy, spatial localization and intermittency, as well as the associated scaling laws. This article is part of the themed issue 'Microdynamics of ice'.

  19. Detecting Near-Surface Ice Formation Over Time Using the Kennaugh Elements Approach From TerraSAR-X

    Science.gov (United States)

    Fernandes, L.

    2016-12-01

    The summer melting has increased substantially at higher elevations on the Canadian Arctic ice caps. The resulting meltwater percolates into the upper layers of snow and firn and then refreeze, building massive ice bodies. It seems likely that these within-firn ice bodies now limit meltwater penetration into the firn and may be creating a feedback whereby the fraction of melt that runs off to the ocean is increasing. Although changes in firn structure as presence of ice layers and ice bodies are well documented over the Devon ice cap, the firm has shown that it exerts a crucial role to predict more accurately the contribution of small ice caps to the sea level rise. However it is still challenging to assess the extent of these features within the shallow subsurface using ice cores and GPR (Ground Penetrating Radar) data collected along a limited number of linear transects. Studying changes in the distribution of ice bodies' formation over time has the potential to provide information about how the growth of ice bodies in the firn is affecting the pattern of water flow in the firn layer. The objective is investigate the potential of Kennaugh Elements (KE) derived from x-band SAR (Synthetic Aperture Radar) for mapping the distribution and growth of large ice bodies within the firn and the evolution of their distribution over time. The evaluation of this method could reveal a new approach suitable for other glacierized regions that would reduce the costs and amount of field work for studying such properties.

  20. Constraining projections of summer Arctic sea ice

    Directory of Open Access Journals (Sweden)

    F. Massonnet

    2012-11-01

    Full Text Available We examine the recent (1979–2010 and future (2011–2100 characteristics of the summer Arctic sea ice cover as simulated by 29 Earth system and general circulation models from the Coupled Model Intercomparison Project, phase 5 (CMIP5. As was the case with CMIP3, a large intermodel spread persists in the simulated summer sea ice losses over the 21st century for a given forcing scenario. The 1979–2010 sea ice extent, thickness distribution and volume characteristics of each CMIP5 model are discussed as potential constraints on the September sea ice extent (SSIE projections. Our results suggest first that the future changes in SSIE with respect to the 1979–2010 model SSIE are related in a complicated manner to the initial 1979–2010 sea ice model characteristics, due to the large diversity of the CMIP5 population: at a given time, some models are in an ice-free state while others are still on the track of ice loss. However, in phase plane plots (that do not consider the time as an independent variable, we show that the transition towards ice-free conditions is actually occurring in a very similar manner for all models. We also find that the year at which SSIE drops below a certain threshold is likely to be constrained by the present-day sea ice properties. In a second step, using several adequate 1979–2010 sea ice metrics, we effectively reduce the uncertainty as to when the Arctic could become nearly ice-free in summertime, the interval [2041, 2060] being our best estimate for a high climate forcing scenario.

  1. Enhancing calculation of thin sea ice growth

    Science.gov (United States)

    Appel, Igor

    2016-12-01

    The goal of the present study is to develop, generate, and integrate into operational practice a new model of ice growth. The development of this Sea Ice Growth Model for Arctic (SIGMA), a description of the theoretical foundation, the model advantages and analysis of its results are considered in the paper. The enhanced model includes two principal modifications. Surface temperature of snow on ice is defined as internal model parameter maintaining rigorous consistency between processes of atmosphere-ice thermodynamic interaction and ice growth. The snow depth on ice is naturally defined as a function of a local snowfall rate and linearly depends on time rather than ice thickness. The model was initially outlined in the Visible Infrared Radiometer Suite (VIIRS) Sea Ice Characterization Algorithm Theoretical Basis Document (Appel et al., 2005) that included two different approaches to retrieve sea ice age: reflectance analysis for daytime and derivation of ice thickness using energy balance for nighttime. Only the latter method is considered in this paper. The improved account for the influence of surface temperature and snow depth increases the reliability of ice thickness calculations and is used to develop an analytical Snow Depth/Ice Thickness Look up table suitable to the VIIRS observations as well as to other instruments. The applicability of SIGMA to retrieve ice thickness from the VIIRS satellite observations and the comparison of its results with the One-dimensional Thermodynamic Ice Model (OTIM) are also considered. The comparison of the two models demonstrating the difference between their assessments of heat fluxes and radical distinction between the influences of snow depth uncertainty on errors of ice thickness calculations is of great significance to further improve the retrieval of ice thickness from satellite observations.

  2. Stratospheric Impacts on Arctic Sea Ice

    Science.gov (United States)

    Reichler, Thomas

    2016-04-01

    Long-term circulation change in the stratosphere can have substantial effects on the oceans and their circulation. In this study we investigate whether and how sea ice at the ocean surface responds to intraseasonal stratospheric variability. Our main question is whether the surface impact of stratospheric sudden warmings (SSWs) is strong and long enough to affect sea ice. A related question is whether the increased frequency of SSWs during the 2000s contributed to the rapid decrease in Arctic sea ice during this time. To this end we analyze observations of sea ice, NCEP/NCAR reanalysis, and a long control integration with a stratospherically-enhanced version of the GFDL CM2.1 climate model. From both observations and the model we find that stratospheric extreme events have a demonstrable impact on the distribution of Arctic sea ice. The areas most affected are near the edge of the climatological ice line over the North Atlantic, North Pacific, and the Arctic Ocean. The absolute changes in sea ice coverage amount to +/-10 %. Areas and magnitudes of increase and decrease are about the same. It is thus unlikely that the increased SSW frequency during the 2000s contributed to the decline of sea ice during that period. The sea ice changes are consistent with the impacts of a negative NAO at the surface and can be understood in terms of (1) dynamical change due to altered surface wind stress and (2) thermodynamical change due to altered temperature advection. Both dynamical and thermodynamical change positively reinforce each other in producing sea change. A simple advection model is used to demonstrate that most of the sea ice change can be explained from the sea ice drift due to the anomalous surface wind stress. Changes in the production or melt of sea ice by thermodynamical effects are less important. Overall, this study adds to an increasing body of evidence that the stratosphere not only impacts weather and climate of the atmosphere but also the surface and

  3. Signature of Arctic first-year ice melt pond fraction in X-band SAR imagery

    Science.gov (United States)

    Fors, Ane S.; Divine, Dmitry V.; Doulgeris, Anthony P.; Renner, Angelika H. H.; Gerland, Sebastian

    2017-03-01

    In this paper we investigate the potential of melt pond fraction retrieval from X-band polarimetric synthetic aperture radar (SAR) on drifting first-year sea ice. Melt pond fractions retrieved from a helicopter-borne camera system were compared to polarimetric features extracted from four dual-polarimetric X-band SAR scenes, revealing significant relationships. The correlations were strongly dependent on wind speed and SAR incidence angle. Co-polarisation ratio was found to be the most promising SAR feature for melt pond fraction estimation at intermediate wind speeds (6. 2 m s-1), with a Spearman's correlation coefficient of 0. 46. At low wind speeds (0. 6 m s-1), this relation disappeared due to low backscatter from the melt ponds, and backscatter VV-polarisation intensity had the strongest relationship to melt pond fraction with a correlation coefficient of -0. 53. To further investigate these relations, regression fits were made both for the intermediate (R2fit = 0. 21) and low (R2fit = 0. 26) wind case, and the fits were tested on the satellite scenes in the study. The regression fits gave good estimates of mean melt pond fraction for the full satellite scenes, with less than 4 % from a similar statistics derived from analysis of low-altitude imagery captured during helicopter ice-survey flights in the study area. A smoothing window of 51 × 51 pixels gave the best reproduction of the width of the melt pond fraction distribution. A considerable part of the backscatter signal was below the noise floor at SAR incidence angles above ˜ 40°, restricting the information gain from polarimetric features above this threshold. Compared to previous studies in C-band, limitations concerning wind speed and noise floor set stricter constraints on melt pond fraction retrieval in X-band. Despite this, our findings suggest new possibilities in melt pond fraction estimation from X-band SAR, opening for expanded monitoring of melt ponds during melt season in the future.

  4. Modeling of Electromagnetic Waves Scattering from Snow Covered First Year Sea Ice

    Science.gov (United States)

    Komarov, A. S.; Barber, D. G.; Isleifson, D. K.

    2011-12-01

    Modeling of electromagnetic wave interaction with sea ice is required for various remote sensing applications, such as an interpretation of Synthetic Aperture Radar (SAR) imagery over sea ice. In this study, we present numerical modeling of the Normalized Radar Cross Section (NRCS) at vertical and horizontal polarizations from snow covered First Year (FY) sea ice. We consider sea ice as a layered medium with an arbitrary profile of dielectric constant, and the snow cover as a homogeneous layer on the top of the sea ice. Surface scattering at the snow-sea ice interface was taken into account by the first-order approximation of the small perturbation method. We obtained an analytical formulation for radar cross-sections at vertical and horizontal polarizations and conducted numerical modeling of the backscattering characteristics. The solution derived for NRCSs includes reflection coefficients from snow and sea ice. The calculation of reflection coefficients from the stratified sea ice is considered separately as an auxiliary problem. In-situ geophysical properties of snow and sea ice collected during the Circumpolar Flow Lead (CFL) system study project were used to estimate the dielectric constants of snow and sea ice for several case studies. The dielectric constant of the sea ice was calculated using the Polder-van-Santen/de Loor (PVD) mixture model, while the dielectric constant of the snow was estimated using a Debye-like model. The calculated angular dependencies of the NRCSs (HH- and VV- polarizations) and co-polarization ratios were compared with in-situ C-band scatterometer measurements. These comparisons demonstrate a good agreement between simulated and observed scattering characteristics.

  5. A SAR Ice-Motion Processing Chain in Support of PROMICE (Programme for the Monitoring of the Greenland Ice Sheet)

    DEFF Research Database (Denmark)

    Merryman Boncori, John Peter; Dall, Jørgen; Ahlstrøm, A. P.;

    2010-01-01

    This paper reports on the development of a SAR icemotion processing chain developed for the PROMICE project – a long-term program funded by the Danish ministry of Climate and Energy to monitor the mass budget of the Greenland ice sheet. The end goal of the SAR data processing is to output map...

  6. Polar bears and sea ice habitat change

    Science.gov (United States)

    Durner, George M.; Atwood, Todd C.; Butterworth, Andy

    2017-01-01

    The polar bear (Ursus maritimus) is an obligate apex predator of Arctic sea ice and as such can be affected by climate warming-induced changes in the extent and composition of pack ice and its impacts on their seal prey. Sea ice declines have negatively impacted some polar bear subpopulations through reduced energy input because of loss of hunting habitats, higher energy costs due to greater ice drift, ice fracturing and open water, and ultimately greater challenges to recruit young. Projections made from the output of global climate models suggest that polar bears in peripheral Arctic and sub-Arctic seas will be reduced in numbers or become extirpated by the end of the twenty-first century if the rate of climate warming continues on its present trajectory. The same projections also suggest that polar bears may persist in the high-latitude Arctic where heavy multiyear sea ice that has been typical in that region is being replaced by thinner annual ice. Underlying physical and biological oceanography provides clues as to why polar bear in some regions are negatively impacted, while bears in other regions have shown no apparent changes. However, continued declines in sea ice will eventually challenge the survival of polar bears and efforts to conserve them in all regions of the Arctic.

  7. Sea Ice Leads and Polynya Detection Using Multi-Mission Altimetry in the Greenland Sea

    Science.gov (United States)

    Muller, Felix L.; Passaro, Marcello; Dettmering, Denise; Bosch, Wolfgang

    2016-08-01

    In this study, we present two methods to detect open water areas in the Greenland Sea based on altimetry measurements. For this purpose, high-frequency data from ENVISAT (pulse-limited altimeter) and Delay-Doppler data from CryoSat-2 are used. The radar echoes of both missions contain information about the reflectance of the overflown surface area. For ENVISAT, we use an unsupervised classification approach to distinguish between water and ice returns. The waveforms are the main input for the classification process. Training data from known surfaces are not necessary for our method. For CryoSat- 2 SAR mode, an advanced approach is used in order to exploit the multi-look processing of the same resolution cell from different look angles. We analyse the Range Integrated Power, a side product providing additional information about the backscatter properties. All classification results are compared with pictures of imaging SAR satellite missions (ALOS and Sentinel-1A). In order to take the time lag between the two observation sets into account, a mean ice-motion is applied to the images. This ensures realistic comparison results. The classification approach allows for an identification of open water (leads and polynyas) in sea-ice regions and will help to improve sea level estimation in these regions.

  8. Mirabilite solubility in equilibrium sea ice brines

    Science.gov (United States)

    Butler, Benjamin Miles; Papadimitriou, Stathys; Santoro, Anna; Kennedy, Hilary

    2016-06-01

    The sea ice microstructure is permeated by brine channels and pockets that contain concentrated seawater-derived brine. Cooling the sea ice results in further formation of pure ice within these pockets as thermal equilibrium is attained, resulting in a smaller volume of increasingly concentrated residual brine. The coupled changes in temperature and ionic composition result in supersaturation of the brine with respect to mirabilite (Na2SO4·10H2O) at temperatures below -6.38 °C, which consequently precipitates within the sea ice microstructure. Here, mirabilite solubility in natural and synthetic seawater derived brines, representative of sea ice at thermal equilibrium, has been measured in laboratory experiments between 0.2 and -20.6 °C, and hence we present a detailed examination of mirabilite dynamics within the sea ice system. Below -6.38 °C mirabilite displays particularly large changes in solubility as the temperature decreases, and by -20.6 °C its precipitation results in 12.90% and 91.97% reductions in the total dissolved Na+ and SO42- concentrations respectively, compared to that of conservative seawater concentration. Such large non-conservative changes in brine composition could potentially impact upon the measurement of sea ice brine salinity and pH, whilst the altered osmotic conditions may create additional challenges for the sympagic organisms that inhabit the sea ice system. At temperatures above -6.38 °C, mirabilite again displays large changes in solubility that likely aid in impeding its identification in field samples of sea ice. Our solubility measurements display excellent agreement with that of the FREZCHEM model, which was therefore used to supplement our measurements to colder temperatures. Measured and modelled solubility data were incorporated into a 1D model for the growth of first-year Arctic sea ice. Model results ultimately suggest that mirabilite has a near ubiquitous presence in much of the sea ice on Earth, and illustrate the

  9. Influence of sea ice on Arctic precipitation.

    Science.gov (United States)

    Kopec, Ben G; Feng, Xiahong; Michel, Fred A; Posmentier, Eric S

    2016-01-05

    Global climate is influenced by the Arctic hydrologic cycle, which is, in part, regulated by sea ice through its control on evaporation and precipitation. However, the quantitative link between precipitation and sea ice extent is poorly constrained. Here we present observational evidence for the response of precipitation to sea ice reduction and assess the sensitivity of the response. Changes in the proportion of moisture sourced from the Arctic with sea ice change in the Canadian Arctic and Greenland Sea regions over the past two decades are inferred from annually averaged deuterium excess (d-excess) measurements from six sites. Other influences on the Arctic hydrologic cycle, such as the strength of meridional transport, are assessed using the North Atlantic Oscillation index. We find that the independent, direct effect of sea ice on the increase of the percentage of Arctic sourced moisture (or Arctic moisture proportion, AMP) is 18.2 ± 4.6% and 10.8 ± 3.6%/100,000 km(2) sea ice lost for each region, respectively, corresponding to increases of 10.9 ± 2.8% and 2.7 ± 1.1%/1 °C of warming in the vapor source regions. The moisture source changes likely result in increases of precipitation and changes in energy balance, creating significant uncertainty for climate predictions.

  10. Halocarbons associated with Arctic sea ice

    OpenAIRE

    Atkinson, Helen M.; Hughes, Claire; Shaw, Marvin J.; Roscoe, Howard K.; Carpenter, Lucy J.; Liss, Peter S.

    2014-01-01

    Short-lived halocarbons were measured in Arctic sea-ice brine, seawater and air above the Greenland and Norwegian seas (∼81°N, 2 to 5°E) in mid-summer, from a melting ice floe at the edge of the ice pack. In the ice floe, concentrations of C2H5I, 2-C3H7I and CH2Br2 showed significant enhancement in the sea ice brine, of average factors of 1.7, 1.4 and 2.5 times respectively, compared to the water underneath and after normalising to brine volume. Concentrations of mono-iodocarbons in air are t...

  11. Arctic and Southern Ocean Sea Ice Concentrations

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Monthly sea ice concentration for Arctic (1901 to 1995) and Southern oceans (1973 to 1990) were digitized on a standard 1-degree grid (cylindrical projection) to...

  12. SAR-based Wind Resource Statistics in the Baltic Sea

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay; Badger, Merete; Pena Diaz, Alfredo;

    2011-01-01

    Ocean winds in the Baltic Sea are expected to power many wind farms in the coming years. This study examines satellite Synthetic Aperture Radar (SAR) images from Envisat ASAR for mapping wind resources with high spatial resolution. Around 900 collocated pairs of wind speed from SAR wind maps...... deviation of 20.11° and R2 of 0.950. The scale and shape parameters, A and k, respectively, from the Weibull probability density function are compared at only one available mast and the results deviate ~2% for A but ~16% for k. Maps of A and k, and wind power density based on more than 1000 satellite images...

  13. Seasonal comparisons of sea ice concentration estimates derived from SSM/I, OKEAN, and RADARSAT data

    Science.gov (United States)

    Belchansky, G.I.; Douglas, D.C.

    2002-01-01

    The Special Sensor Microwave Imager (SSM/I) microwave satellite radiometer and its predecessor SMMR are primary sources of information for global sea ice and climate studies. However, comparisons of SSM/I, Landsat, AVHRR, and ERS-1 synthetic aperture radar (SAR) have shown substantial seasonal and regional differences in their estimates of sea ice concentration. To evaluate these differences, we compared SSM/I estimates of sea ice coverage derived with the NASA Team and Bootstrap algorithms to estimates made using RADARSAT, and OKEAN-01 satellite sensor data. The study area included the Barents Sea, Kara Sea, Laptev Sea, and adjacent parts of the Arctic Ocean, during October 1995 through October 1999. Ice concentration estimates from spatially and temporally near-coincident imagery were calculated using independent algorithms for each sensor type. The OKEAN algorithm implemented the satellite's two-channel active (radar) and passive microwave data in a linear mixture model based on the measured values of brightness temperature and radar backscatter. The RADARSAT algorithm utilized a segmentation approach of the measured radar backscatter, and the SSM/I ice concentrations were derived at National Snow and Ice Data Center (NSIDC) using the NASA Team and Bootstrap algorithms. Seasonal and monthly differences between SSM/I, OKEAN, and RADARSAT ice concentrations were calculated and compared. Overall, total sea ice concentration estimates derived independently from near-coincident RADARSAT, OKEAN-01, and SSM/I satellite imagery demonstrated mean differences of less than 5.5% (S.D. Elsevier Science Inc. All rights reserved.

  14. Floating ice-algal aggregates below melting arctic sea ice.

    Science.gov (United States)

    Assmy, Philipp; Ehn, Jens K; Fernández-Méndez, Mar; Hop, Haakon; Katlein, Christian; Sundfjord, Arild; Bluhm, Katrin; Daase, Malin; Engel, Anja; Fransson, Agneta; Granskog, Mats A; Hudson, Stephen R; Kristiansen, Svein; Nicolaus, Marcel; Peeken, Ilka; Renner, Angelika H H; Spreen, Gunnar; Tatarek, Agnieszka; Wiktor, Jozef

    2013-01-01

    During two consecutive cruises to the Eastern Central Arctic in late summer 2012, we observed floating algal aggregates in the melt-water layer below and between melting ice floes of first-year pack ice. The macroscopic (1-15 cm in diameter) aggregates had a mucous consistency and were dominated by typical ice-associated pennate diatoms embedded within the mucous matrix. Aggregates maintained buoyancy and accumulated just above a strong pycnocline that separated meltwater and seawater layers. We were able, for the first time, to obtain quantitative abundance and biomass estimates of these aggregates. Although their biomass and production on a square metre basis was small compared to ice-algal blooms, the floating ice-algal aggregates supported high levels of biological activity on the scale of the individual aggregate. In addition they constituted a food source for the ice-associated fauna as revealed by pigments indicative of zooplankton grazing, high abundance of naked ciliates, and ice amphipods associated with them. During the Arctic melt season, these floating aggregates likely play an important ecological role in an otherwise impoverished near-surface sea ice environment. Our findings provide important observations and measurements of a unique aggregate-based habitat during the 2012 record sea ice minimum year.

  15. Autonomous Sea-Ice Thickness Survey

    Science.gov (United States)

    2016-06-01

    measurements , assesses the merits of au- tonomous surveys relative to manual ones, and describes potential future applications. DISCLAIMER: The contents...estimated that, compared with borehole measurements , their errors averaged 0.05 m for 2 m of level sea ice. They attributed most of the...average errors of 6% or 0.12 m for 2 m of ice, although their measurements included deformed and ridged ice that probably increased average errors

  16. Radar Backscatter Study of Sea Ice.

    Science.gov (United States)

    1980-02-01

    in controlling the "state" of the ice ( temperatura and salinity) are shown in Figure 4.3-79. The salinity profile is a typical irregular c-shaped...the University of Kansas to provide well- controlled systematic studies to relate radar backscatter return to sea ice and to pin down some of the...34..,. : . - " ... ,. -.. .... .. .. ... ,,, ... ... _ ., ’.. . . , 72. Profiles of the parameters most important in controlling the "state" of the ice (temperature and salinity

  17. 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.

  18. 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.

  19. How reversible is sea ice loss?

    Directory of Open Access Journals (Sweden)

    J. K. Ridley

    2011-09-01

    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 back 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 has little hysteresis while the Antarctic sea ice shows significant hysteresis – its rate of change slower, with falling temperatures, than its rate of change with rising temperatures. However, we show that the driver of the hysteresis is the hemispherical differences in temperature change between transient and stabilisation periods. We find no irreversible behaviour in the sea ice cover.

  20. 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...

  1. SAR ice classification based on GLCM and wavelet feature%基于 GLCM 和小波特征的 SAR 海冰分类

    Institute of Scientific and Technical Information of China (English)

    孔毅; 陈曦; 艾未华; 赵现斌; 刘文俊

    2015-01-01

    A method of sea ice classification was adopted to reduce the influence of speckle moise on synthetic aper-ture radar(SAR) sea ice classification results,based on an overall consideration of grey-level co-occurrence matrix (GLCM) feature and wavelet feature. Texture analysis was carried out with the spacebome imaging Radar-C data. Finally the result shows this method distracts wavelet character based on retaining the edge detail information,re-duces the noise influence and solves the problem of inaccurate classification caused by noise when using GLCM a-lone.%为了减少相干斑噪声对合成孔径雷达(SAR)海冰分类结果的影响,综合灰度共生矩阵(GLCM)和小波特征,提出了融合空间域和频域的纹理特征的 SAR 海冰分类方法,利用航天飞机成像雷达3号(SIR-C)探测数据,开展了 SAR 海冰分类研究。结果表明,该分类方法能在保留图像边缘细节信息的基础上,提取小波特征,减少噪声影响,解决了灰度共生矩阵方法无法克服的斑点状分类不准确问题,提高了分类精度。

  2. Arctic and Antarctic sea ice and climate

    Science.gov (United States)

    Barreira, S.

    2014-12-01

    Principal Components Analysis in T-Mode Varimax rotated was performed on Antarctic and Arctic monthly sea ice concentration anomalies (SICA) fields for the period 1979-2014, in order to investigate which are the main spatial characteristics of sea ice and its relationship with atmospheric circulation. This analysis provides 5 patterns of sea ice for inter-spring period and 3 patterns for summer-autumn for Antarctica (69,2% of the total variance) and 3 different patterns for summer-autumn and 3 for winter-spring season for the Arctic Ocean (67,8% of the total variance).Each of these patterns has a positive and negative phase. We used the Monthly Polar Gridded Sea Ice Concentrations database derived from satellite information generated by NASA Team algorithm. To understand the links between the SICA and climate trends, we extracted the mean pressure and, temperature field patterns for the months with high loadings (positive or negative) of the sea ice patterns that gave distinct atmospheric structures associated with each one. For Antarctica, the first SICA spatial winter-spring pattern in positive phase shows a negative SICA centre over the Drake Passage and north region of Bellingshausen and Weddell Seas together with another negative SICA centre over the East Indian Ocean. Strong positive centres over the rest of the Atlantic and Indian Oceans basins and the Amundsen Sea are also presented. A strong negative pressure anomaly covers most of the Antarctic Continent centered over the Bellingshausen Sea accompanied by three positive pressure anomalies in middle-latitudes. During recent years, the Arctic showed persistent associations of sea-ice and climate patterns principally during summer. Our strongest summer-autumn pattern in negative phase showed a marked reduction on SICA over western Arctic, primarily linked to an overall increase in Arctic atmospheric temperature most pronounced over the Beaufort, Chukchi and East Siberian Seas, and a positive anomaly of

  3. Grease ice in basin-scale sea-ice ocean models

    OpenAIRE

    Lars H. Smedsrud; Martin, Torge

    2015-01-01

    The first stage of sea-ice formation is often grease ice, a mixture of sea water and frazil ice crystals. Over time, grease ice typically congeals first to pancake ice floes and then to a solid sea-ice cover. Grease ice is commonly not explicitly simulated in basin-scale sea-ice ocean models, though it affects oceanic heat loss and ice growth and is expected to play a greater role in a more seasonally icecovered Arctic Ocean. We present an approach to simulate the grease-ice layer with, as ba...

  4. Spatial-temporal characters of Antarctic sea ice variation

    Institute of Scientific and Technical Information of China (English)

    Ma Lijuan; Lu Longhua; Bian Lingen

    2004-01-01

    Using sea ice concentration dataset covering the period of 1968-2002 obtained from the Hadley Center of UK, this paper investigates characters of Antarctic sea ice variations .The finding demonstrates that the change of mean sea-ice extent is almost consistent with that of sea-ice area, so sea-ice extent can be chosen to go on this research. The maximum and the minimum of Antarctic sea ice appear in September and February respectively. The maximum and the maximal variation of sea ice appear in Weddell Sea and Ross Sea, while the minimum and the minimal variation of sea-ice appear in Antarctic Peninsula. In recent 35 years, as a whole, Antarctic sea ice decreased distinctly. Moreover, there are 5 subdivision characteristic regions considering their different variations. Hereinto, the sea-ice extent of Weddell Sea and Ross Sea regions extends and area increases, while the sea-ice extent of the other three regions contracts and area decreases. They are all of obvious 2-4 years and 5-7 years significant oscillation periods. It is of significance for further understanding the sea-ice-air interaction in Antarctica region and discussing the relationship between sea-ice variation and atmospheric circulation.

  5. Arctic sea ice thickness changes in terms of sea ice age

    Institute of Scientific and Technical Information of China (English)

    BI Haibo; FU Min; SUN Ke; LIU Yilin; XU Xiuli; HUANG Haijun

    2016-01-01

    In this study, changes in Arctic sea ice thickness for each ice age category were examined based on satellite observations and modelled results. Interannual changes obtained from Ice, Cloud, and Land Elevation Satellite (ICESat)-based results show a thickness reduction over perennial sea ice (ice that survives at least one melt season with an age of no less than 2 year) up to approximately 0.5–1.0 m and 0.6–0.8 m (depending on ice age) during the investigated winter and autumn ICESat periods, respectively. Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS)-based results provide a view of a continued thickness reduction over the past four decades. Compared to 1980s, there is a clear thickness drop of roughly 0.50 m in 2010s for perennial ice. This overall decrease in sea ice thickness can be in part attributed to the amplified warming climate in north latitudes. Besides, we figure out that strongly anomalous southerly summer surface winds may play an important role in prompting the thickness decline in perennial ice zone through transporting heat deposited in open water (primarily via albedo feedback) in Eurasian sector deep into a broader sea ice regime in central Arctic Ocean. This heat source is responsible for enhanced ice bottom melting, leading to further reduction in ice thickness.

  6. Structural Uncertainty in Antarctic sea ice simulations

    Science.gov (United States)

    Schneider, D. P.

    2016-12-01

    The inability of the vast majority of historical climate model simulations to reproduce the observed increase in Antarctic sea ice has motivated many studies about the quality of the observational record, the role of natural variability versus forced changes, and the possibility of missing or inadequate forcings in the models (such as freshwater discharge from thinning ice shelves or an inadequate magnitude of stratospheric ozone depletion). In this presentation I will highlight another source of uncertainty that has received comparatively little attention: Structural uncertainty, that is, the systematic uncertainty in simulated sea ice trends that arises from model physics and mean-state biases. Using two large ensembles of experiments from the Community Earth System Model (CESM), I will show that the model is predisposed towards producing negative Antarctic sea ice trends during 1979-present, and that this outcome is not simply because the model's decadal variability is out-of-synch with that in nature. In the "Tropical Pacific Pacemaker" ensemble, in which observed tropical Pacific SST anomalies are prescribed, the model produces very realistic atmospheric circulation trends over the Southern Ocean, yet the sea ice trend is negative in every ensemble member. However, if the ensemble-mean trend (commonly interpreted as the forced response) is removed, some ensemble members show a sea ice increase that is very similar to the observed. While this results does confirm the important role of natural variability, it also suggests a strong bias in the forced response. I will discuss the reasons for this systematic bias and explore possible remedies. This an important problem to solve because projections of 21st -Century changes in the Antarctic climate system (including ice sheet surface mass balance changes and related changes in the sea level budget) have a strong dependence on the mean state of and changes in the Antarctic sea ice cover. This problem is not unique to

  7. An Improved Cryosat-2 Sea Ice Freeboard Retrieval Algorithm Through the Use of Waveform Fitting

    Science.gov (United States)

    Kurtz, Nathan T.; Galin, N.; Studinger, M.

    2014-01-01

    We develop an empirical model capable of simulating the mean echo power cross product of CryoSat-2 SAR and SAR In mode waveforms over sea ice covered regions. The model simulations are used to show the importance of variations in the radar backscatter coefficient with incidence angle and surface roughness for the retrieval of surfaceelevation of both sea ice floes and leads. The numerical model is used to fit CryoSat-2 waveforms to enable retrieval of surface elevation through the use of look-up tables and a bounded trust region Newton least squares fitting approach. The use of a model to fit returns from sea ice regions offers advantages over currently used threshold retrackingmethods which are here shown to be sensitive to the combined effect of bandwidth limited range resolution and surface roughness variations. Laxon et al. (2013) have compared ice thickness results from CryoSat-2 and IceBridge, and found good agreement, however consistent assumptions about the snow depth and density of sea ice werenot used in the comparisons. To address this issue, we directly compare ice freeboard and thickness retrievals from the waveform fitting and threshold tracker methods of CryoSat-2 to Operation IceBridge data using a consistent set of parameterizations. For three IceBridge campaign periods from March 20112013, mean differences (CryoSat-2 IceBridge) of 0.144m and 1.351m are respectively found between the freeboard and thickness retrievals using a 50 sea ice floe threshold retracker, while mean differences of 0.019m and 0.182m are found when using the waveform fitting method. This suggests the waveform fitting technique is capable of better reconciling the seaice thickness data record from laser and radar altimetry data sets through the usage of consistent physical assumptions.

  8. Response of passive microwave sea ice concentration algorithms to thin ice

    DEFF Research Database (Denmark)

    Heygster, Georg; Huntemann, Marcus; Ivanova, Natalia;

    2014-01-01

    The influence of sea ice thickness brightness temperatures and ice concentrations retrieved from passive microwave observations is quantified, using horizontally homogeneous sea ice thickness retrievals from ESA's SMOS sensor observations at high incidence angles. Brightness temperatures are infl......The influence of sea ice thickness brightness temperatures and ice concentrations retrieved from passive microwave observations is quantified, using horizontally homogeneous sea ice thickness retrievals from ESA's SMOS sensor observations at high incidence angles. Brightness temperatures...

  9. Using Sea Ice Age as a Proxy for Sea Ice Thickness

    Science.gov (United States)

    Stroeve, J. C.; Tschudi, M. A.; Maslanik, J. A.

    2014-12-01

    Since the beginning of the modern satellite record starting in October 1978, the Arctic sea ice cover has been shrinking, with the largest changes observed at the end of the melt season in September. Through 2013, the September ice extent has declined at a rate of -14.0% dec-1, or -895,300 km2 dec-1. The seven lowest September extents in the satellite record have all occurred in the past seven years. This reduction in ice extent is accompanied by large reductions in winter ice thicknesses that are primarily explained by changes in the ocean's coverage of multiyear ice (MYI). Using the University of Colorado ice age product developed by J. Maslanik and C. Fowler, and currently produced by M. Tschudi we present recent changes in the distribution of ice age from the mid 1980s to present. The CU ice age product is based on (1) the use of ice motion to track areas of sea ice and thus estimate how long the ice survives within the Arctic, and (2) satellite imagery of sea ice concentration to determine when the ice disappears. Age is assigned on a yearly basis, with the age incremented by one year if the ice survives summer melt and stays within the Arctic domain. Age is counted from 1 to 10 years, with all ice older than 10 years assigned to the "10+" age category. The position of the ice is calculated on weekly time steps on NSIDC's 12.5-km EASE-grid. In the mid-1980s, MYI accounted for 70% of total winter ice extent, whereas by the end of 2012 it had dropped to less than 20%. This reflects not only a change in ice type, but also a general thinning of the ice pack, as older ice tends to be thicker ice. Thus, with older ice being replaced by thinner first-year ice, the ice pack is more susceptible to melting out than it was in 1980's. It has been suggested that ice age may be a useful proxy for long-term changes in ice thickness. To assess the relationship between ice age and thickness, and how this may be changing over time, we compare the ice age fields to several

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

    Directory of Open Access Journals (Sweden)

    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

  11. Tomographic SAR analysis of subsurface ice structure in Greenland: first results

    DEFF Research Database (Denmark)

    Banda, Francesco; Dall, Jørgen; Tebaldini, Stefano

    2013-01-01

    Due to the increased melting of ice sheets over the last decades, monitoring of ice dynamics and structure with remote sensing instruments is of extreme importance to achieve a deeper insight on related environmental issues. The study presented in this paper documents an attempt of mapping ice...... structure with P-band SAR tomography. First results from ESA IceSAR 2012 campaign carried out in south-west Greenland are presented. It is found that significant penetration in the upper layers of glacial subsurface can be achieved up to an extent of about 20–60 m, conditional on the different type...

  12. Arctic sea-ice cover and sea-ice cover anomalies over eastern Canadian waters

    Energy Technology Data Exchange (ETDEWEB)

    Agnew, T.

    1990-01-01

    Concerns about global climate warming have increased interest in climate monitoring and analysis of climate trends in Canada. Sea-ice cover is of interest for climate monitoring since it is very sensitive to changes in the climate controls over a region and is an integrator of temperature anomalies over periods of a week and longer. In addition, climate models suggest that polar regions will have the largest climate warming signal. The existence of long-term digital sea-ice databases makes analysis of sea ice as a climate change indicator possible. The northern hemisphere sea-ice concentration database for 1953 to 1988 was qualitatively evaluated for its representativeness over eastern Canadian Arctic waters. Despite inhomogeneity problems, the database identifies the average freezeup and breakup patterns in the Canadian Arctic islands, Baffin Bay/Davis Strait, and the Hudson Bay area, and can be used for sea-ice variability and anomaly studies. However, inhomogeneity problems put into question the use of the database for sea-ice trend analysis. Sea-ice anomalies for the 1982/83 El Nino winter are compared to atmospheric temperature and circulation anomalies over the Baffin Bay/Davis Strait area. Sea-ice anomaly charts for 1953-1988 are calculated and have been made available as an unpublished catalogue within the Canadian Climate Centre. 15 refs., 27 figs.

  13. Evaluation of second-order texture parameters for sea ice classification from radar images

    Science.gov (United States)

    Shokr, Mohammed E.

    1991-06-01

    With the advent of airborne and spaceborne synthetic aperture radar (SAR) systems, sea ice classification from SAR images has become an important research subject. Since gray tone alone has proven to be of limited capability in differentiating ice types, texture has naturally become an attractive avenue to explore. Accordingly, performance of texture quantification parameters as related to their ability to discriminate ice types has to be examined. SAR image appearance depends on radar parameters involved in the image construction procedures from the doppler history record. Therefore the feasibility of using universal texture/ice type relationships that hold for all combinations of radar parameters also has to be investigated. To that end, imagery data from three different SAR systems were used in this study. Five conventional texture parameters, derived from the gray level co-occurrence matrix (GLCM), were examined. Two of them were modified to ensure their invariant character under linear gray tone transformations. Results indicated that all parameters were highly correlated. The parameters did not, in general, vary with the computational variables used in generating co-occurrence matrices. Ice types can be identified uniquely by the mean value of any texture parameter. The relatively high variability of texture parameters, however, confuses ice discrimination, particularly of smoother ice types. Ice classification was conducted using a per-pixel maximum likelihood supervised scheme. When texture was combined with gray tone, the overall average classification accuracy was improved. Texture was successful in improving the classification accuracy of multiyear ice but was less promising in discriminating first-season ice types. The best two GLCM texture parameters, according to the computed overall average classification accuracies, were the inverse difference moment and the entropy. A brief description of GLCM texture parameters as related to ice's physical

  14. Observation of melt onset on multiyear Arctic sea ice using the ERS 1 synthetic aperture radar

    Science.gov (United States)

    Winebrenner, D. P.; Nelson, E. D.; Colony, R.; West, R. D.

    1994-01-01

    We present nearly coincident observations of backscattering from the Earth Remote-Sensing Satellite (ERS) 1 synthetic aperture radar (SAR) and of near-surface temperature from six drifting buoys in the Beaufort Sea, showing that the onset of melting in snow on multiyear sea ice is clearly detectable in the SAR data. Melt onset is marked by a clean, steep decrease in the backscattering cross section of multiyear ice at 5.3 GHz and VV polarization. We investigate the scattering physics responsible for the signature change and find that the cross section decrease is due solely to the appearance of liquid water in the snow cover overlying the ice. A thin layer of moist snow is sufficient to cause the observed decrease. We present a prototype algorithm to estimate the date of melt onset using the ERS 1 SAR and apply the algorithm first to the SAR data for which we have corresponding buoy temperatures. The melt onset dates estimated by the SAR algorithm agree with those obtained independently from the temperature data to within 4 days or less, with the exception of one case in which temperatures oscillated about 0 C for several weeks. Lastly, we apply the algorithm to the entire ERS 1 SAR data record acquired by the Alaska SAR Facility for the Beaufort Sea north of 73 deg N during the spring of 1992, to produce a map of the dates of melt onset over an area roughly 1000 km on a side. The progression of melt onset is primarily poleward but shows a weak meridional dependence at latitudes of approximately 76 deg-77 deg N. Melting begins in the southern part of the study region on June 13 and by June 20 has progressed to the northermost part of the region.

  15. Observation of melt onset on multiyear Arctic sea ice using the ERS 1 synthetic aperture radar

    Science.gov (United States)

    Winebrenner, D. P.; Nelson, E. D.; Colony, R.; West, R. D.

    1994-01-01

    We present nearly coincident observations of backscattering from the Earth Remote-Sensing Satellite (ERS) 1 synthetic aperture radar (SAR) and of near-surface temperature from six drifting buoys in the Beaufort Sea, showing that the onset of melting in snow on multiyear sea ice is clearly detectable in the SAR data. Melt onset is marked by a clean, steep decrease in the backscattering cross section of multiyear ice at 5.3 GHz and VV polarization. We investigate the scattering physics responsible for the signature change and find that the cross section decrease is due solely to the appearance of liquid water in the snow cover overlying the ice. A thin layer of moist snow is sufficient to cause the observed decrease. We present a prototype algorithm to estimate the date of melt onset using the ERS 1 SAR and apply the algorithm first to the SAR data for which we have corresponding buoy temperatures. The melt onset dates estimated by the SAR algorithm agree with those obtained independently from the temperature data to within 4 days or less, with the exception of one case in which temperatures oscillated about 0 C for several weeks. Lastly, we apply the algorithm to the entire ERS 1 SAR data record acquired by the Alaska SAR Facility for the Beaufort Sea north of 73 deg N during the spring of 1992, to produce a map of the dates of melt onset over an area roughly 1000 km on a side. The progression of melt onset is primarily poleward but shows a weak meridional dependence at latitudes of approximately 76 deg-77 deg N. Melting begins in the southern part of the study region on June 13 and by June 20 has progressed to the northermost part of the region.

  16. Ice sheet systems and sea level change.

    Science.gov (United States)

    Rignot, E. J.

    2015-12-01

    Modern views of ice sheets provided by satellites, airborne surveys, in situ data and paleoclimate records while transformative of glaciology have not fundamentally changed concerns about ice sheet stability and collapse that emerged in the 1970's. Motivated by the desire to learn more about ice sheets using new technologies, we stumbled on an unexplored field of science and witnessed surprising changes before realizing that most were coming too fast, soon and large. Ice sheets are integrant part of the Earth system; they interact vigorously with the atmosphere and the oceans, yet most of this interaction is not part of current global climate models. Since we have never witnessed the collapse of a marine ice sheet, observations and exploration remain critical sentinels. At present, these observations suggest that Antarctica and Greenland have been launched into a path of multi-meter sea level rise caused by rapid climate warming. While the current loss of ice sheet mass to the ocean remains a trickle, every mm of sea level change will take centuries of climate reversal to get back, several major marine-terminating sectors have been pushed out of equilibrium, and ice shelves are irremediably being lost. As glaciers retreat from their salty, warm, oceanic margins, they will melt away and retreat slower, but concerns remain about sea level change from vastly marine-based sectors: 2-m sea level equivalent in Greenland and 23-m in Antarctica. Significant changes affect 2/4 marine-based sectors in Greenland - Jakobshavn Isb. and the northeast stream - with Petermann Gl. not far behind. Major changes have affected the Amundsen Sea sector of West Antarctica since the 1980s. Smaller yet significant changes affect the marine-based Wilkes Land sector of East Antarctica, a reminder that not all marine-based ice is in West Antarctica. Major advances in reducing uncertainties in sea level projections will require massive, interdisciplinary efforts that are not currently in place

  17. Arctic Sea Ice : Trends, Stability and Variability

    Science.gov (United States)

    Moon, W.; Wettlaufer, J. S.

    2014-12-01

    A stochastic Arctic sea-ice model is derived and analysed in detail to interpret the recent decay and associated variability of Arctic sea-ice under changes in radiative forcing. The approach begins from a deterministic model of the heat flux balance through the air/sea/ice system, which uses observed monthly-averaged heat fluxesto drive a time evolution of sea-ice thickness. This model reproduces the observed seasonal cycle of the ice cover and it is to this that stochastic noise--representing high frequency variability--is introduced.The model takes the form of a single periodic non-autonomous stochastic ordinary differential equation. The value of such a model is that it provides a relatively simple framework to examine the role of noise in the basic nonlinear interactions at play as transitions in the state of the ice cover (e.g., from perennial to seasonal) are approached. Moreover, the stability and the noise conspire to underlie the inter annual variability and how that variability changes as one approaches the deterministic bifurcations in the system.

  18. Ice Velocity Estimation Using SAR Data in PANDA Section, East Antarctica

    Science.gov (United States)

    Deng, F.; Zhou, C.; Zhou, Y.

    2015-12-01

    Ice-flow velocity is a significant parameter in dynamic models of the Antarctic ice sheet, indicating how ice is transported from the interior to the ocean and how ice mass evolves. PANDA (Prydz Bay - Amery Ice shelf - Dome A) section is the key area of Chinese expedition in the Antarctic, and many scientific studies have been conducted here. In this research, SAR images including ERS-1/2, Envisat and ALOS were applied to estimate the ice velocity of PANDA Section using DInSAR and offset-tracking methods. Compared to MEaSUREs velocity (ice velocity map of the Antarctic released by National Snow and Ice Data Center) of 450 m resolution, our result with 200 m resolution achieved similar accuracy. Ice mass of PANDA section flows into the ocean mainly through Amery Ice Shelf and Polar Record Glacier. The ice velocity at the front edge of Amery Ice shelf is almost 1500 m/a, and the ice velocity of Polar Record Glacier can reach as high as 800 m/a. At most inner area of PANDA section, ice velocity is below 40 m/a. Due to the blocking of rocks and nunataks, ice flow feature in Grove Mountains area is quite complicated, which can help to demonstrate the meteorite concentration mechanism in this area.

  19. Single and Multipolarimetric P-Band SAR Tomography of Subsurface Ice Structure

    DEFF Research Database (Denmark)

    Banda, Francesco; Dall, Jørgen; Tebaldini, Stefano

    2016-01-01

    In this paper, first results concerning the characterization of the subsurface of ice sheets and glaciers through single and multipolarization synthetic aperture radar (SAR) tomography (TomoSAR) are illustrated. To this aim, the processing of data acquired in the framework of the European Space...... was motivated by the fact that cryospheric remote sensing is of fundamental importance in order to understand more in depth the morphology and the dynamic processes regulating ice sheets. The main objective of the tomographic experiment of the campaign herein discussed was indeed to assess the capability of P......-band SAR to retrieve any information about ice subsurface structure. Imaging has been achieved through TomoSAR techniques, applied to airborne multibaseline data acquired in the southwest of Greenland. Different imaging approaches are compared, and the main results achieved are presented: It is found...

  20. 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...

  1. Evaluation of the ESA Sea Ice CCI (SICCI) project sea ice concentration data set

    DEFF Research Database (Denmark)

    Kern, Stefan; Bell, Louisa; Ivanova, Natalia;

    around these two SIC values; consequently SIC can be negative or above 100%. In order to fully evaluate SICCI SIC this natural variability needs to be taken into account. In contrast to most other SIC retrieval algorithms the SICCI algorithm does not filter spurious sea ice over open water with a weather......During phase 1 of the European Space Agency’s (ESA) climate change initiative (CCI) sea ice project (SICCI project) a sea ice concentration (SIC) data product was produced by employing a hybrid SIC retrieval algorithm comprising the Bristol and the Comiso-Bootstrap algorithm in frequency mode. SIC...... filter because by doing so often substantial portions of the sea ice cover along the ice edge are discarded....

  2. Seasonal variations in active microwave signatures of sea ice in the Greenland Sea during 1992 and 1993

    DEFF Research Database (Denmark)

    Thomsen, Bjørn Bavnehøj; Skriver, Henning; Pedersen, Leif Toudal

    1995-01-01

    into the research of other statistical features of the sea ice than the mean value and also their seasonal variations. This paper investigates the backscatter coefficient and texture of different sea ice types and water by using calibrated precision images (PRI) acquired by the synthetic aperture radar (SAR......Derivations of the microwave signatures of sea ice have often been focused on the backscatter coefficient σ0. It is well known that σ0 is rather stable during winter and varies a lot during summer due to the complex mechanisms related to melting. However, less work has been carried out......) on board the ERS-1 satellite. Seasonal variations have been related to the meteorological conditions and the radar system parameters...

  3. Using Airborne SAR Interferometry to Measure the Elevation of a Greenland Ice Cap

    DEFF Research Database (Denmark)

    Dall, Jørgen; Keller, K.; Madsen, S.N.

    2000-01-01

    A digital elevation model (DEM) of an ice cap in Greenland has been generated from airborne SAR interferometry data, calibrated with a new algorithm, and compared with airborne laser altimetry profiles and carrier-phase differential GPS measurements of radar reflectors deployed on the ice cap...

  4. The EUMETSAT sea ice concentration climate data record

    Science.gov (United States)

    Tonboe, Rasmus T.; Eastwood, Steinar; Lavergne, Thomas; Sørensen, Atle M.; Rathmann, Nicholas; Dybkjær, Gorm; Toudal Pedersen, Leif; Høyer, Jacob L.; Kern, Stefan

    2016-09-01

    An Arctic and Antarctic sea ice area and extent dataset has been generated by EUMETSAT's Ocean and Sea Ice Satellite Application Facility (OSISAF) using the record of microwave radiometer data from NASA's Nimbus 7 Scanning Multichannel Microwave radiometer (SMMR) and the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) and Special Sensor Microwave Imager and Sounder (SSMIS) satellite sensors. The dataset covers the period from October 1978 to April 2015 and updates and further developments are planned for the next phase of the project. The methodology for computing the sea ice concentration uses (1) numerical weather prediction (NWP) data input to a radiative transfer model for reduction of the impact of weather conditions on the measured brightness temperatures; (2) dynamical algorithm tie points to mitigate trends in residual atmospheric, sea ice, and water emission characteristics and inter-sensor differences/biases; and (3) a hybrid sea ice concentration algorithm using the Bristol algorithm over ice and the Bootstrap algorithm in frequency mode over open water. A new sea ice concentration uncertainty algorithm has been developed to estimate the spatial and temporal variability in sea ice concentration retrieval accuracy. A comparison to US National Ice Center sea ice charts from the Arctic and the Antarctic shows that ice concentrations are higher in the ice charts than estimated from the radiometer data at intermediate sea ice concentrations between open water and 100 % ice. The sea ice concentration climate data record is available for download at www.osi-saf.org, including documentation.

  5. Analysis of the Arctic sea ice total deformation rates based on SAR remote sensing%基于合成孔径雷达遥感的北极海冰总形变率分析

    Institute of Scientific and Technical Information of China (English)

    谢涛; 方贺; 赵尚卓; 于文金; 王召民; 何宜军

    2015-01-01

    基于 RADARSAT 地球物理处理器系统(RGPS)的北极海冰运动散度、旋度和剪切产品,本文计算了北极海冰总形变率,给出了所有 RGPS 产品时空覆盖范围的总形变率空间分布和时间平均总形变率大于0.01 d-1的概率分布。结果表明:对整个 RGPS 数据库而言(时间跨度从1996年11月至2008年4月),平均总形变率为0.0204 d-1,总形变率大于0.01 d-1的数据样本为总样本的45.89%。总形变率高值主要分布在近岸海域,靠近北极点附近的总形变率相对较小。北极海冰总形变率随季节变化,夏季平均总形变率及总形变率大于0.01 d-1发生概率要比冬季大,其中,夏季总形变率大于0.01 d-1发生概率为59%,而冬季要比夏季低18%。其可能机制主要是,夏季北极地区温度升高,形成海冰融化-破碎-更易融化-更易破碎的放大效果,导致北极海冰总形变率变大。%Total sea ice deformation rates are produced based on RADARSAT Geophysical Processer System (RGPS)dataset (divergence,vorticity and shear)in this paper,as well as the probability distribution of samples whose value of total sea ice deformation rate are lager than 0.01/d in the Arctic Ocean.The results show that mean value of total deformation rates (TDR)of whole dataset (from November 1996 to April 2008)is 0.020 4/d. There are 45.89% samples whose value of TDR are lager than 0.01/d.TDR in coast area are larger than those near North Polar.There are statistically significant differences in the average TDR between summer and winter. Both average TDR and occurrence probabilities of samples whose value of TDR are lager than 0.01/d in summer are larger than those in winter.Where probability of occurrence in summer is 59% which has 18% more than that in winter.It may be lead by the amplify effect of sea ice melting-broken-easier melting-easier broken in summer, and than it makes the Arctic sea ice

  6. Influence of sea ice on ocean water vapor isotopes and Greenland ice core records

    Science.gov (United States)

    Klein, Eric S.; Welker, Jeffrey M.

    2016-12-01

    A warming climate results in sea ice loss and impacts to the Arctic water cycle. The water isotope parameter deuterium excess, a moisture source proxy, can serve as a tracer to help understand hydrological changes due to sea ice loss. However, unlocking the sea ice change signal of isotopes from ice cores requires understanding how sea ice changes impact deuterium excess, which is unknown. Here we present the first isotope data linking a gradient of sea ice extents to oceanic water vapor deuterium excess values. Initial loss of sea ice extent leads to lower deuterium excess moisture sources, and then values progressively increase with further ice loss. Our new process-based interpretation suggests that past rapid (1-3 years) Greenland ice core changes in deuterium excess during warming might not be the result of abrupt atmospheric circulation shifts, but rather gradual loss of sea ice extent at northern latitude moisture sources.

  7. Arctic Sea Ice Decline - Results from Winter 2015/16

    OpenAIRE

    Nicolaus, Marcel; Hendricks, Stefan; Ricker, Robert

    2016-01-01

    Sea ice physicists from the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI), are anticipating that the sea ice cover in the Arctic Ocean this summer may shrink to the record low of 2012. The scientists made this projection after evaluating current satellite data about the thickness of the ice cover. The data show that the arctic sea ice was already extraordinarily thin in the summer of 2015. Comparably little new ice formed during the past winter.

  8. Ice core reconstruction of sea ice change in the Amundsen-Ross Seas since 1702 A.D.

    Science.gov (United States)

    Thomas, Elizabeth R.; Abram, Nerilie J.

    2016-05-01

    Antarctic sea ice has been increasing in recent decades, but with strong regional differences in the expression of sea ice change. Declining sea ice in the Bellingshausen Sea since 1979 (the satellite era) has been linked to the observed warming on the Antarctic Peninsula, while the Ross Sea sector has seen a marked increase in sea ice during this period. Here we present a 308 year record of methansulphonic acid from coastal West Antarctica, representing sea ice conditions in the Amundsen-Ross Sea. We demonstrate that the recent increase in sea ice in this region is part of a longer trend, with an estimated ~1° northward expansion in winter sea ice extent (SIE) during the twentieth century and a total expansion of ~1.3° since 1702. The greatest reconstructed SIE occurred during the mid-1990s, with five of the past 30 years considered exceptional in the context of the past three centuries.

  9. The ASIBIA sea-ice facility: First results from the Atmosphere-Sea-Ice-Biogeochemistry in the Arctic chamber

    Science.gov (United States)

    France, James L.; Thomas, Max

    2016-04-01

    Working in the natural ocean-ice-atmosphere system is very difficult, as conducting fieldwork on sea-ice presents many challenges ice including costs, safety, experimental controls and access. The new ASIBIA (Atmosphere-Sea-Ice-Biogeochemistry in the Arctic) coupled Ocean-Sea-Ice-(Snow)-Atmosphere chamber facility at the University of East Anglia, UK, we are aiming to perform controlled first-year sea-ice investigations in areas such as sea-ice physics, physicochemical and biogeochemical processes in sea-ice and quantification of the bi-directional flux of gases in various states of first-year sea-ice conditions. The facility is a medium sized chamber with programmable temperatures from -55°C to +30°C, allowing a full range of first year sea-ice growing conditions in both the Arctic and Antarctic to be simulated. The water depth can be up to 1 m (including up to 25 cm of sea-ice) and an optional 1 m tall Teflon film atmosphere on top of the sea-ice, thus creating a closed and coupled ocean-sea-ice-atmosphere mesocosm. Ice growth in the tank is well suited for studying first-year sea-ice physical properties, with in-situ ice-profile measurements of temperature, salinity, conductivity, pressure and spectral light transmission. Underwater and above ice cameras are installed to record the physical development of the sea-ice. Here, we present the data from the first suites of experiments in the ASIBIA chamber focussing on sea-ice physics and give a brief description of the capabilities of the facility going forward. The ASIBIA chamber was funded as part of an ERC consolidator grant to the late Prof. Roland von Glasow and we hope this work and further development of the facility will act as a lasting legacy.

  10. Mechanism of seasonal Arctic sea ice evolution and Arctic amplification

    OpenAIRE

    Kim, Kwang-Yul; Hamlington, Benjamin D.; Na, Hanna; Kim, Jinju

    2016-01-01

    Sea ice loss is proposed as a primary reason for the Arctic amplification, although the physical mechanism of the Arctic amplification and its connection with sea ice melting is still in debate. In the present study, monthly ERA-Interim reanalysis data are analyzed via cyclostationary empirical orthogonal function analysis to understand the seasonal mechanism of sea ice loss in the Arctic Ocean and the Arctic amplification. While sea ice loss is widespread over much of the p...

  11. Iron in sea ice: Review and new insights

    Directory of Open Access Journals (Sweden)

    D. Lannuzel

    2016-10-01

    Full Text Available Abstract The discovery that melting sea ice can fertilize iron (Fe-depleted polar waters has recently fostered trace metal research efforts in sea ice. The aim of this review is to summarize and synthesize the current understanding of Fe biogeochemistry in sea ice. To do so, we compiled available data on particulate, dissolved, and total dissolvable Fe (PFe, DFe and TDFe, respectively from sea-ice studies from both polar regions and from sub-Arctic and northern Hemisphere temperate areas. Data analysis focused on a circum-Antarctic Fe dataset derived from 61 ice cores collected during 10 field expeditions carried out between 1997 and 2012 in the Southern Ocean. Our key findings are that 1 concentrations of all forms of Fe (PFe, DFe, TDFe are at least a magnitude larger in fast ice and pack ice than in typical Antarctic surface waters; 2 DFe, PFe and TDFe behave differently when plotted against sea-ice salinity, suggesting that their distributions in sea ice are driven by distinct, spatially and temporally decoupled processes; 3 DFe is actively extracted from seawater into growing sea ice; 4 fast ice generally has more Fe-bearing particles, a finding supported by the significant negative correlation observed between both PFe and TDFe concentrations in sea ice and water depth; 5 the Fe pool in sea ice is coupled to biota, as indicated by the positive correlations of PFe and TDFe with chlorophyll a and particulate organic carbon; and 6 the vast majority of DFe appears to be adsorbed onto something in sea ice. This review also addresses the role of sea ice as a reservoir of Fe and its role in seeding seasonally ice-covered waters. We discuss the pivotal role of organic ligands in controlling DFe concentrations in sea ice and highlight the uncertainties that remain regarding the mechanisms of Fe incorporation in sea ice.

  12. 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.

  13. Use of SAR imagery and other remotely-sensed data in deriving ice information during a severe ice event on the Grand Banks (Newfoundland)

    Science.gov (United States)

    Carsey, F. D.; Argus, S. D.

    1988-01-01

    Image data from synthetic aperture radar (SAR) are used to observe an ice compaction event off the East Coast of Newfoundland in spring, 1987. The information developed from sequential SAR observations is shown to do a remarkably effective job of describing the ice conditions; the difficult variable is the ice thickness which is found to be surprisingly large (2 to 4 times the thickness predictable from thermodynamic growth alone). It may be possible to model the ice thickness using SAR-derived ice motion.

  14. High resolution modelling of the decreasing Arctic sea ice

    DEFF Research Database (Denmark)

    Madsen, K. S.; Rasmussen, T. A. S.; Blüthgen, Jonas

    2012-01-01

    The Arctic sea ice cover has been rapidly decreasing and thinning over the last decade, with minimum ice extent in 2007 and almost as low extent in 2011. This study investigates two aspects of the decreasing ice cover; first the large scale thinning and changing dynamics of the polar sea ice......, and secondly oceanic oil drift in ice affected conditions. Both investigations are made with the coupled ocean - sea ice model HYCOM-CICE at 10 km resolution, which is also used operationally at DMI and allows detailed studies of sea ice build-up, drift and melt. To investigate the sea ice decrease of the last...... and changing dynamics and discuss how they relate to satellite observations. The relation to the upper ocean heat content is also investigated. The decreasing sea ice has opened up for increased ship traffic and oil exploration in the polar oceans. To avoid damage on the pristine Arctic ecosystem...

  15. High resolution modelling of the decreasing Arctic sea ice

    DEFF Research Database (Denmark)

    Madsen, K. S.; Rasmussen, T. A. S.; Blüthgen, Jonas

    2012-01-01

    , and secondly oceanic oil drift in ice affected conditions. Both investigations are made with the coupled ocean - sea ice model HYCOM-CICE at 10 km resolution, which is also used operationally at DMI and allows detailed studies of sea ice build-up, drift and melt. To investigate the sea ice decrease of the last......The Arctic sea ice cover has been rapidly decreasing and thinning over the last decade, with minimum ice extent in 2007 and almost as low extent in 2011. This study investigates two aspects of the decreasing ice cover; first the large scale thinning and changing dynamics of the polar sea ice...... decade, we have performed a reanalysis simulation of the years 1990-2011, forced with ERA Interim atmospheric data. Thus, the simulation includes both the period before the recent sea ice decrease and the full period of decrease up till today. We will present our model results of the thinning...

  16. Early Student Support to Investigate the Role of Sea Ice-Albedo Feedback in Sea Ice Predictions

    Science.gov (United States)

    2014-09-30

    all its versions employs the Los Alamos National Laboratory ( LANL ) sea ice model, known as CICE. The sea ice in CESM1 has been documented in a...their method so successful and yet a nonlocal relationship exists between sea ice meltponds and the location Report Documentation Page Form ApprovedOMB... LANL , who is the chief developer of CICE. Dr. Hunke is a partner with the sea ice prediction network and has a postdoc working with her to improve CICE

  17. Forecasting Future Sea Ice Conditions: A Lagrangian Approach

    Science.gov (United States)

    2014-09-30

    that survives the summer melt season in each of the Arctic peripheral seas. The Lagrangian Model is forced with weekly mean satellite-derived sea- ice ...GCM to drive the Lagrangian code and map the regions for the multi-year ice surviving the summer melt in each of the Arctic peripheral seas in todays...1995, Emery et al. 1997, Meier et al. 2000, Tschudi et al. 2010) 3- Assess whether the source region of sea ice melting in peripheral seas in the

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

    Directory of Open Access Journals (Sweden)

    A. A. Marks

    2013-03-01

    Full Text Available 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-year sea ice and "dry" and "wet" snow types that suggest black carbon is the dominating absorbing impurity. The albedo response of first year and multi-year sea ice to increasing black carbon, from 1–1024 ng g−1, in a top 5 cm layer of a 155 cm thick sea ice was calculated using the radiative transfer model: TUV-snow. Sea ice albedo is surprisingly unresponsive to black carbon additions up to 100 ng g−1 with a decrease in albedo to 98.7% of the original albedo value due to an addition of 8 ng g−1 of black carbon in first year sea ice compared to an albedo decrease to 99.6% for the same black carbon mass ratio increase in multi-year sea ice. The first year sea ice proved more responsive to black carbon additions than the multi-year ice. Comparison with previous modelling of black carbon in sea ice suggests a more scattering sea ice environment will be less responsive to black carbon additions. 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 were added onto the sea ice surface and the snow surface albedo calculated with the same increase in black carbon in the underlying sea ice. Just a 0.5 cm layer of snow greatly diminishes the effect of black carbon on surface albedo, and a 2–5 cm layer (less than half the e-folding depth of snow is enough to "mask" any change in surface albedo owing to additional black carbon in sea ice, but not thick enough to ignore the underlying sea ice.

  19. Recent sea-ice reduction and possible causes

    Science.gov (United States)

    Park, Doo-Sun R.

    2016-04-01

    Arctic sea-ice extent has been rapidly declining since the late 20th century. Given the accelerating rate of the sea-ice decline, an ice-free Arctic Ocean is expected to occur within this century. This rapid sea-ice melting is attributable to various Arctic environmental changes, such as increased downward infrared radiation (IR), sea-ice preconditioning, temperate ocean water inflow, and sea-ice export. However, their relative contributions are uncertain. Assessing the relative contributions is essential for improving our prediction of the future state of the Arctic sea ice. Most of the previous research had focused on summer sea ice, which is however sensitive to previous winter sea ice, suggesting that winter sea-ice processes are also important for understanding sea-ice variability and its trend. Here we show, for the Arctic winter of 1979-2011, that a positive trend of downward IR accounts for nearly half of the sea-ice concentration (SIC) decline. Furthermore, we show that the Arctic downward IR increase is driven by horizontal atmospheric water flux into the Arctic, and not by evaporation from the Arctic Ocean. The rest of the SIC decline likely comes from warm ocean.

  20. Iodine emissions from the sea ice of the Weddell Sea

    Directory of Open Access Journals (Sweden)

    H. M. Atkinson

    2012-05-01

    Full Text Available Iodine compounds were measured above, below and within the sea ice of the Weddell Sea during a cruise in 2009, to elucidate the mechanism of local enhancement and volatilisation of iodine. I2 mixing ratios of up to 12.4 pptv were measured 10 m above the sea ice, and up to 31 pptv was observed above surface snow on the nearby Brunt Ice Shelf – large amounts. Atmospheric IO of up to 7 pptv was measured from the ship, and the average sum of HOI and ICl was 1.9 pptv. These measurements confirm the Weddell Sea as an iodine hotspot. Average atmospheric concentrations of CH3I, C2H5I, CH2ICl, 2-C3H7I, CH2IBr and 1-C3H7I were each 0.2 pptv or less. On the Brunt Ice Shelf, enhanced concentrations of CH3I and C2H5I (up to 0.5 and 1 pptv, respectively were observed in firn air, with a diurnal profile that suggests the snow may be a source. In the sea ice brine, iodocarbons concentrations were over 10 times those of the sea water below. The sum of iodide + iodate was depleted in sea ice samples, suggesting some missing iodine chemistry. Flux calculations suggest I2 dominates the iodine atom flux to the atmosphere, but models cannot reconcile the observations and suggest either a missing iodine source or other deficiencies in our understanding of iodine chemistry. The observation of new particle formation, consistent with the model predictions, strongly suggests an iodine source. This combined study of iodine compounds is the first of its kind in this unique region of sea ice rich in biology and rich in iodine chemistry.

  1. Iodine emissions from the sea ice of the Weddell Sea

    Directory of Open Access Journals (Sweden)

    H. M. Atkinson

    2012-11-01

    Full Text Available Iodine compounds were measured above, below and within the sea ice of the Weddell Sea during a cruise in 2009, to make progress in elucidating the mechanism of local enhancement and volatilisation of iodine. I2 mixing ratios of up to 12.4 pptv were measured 10 m above the sea ice, and up to 31 pptv was observed above surface snow on the nearby Brunt Ice Shelf – large amounts. Atmospheric IO of up to 7 pptv was measured from the ship, and the average sum of HOI and ICl was 1.9 pptv. These measurements confirm the Weddell Sea as an iodine hotspot. Average atmospheric concentrations of CH3I, C2H5I, CH2ICl, 2-C3H7I, CH2IBr and 1-C3H7I were each 0.2 pptv or less. On the Brunt Ice Shelf, enhanced concentrations of CH3I and C2H5I (up to 0.5 and 1 pptv respectively were observed in firn air, with a diurnal profile that suggests the snow may be a source. In the sea ice brine, iodocarbons concentrations were over 10 times those of the sea water below. The sum of iodide + iodate was depleted in sea ice samples, suggesting some missing iodine chemistry. Flux calculations suggest I2 dominates the iodine atom flux to the atmosphere, but models cannot reconcile the observations and suggest either a missing iodine source or other deficiencies in our understanding of iodine chemistry. The observation of new particle formation, consistent with the model predictions, strongly suggests an iodine source. This combined study of iodine compounds is the first of its kind in this unique region of sea ice rich in biology and rich in iodine chemistry.

  2. Ku-Band radar penetration into Snow over Arctic Sea Ice

    DEFF Research Database (Denmark)

    Hendricks, Stefan; Stenseng, Lars; Helm, Veit

    Sea ice freeboard measurements are of great interest for basin-scale ice mass balance monitoring. Typically, laser- and radar-altimeters are used for freeboard retrieval in operational systems such as aircrafts and satellites. For laser beams it can be assumed that the dominant reflector......, 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...... observations are converted into freeboard profiles, taking the different footprints into account when comparing the two systems. Based on the probability distribution of laser and radar freeboard we discuss the specific characteristics of both systems and the apparent radar penetration over sea ice...

  3. Intercomparison of the Arctic sea ice cover in global ocean-sea ice reanalyses from the ORA-IP project

    Science.gov (United States)

    Chevallier, Matthieu; Smith, Gregory C.; Dupont, Frédéric; Lemieux, Jean-François; Forget, Gael; Fujii, Yosuke; Hernandez, Fabrice; Msadek, Rym; Peterson, K. Andrew; Storto, Andrea; Toyoda, Takahiro; Valdivieso, Maria; Vernieres, Guillaume; Zuo, Hao; Balmaseda, Magdalena; Chang, You-Soon; Ferry, Nicolas; Garric, Gilles; Haines, Keith; Keeley, Sarah; Kovach, Robin M.; Kuragano, Tsurane; Masina, Simona; Tang, Yongming; Tsujino, Hiroyuki; Wang, Xiaochun

    2017-08-01

    Ocean-sea ice reanalyses are crucial for assessing the variability and recent trends in the Arctic sea ice cover. This is especially true for sea ice volume, as long-term and large scale sea ice thickness observations are inexistent. Results from the Ocean ReAnalyses Intercomparison Project (ORA-IP) are presented, with a focus on Arctic sea ice fields reconstructed by state-of-the-art global ocean reanalyses. Differences between the various reanalyses are explored in terms of the effects of data assimilation, model physics and atmospheric forcing on properties of the sea ice cover, including concentration, thickness, velocity and snow. Amongst the 14 reanalyses studied here, 9 assimilate sea ice concentration, and none assimilate sea ice thickness data. The comparison reveals an overall agreement in the reconstructed concentration fields, mainly because of the constraints in surface temperature imposed by direct assimilation of ocean observations, prescribed or assimilated atmospheric forcing and assimilation of sea ice concentration. However, some spread still exists amongst the reanalyses, due to a variety of factors. In particular, a large spread in sea ice thickness is found within the ensemble of reanalyses, partially caused by the biases inherited from their sea ice model components. Biases are also affected by the assimilation of sea ice concentration and the treatment of sea ice thickness in the data assimilation process. An important outcome of this study is that the spatial distribution of ice volume varies widely between products, with no reanalysis standing out as clearly superior as compared to altimetry estimates. The ice thickness from systems without assimilation of sea ice concentration is not worse than that from systems constrained with sea ice observations. An evaluation of the sea ice velocity fields reveals that ice drifts too fast in most systems. As an ensemble, the ORA-IP reanalyses capture trends in Arctic sea ice area and extent

  4. Some Results from SAR and Optical Sensor Monitoring of China Seas

    Science.gov (United States)

    Yang, Jingsong; Lou, Xiulin; Chen, Peng; Wang, Juan; Ren, Lin; Chang, Junfang; Pan, Yufang

    2013-01-01

    As part of the final results of Dragon 2 Project Id. 5316 “Demonstrating SAR and optical sensor monitoring of Chinese Seas”, some results from SAR and optical sensor monitoring of China Seas including sea surface winds, ocean surface waves, typhoon and typhoon waves, ocean internal waves, red tides, and ships are given in this paper.

  5. Ocean circulation: its effects on seasonal sea-ice simulations.

    Science.gov (United States)

    Hibler, W D; Bryan, K

    1984-05-04

    A diagnostic ice-ocean model of the Arctic, Greenland, and Norwegian seas is constructed and used to examine the role of ocean circulation in seasonal sea-ice simulations. The model includes lateral ice motion and three-dimensional ocean circulation. The ocean portion of the model is weakly forced by observed temperature and salinity data. Simulation results show that including modeled ocean circulation in seasonal sea-ice simulations substantially improves the predicted ice drift and ice margin location. Simulations that do not include lateral ocean movment predict a much less realistic ice edge.

  6. Dynamic preconditioning of the September sea-ice extent minimum

    Science.gov (United States)

    Williams, James; Tremblay, Bruno; Newton, Robert; Allard, Richard

    2016-04-01

    There has been an increased interest in seasonal forecasting of the sea-ice extent in recent years, in particular the minimum sea-ice extent. We propose a dynamical mechanism, based on winter preconditioning through first year ice formation, that explains a significant fraction of the variance in the anomaly of the September sea-ice extent from the long-term linear trend. To this end, we use a Lagrangian trajectory model to backtrack the September sea-ice edge to any time during the previous winter and quantify the amount of sea-ice divergence along the Eurasian and Alaskan coastlines as well as the Fram Strait sea-ice export. We find that coastal divergence that occurs later in the winter (March, April and May) is highly correlated with the following September sea-ice extent minimum (r = -0.73). This is because the newly formed first year ice will melt earlier allowing for other feedbacks (e.g. ice albedo feedback) to start amplifying the signal early in the melt season when the solar input is large. We find that the winter mean Fram Strait sea-ice export anomaly is also correlated with the minimum sea-ice extent the following summer. Next we backtrack a synthetic ice edge initialized at the beginning of the melt season (June 1st) in order to develop hindcast models of the September sea-ice extent that do not rely on a-priori knowledge of the minimum sea-ice extent. We find that using a multi-variate regression model of the September sea-ice extent anomaly based on coastal divergence and Fram Strait ice export as predictors reduces the error by 41%. A hindcast model based on the mean DJFMA Arctic Oscillation index alone reduces the error by 24%.

  7. Wave-Ice and Air-Ice-Ocean Interaction During the Chukchi Sea Ice Edge Advance

    Science.gov (United States)

    2015-09-30

    Ocean Heat: In the new Arctic summer ice regime, with extended open water periods in areas previously covered with sea ice, ocean heat, received...additional buoy with an 80m temperature chain for monitoring the upper ocean evolution has been built at WHOI to replace the loss of one of the UpTempo...addition was made to the Sea State field program through separate funding to Luc Rainville of APL, who will provide an underway temperature and salinity

  8. Recent wind driven high sea ice export in the Fram Strait contributes to Arctic sea ice decline

    Directory of Open Access Journals (Sweden)

    L. H. Smedsrud

    2011-05-01

    Full Text Available Arctic sea ice area decrease has been visible for two decades, and continues at a steady rate. Apart from melting, the southward drift through Fram Strait is the main loss. We present high resolution sea ice drift across 79° N from 2004 to 2010. The ice drift is based on radar satellite data and correspond well with variability in local geostrophic wind. The underlying current contributes with a constant southward speed close to 5 cm s−1, and drives about 33 % of the ice export. We use geostrophic winds derived from reanalysis data to calculate the Fram Strait ice area export back to 1957, finding that the sea ice area export recently is about 25 % larger than during the 1960's. The increase in ice export occurred mostly during winter and is directly connected to higher southward ice drift velocities, due to stronger geostrophic winds. The increase in ice drift is large enough to counteract a decrease in ice concentration of the exported sea ice. Using storm tracking we link changes in geostrophic winds to more intense Nordic Sea low pressure systems. Annual sea ice export likely has a significant influence on the summer sea ice variability and we find low values in the 60's, the late 80's and 90's, and particularly high values during 2005–2008. The study highlight the possible role of variability in ice export as an explanatory factor for understanding the dramatic loss of Arctic sea ice the last decades.

  9. Thermal Diffusivity Identification of Distributed Parameter Systems to Sea Ice

    Directory of Open Access Journals (Sweden)

    Liqiong Shi

    2013-01-01

    Full Text Available A method of optimal control is presented as a numerical tool for solving the sea ice heat transfer problem governed by a parabolic partial differential equation. Taken the deviation between the calculated ice temperature and the measurements as the performance criterion, an optimal control model of distributed parameter systems with specific constraints of thermal properties of sea ice was proposed to determine the thermal diffusivity of sea ice. Based on sea ice physical processes, the parameterization of the thermal diffusivity was derived through field data. The simulation results illustrated that the identified parameterization of the thermal diffusivity is reasonably effective in sea ice thermodynamics. The direct relation between the thermal diffusivity of sea ice and ice porosity is physically significant and can considerably reduce the computational errors. The successful application of this method also explained that the optimal control model of distributed parameter systems in conjunction with the engineering background has great potential in dealing with practical problems.

  10. Role of sea ice in air-sea exchange and its relation to sea fog

    Institute of Scientific and Technical Information of China (English)

    解思梅; 包澄澜; 姜德中; 邹斌

    2001-01-01

    Synchronous or quasi-synchronous stereoscopic sea-ice-air comprehensive observation was conducted during the First China Arctic Expedition in summer of 1999. Based on these data, the role of sea ice in sea-air exchange was studied. The study shows that the kinds, distribution and thickness of sea ice and their variation significantly influence the air-sea heat exchange. In floating ice area, the heat momentum transferred from ocean to atmosphere is in form of latent heat; latent heat flux is closely related to floating ice concentration; if floating ice is less, the heat flux would be larger. Latent heat flux is about 21 23.6 W*m-2, which is greater than sensible heat flux. On ice field or giant floating ice, heat momentum transferred from atmosphere to sea ice or snow surface is in form of sensible heat. In the floating ice area or polynya, sea-air exchange is the most active, and also the most sensible for climate. Also this area is the most important condition for the creation of Arctic vapor fog. The heat exchange of a large-scale vapor fog process of about 500000 km2 on Aug. 21 22,1999 was calculated; the heat momentum transferred from ocean to air was about 14.8×109 kW. There are various kinds of sea fog, radiation fog, vapor fog and advection fog, forming in the Arctic Ocean in summer. One important cause is the existence of sea ice and its resultant complexity of both underlying surface and sea-air exchange.

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

    Directory of Open Access Journals (Sweden)

    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.

  12. A network model for electrical transport in sea ice

    Energy Technology Data Exchange (ETDEWEB)

    Zhu, J., E-mail: zhu@math.utah.ed [University of Utah, Department of Mathematics, 155 S 1400 E RM 233, Salt Lake City, UT 84112-0090 (United States); Golden, K.M., E-mail: golden@math.utah.ed [University of Utah, Department of Mathematics, 155 S 1400 E RM 233, Salt Lake City, UT 84112-0090 (United States); Gully, A., E-mail: gully@math.utah.ed [University of Utah, Department of Mathematics, 155 S 1400 E RM 233, Salt Lake City, UT 84112-0090 (United States); Sampson, C., E-mail: christian.sampson@gmail.co [University of Utah, Department of Mathematics, 155 S 1400 E RM 233, Salt Lake City, UT 84112-0090 (United States)

    2010-07-15

    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.

  13. 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.

  14. Mechanical sea-ice strength parameterized as a function of ice temperature

    Science.gov (United States)

    Hata, Yukie; Tremblay, Bruno

    2016-04-01

    Mechanical sea-ice strength is key for a better simulation of the timing of landlock ice onset and break-up in the Canadian Arctic Archipelago (CAA). We estimate the mechanical strength of sea ice in the CAA by analyzing the position record measured by the several buoys deployed in the CAA between 2008 and 2013, and wind data from the Canadian Meteorological Centre's Global Deterministic Prediction System (CMC_GDPS) REforecasts (CGRF). First, we calculate the total force acting on the ice using the wind data. Next, we estimate upper (lower) bounds on the sea-ice strength by identifying cases when the sea ice deforms (does not deform) under the action of a given total force. Results from this analysis show that the ice strength of landlock sea ice in the CAA is approximately 40 kN/m on the landfast ice onset (in ice growth season). Additionally, it becomes approximately 10 kN/m on the landfast ice break-up (in melting season). The ice strength decreases with ice temperature increase, which is in accord with results from Johnston [2006]. We also include this new parametrization of sea-ice strength as a function of ice temperature in a coupled slab ocean sea ice model. The results from the model with and without the new parametrization are compared with the buoy data from the International Arctic Buoy Program (IABP).

  15. Increased CO2 uptake due to sea ice growth and decay in the Nordic Seas

    DEFF Research Database (Denmark)

    Rysgaard, Søren; Bendtsen, Jørgen; Petersen, L.T.

    2009-01-01

    uptake in the Nordic Seas is currently unknown. We present evidence from 50 localities in the Arctic Ocean that dissolved inorganic carbon is rejected together with brine from growing sea ice and that sea ice melting during summer is rich in carbonates. Model calculations show that melting of sea ice......The uptake rates of atmospheric CO2 in the Nordic Seas are among the highest in the world's oceans. This has been ascribed mainly to a strong biological drawdown, but chemical processes within the sea ice itself have also been suggested to play a role. The importance of sea ice for the carbon...

  16. Simulation of the satellite radar altimeter sea ice thickness retrieval uncertainty

    Directory of Open Access Journals (Sweden)

    R. T. Tonboe

    2009-07-01

    Full Text Available Although it is well known that radar waves penetrate into snow and sea ice, the exact mechanisms for radar-altimeter scattering and its link to the depth of the effective scattering surface from sea ice are still unknown. Previously proposed mechanisms linked the snow ice interface, i.e. the dominating scattering horizon, directly with the depth of the effective scattering surface. However, simulations using a multilayer radar scattering model show that the effective scattering surface is affected by snow-cover and ice properties. With the coming Cryosat-2 (planned launch 2009 satellite radar altimeter it is proposed that sea ice thickness can be derived by measuring its freeboard. In this study we evaluate the radar altimeter sea ice thickness retrieval uncertainty in terms of floe buoyancy, radar penetration and ice type distribution using both a scattering model and ''Archimedes' principle''. The effect of the snow cover on the floe buoyancy and the radar penetration and on the ice cover spatial and temporal variability is assessed from field campaign measurements in the Arctic and Antarctic. In addition to these well known uncertainties we use high resolution RADARSAT SAR data to simulate errors due to the variability of the effective scattering surface as a result of the sub-footprint spatial backscatter and elevation distribution sometimes called preferential sampling. In particular in areas where ridges represent a significant part of the ice volume (e.g. the Lincoln Sea the simulated altimeter thickness estimate is lower than the real average footprint thickness. This means that the errors are large, yet manageable if the relevant quantities are known a priori. A discussion of the radar altimeter ice thickness retrieval uncertainties concludes the paper.

  17. Simulation of the satellite radar altimeter sea ice thickness retrieval uncertainty

    Science.gov (United States)

    Tonboe, R. T.; Pedersen, L. T.; Haas, C.

    2009-07-01

    Although it is well known that radar waves penetrate into snow and sea ice, the exact mechanisms for radar-altimeter scattering and its link to the depth of the effective scattering surface from sea ice are still unknown. Previously proposed mechanisms linked the snow ice interface, i.e. the dominating scattering horizon, directly with the depth of the effective scattering surface. However, simulations using a multilayer radar scattering model show that the effective scattering surface is affected by snow-cover and ice properties. With the coming Cryosat-2 (planned launch 2009) satellite radar altimeter it is proposed that sea ice thickness can be derived by measuring its freeboard. In this study we evaluate the radar altimeter sea ice thickness retrieval uncertainty in terms of floe buoyancy, radar penetration and ice type distribution using both a scattering model and ''Archimedes' principle''. The effect of the snow cover on the floe buoyancy and the radar penetration and on the ice cover spatial and temporal variability is assessed from field campaign measurements in the Arctic and Antarctic. In addition to these well known uncertainties we use high resolution RADARSAT SAR data to simulate errors due to the variability of the effective scattering surface as a result of the sub-footprint spatial backscatter and elevation distribution sometimes called preferential sampling. In particular in areas where ridges represent a significant part of the ice volume (e.g. the Lincoln Sea) the simulated altimeter thickness estimate is lower than the real average footprint thickness. This means that the errors are large, yet manageable if the relevant quantities are known a priori. A discussion of the radar altimeter ice thickness retrieval uncertainties concludes the paper.

  18. Influence of stochastic sea ice parametrization on climate and the role of atmosphere-sea ice-ocean interaction.

    Science.gov (United States)

    Juricke, Stephan; Jung, Thomas

    2014-06-28

    The influence of a stochastic sea ice strength parametrization on the mean climate is investigated in a coupled atmosphere-sea ice-ocean model. The results are compared with an uncoupled simulation with a prescribed atmosphere. It is found that the stochastic sea ice parametrization causes an effective weakening of the sea ice. In the uncoupled model this leads to an Arctic sea ice volume increase of about 10-20% after an accumulation period of approximately 20-30 years. In the coupled model, no such increase is found. Rather, the stochastic perturbations lead to a spatial redistribution of the Arctic sea ice thickness field. A mechanism involving a slightly negative atmospheric feedback is proposed that can explain the different responses in the coupled and uncoupled system. Changes in integrated Antarctic sea ice quantities caused by the stochastic parametrization are generally small, as memory is lost during the melting season because of an almost complete loss of sea ice. However, stochastic sea ice perturbations affect regional sea ice characteristics in the Southern Hemisphere, both in the uncoupled and coupled model. Remote impacts of the stochastic sea ice parametrization on the mean climate of non-polar regions were found to be small.

  19. Defining a Sea Ice Flag for Envisat Altimetry Mission

    OpenAIRE

    Tran, N; Ardhuin, Fanny; Ezraty, Robert; Feng, H.; Femenias, P

    2009-01-01

    This letter presents the development of a sea ice flag algorithm for the Envisat altimetry mission to detect sea ice corrupted sea surface height data within quality control processing. The algorithm takes advantage of having both passive and active microwave sensors on the same platform with coregistered measurements. Its performances have been evaluated based on collocations between the along-track Envisat data with reference maps built from combination of daily grids of sea ice concentrati...

  20. In situ primary production in young Antarctic sea ice

    OpenAIRE

    Mock, Thomas

    2002-01-01

    An in situ incubation technique used successfully to measure the photosynthetic carbon assimilation of internal algal assemblages within thick multiyear Arctic sea ice was developed and improved to measure the photosynthetic carbon assimilation within young sea ice only 50 cm thick (Eastern Weddell Sea, Antarctica). The new device enabled some of the first precise measurements of in situ photosynthetic carbon assimilation in newly formed Antarctic sea ice.

  1. Multifractals, random walks and Arctic sea ice

    Science.gov (United States)

    Agarwal, Sahil; Wettlaufer, John

    We examine the long-term correlations and multifractal properties of daily satellite retrievals of Arctic sea ice albedo, extent, and ice velocity for decadal periods. The approach harnesses a recent development called Multifractal Temporally Weighted Detrended Fluctuation Analysis (MF-TWDFA), which exploits the intuition that points closer in time are more likely to be related than distant points. In both data sets we extract multiple crossover times, as characterized by generalized Hurst exponents, ranging from synoptic to decadal. The method goes beyond treatments that assume a single decay scale process, such as a first-order autoregression, which cannot be justifiably fit to these observations. The ice extent data exhibits white noise behavior from seasonal to bi-seasonal time scales, whereas the clear fingerprints of the short (weather) and long (~ 7 and 9 year) time scales remain, the latter associated with the recent decay in the ice cover. Thus, long term persistence is reentrant beyond the seasonal scale and it is not possible to distinguish whether a given ice extent minimum/maximum will be followed by a minimum/maximum that is larger or smaller in magnitude. The ice velocity data show long term persistence in auto covariance. NASA Grant NNH13ZDA001N-CRYO and Swedish Research Council Grant No. 638-2013-9243.

  2. Antarctic Sea Ice Variability and Trends, 1979-2010

    Science.gov (United States)

    Parkinson, C. L.; Cavalieri, D. J.

    2012-01-01

    In sharp contrast to the decreasing sea ice coverage of the Arctic, in the Antarctic the sea ice cover has, on average, expanded since the late 1970s. More specifically, satellite passive-microwave data for the period November 1978 - December 2010 reveal an overall positive trend in ice extents of 17,100 +/- 2,300 square km/yr. Much of the increase, at 13,700 +/- 1,500 square km/yr, has occurred in the region of the Ross Sea, with lesser contributions from the Weddell Sea and Indian Ocean. One region, that of the Bellingshausen/Amundsen Seas, has, like the Arctic, instead experienced significant sea ice decreases, with an overall ice extent trend of -8,200 +/- 1,200 square km/yr. When examined through the annual cycle over the 32-year period 1979-2010, the Southern Hemisphere sea ice cover as a whole experienced positive ice extent trends in every month, ranging in magnitude from a low of 9,100 +/- 6,300 square km/yr in February to a high of 24,700 +/- 10,000 square km/yr in May. The Ross Sea and Indian Ocean also had positive trends in each month, while the Bellingshausen/Amundsen Seas had negative trends in each month, and the Weddell Sea and Western Pacific Ocean had a mixture of positive and negative trends. Comparing ice-area results to ice-extent results, in each case the ice-area trend has the same sign as the ice-extent trend, but differences in the magnitudes of the two trends identify regions with overall increasing ice concentrations and others with overall decreasing ice concentrations. The strong pattern of decreasing ice coverage in the Bellingshausen/Amundsen Seas region and increasing ice coverage in the Ross Sea region is suggestive of changes in atmospheric circulation. This is a key topic for future research.

  3. Antarctic sea ice variability and trends, 1979–2010

    Directory of Open Access Journals (Sweden)

    D. J. Cavalieri

    2012-03-01

    Full Text Available In sharp contrast to the decreasing sea ice coverage of the Arctic, in the Antarctic the sea ice cover has, on average, expanded since the late 1970s. More specifically, satellite passive-microwave data for the period November 1978–December 2010 reveal an overall positive trend in ice extents of 17 100 ± 2300 km2 yr−1. Much of the increase, at 13 700 ± 1500 km2 yr−1, has occurred in the region of the Ross Sea, with lesser contributions from the Weddell Sea and Indian Ocean. One region, that of the Bellingshausen/Amundsen Seas, has, like the Arctic, instead experienced significant sea ice decreases, with an overall ice extent trend of −8200 ± 1200 km2 yr−1. When examined through the annual cycle over the 32-yr period 1979–2010, the Southern Hemisphere sea ice cover as a whole experienced positive ice extent trends in every month, ranging in magnitude from a low of 9100 ± 6300 km2 yr−1 in February to a high of 24 700 ± 10 000 km2 yr−1 in May. The Ross Sea and Indian Ocean also had positive trends in each month, while the Bellingshausen/Amundsen Seas had negative trends in each month, and the Weddell Sea and Western Pacific Ocean had a mixture of positive and negative trends. Comparing ice-area results to ice-extent results, in each case the ice-area trend has the same sign as the ice-extent trend, but differences in the magnitudes of the two trends identify regions with overall increasing ice concentrations and others with overall decreasing ice concentrations. The strong pattern of decreasing ice coverage in the Bellingshausen/Amundsen Seas region and increasing ice coverage in the Ross Sea region is suggestive of changes in atmospheric circulation. This is a key topic for future research.

  4. 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.

  5. Antarctic sea ice variability and trends, 1979–2010

    Directory of Open Access Journals (Sweden)

    D. J. Cavalieri

    2012-08-01

    Full Text Available In sharp contrast to the decreasing sea ice coverage of the Arctic, in the Antarctic the sea ice cover has, on average, expanded since the late 1970s. More specifically, satellite passive-microwave data for the period November 1978–December 2010 reveal an overall positive trend in ice extents of 17 100 ± 2300 km2 yr−1. Much of the increase, at 13 700 ± 1500 km2 yr−1, has occurred in the region of the Ross Sea, with lesser contributions from the Weddell Sea and Indian Ocean. One region, that of the Bellingshausen/Amundsen Seas, has (like the Arctic instead experienced significant sea ice decreases, with an overall ice extent trend of −8200 ± 1200 km2 yr−1. When examined through the annual cycle over the 32-yr period 1979–2010, the Southern Hemisphere sea ice cover as a whole experienced positive ice extent trends in every month, ranging in magnitude from a low of 9100 ± 6300 km2 yr−1 in February to a high of 24 700 ± 10 000 km2 yr−1 in May. The Ross Sea and Indian Ocean also had positive trends in each month, while the Bellingshausen/Amundsen Seas had negative trends in each month, and the Weddell Sea and western Pacific Ocean had a mixture of positive and negative trends. Comparing ice-area results to ice-extent results, in each case the ice-area trend has the same sign as the ice-extent trend, but the magnitudes of the two trends differ, and in some cases these differences allow inferences about the corresponding changes in sea ice concentrations. The strong pattern of decreasing ice coverage in the Bellingshausen/Amundsen Seas region and increasing ice coverage in the Ross Sea region is suggestive of changes in atmospheric circulation. This is a key topic for future research.

  6. Canadian Arctic sea ice reconstructed from bromine in the Greenland NEEM ice core

    Science.gov (United States)

    Spolaor, Andrea; Vallelonga, Paul; Turetta, Clara; Maffezzoli, Niccolò; Cozzi, Giulio; Gabrieli, Jacopo; Barbante, Carlo; Goto-Azuma, Kumiko; Saiz-Lopez, Alfonso; Cuevas, Carlos A.; Dahl-Jensen, Dorthe

    2016-09-01

    Reconstructing the past variability of Arctic sea ice provides an essential context for recent multi-year sea ice decline, although few quantitative reconstructions cover the Holocene period prior to the earliest historical records 1,200 years ago. Photochemical recycling of bromine is observed over first-year, or seasonal, sea ice in so-called “bromine explosions” and we employ a 1-D chemistry transport model to quantify processes of bromine enrichment over first-year sea ice and depositional transport over multi-year sea ice and land ice. We report bromine enrichment in the Northwest Greenland Eemian NEEM ice core since the end of the Eemian interglacial 120,000 years ago, finding the maximum extension of first-year sea ice occurred approximately 9,000 years ago during the Holocene climate optimum, when Greenland temperatures were 2 to 3 °C above present values. First-year sea ice extent was lowest during the glacial stadials suggesting complete coverage of the Arctic Ocean by multi-year sea ice. These findings demonstrate a clear relationship between temperature and first-year sea ice extent in the Arctic and suggest multi-year sea ice will continue to decline as polar amplification drives Arctic temperatures beyond the 2 °C global average warming target of the recent COP21 Paris climate agreement.

  7. Canadian Arctic sea ice reconstructed from bromine in the Greenland NEEM ice core.

    Science.gov (United States)

    Spolaor, Andrea; Vallelonga, Paul; Turetta, Clara; Maffezzoli, Niccolò; Cozzi, Giulio; Gabrieli, Jacopo; Barbante, Carlo; Goto-Azuma, Kumiko; Saiz-Lopez, Alfonso; Cuevas, Carlos A; Dahl-Jensen, Dorthe

    2016-09-21

    Reconstructing the past variability of Arctic sea ice provides an essential context for recent multi-year sea ice decline, although few quantitative reconstructions cover the Holocene period prior to the earliest historical records 1,200 years ago. Photochemical recycling of bromine is observed over first-year, or seasonal, sea ice in so-called "bromine explosions" and we employ a 1-D chemistry transport model to quantify processes of bromine enrichment over first-year sea ice and depositional transport over multi-year sea ice and land ice. We report bromine enrichment in the Northwest Greenland Eemian NEEM ice core since the end of the Eemian interglacial 120,000 years ago, finding the maximum extension of first-year sea ice occurred approximately 9,000 years ago during the Holocene climate optimum, when Greenland temperatures were 2 to 3 °C above present values. First-year sea ice extent was lowest during the glacial stadials suggesting complete coverage of the Arctic Ocean by multi-year sea ice. These findings demonstrate a clear relationship between temperature and first-year sea ice extent in the Arctic and suggest multi-year sea ice will continue to decline as polar amplification drives Arctic temperatures beyond the 2 °C global average warming target of the recent COP21 Paris climate agreement.

  8. Canadian Arctic sea ice reconstructed from bromine in the Greenland NEEM ice core

    Science.gov (United States)

    Spolaor, Andrea; Vallelonga, Paul; Turetta, Clara; Maffezzoli, Niccolò; Cozzi, Giulio; Gabrieli, Jacopo; Barbante, Carlo; Goto-Azuma, Kumiko; Saiz-Lopez, Alfonso; Cuevas, Carlos A.; Dahl-Jensen, Dorthe

    2016-01-01

    Reconstructing the past variability of Arctic sea ice provides an essential context for recent multi-year sea ice decline, although few quantitative reconstructions cover the Holocene period prior to the earliest historical records 1,200 years ago. Photochemical recycling of bromine is observed over first-year, or seasonal, sea ice in so-called “bromine explosions” and we employ a 1-D chemistry transport model to quantify processes of bromine enrichment over first-year sea ice and depositional transport over multi-year sea ice and land ice. We report bromine enrichment in the Northwest Greenland Eemian NEEM ice core since the end of the Eemian interglacial 120,000 years ago, finding the maximum extension of first-year sea ice occurred approximately 9,000 years ago during the Holocene climate optimum, when Greenland temperatures were 2 to 3 °C above present values. First-year sea ice extent was lowest during the glacial stadials suggesting complete coverage of the Arctic Ocean by multi-year sea ice. These findings demonstrate a clear relationship between temperature and first-year sea ice extent in the Arctic and suggest multi-year sea ice will continue to decline as polar amplification drives Arctic temperatures beyond the 2 °C global average warming target of the recent COP21 Paris climate agreement. PMID:27650478

  9. Sea Ice Microorganisms: Environmental Constraints and Extracellular Responses

    Directory of Open Access Journals (Sweden)

    Jody W. Deming

    2013-03-01

    Full Text Available Inherent to sea ice, like other high latitude environments, is the strong seasonality driven by changes in insolation throughout the year. Sea-ice organisms are exposed to shifting, sometimes limiting, conditions of temperature and salinity. An array of adaptations to survive these and other challenges has been acquired by those organisms that inhabit the ice. One key adaptive response is the production of extracellular polymeric substances (EPS, which play multiple roles in the entrapment, retention and survival of microorganisms in sea ice. In this concept paper we consider two main areas of sea-ice microbiology: the physico-chemical properties that define sea ice as a microbial habitat, imparting particular advantages and limits; and extracellular responses elicited in microbial inhabitants as they exploit or survive these conditions. Emphasis is placed on protective strategies used in the face of fluctuating and extreme environmental conditions in sea ice. Gaps in knowledge and testable hypotheses are identified for future research.

  10. Albedo parametrization and reversibility of sea ice decay

    OpenAIRE

    M. Müller-Stoffels; R. Wackerbauer

    2012-01-01

    The Arctic's sea ice cover has been receding rapidly in recent years, and global climate models typically predict a further decline over the next century. It is an open question whether a possible loss of Arctic sea ice is reversible. We study the stability of Arctic model sea ice in a conceptual, two-dimensional energy-based regular network model of the ice-ocean layer that considers ARM's longwave radiative budget data and SHEBA albedo measurements. Seasonal ice cover, perennial ice and per...

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

    Science.gov (United States)

    Douglas, D.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

  12. Theory of the sea ice thickness distribution

    CERN Document Server

    Toppaladoddi, Srikanth

    2015-01-01

    We use concepts from statistical physics to transform the original evolution equation for the sea ice thickness distribution $g(h)$ due to Thorndike et al., (1975) into a Fokker-Planck like conservation law. The steady solution is $g(h) = {\\cal N}(q) h^q \\mathrm{e}^{-~ h/H}$, where $q$ and $H$ are expressible in terms of moments over the transition probabilities between thickness categories. The solution exhibits the functional form used in observational fits and shows that for $h \\ll 1$, $g(h)$ is controlled by both thermodynamics and mechanics, whereas for $h \\gg 1$ only mechanics controls $g(h)$. Finally, we derive the underlying Langevin equation governing the dynamics of the ice thickness $h$, from which we predict the observed $g(h)$. The genericity of our approach provides a framework for studying the geophysical scale structure of the ice pack using methods of broad relevance in statistical mechanics.

  13. Using the MicroASAR on the NASA SIERRA UAS in the Characterization of Arctic Sea Ice Experiment

    Science.gov (United States)

    Zaugg, Evan; Long, David; Edwards, Matthew; Fladeland, Matthew; Kolyer, Richard; Crocker, Ian; Maslanik, James; Herzfeld, Ute; Wallin, Bruce

    2010-01-01

    The MicroASAR is a flexible, robust SAR system built on the successful legacy of the BYU microSAR. It is a compact LFM-CW SAR system designed for low-power operation on small, manned aircraft or UAS. The NASA SIERRA UAS was designed to test new instruments and support flight experiments. NASA used the MicroASAR on the SIERRA during a science field campaign in 2009 to study sea ice roughness and break-up in the Arctic and high northern latitudes. This mission is known as CASIE-09 (Characterization of Arctic Sea Ice Experiment 2009). This paper describes the MicroASAR and its role flying on the SIERRA UAS platform as part of CASIE-09.

  14. Mechanism of seasonal Arctic sea ice evolution and Arctic amplification

    Science.gov (United States)

    Kim, Kwang-Yul; Hamlington, Benjamin D.; Na, Hanna; Kim, Jinju

    2016-09-01

    Sea ice loss is proposed as a primary reason for the Arctic amplification, although the physical mechanism of the Arctic amplification and its connection with sea ice melting is still in debate. In the present study, monthly ERA-Interim reanalysis data are analyzed via cyclostationary empirical orthogonal function analysis to understand the seasonal mechanism of sea ice loss in the Arctic Ocean and the Arctic amplification. While sea ice loss is widespread over much of the perimeter of the Arctic Ocean in summer, sea ice remains thin in winter only in the Barents-Kara seas. Excessive turbulent heat flux through the sea surface exposed to air due to sea ice reduction warms the atmospheric column. Warmer air increases the downward longwave radiation and subsequently surface air temperature, which facilitates sea surface remains to be free of ice. This positive feedback mechanism is not clearly observed in the Laptev, East Siberian, Chukchi, and Beaufort seas, since sea ice refreezes in late fall (November) before excessive turbulent heat flux is available for warming the atmospheric column in winter. A detailed seasonal heat budget is presented in order to understand specific differences between the Barents-Kara seas and Laptev, East Siberian, Chukchi, and Beaufort seas.

  15. Storm-induced sea-ice breakup and the implications for ice extent

    Science.gov (United States)

    Kohout, A. L.; Williams, M. J. M.; Dean, S. M.; Meylan, M. H.

    2014-05-01

    The propagation of large, storm-generated waves through sea ice has so far not been measured, limiting our understanding of how ocean waves break sea ice. Without improved knowledge of ice breakup, we are unable to understand recent changes, or predict future changes, in Arctic and Antarctic sea ice. Here we show that storm-generated ocean waves propagating through Antarctic sea ice are able to transport enough energy to break sea ice hundreds of kilometres from the ice edge. Our results, which are based on concurrent observations at multiple locations, establish that large waves break sea ice much farther from the ice edge than would be predicted by the commonly assumed exponential decay. We observed the wave height decay to be almost linear for large waves--those with a significant wave height greater than three metres--and to be exponential only for small waves. This implies a more prominent role for large ocean waves in sea-ice breakup and retreat than previously thought. We examine the wider relevance of this by comparing observed Antarctic sea-ice edge positions with changes in modelled significant wave heights for the Southern Ocean between 1997 and 2009, and find that the retreat and expansion of the sea-ice edge correlate with mean significant wave height increases and decreases, respectively. This includes capturing the spatial variability in sea-ice trends found in the Ross and Amundsen-Bellingshausen seas. Climate models fail to capture recent changes in sea ice in both polar regions. Our results suggest that the incorporation of explicit or parameterized interactions between ocean waves and sea ice may resolve this problem.

  16. Temporal dynamics of ikaite in experimental sea ice

    DEFF Research Database (Denmark)

    Rysgaard, Søren; Wang, F.; Galley, R.J.

    2014-01-01

    -covered seas. Little is known, however, of the spatial and temporal dynamics of ikaite in sea ice. Here we present evidence for highly dynamic ikaite precipitation and dissolution in sea ice grown at an outdoor pool of the Sea-ice Environmental Research Facility (SERF) in Manitoba, Canada. During...... with ikaite concentrations of 200–400 μmol kg−1, and (3) a bottom layer with ikaite concentrations of Manual removal of the snow cover allowed the sea ice to cool and brine salinities to increase, resulting in rapid...

  17. Characterization of Fram Strait Sea Ice Conditions Using the NASA SIERRA Unmanned Aircraft System

    Science.gov (United States)

    Maslanik, J. A.; Crocker, R. I.; Wegrzyn, K.; Fowler, C.; Herzfeld, U. C.; Long, D.; Kwok, R.; Fladeland, M. M.; Bui, P.

    2009-12-01

    In addition to record decreases in summer ice extent, the Arctic Ocean has also experienced extensive loss of the oldest, thickest sea ice types. The significance of this loss on overall sea ice mass and on the stability of the ice cover depends on how the thickness and physical properties of these older ice types vary with age, and on the degree to which a transition to generally thinner first-year ice might be in part compensated for by ice accumulating through increased ridging and rafting. Due to the difficulty of accessing and surveying a wide range ice types in the field, detailed, spatially extensive information regarding how factors such as thickness, ridging, and melt ponding differ with ice type are relatively rare. To address this, an experiment was carried out to map surface conditions at high spatial resolution using a low- and relatively slow-flying unmanned aircraft system (UAS) operated over the various ice types that are transported through the Fram Strait region, where ice with different ages and life cycle histories leaves the Arctic Basin. This effort - the “Characterization of Arctic Sea Ice Experiment” (CASIE) - measured ice surface roughness, thickness, ice ridging, floe morphology and melt pond characteristics to quantify differences among ice types and to assist in validating retrievals from satellite sensors. The nature of the flights - relatively hazardous low-altitude, long-range flying under Arctic summer conditions over ocean - made the experiment particularly well suited for UAS. The aircraft selected for the project was the National Aeronautics and Space Administration’s SIERRA, which provided 10 hour/1000 km flight range with a payload capacity of 25 kg; sufficient to meet the experiment’s remote sensing goals of acquiring coincident, multisensor data over large areas. Flights were carried out from the Ny-Alesund research base in Svalbard during July 10th. through July 29th., 2009, yielding 2500 km of coverage over sea ice

  18. Mapping Arctic sea ice from the Earth Resources Technology Satellite

    Science.gov (United States)

    Barnes, J. C. (Principal Investigator); Bowley, C. J.

    1973-01-01

    The author has identified the following significant results. Methods of detecting ice and for distinguishing between ice and clouds are discussed, and examples of ERTS-1 data showing ice distributions in northern Hudson Bay, M'Clure Strait, the eastern Beaufort Sea, and the Greenland Sea are presented. The results of the initial analysis of ERTS-1 data indicate that the locations of ice edges and ice concentrations can be accurately mapped, and that considerable information on ice type can be derived through use of the various spectral bands. Ice features as small as 80 to 100 m width can be mapped.

  19. The application of ERTS imagery to monitoring Arctic sea ice. [mapping ice in Bering Sea, Beaufort Sea, Canadian Archipelago, and Greenland Sea

    Science.gov (United States)

    Barnes, J. C. (Principal Investigator); Bowley, C. J.

    1974-01-01

    The author has identified the following significant results. Because of the effect of sea ice on the heat balance of the Arctic and because of the expanding economic interest in arctic oil and minerals, extensive monitoring and further study of sea ice is required. The application of ERTS data for mapping ice is evaluated for several arctic areas, including the Bering Sea, the eastern Beaufort Sea, parts of the Canadian Archipelago, and the Greenland Sea. Interpretive techniques are discussed, and the scales and types of ice features that can be detected are described. For the Bering Sea, a sample of ERTS-1 imagery is compared with visual ice reports and aerial photography from the NASA CV-990 aircraft. The results of the investigation demonstrate that ERTS-1 imagery has substantial practical application for monitoring arctic sea ice. Ice features as small as 80-100 m in width can be detected, and the combined use of the visible and near-IR imagery is a powerful tool for identifying ice types. Sequential ERTS-1 observations at high latitudes enable ice deformations and movements to be mapped. Ice conditions in the Bering Sea during early March depicted in ERTS-1 images are in close agreement with aerial ice observations and photographs.

  20. Sensitivity of sea ice and ocean simulations to sea ice salinity in a coupled global climate model

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    The impacts of the spatiotemporal variations of sea ice salinity on sea ice and ocean characteristics have not been studied in detail, as the existing climate models neglect or misrepresent this process. To address this issue, this paper formulated a parameterization with more realistic sea ice salinity budget, and examined the sensitivity of sea ice and ocean simulations to the ice salinity variations and associated salt flux into the ocean using a coupled global climate model. Results show that the inclusion of such a parameterization leads to an increase and thickening of sea ice in the Eurasian Arctic and within the ice pack in the Antarctic circumpolar region, and a weakening of the North Atlantic Deep Water and a strengthening of the Antarctic Bottom Water. The atmospheric responses associated with the ice changes were also discussed.

  1. 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.

  2. 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.

  3. 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

  4. Mapping Glacier Surface Elevation and its Changes of Puruogangri Ice Field with SAR Interferometry

    Science.gov (United States)

    Liu, Lin; Jiang, Liming; Sun, Yafei; Wang, Hansheng; Sun, Yongling

    2014-11-01

    Accurate DEMs are required for measuring glacier volume and mass change. The recently launched TanDEM-X (TDX) and TerraSAR-X (TSX) satellite system, which is the first bistatic spaceborne SAR mission, has the potential to acquire the accurate DEMs of most glaciers and ice caps. Here, we report on the application of TSX/TDX data sets for the measurement of mountain glacier DEMs over Tibetan Plateau. A DEM is generated with two pairs of TSX/TDX SAR images obtained in January 2012 over Puruogangri ice field (PIF). Moreover, we also estimate the elevation changes of the PIF by subtracting the SRTM-X DEM from the TSX/TDX DEM. Mean annual thinning rate of -0.0225±0.015 m yr-1 is observed between 2000 and 2012.

  5. Statistical Analysis of SAR Sea Clutter for Classification Purposes

    Directory of Open Access Journals (Sweden)

    Jaime Martín-de-Nicolás

    2014-09-01

    Full Text Available Statistical analysis of radar clutter has always been one of the topics, where more effort has been put in the last few decades. These studies were usually focused on finding the statistical models that better fitted the clutter distribution; however, the goal of this work is not the modeling of the clutter, but the study of the suitability of the statistical parameters to carry out a sea state classification. In order to achieve this objective and provide some relevance to this study, an important set of maritime and coastal Synthetic Aperture Radar data is considered. Due to the nature of the acquisition of data by SAR sensors, speckle noise is inherent to these data, and a specific study of how this noise affects the clutter distribution is also performed in this work. In pursuit of a sense of wholeness, a thorough study of the most suitable statistical parameters, as well as the most adequate classifier is carried out, achieving excellent results in terms of classification success rates. These concluding results confirm that a sea state classification is not only viable, but also successful using statistical parameters different from those of the best modeling distribution and applying a speckle filter, which allows a better characterization of the parameters used to distinguish between different sea states.

  6. The impact of under-ice melt ponds on Arctic sea ice volume

    Science.gov (United States)

    Smith, Naomi; Flocco, Daniela; Feltham, Daniel

    2016-04-01

    A one-dimensional, thermodynamic model of Arctic sea ice [Flocco et al, 2015] has been adapted to study the evolution of under-ice melt ponds, pools of fresh water that are found below the Arctic sea ice, and false bottoms, sheets of ice that form at the boundary between the under-ice melt pond and the oceanic mixed layer. Over time, either the under-ice melt pond freezes or the false bottom is completely ablated. We have been investigating the impact that these features have on the growth or ablation of sea ice during the time that they are present. The sensitivity of our model to a range of parameters has been tested, revealing some interesting effects of the thermodynamic processes taking place during the life-cycle of these phenomena. For example, the under-ice melt pond and its associated false bottom can insulate the sea ice layer from ocean, increasing the thickness of sea ice present at the end of the time frame considered. A comparison of the results of the model of under-ice melt pond evolution with that of sea ice with a bare base has been used to estimate the impact of under-ice melt ponds on sea ice volume towards the end of the melt season. We find that the under-ice melt ponds could have a significant impact on the mass balance of the sea ice, suggesting that it could be desirable to include a parameterisation of the effects of under-ice melt pond in the sea ice components of climate models.

  7. 30-Year Satellite Record Reveals Accelerated Arctic Sea Ice Loss, Antarctic Sea Ice Trend Reversal

    Science.gov (United States)

    Cavalieri, Donald J.; Parkinson, C. L.; Vinnikov, K. Y.

    2003-01-01

    Arctic sea ice extent decreased by 0.30 plus or minus 0.03 x 10(exp 6) square kilometers per decade from 1972 through 2002, but decreased by 0.36 plus or minus 0.05 x 10(exp 6) square kilometers per decade from 1979 through 2002, indicating an acceleration of 20% in the rate of decrease. In contrast to the Arctic, the Antarctic sea ice extent decreased dramatically over the period 1973-1977, then gradually increased, with an overall 30-year trend of -0.15 plus or minus 0.08 x 10(exp 6) square kilometers per 10yr. The trend reversal is attributed to a large positive anomaly in Antarctic sea ice extent observed in the early 1970's.

  8. Evaluation of the ESA Sea Ice CCI (SICCI) project sea ice concentration data set

    DEFF Research Database (Denmark)

    Kern, Stefan; Bell, Louisa; Ivanova, Natalia

    During phase 1 of the European Space Agency’s (ESA) climate change initiative (CCI) sea ice project (SICCI project) a sea ice concentration (SIC) data product was produced by employing a hybrid SIC retrieval algorithm comprising the Bristol and the Comiso-Bootstrap algorithm in frequency mode. SIC...... process, and SIC total uncertainty. A flag layer allows to identify where SIC may be less reliable. The unlimited SIC contains the full range of SIC values retrieved. The natural variability of the measured TBs around the typical TBs at 0% and 100% SIC (the so-called tie points) causes SIC to spread...... around these two SIC values; consequently SIC can be negative or above 100%. In order to fully evaluate SICCI SIC this natural variability needs to be taken into account. In contrast to most other SIC retrieval algorithms the SICCI algorithm does not filter spurious sea ice over open water with a weather...

  9. Model resolution influence on simulated sea ice decline

    Directory of Open Access Journals (Sweden)

    J. O. Sewall

    2008-10-01

    Full Text Available Satellite observations and model predictions of recent and future Arctic sea ice decline have raised concerns over the timing and potential impacts of a seasonally ice-free Arctic Ocean. Model predictions of seasonally ice-free Arctic conditions are, however, highly variable. Here I present results from fourteen climate system models from the World Climate Research Programme's (WCRP's Coupled Model Intercomparison Project phase 3 (CMIP3 multi-model dataset that indicate modeled Arctic sea ice sensitivity to increased atmospheric CO2 forcing is strongly correlated with ice/ocean model horizontal resolution. Based on coupled model analyses and ice only simulations with the Los Alamos National Lab sea ice model (CICE, the correlation between declining Arctic sea ice cover and ice/ocean model resolution appears to depend largely on ocean model resolution and its influence on ocean heat transport into the Arctic basin. The correlation between model resolution, northward ocean heat transport, and the degree of Arctic ice loss is independent of ice model physics and complexity. This not only illustrates one difficulty in using numerical models to accurately predict the timing and magnitude of Arctic sea ice decline under increasing atmospheric greenhouse gas forcing, but also highlights one area where improved simulation (of northward ocean heat transport could greatly decrease the uncertainties associated with predictions of future Arctic sea ice cover.

  10. The signature analysis of summer Antarctic sea-ice distribution by ship-based sea-ice observation

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    Based on the Chinese 19th National Antarctic Research Expedition,we carried out ship-based Antarctic sea-ice observa-tion on icebreaker Xue Long using Antarctic sea-ice process and climate (ASPeCt) criteria during austral summer.Sea-ice distribution data were obtained along nearly 6,500 km of the ship’s track.The measurement parameters included sea-ice thickness,sea-ice concentration,snow thickness,and floe size.Analysis showed the presence of the large spatial varia-tions of the observed sea-ice characteristics.Sea-ice concentration varied between 0 and 80 percent and reached its peak value in Weddell Sea because of the specific dynamical process affecting in summer sea-ice melting.There are large areas of open water along the study section.Sea ice and the upper snow thickness of the section varied between 10 cm and 210 cm and 2 cm and 80 cm,respectively,and each reaches its peak values near Amery ice shelf.The floe size varied from less than 10 cm and the maximum of more than 2,000 km along the section.

  11. Validation of CryoSat-2 Performance over Arctic Sea Ice

    DEFF Research Database (Denmark)

    di Bella, Alessandro; Skourup, Henriette; Bouffard, J.;

    The main objective of this work is to validate CryoSat-2 (CS2) SARIn performance over sea ice by use of airborne laser altimetry data obtained during the CryoVEx 2012 campaign. A study by [1] has shown that the extra information from the CS2 SARIn mode increases the number of valid sea surface...... height estimates which are usually discarded in the SAR mode due to snagging of the radar signal. As the number of valid detected leads increases, the uncertainty of the freeboard heights decreases. In this study, the snow freeboard heights estimated using data from the airborne laser scanner are used...

  12. Air-ice carbon pathways inferred from a sea ice tank experiment

    OpenAIRE

    Marie Kotovitch; Sébastien Moreau; Jiayun Zhou; Martin Vancoppenolle; Dieckmann, Gerhard S.; Karl-Ulrich Evers; Fanny Van der Linden; Thomas, David N.; Jean-Louis Tison; Bruno Delille

    2016-01-01

    Abstract Given rapid sea ice changes in the Arctic Ocean in the context of climate warming, better constraints on the role of sea ice in CO2 cycling are needed to assess the capacity of polar oceans to buffer the rise of atmospheric CO2 concentration. Air-ice CO2 fluxes were measured continuously using automated chambers from the initial freezing of a sea ice cover until its decay during the INTERICE V experiment at the Hamburg Ship Model Basin. Cooling seawater prior to sea ice formation act...

  13. Definition of Arctic and Antarctic Sea Ice Variation Index

    Institute of Scientific and Technical Information of China (English)

    Chen Hongxia; Liu Na; Pan Zengdi; Zhang Qinghua

    2004-01-01

    It is well known that varying of the sea ice not only in the Antarctic but also in the Arctic has an active influence on the globe atmosphere and ocean. In order to understand the sea ice variation in detail, for the first time, an objective index of the Arctic and Antarctic sea ice variation is defined by projecting the monthly sea ice concentration anomalies poleward of 20°N or 20°S onto the EOF (empirical orthogonal function)-1 spatial pattern. Comparing with some work in former studies of polar sea ice, the index has the potential for clarifying the variability of sea ice in northern and southern high latitudes.

  14. Draft Genome Sequence of Uncultured SAR324 Bacterium lautmerah10, Binned from a Red Sea Metagenome

    KAUST Repository

    Haroon, Mohamed

    2016-02-11

    A draft genome of SAR324 bacterium lautmerah10 was assembled from a metagenome of a surface water sample from the Red Sea, Saudi Arabia. The genome is more complete and has a higher G+C content than that of previously sequenced SAR324 representatives. Its genomic information shows a versatile metabolism that confers an advantage to SAR324, which is reflected in its distribution throughout different depths of the marine water column.

  15. Global coupled sea ice-ocean state estimation

    Science.gov (United States)

    Fenty, Ian; Menemenlis, Dimitris; Zhang, Hong

    2015-09-01

    We study the impact of synthesizing ocean and sea ice concentration data with a global, eddying coupled sea ice-ocean configuration of the Massachusetts Institute of Technology general circulation model with the goal of reproducing the 2004 three-dimensional time-evolving ice-ocean state. This work builds on the state estimation framework developed in the Estimating the Circulation and Climate of the Ocean consortium by seeking a reconstruction of the global sea ice-ocean system that is simultaneously consistent with (1) a suite of in situ and remotely-sensed ocean and ice data and (2) the physics encoded in the numerical model. This dual consistency is successfully achieved here by adjusting only the model's initial hydrographic state and its atmospheric boundary conditions such that misfits between the model and data are minimized in a least-squares sense. We show that synthesizing both ocean and sea ice concentration data is required for the model to adequately reproduce the observed details of the sea ice annual cycle in both hemispheres. Surprisingly, only modest adjustments to our first-guess atmospheric state and ocean initial conditions are necessary to achieve model-data consistency, suggesting that atmospheric reanalysis products remain a leading source of errors for sea ice-ocean model hindcasts and reanalyses. The synthesis of sea ice data is found to ameliorate misfits in the high latitude ocean, especially with respect to upper ocean stratification, temperature, and salinity. Constraining the model to sea ice concentration modestly reduces ICESat-derived Arctic ice thickness errors by improving the temporal and spatial evolution of seasonal ice. Further increases in the accuracy of global sea ice thickness in the model likely require the direct synthesis of sea ice thickness data.

  16. Assessment of the sea-ice carbon pump

    DEFF Research Database (Denmark)

    Grimm, R.; Notz, D.; Glud, Ronnie N.

    2016-01-01

    It has been suggested that geochemical processes related to sea-ice growth and melt might be important for the polar carbon cycle via the so called sea-ice carbon pump (SICP). The SICP affects the air-sea CO2 exchange by influencing the composition of dissolved inorganic carbon (DIC) and total...... in regions with net sea-ice melt, and enhanced SICP-induced oceanic CO2 out-gassing in regions with net sea-ice growth. These general regional patterns are modified further by the blockage of air-sea gas exchange through sea-ice coverage. Integrated over the sea-ice zones of both hemispheres, the SICP...... alkalinity (TA) in the surface ocean. Here we quantify the strength of the SICP-induced air-sea CO2 flux using the global three-dimensional ocean-sea-ice-biogeochemical model MPIOM/HAMOCC. Simulations prescribing the range of observed DIC and TA concentrations in the sea ice were performed under two...

  17. Variations in the Sea Ice Edge and the Marginal Ice Zone on Different Spatial Scales as Observed from Different Satellite Sensor

    Science.gov (United States)

    Markus, Thorsten; Henrichs, John

    2006-01-01

    The Marginal sea Ice Zone (MIZ) and the sea ice edge are the most dynamic areas of the sea ice cover. Knowledge of the sea ice edge location is vital for routing shipping in the polar regions. The ice edge is the location of recurrent plankton blooms, and is the habitat for a number of animals, including several which are under severe ecological threat. Polar lows are known to preferentially form along the sea ice edge because of induced atmospheric baroclinicity, and the ice edge is also the location of both vertical and horizontal ocean currents driven by thermal and salinity gradients. Finally, sea ice is both a driver and indicator of climate change and monitoring the position of the ice edge accurately over long time periods enables assessment of the impact of global and regional warming near the poles. Several sensors are currently in orbit that can monitor the sea ice edge. These sensors, though, have different spatial resolutions, different limitations, and different repeat frequencies. Satellite passive microwave sensors can monitor the ice edge on a daily or even twice-daily basis, albeit with low spatial resolution - 25 km for the Special Sensor Microwave Imager (SSM/I) or 12.5 km for the Advanced Microwave Scanning Radiometer (AMSR-E). Although special methods exist that allow the detection of the sea ice edge at a quarter of that nominal resolution (PSSM). Visible and infrared data from the Advanced Very High Resolution Radiometer (AVHRR) and from the Moderate Resolution Imaging Spectroradiometer (MODIS) provide daily coverage at 1 km and 250 m, respectively, but the surface observations me limited to cloud-free periods. The Landsat 7 Enhanced Thematic Mapper (ETM+) has a resolution of 15 to 30 m but is limited to cloud-free periods as well, and does not provide daily coverage. Imagery from Synthetic Aperture Radar (SAR) instruments has resolutions of tens of meters to 100 m, and can be used to distinguish open water and sea ice on the basis of surface

  18. Validation and operational measurements with SUSIE – A sar ice motion processing chain developed within promice (Programme for monitoring of Greenland ice-sheet)

    DEFF Research Database (Denmark)

    Merryman Boncori, John Peter; Dall, Jørgen; Ahlstrøm, A. P.;

    2010-01-01

    This paper describes the validation of an ice-motion processing chain developed for the PROMICE project – a long-term program funded by the Danish ministry of Climate and Energy to monitor the mass budget of the Greenland ice-sheet. The processor, named SUSIE, (Scripts and Utilities for SAR Ice...

  19. Arctic sea ice and Eurasian climate: A review

    OpenAIRE

    Gao, Yongqi; Sun, Jianqi; Li, Fei; He, Shengping; SANDVEN, Stein; Yan, Qing; Zhang, Zhongshi; LOHMANN, Katja; KEENLYSIDE, Noel; Furevik, Tore; Suo, Lingling

    2014-01-01

    The Arctic plays a fundamental role in the climate system and has shown significant climate change in recent decades, including the Arctic warming and decline of Arctic sea-ice extent and thickness. In contrast to the Arctic warming and reduction of Arctic sea ice, Europe, East Asia and North America have experienced anomalously cold conditions, with record snowfall during recent years. In this paper, we review current understanding of the sea-ice impacts on the Eurasian climate. Paleo, obser...

  20. Sunlight, Sea Ice, and the Ice Albedo Feedback in a Changing Arctic Sea Ice Cover

    Science.gov (United States)

    2013-09-30

    ice age, and iv) onset dates of melt and freezeup . 4. Assess the magnitude of the contribution from ice-albedo feedback to the observed decrease of...the impact on albedo evolution of ice concentration and melt and freezeup onset dates. This effort will expand on previous work by i) examining...radiation, ice concentration, ice type, and melt and freezeup onset dates on a 25 x 25 km equal area scalable grid. We have daily values of these parameters

  1. Characterizing "Rotten" Ice: Changes in first-year Arctic sea ice during advanced summer melt

    Science.gov (United States)

    Frantz, C. M.; Junge, K.; Light, B.; Orellana, M. V.; Carpenter, S.; Farley, S. M.; Crump, B. C.; Lieb-Lappen, R.; Courville, Z.

    2016-12-01

    Arctic melt seasons are lengthening; as this happens, more Arctic sea ice will undergo advanced stages of melt, becoming so-called "rotten" ice. However, very little is known about this increasingly important ice type. Here, we present results of a physical, optical, chemical, and biological characterization of rotten Arctic sea ice. Sea ice core samples and measurements were collected from landfast sea ice and summer ice floes near Barrow, Alaska during May-July of 2015. We captured a normal progression of ice warming and freshening from May-June which contrasted sharply to physical properties and biological composition of the "rotten" ice targeted in July. Rotten ice is approximately isothermal and highly permeable, a consequence of its characteristic multi-cm-scale brine channels, resulting in an ice that is largely drained of brine and flushed with seawater. 3D micro-CT images of the ice allow us to quantify the evolution of factors related to ice porosity and channel connectivity in May-June vs. rotten ice. Patterns in measured chemistry show an environment in rotten ice that is distinct from May-June ice as well as from the seawater that underlies and permeates the ice. The physical and chemical parameters taken together represent an entirely different microbial habitat than the saline ice of May and June. Correspondingly, the sea ice microbial community also changes significantly over the course of melt. The ice-bottom algal community that dominates the biomass of the cores in May and June was lost by July, yet in July samples some algae appear to remain embedded in or attached to the ice throughout the full core depth. In addition, bacterial counts in upper horizons of rotten ice were dramatically higher than those observed in May-June. Pending results from SSU rRNA amplicon sequencing and exopolymer/gel analyses will also be presented.

  2. 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

    the ocean temperature is cooled to prevent the ice from immediately melting . Conversely, if ice is removed from a grid cell that had ice , the ocean...of moist snow, wet ice surfaces and melt ponds. By confusing water atop sea ice with open ocean, passive microwave products tend to underestimate the... ice concentration and adjusts other fields (e.g., volume and energy of melting for both ice and snow) for consistency. However, in ACNFS, we only use

  3. Ice Velocity Mapping Using TOPS SAR Data and Offset Tracking

    DEFF Research Database (Denmark)

    Dall, Jørgen; Kusk, Anders; Nielsen, Ulrik;

    2015-01-01

    Feature tracking and speckle tracking, are robust techniques to measure the velocity of glaciers and ice sheets. Displacement maps based on TOPS data may have small gaps if the bursts are not handled properly. Ice moving from one burst to a consecutive burst between two observations is not observ...

  4. A recent bifurcation in Arctic sea-ice cover

    Directory of Open Access Journals (Sweden)

    V. N. Livina

    2012-07-01

    Full Text Available There is ongoing debate over whether Arctic sea-ice has already passed a "tipping point", or whether it will do so in future, with several recent studies arguing that the loss of summer sea ice does not involve a bifurcation because it is highly reversible in models. Recently developed methods can detect and sometimes forewarn of bifurcations in time-series data, hence we applied them to satellite data for Arctic sea-ice cover. Here we show that a new low ice cover state has appeared from 2007 onwards, which is distinct from the normal state of seasonal sea ice variation, suggesting a bifurcation has occurred from one attractor to two. There was no robust early warning signal of critical slowing down prior to this bifurcation, consistent with it representing the appearance of a new ice cover state rather than the loss of stability of the existing state. The new low ice cover state has been sampled predominantly in summer-autumn and seasonal forcing combined with internal climate variability are likely responsible for triggering recent transitions between the two ice cover states. However, all early warning indicators show destabilization of the summer-autumn sea-ice since 2007. This suggests the new low ice cover state may be a transient feature and further abrupt changes in summer-autumn Arctic sea-ice cover could lie ahead; either reversion to the normal state or a yet larger ice loss.

  5. Interannual Variability of the Sea-Ice-Induced Salt Flux in the Greenland Sea

    DEFF Research Database (Denmark)

    Pedersen, Leif Toudal; Coon, M.D.

    2001-01-01

    ; Visbeck and others, 1995). The predominant ice types in the Greenland Sea arc frazil/grease ice and pancake ice. A numerical model has been developed relating ice formation and decay of these ice types as observed by the SMMR and SSM/I microwave radiometers and evaluating their contribution to salt...

  6. Interannual Variability of the Sea-Ice-Induced Salt Flux in the Greenland Sea

    DEFF Research Database (Denmark)

    Pedersen, Leif Toudal; Coon, M.D.

    2001-01-01

    ; Visbeck and others, 1995). The predominant ice types in the Greenland Sea arc frazil/grease ice and pancake ice. A numerical model has been developed relating ice formation and decay of these ice types as observed by the SMMR and SSM/I microwave radiometers and evaluating their contribution to salt...

  7. Sea ice dynamics influence halogen deposition to Svalbard

    Directory of Open Access Journals (Sweden)

    A. Spolaor

    2013-03-01

    Full Text Available Sea ice is an important parameter in the climate system and its changes impact upon the polar albedo and the atmospheric and oceanic circulation. Iodine (I and bromine (Br have been measured in a shallow ice core drilled at the summit of the Holtedahlfonna glacier (Northwest Spitsbergen, Svalbard. Changing I concentrations can be linked to the spring 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 spring sea ice coincides with enlargement of the open ocean surface which enhances marine primary production and consequent I emission. The observed Br enrichment can be explained by greater Br emissions during the Br explosion that have been observed to occur 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.

  8. 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.

  9. PS-InSAR Monitoring of Landslide Activity in the Black Sea Coast of the Caucasus

    NARCIS (Netherlands)

    Kiseleva, E.; Mikhailov, V.; Smolyaninova, E.; Dmitriev, P.; Golubev, V.; Timoshkina, E.; Hooper, A.; Samiei-Esfahany, S.; Hanssen, R.F.

    2014-01-01

    The landslide activity in the area of Bolshoy Sochi (Big Sochi) situated at the Black Sea coast of the Great Caucasus has been studied using the StaMPS PS-InSAR method. We incorporated three sets of radar images from the satellites with different wavelengths ALOS, Envisat and Terra-SAR-X from both

  10. PS-InSAR Monitoring of Landslide Activity in the Black Sea Coast of the Caucasus

    NARCIS (Netherlands)

    Kiseleva, E.; Mikhailov, V.; Smolyaninova, E.; Dmitriev, P.; Golubev, V.; Timoshkina, E.; Hooper, A.; Samiei-Esfahany, S.; Hanssen, R.F.

    2014-01-01

    The landslide activity in the area of Bolshoy Sochi (Big Sochi) situated at the Black Sea coast of the Great Caucasus has been studied using the StaMPS PS-InSAR method. We incorporated three sets of radar images from the satellites with different wavelengths ALOS, Envisat and Terra-SAR-X from both a

  11. 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

  12. 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...... and gas deposits known to occur throughout the Arctic. Here we show that hazardous ice features remain a threat to stationary and mobile infrastructure in the southern Beaufort Sea. With the opening up of the ice pack, forecasting of high-frequency oscillations or local eddy-driven ice motion...

  13. Ice Draft and Ice Velocity Data in the Beaufort Sea, 1990-2003

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set provides measurement of sea ice draft (m) and the movement of sea ice (cm/s) over the continental shelf of the Eastern Beaufort Sea. The data set spans...

  14. The seasonal appearance of ice shelf water in coastal Antarctica and its effect on sea ice growth

    National Research Council Canada - National Science Library

    Andrew R. Mahoney; Alexander J. Gough; Patricia J. Langhorne; Natalie J. Robinson; Craig L. Stevens; Michael M. J. Williams; Timothy G. Haskell

    2011-01-01

      We present data from first year-round mooring beneath sea ice in McMurdo Sound Presence of ice shelf water below sea ice is related to enhanced growth We identify distinct stages in arrival of ISW...

  15. Nonlinear threshold behavior during the loss of Arctic sea ice.

    Science.gov (United States)

    Eisenman, I; Wettlaufer, J S

    2009-01-06

    In light of the rapid recent retreat of Arctic sea ice, a number of studies have discussed the possibility of a critical threshold (or "tipping point") beyond which the ice-albedo feedback causes the ice cover to melt away in an irreversible process. The focus has typically been centered on the annual minimum (September) ice cover, which is often seen as particularly susceptible to destabilization by the ice-albedo feedback. Here, we examine the central physical processes associated with the transition from ice-covered to ice-free Arctic Ocean conditions. We show that although the ice-albedo feedback promotes the existence of multiple ice-cover states, the stabilizing thermodynamic effects of sea ice mitigate this when the Arctic Ocean is ice covered during a sufficiently large fraction of the year. These results suggest that critical threshold behavior is unlikely during the approach from current perennial sea-ice conditions to seasonally ice-free conditions. In a further warmed climate, however, we find that a critical threshold associated with the sudden loss of the remaining wintertime-only sea ice cover may be likely.

  16. Towards a satellite-based sea ice climate data record

    Science.gov (United States)

    Meier, W. N.; Fetterer, F.; Stroeve, J.; Cavalieri, D.; Parkinson, C.; Comiso, J.; Weaver, R.

    2005-12-01

    Sea ice plays an important role in the Earth's climate through its influence on the surface albedo, heat and moisture transfer between the ocean and the atmosphere, and the thermohaline circulation. Satellite data reveal that since 1979, summer Arctic sea ice has, overall, been declining at a rate of almost 8%/decade, with recent summers (beginning in 2002) being particularly low. The receding sea ice is having an effect on wildlife and indigenous peoples in the Arctic, and concern exists that these effects may become increasingly severe. Thus, a long-term, ongoing climate data record of sea ice is crucial for tracking the changes in sea ice and for assessing the significance of long-term trends. Since the advent of passive microwave satellite instruments in the early 1970s, sea ice has been one of the most consistently monitored climate parameters. There is now a 27+ year record of sea ice extent and concentration from multi-channel passive microwave radiometers that has undergone inter-sensor calibration and other quality controls to ensure consistency throughout the record. Several algorithms have been developed over the years to retrieve sea ice extent and concentration and two of the most commonly used algorithms, the NASA Team and Bootstrap, have been applied to the entire SMMR-SSM/I record to obtain a consistent time series. These algorithms were developed at NASA Goddard Space Flight Center and are archived at the National Snow and Ice Data Center. However, the complex surface properties of sea ice affect the microwave signature, and algorithms can yield ambiguous results; no single algorithm has been found to work uniformly well under all sea ice conditions. Thus there are ongoing efforts to further refine the algorithms and the time series. One approach is to develop data fusion methods to optimally combine sea ice fields from two or more algorithms. Another approach is to take advantage of the improved capabilities of JAXA's AMSR-E sensor on NASA's Aqua

  17. SEDNA: Sea ice Experiment - Dynamic Nature of the Arctic

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Sea Ice Experiment - Dynamic Nature of the Arctic (SEDNA) is an international collaborative effort to improve the understanding of the interaction between sea...

  18. 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

  19. Ice Velocity Mapping Using TOPS SAR Data and Offset Tracking

    DEFF Research Database (Denmark)

    Dall, Jørgen; Kusk, Anders; Nielsen, Ulrik

    2015-01-01

    Feature tracking and speckle tracking, are robust techniques to measure the velocity of glaciers and ice sheets. Displacement maps based on TOPS data may have small gaps if the bursts are not handled properly. Ice moving from one burst to a consecutive burst between two observations is not observed...... under the same squint angle, and hence speckle tracking is supposed to fail when cross-correlating consecutive bursts, whereas feature tracking provides the same result as when cross-correlating corresponding bursts. The size of the potential gaps depends on the ice displacement and the choice...

  20. National Ice Center Arctic Sea Ice Charts and Climatologies in Gridded Format

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The U.S. National Ice Center (NIC) is an inter-agency sea ice analysis and forecasting center comprised of the Department of Commerce/NOAA, the Department of...

  1. Air-ice carbon pathways inferred from a sea ice tank experiment

    Directory of Open Access Journals (Sweden)

    Marie Kotovitch

    2016-06-01

    Full Text Available Abstract Given rapid sea ice changes in the Arctic Ocean in the context of climate warming, better constraints on the role of sea ice in CO2 cycling are needed to assess the capacity of polar oceans to buffer the rise of atmospheric CO2 concentration. Air-ice CO2 fluxes were measured continuously using automated chambers from the initial freezing of a sea ice cover until its decay during the INTERICE V experiment at the Hamburg Ship Model Basin. Cooling seawater prior to sea ice formation acted as a sink for atmospheric CO2, but as soon as the first ice crystals started to form, sea ice turned to a source of CO2, which lasted throughout the whole ice growth phase. Once ice decay was initiated by warming the atmosphere, the sea ice shifted back again to a sink of CO2. Direct measurements of outward ice-atmosphere CO2 fluxes were consistent with the depletion of dissolved inorganic carbon in the upper half of sea ice. Combining measured air-ice CO2 fluxes with the partial pressure of CO2 in sea ice, we determined strongly different gas transfer coefficients of CO2 at the air-ice interface between the growth and the decay phases (from 2.5 to 0.4 mol m−2 d−1 atm−1. A 1D sea ice carbon cycle model including gas physics and carbon biogeochemistry was used in various configurations in order to interpret the observations. All model simulations correctly predicted the sign of the air-ice flux. By contrast, the amplitude of the flux was much more variable between the different simulations. In none of the simulations was the dissolved gas pathway strong enough to explain the large fluxes during ice growth. This pathway weakness is due to an intrinsic limitation of ice-air fluxes of dissolved CO2 by the slow transport of dissolved inorganic carbon in the ice. The best means we found to explain the high air-ice carbon fluxes during ice growth is an intense yet uncertain gas bubble efflux, requiring sufficient bubble nucleation and upwards rise. We

  2. 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.

  3. Arctic Summer Sea-Ice Extent: How Free is Free?

    Science.gov (United States)

    Tremblay, B.; Cullather, R. I.; DeRepentigny, P.; Pfirman, S. L.; Newton, R.

    2015-12-01

    As Northern Hemisphere perennial sea ice cover continues a long-term downward trend, attention has begun to focus on the implications of the changing conditions. A summertime ice-free Arctic Ocean is frequently indicated as a signature milestone for these changes, however "ice-free" has a substantially different meaning among scientists and interested stakeholders. To climate scientists it may mean when there is so little sea ice that it plays a minimal role in the climate system. To those interested in development, it may mean a threshold where icebreaker support is not required. To coastal communities it may mean so little ice that hunting is not possible. To species dependent on sea ice, it may mean the point where they cannot find sufficient habitat to survive from spring until fall. In this contribution we document the projected seasonality of the sea ice retreat and address the following questions. For how long will the Arctic Ocean be ice free on average each year? What is the impact of such changes in the seasonality of the sea ice cover on species that are dependent on sea ice? To this end, we analyze the seasonal cycle in the sea-ice extent simulated by the Community Earth System Model 1 - Large Ensemble (CESM1-LE) output for the 21st century. CESM1-LE simulates a realistic late 20th, early 21st century Arctic climate with a seasonal cycle in sea ice extent and rate of decline in good agreement with observations. Results from this model show that even by the end of the 21st century, the length of the ice-free season is relatively short, with ice-free conditions mainly present for 2-3 months between August and October. The result is a much larger amplitude seasonal cycle when compared with the late 20th century climate.

  4. Wind, current and swell influences on the ice extent and flux in the Grand Banks-Labrador sea area as observed in the LIMEX '87 experiment

    Science.gov (United States)

    Argus, Susan Digby; Carsey, Frank; Holt, Benjamin

    1988-01-01

    This paper presents data collected by airborne and satellite instruments during the Labrador Ice Margin Experiment, that demonstrate the effects of oceanic and atmospheric processes on the ice conditions in the Grand Banks-Labrador sea area. Special consideration is given to the development of algorithms for extracting information from SAR data. It is shown that SAR data can be used to monitor ice extent, determine ice motion, locate shear zones, monitor the penetration of swell into the ice, estimate floe sizes, and establish the dimensions of the ice velocity zones. It is also shown that the complex interaction of the ice cover with winds, currents, swell, and coastlines is similar to the dynamics established for a number of sites in both polar regions.

  5. Controls on Arctic sea ice from first-year and multi-year ice survival rates

    Science.gov (United States)

    Armour, K.; Bitz, C. M.; Hunke, E. C.; Thompson, L.

    2009-12-01

    The recent decrease in Arctic sea ice cover has transpired with a significant loss of multi-year (MY) ice. The transition to an Arctic that is populated by thinner first-year (FY) sea ice has important implications for future trends in area and volume. We develop a reduced model for Arctic sea ice with which we investigate how the survivability of FY and MY ice control various aspects of the sea-ice system. We demonstrate that Arctic sea-ice area and volume behave approximately as first-order autoregressive processes, which allows for a simple interpretation of September sea-ice in which its mean state, variability, and sensitivity to climate forcing can be described naturally in terms of the average survival rates of FY and MY ice. This model, used in concert with a sea-ice simulation that traces FY and MY ice areas to estimate the survival rates, reveals that small trends in the ice survival rates explain the decline in total Arctic ice area, and the relatively larger loss of MY ice area, over the period 1979-2006. Additionally, our model allows for a calculation of the persistence time scales of September area and volume anomalies. A relatively short memory time scale for ice area (~ 1 year) implies that Arctic ice area is nearly in equilibrium with long-term climate forcing at all times, and therefore observed trends in area are a clear indication of a changing climate. A longer memory time scale for ice volume (~ 5 years) suggests that volume can be out of equilibrium with climate forcing for long periods of time, and therefore trends in ice volume are difficult to distinguish from its natural variability. With our reduced model, we demonstrate the connection between memory time scale and sensitivity to climate forcing, and discuss the implications that a changing memory time scale has on the trajectory of ice area and volume in a warming climate. Our findings indicate that it is unlikely that a “tipping point” in September ice area and volume will be

  6. The research of Polar sea ice and its role in climate change

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    As an important part of global climate system, the Polar sea ice is effecting on global climate changes through ocean surface radiation balance, mass balance, energy balance as well as the circulating of sea water temperature and salinity. Sea ice research has a centuries-old history. The many correlative sea ice projects were established through the extensive international cooperation during the period from the primary research of intensity and the bearing capacity of sea ice to the development of sea/ice/air coupled model. Based on these researches, the sea ice variety was combined with the global climate change. All research about sea ice includes: the physical properties and processes of sea ice and its snow cover, the ecosystem of sea ice regions, sea ice and upper snow albedo, mass balance of sea ice regions, sea ice and climate coupled model. The simulation suggests that the both of the area and volume of polar sea ice would be reduced in next century. With the developing of the sea ice research, more scientific issues are mentioned. Such as the interaction between sea ice and the other factors of global climate system, the seasonal and regional distribution of polar sea ice thickness, polar sea ice boundary and area variety trends, the growth and melt as well as their influencing factors, the role of the polynya and the sea/air interactions. We should give the best solutions to all of the issues in future sea ice studying.

  7. Interdecadal changes in snow depth on Arctic sea ice

    Science.gov (United States)

    Webster, Melinda A.; Rigor, Ignatius G.; Nghiem, Son V.; Kurtz, Nathan T.; Farrell, Sinead L.; Perovich, Donald K.; Sturm, Matthew

    2014-08-01

    Snow plays a key role in the growth and decay of Arctic sea ice. In winter, it insulates sea ice from cold air temperatures, slowing sea ice growth. From spring to summer, the albedo of snow determines how much insolation is absorbed by the sea ice and underlying ocean, impacting ice melt processes. Knowledge of the contemporary snow depth distribution is essential for estimating sea ice thickness and volume, and for understanding and modeling sea ice thermodynamics in the changing Arctic. This study assesses spring snow depth distribution on Arctic sea ice using airborne radar observations from Operation IceBridge for 2009-2013. Data were validated using coordinated in situ measurements taken in March 2012 during the Bromine, Ozone, and Mercury Experiment (BROMEX) field campaign. We find a correlation of 0.59 and root-mean-square error of 5.8 cm between the airborne and in situ data. Using this relationship and IceBridge snow thickness products, we compared the recent results with data from the 1937, 1954-1991 Soviet drifting ice stations. The comparison shows thinning of the snowpack, from 35.1 ± 9.4 to 22.2 ± 1.9 cm in the western Arctic, and from 32.8 ± 9.4 to 14.5 ± 1.9 cm in the Beaufort and Chukchi seas. These changes suggest a snow depth decline of 37 ± 29% in the western Arctic and 56 ± 33% in the Beaufort and Chukchi seas. Thinning is negatively correlated with the delayed onset of sea ice freezeup during autumn.

  8. 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.

  9. NWS Alaska Sea Ice Program: Operations and Decision Support Services

    Science.gov (United States)

    Schreck, M. B.; Nelson, J. A., Jr.; Heim, R.

    2015-12-01

    The National Weather Service's Alaska Sea Ice Program is designed to service customers and partners operating and planning operations within Alaska waters. The Alaska Sea Ice Program offers daily sea ice and sea surface temperature analysis products. The program also delivers a five day sea ice forecast 3 times each week, provides a 3 month sea ice outlook at the end of each month, and has staff available to respond to sea ice related information inquiries. These analysis and forecast products are utilized by many entities around the state of Alaska and nationally for safety of navigation and community strategic planning. The list of current customers stem from academia and research institutions, to local state and federal agencies, to resupply barges, to coastal subsistence hunters, to gold dredgers, to fisheries, to the general public. Due to a longer sea ice free season over recent years, activity in the waters around Alaska has increased. This has led to a rise in decision support services from the Alaska Sea Ice Program. The ASIP is in constant contact with the National Ice Center as well as the United States Coast Guard (USCG) for safety of navigation. In the past, the ASIP provided briefings to the USCG when in support of search and rescue efforts. Currently, not only does that support remain, but our team is also briefing on sea ice outlooks into the next few months. As traffic in the Arctic increases, the ASIP will be called upon to provide more and more services on varying time scales to meet customer needs. This talk will address the many facets of the current Alaska Sea Ice Program as well as delve into what we see as the future of the ASIP.

  10. First Results from the ASIBIA (Arctic Sea-Ice, snow, Biogeochemistry and Impacts on the Atmosphere) Sea-Ice Chamber

    Science.gov (United States)

    Frey, M. M.; France, J.; von Glasow, R.; Thomas, M.

    2015-12-01

    The ocean-ice-atmosphere system is very complex, and there are numerous challenges with conducting fieldwork on sea-ice including costs, safety, experimental controls and access. By creating a new coupled Ocean-Sea-Ice-(Snow)-Atmosphere facility at the University of East Anglia, UK, we are able to perform controlled investigations in areas such as sea-ice physics, physicochemical and biogeochemical processes in sea-ice, and to quantify the bi-directional flux of gases in established, freezing and melting sea-ice. The environmental chamber is capable of controlled programmable temperatures from -55°C to +30°C, allowing a full range of first year sea-ice growing conditions in both the Arctic and Antarctic to be simulated. The sea-ice tank within the chamber measures 2.4 m x 1.4 m x 1 m water depth, with an identically sized Teflon film atmosphere on top of the tank. The tank and atmosphere forms a coupled, isolated mesocosm. Above the atmosphere is a light bank with dimmable solar simulation LEDs, and UVA and UVB broadband fluorescent battens, providing light for a range of experiments such as under ice biogeochemistry and photochemistry. Ice growth in the tank will be ideally suited for studying first-year sea-ice physical properties, with in-situ ice-profile measurements of temperature, salinity, conductivity, pressure and spectral light transmission. Under water and above ice cameras are installed to observe the physical development of the sea-ice. The ASIBIA facility is also well equipped for gas exchange and diffusion studies through sea-ice with a suite of climate relevant gas measuring instruments (CH4, CO2, O3, NOx, NOy permanently installed, further instruments available) able to measure either directly in the atmospheric component, or via a membrane for water side dissolved gases. Here, we present the first results from the ASIBIA sea-ice chamber, focussing on the physical development of first-year sea-ice and show the future plans for the facility over

  11. SAR Ice Image Classification Using Parallelepiped Classifier Based on Gram-Schmidt Spectral Technique

    Directory of Open Access Journals (Sweden)

    A.Vanitha

    2013-05-01

    Full Text Available Synthetic Aperture Radar (SAR is a special type of imaging radar that involves advanced technology and complex data processing to obtain de tailed images from the lake surface. Lake ice typically reflects more of the radar energy emi tted by the sensor than the surrounding area, which makes it easy to distinguish between the wate r and the ice surface. In this research work, SAR images are used for ice classification based on supervised and unsupervised classification algorithms. In the pre-processing stage, Hue satura tion value (HSV and Gram–Schmidt spectral sharpening techniques are applied for shar pening and resampling to attain high- resolution pixel size. Based on the performance eva luation metrics it is proved that Gram- Schmidt spectral sharpening performs better than sh arpening the HSV between the boundaries. In classification stage, Gram–Schmidt spectral tech nique based sharpened SAR images are used as the input for classifying using parallelepiped a nd ISO data classifier. The performances of the classifiers are evaluated with overall accuracy and kappa coefficient. From the experimental results, ice from water is classified more accurately in the parallelepiped supervised classification algorithm.

  12. Amplification of European Little Ice Age by sea ice-ocean-atmosphere feedbacks

    Science.gov (United States)

    Lehner, Flavio; Born, Andreas; Raible, Christoph C.; Stocker, Thomas F.

    2013-04-01

    The transition from the Medieval Climate Anomaly (~950-1250 AD) to the Little Ice Age (~1400-1700 AD) is believed to have been driven by an interplay of external forcing and climate system-internal variability. While the hemispheric signal seems to have been dominated by solar irradiance and volcanic eruptions, the understanding of mechanisms shaping the climate on continental scale is less robust. Examining an ensemble of transient model simulations as well as a new type of sensitivity experiments with artificial sea ice growth, we identify a sea ice-ocean-atmosphere feedback mechanism that amplifies the Little Ice Age cooling in the North Atlantic-European region and produces the temperature pattern expected from reconstructions. Initiated by increasing negative forcing, the Arctic sea ice substantially expands at the beginning of the Little Ice Age. The excess of sea ice is exported to the subpolar North Atlantic, where it melts, thereby weakening convection of the ocean. As a consequence, northward ocean heat transport is reduced, reinforcing the expansion of the sea ice and the cooling of the Northern Hemisphere. In the Nordic Seas, sea surface height anomalies cause the oceanic recirculation to strengthen at the expense of the warm Barents Sea inflow, thereby further reinforcing sea ice growth in the Barents Sea. The absent ocean-atmosphere heat flux in the Barents Sea results in an amplified cooling over Northern Europe. The positive nature of this feedback mechanism enables sea ice to remain in an expanded state for decades to centuries and explain sustained cold periods over Europe such as the Little Ice Age. Support for the feedback mechanism comes from recent proxy reconstructions around the Nordic Seas.

  13. NUMERICAL SIMULATIONS OF SEA ICE WITH DIFFERENT ADVECTION SCHEMES

    Institute of Scientific and Technical Information of China (English)

    LIU Xi-ying

    2011-01-01

    Numerical simulations are carried out for sea ice with four different advection schemes to study their effects on the simulation results.The sea ice model employed here is the Sea Ice Simulator (SIS) of the Geophysical Fluid Dynamics Laboratory (GFDL) Modular Ocean Model version 4b (MOM4b) and the four advection schemes are, the upwind scheme originally used in the SIS, the Multi-Dimensional Positive Advection (MDPA) scheme, the Incremental Remapping Scheme (IRS) and the Two Step Shape Preserving (TSSP) scheme.The latter three schemes are newly introduced.To consider the interactions between sea ice and ocean, a mixed layer ocean model is introduced and coupled to the SIS.The coupled model uses a tri-polar coordinate with 120×65 grids,covering the whole earth globe, in the horizontal plane.Simulation results in the northern high latitudes are analyzed.In all simulations, the model reproduces the seasonal variation of sea ice in the northern high latitudes well.Compared with the results from the observation, the sea ice model produces some extra sea ice coverage in the Greenland Sea and Barents Sea in winter due to the exclusion of ocean current effects and the smaller simulated sea ice thickness in the Arctic basin.There are similar features among the results obtained with the introduced three advection schemes.The simulated sea ice thickness with the three newly introduced schemes are all smaller than that of the upwind scheme and the simulated sea ice velocities of movement are all smaller than that of the upwind scheme.There are more similarities shared in the results obtained with the MPDA and TSSP schemes.

  14. The Floe Size Distribution in the Marginal Ice Zone of the Beaufort and Chukchi Seas

    Science.gov (United States)

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

    2014-12-01

    Several key processes in the Marginal Ice Zone (MIZ) of the Arctic Ocean are related to the size of the ice floes, whose diameters range from meters to tens of kilometers. The floe size distribution (FSD) influences the mechanical properties of the ice cover, air-sea momentum and heat transfer, lateral melting, and light penetration. However, no existing sea-ice/ocean models currently simulate the FSD in the MIZ. Model development depends on observations of the FSD for parameterization, calibration, and validation. To support the development and implementation of the FSD in the Marginal Ice Zone Modeling and Assimilation System (MIZMAS), we have analyzed the FSD in the Beaufort and Chukchi seas using multiple sources of satellite imagery: NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua satellites (250 m pixel size), the USGS Landsat 8 satellite (80 m pixel size), the Canadian Space Agency's synthetic aperture radar (SAR) on RADARSAT (50 meter pixel size), and declassified National Technical Means imagery from the Global Fiducials Library (GFL) of the USGS (1 m pixel size). The procedure for identifying ice floes in the imagery begins with manually delineating cloud-free regions (if necessary). A threshold is then chosen to separate ice from water. Morphological operations and other semi-automated techniques are used to identify individual floes, whose properties are then easily calculated. We use the mean caliper diameter as the measure of floe size. The FSD is adequately described by a power-law in which the exponent characterizes the relative number of large and small floes. Changes in the exponent over time and space reflect changes in physical processes in the MIZ, such as sea-ice deformation, fracturing, and melting. We report results of FSD analysis for the spring and summer of 2013 and 2014, and show how the FSD will be incorporated into the MIZMAS model.

  15. Image Techniques for Identifying Sea-Ice Parameters

    Directory of Open Access Journals (Sweden)

    Qin Zhang

    2014-10-01

    Full Text Available The estimation of ice forces are critical to Dynamic Positioning (DP operations in Arctic waters. Ice conditions are important for the analysis of ice-structure interaction in an ice field. To monitor sea-ice conditions, cameras are used as field observation sensors on mobile sensor platforms in Arctic. Various image processing techniques, such as Otsu thresholding, k-means clustering, distance transform, Gradient Vector Flow (GVF Snake, mathematical morphology, are then applied to obtain ice concentration, ice types, and floe size distribution from sea-ice images to ensure safe operations of structures in ice covered regions. Those techniques yield acceptable results, and their effectiveness are demonstrated in case studies.

  16. Constraining ice mass loss from Jakobshavn Isbræ (Greenland) using InSAR-measured crustal uplift

    DEFF Research Database (Denmark)

    Liu, Lin; Wahr, John; Howat, Ian

    2012-01-01

    Jakobshavn Isbræ in west Greenland has been undergoing dramatic thinning since 1997. Applying the interferometric synthetic aperture radar (InSAR) technique to Radarsat-1 SAR data, we measure crustal uplift near Jakobshavn Isbræ caused by recent ice mass loss. The crustal uplift is predominantly....... Overall, our results suggest that despite the inherent difficulties of working with a signal that has significant large-scale components, InSAR-measured crustal deformation can be used to study the ice mass loss of a rapidly thinning glacier and its surrounding catchment, providing both a constraint...... on any existing model of ice mass loss and a data source that can be used to invert for ice mass loss. These new applications of InSAR can help to better understand a glacier’s rapid response to a warming climate....

  17. Age characteristics in a multidecadal Arctic sea ice simulation

    Energy Technology Data Exchange (ETDEWEB)

    Hunke, Elizabeth C [Los Alamos National Laboratory; Bitz, Cecllia M [UNIV. OF WASHINGTON

    2008-01-01

    Results from adding a tracer for age of sea ice to a sophisticated sea ice model that is widely used for climate studies are presented. The consistent simulation of ice age, dynamics, and thermodynamics in the model shows explicitly that the loss of Arctic perennial ice has accelerated in the past three decades, as has been seen in satellite-derived observations. Our model shows that the September ice age average across the Northern Hemisphere varies from about 5 to 8 years, and the ice is much younger (about 2--3 years) in late winter because of the expansion of first-year ice. We find seasonal ice on average comprises about 5% of the total ice area in September, but as much as 1.34 x 10{sup 6} km{sup 2} survives in some years. Our simulated ice age in the late 1980s and early 1990s declined markedly in agreement with other studies. After this period of decline, the ice age began to recover, but in the final years of the simulation very little young ice remains after the melt season, a strong indication that the age of the pack will again decline in the future as older ice classes fail to be replenished. The Arctic ice pack has fluctuated between older and younger ice types over the past 30 years, while ice area, thickness, and volume all declined over the same period, with an apparent acceleration in the last decade.

  18. Impacts of freshwater changes on Antarctic sea ice in an eddy-permitting sea-ice-ocean model

    Science.gov (United States)

    Haid, Verena; Iovino, Doroteaciro; Masina, Simona

    2017-06-01

    In a warming climate, satellite data indicate that the sea ice extent around Antarctica has increased over the last decades. One of the suggested explanations is the stabilizing effect of increased mass loss of the Antarctic ice sheet. Here, we investigate the sea ice response to changes in both the amount and the spatial distribution of freshwater input to the ocean by comparing a set of numerical sensitivity simulations with additional supply of water at the Antarctic ocean surface. We analyze the short-term response of the sea ice cover and the on-shelf water column to variations in the amount and distribution of the prescribed surface freshwater flux.Our results confirm that enhancing the freshwater input can increase the sea ice extent. Our experiments show a negative development of the sea ice extent only for extreme freshwater additions. We find that the spatial distribution of freshwater is of great influence on sea ice concentration and thickness as it affects sea ice dynamics and thermodynamics. For strong regional contrasts in the freshwater addition the dynamic response dominates the local change in sea ice, which generally opposes the thermodynamic response. Furthermore, we find that additional coastal runoff generally leads to fresher and warmer dense shelf waters.

  19. Seasonal sea ice changes in the Amundsen Sea, Antarctica, over the period of 1979–2014

    Directory of Open Access Journals (Sweden)

    S. E. Stammerjohn

    2015-06-01

    Full Text Available Abstract Recent attention has focused on accelerated glacial losses along the Amundsen Sea coast that result from changes in atmosphere and ocean circulation, with sea ice playing a mediating but not well-understood role. Here, we investigated how sea ice has changed in the Amundsen Sea over the period of 1979 to 2014, focusing on spatio-temporal changes in ice edge advance/retreat and percent sea ice cover in relation to changes in winds. In contrast to the widespread sea ice decreases to the east and increases to the west of the Amundsen Sea, sea ice changes in the Amundsen Sea were confined to three areas: (i offshore of the shelf break, (ii the southern Pine Island Polynya, and (iii the eastern Amundsen Sea Polynya. Offshore, a 2-month decrease in ice season duration coincided with seasonal shifts in wind speed and direction from March to May (relating to later ice advance and from September to August (relating to earlier retreat, consistent with reported changes in the depth/location of the Amundsen Sea Low. In contrast, sea ice decreases in the polynya areas corresponded to episodic or step changes in spring ice retreat (earlier by 1–2 months and were coincident with changes to Thwaites Iceberg Tongue (located between the two polynyas and increased southeasterly winds. Temporal correlations among these three areas were weak, indicating different local forcing and/or differential response to large-scale forcing. Although our analysis has shown that part of the variability can be explained by changes in winds or to the coastal icescape, an additional but unknown factor is how sea ice has responded to changes in ocean heat and freshwater inputs. Unraveling cause and effect, critical for predicting changes to this rapidly evolving ocean-ice shelf-sea ice system, will require in situ observations, along with improved remote sensing capabilities and ocean modeling.

  20. 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.

  1. Quantifying uncertainty and sensitivity in sea ice models

    Energy Technology Data Exchange (ETDEWEB)

    Urrego Blanco, Jorge Rolando [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Hunke, Elizabeth Clare [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Urban, Nathan Mark [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-07-15

    The Los Alamos Sea Ice model has a number of input parameters for which accurate values are not always well established. We conduct a variance-based sensitivity analysis of hemispheric sea ice properties to 39 input parameters. The method accounts for non-linear and non-additive effects in the model.

  2. MEASURING SEA ICE DRIFT VIA CROSS-CORRELATION OF RADAR ICE IMAGES

    Institute of Scientific and Technical Information of China (English)

    SUN He-quan; SHEN Yong-ming; Qiu Da-hong

    2004-01-01

    The motion of sea ice has a great effect on winter navigation, and oil field exploration in the Bohai Sea. It is very important to measure the ice drift accurately and efficiently. As a practical technique, radar imagery has been used for sea ice monitoring and forecasting for a long time. Combining with the radar imagery and cross-correlation technique, a new measurement method based on the cross-correlation of radar ice images is specified in this paper to obtain full field measurement of sea ice drift. The theory and fast implementation of cross-correlation are presented briefly in the paper, including the filtering method to modify the invalid vectors. To show deeply the validity of the present method, the velocity maps of sea ice drift are provided in the paper, which are calculated from the radar images grabbed in the Liaodong Gulf. The comparison with the traditional tracing method is also conducted.

  3. Physical characteristics of summer sea ice across the Arctic Ocean

    Science.gov (United States)

    Tucker, W. B.; Gow, A.J.; Meese, D.A.; Bosworth, H.W.; Reimnitz, E.

    1999-01-01

    Sea ice characteristics were investigated during July and August on the 1994 transect across the Arctic Ocean. Properties examined from ice cores included salinity, temperature, and ice structure. Salinities measured near zero at the surface, increasing to 3-4??? at the ice-water interface. Ice crystal texture was dominated by columnar ice, comprising 90% of the ice sampled. Surface albedos of various ice types, measured with radiometers, showed integrated shortwave albedos of 0.1 to 0.3 for melt ponds, 0.5 for bare, discolored ice, and 0.6 to 0.8 for a deteriorated surface or snow-covered ice. Aerial photography was utilized to document the distribution of open melt ponds, which decreased from 12% coverage of the ice surface in late July at 76??N to almost none in mid-August at 88??N. Most melt ponds were shallow, and depth bore no relationship to size. Sediment was pervasive from the southern Chukchi Sea to the north pole, occurring in bands or patches. It was absent in the Eurasian Arctic, where it had been observed on earlier expeditions. Calculations of reverse trajectories of the sediment-bearing floes suggest that the southernmost sediment was entrained during ice formation in the Beaufort Sea while more northerly samples probably originated in the East Siberian Sea, some as far west as the New Siberian Islands.

  4. Land-ice modeling for sea-level prediction

    Energy Technology Data Exchange (ETDEWEB)

    Lipscomb, William H [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2010-06-11

    There has been major progress in ice sheet modeling since IPCC AR4. We will soon have efficient higherorder ice sheet models that can run at ",1 km resolution for entire ice sheets, either standalone or coupled to GeMs. These models should significantly reduce uncertainties in sea-level predictions. However, the least certain and potentially greatest contributions to 21st century sea-level rise may come from ice-ocean interactions, especially in West Antarctica. This is a coupled modeling problem that requires collaboration among ice, ocean and atmosphere modelers.

  5. Quantifying the influence of sea ice on ocean microseism using observations from the Bering Sea, Alaska

    Science.gov (United States)

    Tsai, Victor C.; McNamara, Daniel E.

    2011-01-01

    Microseism is potentially affected by all processes that alter ocean wave heights. Because strong sea ice prevents large ocean waves from forming, sea ice can therefore significantly affect microseism amplitudes. Here we show that this link between sea ice and microseism is not only a robust one but can be quantified. In particular, we show that 75–90% of the variability in microseism power in the Bering Sea can be predicted using a fairly crude model of microseism damping by sea ice. The success of this simple parameterization suggests that an even stronger link can be established between the mechanical strength of sea ice and microseism power, and that microseism can eventually be used to monitor the strength of sea ice, a quantity that is not as easily observed through other means.

  6. Sea Ice Thickness, Freeboard, and Snow Depth products from Operation IceBridge Airborne Data

    Science.gov (United States)

    Kurtz, N. T.; Farrell, S. L.; Studinger, M.; Galin, N.; Harbeck, J. P.; Lindsay, R.; Onana, V. D.; Panzer, B.; Sonntag, J. G.

    2013-01-01

    The study of sea ice using airborne remote sensing platforms provides unique capabilities to measure a wide variety of sea ice properties. These measurements are useful for a variety of topics including model evaluation and improvement, assessment of satellite retrievals, and incorporation into climate data records for analysis of interannual variability and long-term trends in sea ice properties. In this paper we describe methods for the retrieval of sea ice thickness, freeboard, and snow depth using data from a multisensor suite of instruments on NASA's Operation IceBridge airborne campaign. We assess the consistency of the results through comparison with independent data sets that demonstrate that the IceBridge products are capable of providing a reliable record of snow depth and sea ice thickness. We explore the impact of inter-campaign instrument changes and associated algorithm adaptations as well as the applicability of the adapted algorithms to the ongoing IceBridge mission. The uncertainties associated with the retrieval methods are determined and placed in the context of their impact on the retrieved sea ice thickness. Lastly, we present results for the 2009 and 2010 IceBridge campaigns, which are currently available in product form via the National Snow and Ice Data Center

  7. Arctic sea ice decline contributes to thinning lake ice trend in northern Alaska

    Science.gov (United States)

    Alexeev, Vladimir A.; Arp, Christopher D.; Jones, Benjamin M.; Cai, Lei

    2016-07-01

    Field measurements, satellite observations, and models document a thinning trend in seasonal Arctic lake ice growth, causing a shift from bedfast to floating ice conditions. September sea ice concentrations in the Arctic Ocean since 1991 correlate well (r = +0.69, p Weather Research and Forecasting model output produced a 7% decrease in lake ice growth when 2007/08 sea ice was imposed on 1991/92 climatology and a 9% increase in lake ice growth for the opposing experiment. Here, we clearly link early winter ‘ocean-effect’ snowfall and warming to reduced lake ice growth. Future reductions in sea ice extent will alter hydrological, biogeochemical, and habitat functioning of Arctic lakes and cause sub-lake permafrost thaw.

  8. Sea-ice switches and abrupt climate change.

    Science.gov (United States)

    Gildor, Hezi; Tziperman, Eli

    2003-09-15

    We propose that past abrupt climate changes were probably a result of rapid and extensive variations in sea-ice cover. We explain why this seems a perhaps more likely explanation than a purely thermohaline circulation mechanism. We emphasize that because of the significant influence of sea ice on the climate system, it seems that high priority should be given to developing ways for reconstructing high-resolution (in space and time) sea-ice extent for past climate-change events. If proxy data can confirm that sea ice was indeed the major player in past abrupt climate-change events, it seems less likely that such dramatic abrupt changes will occur due to global warming, when extensive sea-ice cover will not be present.

  9. Physical Characteristics and Geobiology of 'Rotten' Arctic Sea Ice

    Science.gov (United States)

    Frantz, C. M.; Light, B.; Orellana, M. V.; Carpenter, S.; Junge, K.

    2015-12-01

    Arctic sea ice in its final stage of demise, "rotten ice", is characterized by seriously compromised structural integrity, making it difficult to collect and study. Consequently, little is known about the physical, chemical and biological properties of this ice type. Yet, as the Arctic melt season lengthens, this ice type will likely appear sooner and become more prevalent in the Arctic Ocean and its occurrence may be more common than satellite mapping and ice charts suggest (e.g., Barber et al., 2009). Here we present physical, chemical, biological, and optical measurements of first-year ice near Barrow, Alaska during the spring and summer of 2015. Samples represent a progression from solid, "springtime" shorefast ice (May); through melting, heavily melt-ponded, "summertime" shorefast ice (June); to the final stage of barely-intact, "rotten" ice collected from small floes Beaufort Sea (July). Results indicate that rotten ice exhibits low salinity, is well drained and has a lower density than its springtime counterpart. X-ray tomography of dimethyl phthalate-casted sea ice samples indicates differences in porosity and relative permeability in rotten ice vs. spring- and summertime ice. We also present a preliminary characterization of rotten sea ice as a microbial habitat using preliminary results of chemical measurements (nutrients, dissolved organic and inorganic carbon), and microbiological characterizations (concentrations and16S/18S rDNA-based identifications) from seawater vs. sea ice vs. sea ice brines. Optical measurements show that while decreased ice thickness and increased melt pond coverage cause an overall increase in solar radiation to the ocean as sea ice warms, rotten ice is actually less transparent to solar radiation than its spring- and summertime counterparts. These factors determine solar heating in the ocean and, ultimately, the potential for accelerated ice melting (e.g., Light et al., 2008). This work provides a foundation for understanding

  10. Arctic sea ice decline contributes to thinning lake ice trend in northern Alaska

    Science.gov (United States)

    Alexeev, Vladimir; Arp, Christopher D.; Jones, Benjamin M.; Cai, Lei

    2016-01-01

    Field measurements, satellite observations, and models document a thinning trend in seasonal Arctic lake ice growth, causing a shift from bedfast to floating ice conditions. September sea ice concentrations in the Arctic Ocean since 1991 correlate well (r = +0.69,p sea ice affects lakes, we conducted model experiments to simulate winters with years of high (1991/92) and low (2007/08) sea ice extent for which we also had field measurements and satellite imagery characterizing lake ice conditions. A lake ice growth model forced with Weather Research and Forecasting model output produced a 7% decrease in lake ice growth when 2007/08 sea ice was imposed on 1991/92 climatology and a 9% increase in lake ice growth for the opposing experiment. Here, we clearly link early winter 'ocean-effect' snowfall and warming to reduced lake ice growth. Future reductions in sea ice extent will alter hydrological, biogeochemical, and habitat functioning of Arctic lakes and cause sub-lake permafrost thaw.

  11. Topography and Penetration of the Greenland Ice Sheet Measured with Airborne SAR Interferometry

    DEFF Research Database (Denmark)

    Dall, Jørgen; Madsen, Søren Nørvang; Keller, K.

    2001-01-01

    A digital elevation model (DEM) of the Geikie ice sap in East Greenland has been generated from interferometric C-band synthetic aperture radar (SAR) data acquired with the airborne EMISAR system. GPS surveyed radar reflectors and an airborne laser altimeter supplemented the experiment. The accur......A digital elevation model (DEM) of the Geikie ice sap in East Greenland has been generated from interferometric C-band synthetic aperture radar (SAR) data acquired with the airborne EMISAR system. GPS surveyed radar reflectors and an airborne laser altimeter supplemented the experiment....... The accuracy of the SAR DEM is about 1.5 m. The mean difference between the laser heights and the SAR heights changes from 0 m in the soaked zone to a maximum of 13 m in the percolation zone. This is explained by the fact that the snow in the soaked zone contains liquid water which attenuates the radar signals......, while the transparency of the firn in the percolation zone makes volume scattering dominate at the higher elevations. For the first time, the effective penetration has been measured directly as the difference between the interferometric heights and reference heights obtained with GPS and laser altimetry....

  12. Wave observation in the marginal ice zone with the TerraSAR-X satellite

    Science.gov (United States)

    Gebhardt, Claus; Bidlot, Jean-Raymond; Gemmrich, Johannes; Lehner, Susanne; Pleskachevsky, Andrey; Rosenthal, Wolfgang

    2016-07-01

    This article investigates the penetration of ocean waves into the marginal ice zone (MIZ), observed by satellite, and likewise provides a basis for the future cross-validation of respective models. To this end, synthetic aperture radar images from the TerraSAR-X satellite (TS-X) and numerical simulations of the European Centre for Medium-Range Weather Forecasts (ECMWF) are used. The focus is an event of swell waves, developed during a storm passage in the Atlantic, penetrating deeply into the MIZ off the coast of Eastern Greenland in February 2013. The TS-X scene which is the basis for this investigation extends from the ice-free open ocean to solid ice. The variation of the peak wavelength is analysed and potential sources of variability are discussed. We find an increase in wavelength which is consistent with the spatial dispersion of deep water waves, even within the ice-covered region.

  13. Ice Velocity Measurement from SAR: Comparison of Sentinel-1A and RADARSAT-2

    DEFF Research Database (Denmark)

    Kusk, Anders; Dall, Jørgen

    Mapping the velocity fields of the continental ice sheets and their outlet glaciers is important in order to monitor and model the response of the cryosphere to global climate change. Since the mid 1990s, space-based SAR data have enabled measurement of ice velocities on a continental scale...... fields. Two Greenland-wide RADARSAT-2 campaigns were carried out during January-March 2014, and a smaller one in December 2014-February 2015. Ice velocity maps from both campaigns will be presented. A preliminary ice velocity map from the former campaign is attached with this abstract, while the latter...... with this abstract. The overlapping temporal coverage of the second RADARSAT-2 campaign and the first Sentinel-1 campaign allows a comparison of the two sensors in terms of: Impact of differing imaging modes (stripmap vs TOPS). The better coverage of Sentinel-1 is at the cost of a reduced azimuth resolution, however...

  14. Sea ice thickness estimation in the Bohai Sea using geostationary ocean color imager data

    Institute of Scientific and Technical Information of China (English)

    LIU Wensong; SHENG Hui; ZHANG Xi

    2016-01-01

    A method to estimate the thickness of the sea ice of the Bohai Sea is proposed using geostationary ocean color imager (GOCI) data and then applied to the dynamic monitoring of the sea ice thickness in the Bohai Sea during the winter of 2014 to 2015. First of all, a model is given between the GOCI shortwave broadband albedo and the reflectance of each band with high temporal resolution GOCI data. Then, the relationship model between the sea ice thickness and the GOCI shortwave broadband albedo is established and applied to the thickness extraction of the sea ice in the Bohai Sea. Finally, the sea ice thickness extraction method is tested by the results based on the MODIS data, thermodynamic empirical models (Lebedev and Zubov), and thein situ ice thickness data. The test results not only indicated that the sea ice thickness retrieval method based on the GOCI data was a good correlation (r2>0.86) with the sea ice thickness retrieved by the MODIS and thermodynamic empirical models, but also that the RMS is only 6.82 cm different from the thickness of the sea ice based on the GOCI andin situ data.

  15. Nonlinear threshold behavior during the loss of Arctic sea ice

    CERN Document Server

    Eisenman, I; 10.1073/pnas.0806887106

    2008-01-01

    In light of the rapid recent retreat of Arctic sea ice, a number of studies have discussed the possibility of a critical threshold (or "tipping point") beyond which the ice-albedo feedback causes the ice cover to melt away in an irreversible process. The focus has typically been centered on the annual minimum (September) ice cover, which is often seen as particularly susceptible to destabilization by the ice-albedo feedback. Here we examine the central physical processes associated with the transition from ice-covered to ice-free Arctic Ocean conditions. We show that while the ice-albedo feedback promotes the existence of multiple ice cover states, the stabilizing thermodynamic effects of sea ice mitigate this when the Arctic Ocean is ice-covered during a sufficiently large fraction of the year. These results suggest that critical threshold behavior is unlikely during the approach from current perennial sea ice conditions to seasonally ice-free conditions. In a further warmed climate, however, we find that a ...

  16. Geometrical constraints on the evolution of ridged sea ice

    Science.gov (United States)

    Amundrud, Trisha L.; Melling, Humfrey; Ingram, R. Grant

    2004-06-01

    A numerical model of the evolving draft distribution of seasonal pack ice is driven by freezing and ice field compression in one dimension. Spatial transects of sea ice draft acquired during winter in the Beaufort Sea are used to evaluate the model. Histograms obtained by ice-profiling sonar on subsea moorings reveal changes in the draft distribution, while observations of ice velocity by Doppler sonar allow calculation of the strain to which the draft distribution is responding. Numerical diffusion in thermal ice growth is controlled using a remapping algorithm. Mechanical redistribution algorithms in common use generate much more deep ridged ice than is observed. Geometric constraints on ridge-keel development that reflect the finite extent of level floes available for ridge building and the true average shape of keels produce more realistic results. In the seasonal pack ice of the Beaufort Sea, 75% of all floes are too small to provide a volume of ice sufficient to construct a keel of draft equal to that commonly assumed in ice dynamics modeling. On average, the distribution of draft within keels has a negative exponential form, implying a cusped keel shape with more area on the thinner flanks than at the crest; models commonly assume a uniform redistribution of ice into a keel of triangular shape. Clearly, the spatial organization of ice within seasonal pack or, equivalently, the existence of ridges and floes should be an acknowledged factor in redistribution theory for pack ice thickness.

  17. Relationship between Hadley circulation and sea ice extent in the Bering Sea

    Institute of Scientific and Technical Information of China (English)

    ZHOU BoTao; WANG HuiJun

    2008-01-01

    The linkage between Hadley circulation (HC) and sea ice extent in the Bering Sea during March-April is investigated through an analysis of observed data in this research. It is found that HC is negatively correlated to the sea ice extent in the Bering Sea, namely, strong (weak) HC is corresponding to less (more) sea ice in the Bering Sea. The present study also addresses the large-scale atmospheric general circulation changes underlying the relationship between HC and sea ice in the Bering Sea. It follows that a positive phase of HC corresponds to westward located Aleutian low, anomalous southerlies over the eastern North Pacific and higher temperature in the Bering Sea, providing unfavorable atmospheric and thermal conditions for the sea ice forming, and thus sea ice extent in the Bering Sea is decreased, and vice versa. In addition, it is further identified that East Asian-North Pacific-North America telecon-nection may play an important role in linking HC and changes of atmospheric circulations as well as sea ice in the Bering Sea.

  18. Fram Strait sea ice export variability and September Arctic sea ice extent over the last 80 years

    Science.gov (United States)

    Smedsrud, Lars H.; Halvorsen, Mari H.; Stroeve, Julienne C.; Zhang, Rong; Kloster, Kjell

    2017-01-01

    A new long-term data record of Fram Strait sea ice area export from 1935 to 2014 is developed using a combination of satellite radar images and station observations of surface pressure across Fram Strait. This data record shows that the long-term annual mean export is about 880 000 km2, representing 10 % of the sea-ice-covered area inside the basin. The time series has large interannual and multi-decadal variability but no long-term trend. However, during the last decades, the amount of ice exported has increased, with several years having annual ice exports that exceeded 1 million km2. This increase is a result of faster southward ice drift speeds due to stronger southward geostrophic winds, largely explained by increasing surface pressure over Greenland. Evaluating the trend onwards from 1979 reveals an increase in annual ice export of about +6 % per decade, with spring and summer showing larger changes in ice export (+11 % per decade) compared to autumn and winter (+2.6 % per decade). Increased ice export during winter will generally result in new ice growth and contributes to thinning inside the Arctic Basin. Increased ice export during summer or spring will, in contrast, contribute directly to open water further north and a reduced summer sea ice extent through the ice-albedo feedback. Relatively low spring and summer export from 1950 to 1970 is thus consistent with a higher mid-September sea ice extent for these years. Our results are not sensitive to long-term change in Fram Strait sea ice concentration. We find a general moderate influence between export anomalies and the following September sea ice extent, explaining 18 % of the variance between 1935 and 2014, but with higher values since 2004.

  19. Smoluchowski coagulation models of sea ice thickness distribution dynamics

    Science.gov (United States)

    Godlovitch, D.; Illner, R.; Monahan, A.

    2011-12-01

    Sea ice thickness distributions display a ubiquitous exponential decrease with thickness. This tail characterizes the range of ice thickness produced by mechanical redistribution of ice through the process of ridging, rafting, and shearing. We investigate how well the thickness distribution can be simulated by representing mechanical redistribution as a generalized stacking process. Such processes are naturally described by a well-studied class of models known as Smoluchowski Coagulation Models (SCMs), which describe the dynamics of a population of fixed-mass "particles" which combine in pairs to form a "particle" with the combined mass of the constituent pair at a rate which depends on the mass of the interacting particles. Like observed sea ice thickness distributions, the mass distribution of the populations generated by SCMs has an exponential or quasi-exponential form. We use SCMs to model sea ice, identifying mass-increasing particle combinations with thickness-increasing ice redistribution processes. Our model couples an SCM component with a thermodynamic component and generates qualitatively accurate thickness distributions with a variety of rate kernels. Our results suggest that the exponential tail of the sea ice thickness distribution arises from the nature of the ridging process, rather than specific physical properties of sea ice or the spatial arrangement of floes, and that the relative strengths of the dynamic and thermodynamic processes are key in accurately simulating the rate at which the sea ice thickness tail drops off with thickness.

  20. Global warming releases microplastic legacy frozen in Arctic Sea ice

    Science.gov (United States)

    Obbard, Rachel W.; Sadri, Saeed; Wong, Ying Qi; Khitun, Alexandra A.; Baker, Ian; Thompson, Richard C.

    2014-06-01

    When sea ice forms it scavenges and concentrates particulates from the water column, which then become trapped until the ice melts. In recent years, melting has led to record lows in Arctic Sea ice extent, the most recent in September 2012. Global climate models, such as that of Gregory et al. (2002), suggest that the decline in Arctic Sea ice volume (3.4% per decade) will actually exceed the decline in sea ice extent, something that Laxon et al. (2013) have shown supported by satellite data. The extent to which melting ice could release anthropogenic particulates back to the open ocean has not yet been examined. Here we show that Arctic Sea ice from remote locations contains concentrations of microplastics at least two orders of magnitude greater than those that have been previously reported in highly contaminated surface waters, such as those of the Pacific Gyre. Our findings indicate that microplastics have accumulated far from population centers and that polar sea ice represents a major historic global sink of man-made particulates. The potential for substantial quantities of legacy microplastic contamination to be released to the ocean as the ice melts therefore needs to be evaluated, as do the physical and toxicological effects of plastics on marine life.

  1. Sea ice growth rates from tide-driven visible banding

    Science.gov (United States)

    Turner, Kate E.; Smith, Inga J.; Tison, Jean-Louis; Verbeke, Véronique; McGuinness, Mark; Ingham, Malcolm; Vennell, Ross; Trodahl, Joe

    2017-06-01

    In this paper, periodic tide-current-driven banding in a sea-ice core is demonstrated as a measure of the growth rate of first-year sea ice at congelation-ice depths. The study was performed on a core from the eastern McMurdo Sound, exploiting the well-characterized tidal pattern at the site. It points the way to a technique for determining early-season ice growth rates from late-season cores, in areas where under ice currents are known to be tidally dominated and the ice is landfast, thus providing data for a time of year when thin ice prevents direct thickness (and therefore growth rate) measurements. The measured results were compared to the growth-versus-depth predicted by a thermodynamic model.Plain Language SummaryIt is currently very difficult to measure sea-ice growth rates, due to the danger of traveling on thin ice early in the growing season. This paper introduces the use of tidal patterns to determine sea-ice growth rates at the end of the growing season, when ice cores can be taken. The technique utilizes the visible light and dark bands that are often present in sea ice near land, and are driven by changes in the tidal current beneath the ice. As well as being important for climate research, this method could contribute to the understanding biological ecosystems within the ice, by providing a method to date depths in an ice core where particular organisms are observed or samples taken.

  2. Optical properties of sea ice in Liaodong Bay, China

    Science.gov (United States)

    Xu, Zhantang; Yang, Yuezhong; Wang, Guifen; Cao, Wenxi; Li, Zhijun; Sun, Zhaohua

    2012-03-01

    Many industrial, agricultural, and residential areas surrounding Liaodong Bay are responsible for much of the particulate matter (PM) and colored dissolved organic matter (CDOM) found in the sea ice in the bay. Understanding the optical properties of "dirty" sea ice is important for analyzing remote sensing data and calculating energy balances. We designed a hyperspectral radiation instrument to observe the optical properties of sea ice. The results show that albedo peaks ranged from 0.3 to 0.85 and that the peaks shifted to a longer wavelength for high PM and CDOM concentrations. The absorption and scattering coefficients for sea ice were obtained. The bulk absorption coefficient shows that bulk absorption is primarily determined by PM and CDOM at shorter wavelengths, while pure ice and brine pockets become more important at longer wavelengths. Scattering coefficients for sea ice ranged from 197 to 1072 m-1, and showed consistent variations with gas bubble and brine pocket concentrations. The effects of PM and CDOM on the bulk absorption coefficient of sea ice were studied. At 440 nm, particulates accounted for 55-98% and CDOM accounted for 2-37% of the bulk absorption. Ratios between particulate absorption and bulk absorption for sea ice were almost constant from 400 to 550 nm, and began to decrease sharply for wavelengths >550 nm. Ratios between CDOM and bulk absorption decreased almost linearly with increasing wavelength.

  3. What sea-ice biogeochemical modellers need from observers

    Directory of Open Access Journals (Sweden)

    Nadja Steiner

    2016-02-01

    Full Text Available Abstract Numerical models can be a powerful tool helping to understand the role biogeochemical processes play in local and global systems and how this role may be altered in a changing climate. With respect to sea-ice biogeochemical models, our knowledge is severely limited by our poor confidence in numerical model parameterisations representing those processes. Improving model parameterisations requires communication between observers and modellers to guide model development and improve the acquisition and presentation of observations. In addition to more observations, modellers need conceptual and quantitative descriptions of the processes controlling, for example: primary production and diversity of algal functional types in sea ice, ice algal growth, release from sea ice, heterotrophic remineralisation, transfer and emission of gases (e.g., DMS, CH4, BrO, incorporation of seawater components in growing sea ice (including Fe, organic and inorganic carbon, and major salts and subsequent release; CO2 dynamics (including CaCO3 precipitation, flushing and supply of nutrients to sea-ice ecosystems; and radiative transfer through sea ice. These issues can be addressed by focused observations, as well as controlled laboratory and field experiments that target specific processes. The guidelines provided here should help modellers and observers improve the integration of measurements and modelling efforts and advance toward the common goal of understanding biogeochemical processes in sea ice and their current and future impacts on environmental systems.

  4. Ice Freeze-up and Break-up Detection of Shallow Lakes in Northern Alaska with Spaceborne SAR

    Directory of Open Access Journals (Sweden)

    Cristina M. Surdu

    2015-05-01

    Full Text Available Shallow lakes, with depths less than ca. 3.5–4 m, are a ubiquitous feature of the Arctic Alaskan Coastal Plain, covering up to 40% of the land surface. With such an extended areal coverage, lakes and their ice regimes represent an important component of the cryosphere. The duration of the ice season has major implications for the regional and local climate, as well as for the physical and biogeochemical processes of the lakes. With day and night observations in all weather conditions, synthetic aperture radar (SAR sensors provide year-round acquisitions. Monitoring the evolution of radar backscatter (σ° is useful for detecting the timing of the beginning and end of the ice season. Analysis of the temporal evolution of C-band σ° from Advanced Synthetic Aperture Radar (ASAR Wide Swath and RADARSAT-2 ScanSAR, with a combined frequency of acquisitions from two to five days, was employed to evaluate the potential of SAR to detect the timing of key lake-ice events. SAR observations from 2005 to 2011 were compared to outputs of the Canadian Lake Ice Model (CLIMo. Model simulations fall within similar ranges with those of the SAR observations, with a mean difference between SAR observations and model simulations of only one day for water-clear-of-ice (WCI from 2006 to 2010. For freeze onset (FO, larger mean differences were observed. SAR analysis shows that the mean FO date for these shallow coastal lakes is 30 September and the mean WCI date is 5 July. Results reveal that greater variability existed in the mean FO date (up to 26 days than in that of melt onset (MO (up to 12 days and in that of WCI (6 days. Additionally, this study also identifies limitations and provides recommendations for future work using C-band SAR for monitoring the lake- ice phenology of shallow Arctic lakes.

  5. Fine-resolution simulation of surface current and sea ice in the Arctic Mediterranean Seas

    Institute of Scientific and Technical Information of China (English)

    LIU Xiying; ZHANG Xuehong; YU Rucong; LIU Hailong; LI Wei

    2007-01-01

    A fine-resolution model is developed for ocean circulation simulation in the National Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG),Chinese Academy of Sciences, and is applied to simulate surface current and sea ice variations in the Arctic Mediterranean Seas. A dynamic sea ice model in elastic-viscous-plastic rheology and a thermodynamic sea ice model are employed. A 200-year simulation is performed and a dimatological average of a 10-year period (141 st-150 th) is presented with focus on sea ice concentration and surface current variations in the Arctic Mediterranean Seas. The model is able to simulate well the East Greenland Current, Beaufort Gyre and the Transpolar Drift, but the simulated West Spitsbergen Current is small and weak. In the March climatology, the sea ice coverage can be simulated well except for a bit more ice in east of Spitsbergen Island. The result is also good for the September scenario except for less ice concentration east of Greenland and greater ice concentration near the ice margin. The extra ice east of Spitsbergen Island is caused by sea ice current convergence forced by atmospheric wind stress.

  6. Contributing factors to an enhanced ice albedo feedback in Arctic sea ice

    Science.gov (United States)

    Perovich, D. K.; Jones, K. F.; Light, B.; Holland, M. M.

    2012-12-01

    The Arctic sea ice cover is in decline. In recent years there has been a decrease in summer ice area; a thinning of the ice cover; an increase in the amount of seasonal ice; an earlier onset of summer melt; and a later start of fall freeze up. Decreases in ice concentration substantially increase solar heat input to the ocean. Earlier dates of melt onset reduce ice albedo during a period when incident solar irradiance is large increasing solar heat input to the ice. Seasonal sea ice typically has a smaller albedo than perennial ice throughout the melt season. Thus, the observed shift to a seasonal ice cover causes greater solar heat input to the ice and more melting thereby accelerating ice decay. Thinner ice results in greater transmission of solar heat to the upper ocean, where it contributes to bottom melting, lateral melting, and warming of the water. All of these changes enhance the amount of solar energy deposited in the ice ocean system, and increasing ice melt. We will examine the relative magnitude of each of these changes individually as well as their collective contribution to the ice albedo feedback.

  7. 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.

  8. Victoria Land, Ross Sea, and Ross Ice Shelf, Antarctica

    Science.gov (United States)

    2002-01-01

    On December 19, 2001, MODIS acquired data that produced this image of Antarctica's Victoria Land, Ross Ice Shelf, and the Ross Sea. The coastline that runs up and down along the left side of the image denotes where Victoria Land (left) meets the Ross Ice Shelf (right). The Ross Ice Shelf is the world's largest floating body of ice, approximately the same size as France. Credit: Jacques Descloitres, MODIS Land Rapid Response Team, NASA/GSFC

  9. Influence of ice thickness and surface properties on light transmission through Arctic sea ice

    Science.gov (United States)

    Katlein, Christian; Arndt, Stefanie; Nicolaus, Marcel; Perovich, Donald K.; Jakuba, Michael V.; Suman, Stefano; Elliott, Stephen; Whitcomb, Louis L.; McFarland, Christopher J.; Gerdes, Rüdiger; Boetius, Antje; German, Christopher R.

    2015-09-01

    The observed changes in physical properties of sea ice such as decreased thickness and increased melt pond cover severely impact the energy budget of Arctic sea ice. Increased light transmission leads to increased deposition of solar energy in the upper ocean and thus plays a crucial role for amount and timing of sea-ice-melt and under-ice primary production. Recent developments in underwater technology provide new opportunities to study light transmission below the largely inaccessible underside of sea ice. We measured spectral under-ice radiance and irradiance using the new Nereid Under-Ice (NUI) underwater robotic vehicle, during a cruise of the R/V Polarstern to 83°N 6°W in the Arctic Ocean in July 2014. NUI is a next generation hybrid remotely operated vehicle (H-ROV) designed for both remotely piloted and autonomous surveys underneath land-fast and moving sea ice. Here we present results from one of the first comprehensive scientific dives of NUI employing its interdisciplinary sensor suite. We combine under-ice optical measurements with three dimensional under-ice topography (multibeam sonar) and aerial images of the surface conditions. We investigate the influence of spatially varying ice-thickness and surface properties on the spatial variability of light transmittance during summer. Our results show that surface properties such as melt ponds dominate the spatial distribution of the under-ice light field on small scales (<1000 m2), while sea ice-thickness is the most important predictor for light transmission on larger scales. In addition, we propose the use of an algorithm to obtain histograms of light transmission from distributions of sea ice thickness and surface albedo.

  10. Influence of ice thickness and surface properties on light transmission through Arctic sea ice

    Science.gov (United States)

    Katlein, C.; Arndt, S.; Nicolaus, M.; Perovich, D. K.; Jakuba, M.; Suman, S.; Elliott, S.; Whitcomb, L. L.; McFarland, C.; Gerdes, R.; Boetius, A.

    2015-12-01

    The changes in physical properties of sea ice such as decreased thickness and increased melt pond cover observed over the last decades severely impact the energy budget of Arctic sea ice. Increased light transmission leads to increased deposition of solar energy in the upper ocean and thus plays a crucial role in the amount and timing of sea-ice-melt and under-ice primary production. Recent developments in underwater technology provide new opportunities to undertake challenging research at the largely inaccessible underside of sea ice. We measured spectral under-ice radiance and irradiance onboard the new Nereid Under-Ice (NUI) underwater robotic vehicle, during a cruise of the R/V Polarstern to 83°N 6°W in the Arctic Ocean in July 2014. NUI is a next generation hybrid remotely operated vehicle (H-ROV) designed for both remotely-piloted and autonomous surveys underneath land-fast and moving sea ice. Here we present results from one of the first comprehensive scientific dives of NUI employing its interdisciplinary sensor suite. We combine under-ice optical measurements with three-dimensional under-ice topography and aerial images of the surface conditions. We investigate the influence of spatially varying ice-thickness and surface properties during summer on the spatial variability of light transmittance. Results show that surface properties dominate the spatial distribution of the under-ice light field on small scales (<1000m²), while sea ice-thickness is the most important predictor for light transmission on larger scales. In addition, we suggest an algorithm to obtain histograms of light transmission from distributions of sea ice thickness and surface albedo.

  11. Pacific Walrus Response to Arctic Sea Ice Losses

    Science.gov (United States)

    Jay, Chadwick V.; Fischbach, Anthony S.

    2008-01-01

    Sea ice plays an important role in the life of the Pacific walrus (Odobenus rosmarus divergens). U.S. Geological Survey (USGS) scientists are seeking to understand how losses of sea ice during summer over important foraging grounds in the Chukchi Sea will affect walruses. USGS scientists recently modified a remotely deployed satellite radio-tag that will aid in studying walrus foraging habitats and behaviors. Information from the tags will help USGS understand how walruses are responding to their changing environment.

  12. On the assimilation of ice velocity and concentration data into large-scale sea ice models

    Directory of Open Access Journals (Sweden)

    V. Dulière

    2007-03-01

    Full Text Available Data assimilation into sea ice models designed for climate studies has started about 15 years ago. In most of the studies conducted so far, it is assumed that the improvement brought by the assimilation is straightforward. However, some studies suggest this might not be true. In order to elucidate this question and to find an appropriate way to further assimilate sea ice concentration and velocity observations into a global sea ice-ocean model, we analyze here results from a number of twin experiments (i.e. experiments in which the assimilated data are model outputs carried out with a simplified model of the Arctic sea ice pack. Our objective is to determine to what degree the assimilation of ice velocity and/or concentration data improves the global performance of the model and, more specifically, reduces the error in the computed ice thickness. A simple optimal interpolation scheme is used, and outputs from a control run and from perturbed experiments without and with data assimilation are thoroughly compared. Our results indicate that, under certain conditions depending on the assimilation weights and the type of model error, the assimilation of ice velocity data enhances the model performance. The assimilation of ice concentration data can also help in improving the model behavior, but it has to be handled with care because of the strong connection between ice concentration and ice thickness.

    This study is preliminary study towards real observation data assimilation into NEMOLIM, a global sea ice-ocean model.

  13. Winter Sea Ice Mapping From Multi-Parameter Synthetic Aperture Radar Data

    Science.gov (United States)

    Rignot, E.; Drinkwater, M.

    1993-01-01

    This paper presents examples of quantitative improvements in classification accuracy of six winter ice conditions using SAR data resulting from the combination of multiple polarizations and frequencies.

  14. Modeling the seasonal evolution of the Arctic sea ice floe size distribution

    Directory of Open Access Journals (Sweden)

    Jinlun Zhang

    2016-09-01

    Full Text Available Abstract To better simulate the seasonal evolution of sea ice in the Arctic, with particular attention to the marginal ice zone, a sea ice model of the distribution of ice thickness, floe size, and enthalpy was implemented into the Pan-arctic Ice–Ocean Modeling and Assimilation System (PIOMAS. Theories on floe size distribution (FSD and ice thickness distribution (ITD were coupled in order to explicitly simulate multicategory FSD and ITD distributions simultaneously. The expanded PIOMAS was then used to estimate the seasonal evolution of the Arctic FSD in 2014 when FSD observations are available for model calibration and validation. Results indicate that the simulated FSD, commonly described equivalently as cumulative floe number distribution (CFND, generally follows a power law across space and time and agrees with the CFND observations derived from TerraSAR-X satellite images. The simulated power-law exponents also correlate with those derived using MODIS images, with a low mean bias of –2%. In the marginal ice zone, the modeled CFND shows a large number of small floes in winter because of stronger winds acting on thin, weak first-year ice in the ice edge region. In mid-spring and summer, the CFND resembles an upper truncated power law, with the largest floes mostly broken into smaller ones; however, the number of small floes is lower than in winter because floes of small sizes or first-year ice are easily melted away. In the ice pack interior there are fewer floes in late fall and winter than in summer because many of the floes are “welded” together into larger floes in freezing conditions, leading to a relatively flat CFND with low power-law exponents. The simulated mean floe size averaged over all ice-covered areas shows a clear annual cycle, large in winter and smaller in summer. However, there is no obvious annual cycle of mean floe size averaged over the marginal ice zone. The incorporation of FSD into PIOMAS results in reduced

  15. Measurements of sea ice proxies from Antarctic coastal shallow cores

    Science.gov (United States)

    Maffezzoli, Niccolò; Vallelonga, Paul; Spolaor, Andrea; Barbante, Carlo; Frezzotti, Massimo

    2015-04-01

    Despite its close relationship with climate, the climatic impact of sea ice remains only partially understood: an indication of this is the Arctic sea ice which is declining at a faster rate than models predict. Thus, the need for reliable sea ice proxies is of crucial importance. Among the sea ice proxies that can be extracted from ice cores, interest has recently been shown in the halogens Iodine (I) and Bromine (Br) (Spolaor, A., et al., 2013a, 2013b). The production of sea ice is a source of Sodium and Bromine aerosols through frost flower crystal formation and sublimation of salty blowing snow, while Iodine is emitted by the algae living underneath sea ice. We present here the results of Na, Br and I measurements in Antarctic shallow cores, drilled during a traverse made in late 2013 - early 2014 from Talos Dome (72° 00'S, 159°12'E) to GV7 (70° 41'S, 158° 51'E) seeking for sea ice signature. The samples were kept frozen until the analyses, that were carried out by Sector Field Mass Spectroscopy Inductive Coupled Plasma (SFMS-ICP): special precautions and experimental steps were adopted for the detection of such elements. The coastal location of the cores allows a clear signal from the nearby sea ice masses. The multiple cores are located about 50 km from each other and can help us to infer the provenance of the sea ice that contributed to the proxy signature. Moreover, by simultaneously determining other chemical elements and compounds in the snow, it is possible to determine the relative timing of their deposition, thus helping us to understand their processes of emission and deposition.

  16. The microwave scattering characteristics of sea ice in the Bohai Sea

    Institute of Scientific and Technical Information of China (English)

    LIU Meijie; DAI Yongshou; ZHANG Jie; ZHANG Xi; MENG Junmin; ZHU Xiuqin; YIN Yalei

    2016-01-01

    Microwave remote sensing has become the primary means for sea-ice research, and has been supported by a great deal of field experiments and theoretical studies regarding sea-ice microwave scattering. However, these studies have been barely carried in the Bohai Sea. The sea-ice microwave scattering mechanism was first developed for the thin sea ice with slight roughness in the Bohai Sea in the winter of 2012, and included the backscattering coefficients which were measured on the different conditions of three bands (L, C and X), two polarizations (HH and VV), and incident angles of 20° to 60°, using a ground-based scatterometer and the synchronous physical parameters of the sea-ice temperature, density, thickness, salinity, and so on. The theoretical model of the sea-ice electromagnetic scattering is obtained based on these physical parameters. The research regarding the sea-ice microwave scattering mechanism is carried out through two means, which includes the comparison between the field microwave scattering data and the simulation results of the theoretical model, as well as the feature analysis of the four components of the sea-ice electromagnetic scattering. It is revealed that the sea-ice microwave scattering data and the theoretical simulation results vary in the same trend with the incident angles. Also, there is a visible variant in the sensitivity of every component to the different bands. For example, the C and X bands are sensitive to the top surface, the X band is sensitive to the scatterers, and the L and C bands are sensitive to the bottom surface, and so on. It is suggested that the features of the sea-ice surfaces and scatterers can be retrieved by the further research in the future. This experiment can provide an experimental and theoretical foundation for research regarding the sea-ice microwave scattering characteristics in the Bohai Sea.

  17. A multivariate analysis of Antarctic sea ice since 1979

    Energy Technology Data Exchange (ETDEWEB)

    Magalhaes Neto, Newton de; Evangelista, Heitor [Universidade do Estado do Rio de Janeiro (Uerj), LARAMG - Laboratorio de Radioecologia e Mudancas Globais, Maracana, Rio de Janeiro, RJ (Brazil); Tanizaki-Fonseca, Kenny [Universidade do Estado do Rio de Janeiro (Uerj), LARAMG - Laboratorio de Radioecologia e Mudancas Globais, Maracana, Rio de Janeiro, RJ (Brazil); Universidade Federal Fluminense (UFF), Dept. Analise Geoambiental, Inst. de Geociencias, Niteroi, RJ (Brazil); Penello Meirelles, Margareth Simoes [Universidade do Estado do Rio de Janeiro (UERJ)/Geomatica, Maracana, Rio de Janeiro, RJ (Brazil); Garcia, Carlos Eiras [Universidade Federal do Rio Grande (FURG), Laboratorio de Oceanografia Fisica, Rio Grande, RS (Brazil)

    2012-03-15

    Recent satellite observations have shown an increase in the total extent of Antarctic sea ice, during periods when the atmosphere and oceans tend to be warmer surrounding a significant part of the continent. Despite an increase in total sea ice, regional analyses depict negative trends in the Bellingshausen-Amundsen Sea and positive trends in the Ross Sea. Although several climate parameters are believed to drive the formation of Antarctic sea ice and the local atmosphere, a descriptive mechanism that could trigger such differences in trends are still unknown. In this study we employed a multivariate analysis in order to identify the response of the Antarctic sea ice with respect to commonly utilized climate forcings/parameters, as follows: (1) The global air surface temperature, (2) The global sea surface temperature, (3) The atmospheric CO{sub 2} concentration, (4) The South Annular Mode, (5) The Nino 3, (6) The Nino (3 + 4, 7) The Nino 4, (8) The Southern Oscillation Index, (9) The Multivariate ENSO Index, (10) the Total Solar Irradiance, (11) The maximum O{sub 3} depletion area, and (12) The minimum O{sub 3} concentration over Antarctica. Our results indicate that western Antarctic sea ice is simultaneously impacted by several parameters; and that the minimum, mean, and maximum sea ice extent may respond to a separate set of climatic/geochemical parameters. (orig.)

  18. Global Fiducials Program - Arctic Buoy Sea Ice Studies

    Science.gov (United States)

    Wilson, E. M.; Wilds, S. R.; Friesen, B. A.; Sloan, J. L.

    2012-12-01

    The U.S. Geological Survey has utilized remotely sensed imagery to analyze Arctic Sea Ice since 1997, and has collected and created thousands of Literal Image Derived Products (LIDPS) at one meter resolution for public distribution. From 1997-2012, six static sea ice sites located in the Arctic Basin were selected and added to the Global Fiducial Library (GFL), to create an annual series of geographically referenced images to allow scientists to study seasonal changes in Arctic ice. In early 2009, a scientific group known as MEDEA (Measurements of Earth Data for Environmental Analysis) requested additional collections to track ice floe movements during the course of an entire summer (April through September), to better understand seasonal changes in the Arctic Sea Ice. In order to track and capture the same ice cover over time, USGS adopted a methodology to utilize buoys deployed at various locations across the Arctic by the International Arctic Buoy Program. The data buoys record and transmit hourly GPS positions, along with meteorologic and climatologic data associated with the sea ice in which they are anchored. Repeated imaging of the ice cover is guided by the data buoy GPS to help estimate travel direction and speed of the ice cover. Imagery is referenced by the MEDEA scientists to study ice fracture patterns, sea ice ridge heights, ice cover percentages, seasonal development and coverage of melt ponds, evolution of ice concentrations, floe size distribution, lateral melting, and other variables that are used for input to refine and develop climate models. These same ice floe images have been added to the GFL for various buoy locations from 2009 through 2011, and are being acquired for the 2012 summer season.

  19. Early Student Support to Investigate the Role of Sea Ice Albedo Feedback in Sea Ice Predictions

    Science.gov (United States)

    2015-09-30

    melt-pond scheme that remains an option in CICE5. The simplest melt-pond parameterization keeps an account of all the snow meltwater starting each... meltwater account is depleted with an assumed decay rate. The newer detailed physics scheme is described in Hunke et al. (2013) that is in CICE5 and is...remain tightly concentrated around the Canadian archipelago and Greenland . Thus later in the 21st century, as the sea ice becomes mostly seasonal, much

  20. Airborne radar surveys of snow depth over Antarctic sea ice during Operation IceBridge

    Science.gov (United States)

    Panzer, B.; Gomez-Garcia, D.; Leuschen, C.; Paden, J. D.; Gogineni, P. S.

    2012-12-01

    Over the last decade, multiple satellite-based laser and radar altimeters, optimized for polar observations, have been launched with one of the major objectives being the determination of global sea ice thickness and distribution [5, 6]. Estimation of sea-ice thickness from these altimeters relies on freeboard measurements and the presence of snow cover on sea ice affects this estimate. Current means of estimating the snow depth rely on daily precipitation products and/or data from passive microwave sensors [2, 7]. Even a small uncertainty in the snow depth leads to a large uncertainty in the sea-ice thickness estimate. To improve the accuracy of the sea-ice thickness estimates and provide validation for measurements from satellite-based sensors, the Center for Remote Sensing of Ice Sheets deploys the Snow Radar as a part of NASA Operation IceBridge. The Snow Radar is an ultra-wideband, frequency-modulated, continuous-wave radar capable of resolving snow depth on sea ice from 5 cm to more than 2 meters from long-range, airborne platforms [4]. This paper will discuss the algorithm used to directly extract snow depth estimates exclusively using the Snow Radar data set by tracking both the air-snow and snow-ice interfaces. Prior work in this regard used data from a laser altimeter for tracking the air-snow interface or worked under the assumption that the return from the snow-ice interface was greater than that from the air-snow interface due to a larger dielectric contrast, which is not true for thick or higher loss snow cover [1, 3]. This paper will also present snow depth estimates from Snow Radar data during the NASA Operation IceBridge 2010-2011 Antarctic campaigns. In 2010, three sea ice flights were flown, two in the Weddell Sea and one in the Amundsen and Bellingshausen Seas. All three flight lines were repeated in 2011, allowing an annual comparison of snow depth. In 2011, a repeat pass of an earlier flight in the Weddell Sea was flown, allowing for a

  1. Sea ice as a source of sea salt aerosol to Greenland ice cores: a model-based study

    Science.gov (United States)

    Rhodes, Rachael H.; Yang, Xin; Wolff, Eric W.; McConnell, Joseph R.; Frey, Markus M.

    2017-08-01

    Growing evidence suggests that the sea ice surface is an important source of sea salt aerosol and this has significant implications for polar climate and atmospheric chemistry. It also suggests the potential to use ice core sea salt records as proxies for past sea ice extent. To explore this possibility in the Arctic region, we use a chemical transport model to track the emission, transport, and deposition of sea salt from both the open ocean and the sea ice, allowing us to assess the relative importance of each. Our results confirm the importance of sea ice sea salt (SISS) to the winter Arctic aerosol burden. For the first time, we explicitly simulate the sea salt concentrations of Greenland snow, achieving values within a factor of two of Greenland ice core records. Our simulations suggest that SISS contributes to the winter maxima in sea salt characteristic of ice cores across Greenland. However, a north-south gradient in the contribution of SISS relative to open-ocean sea salt (OOSS) exists across Greenland, with 50 % of winter sea salt being SISS at northern sites such as NEEM (77° N), while only 10 % of winter sea salt is SISS at southern locations such as ACT10C (66° N). Our model shows some skill at reproducing the inter-annual variability in sea salt concentrations for 1991-1999, particularly at Summit where up to 62 % of the variability is explained. Future work will involve constraining what is driving this inter-annual variability and operating the model under different palaeoclimatic conditions.

  2. Remote sensing of sea ice: advances during the DAMOCLES project

    Directory of Open Access Journals (Sweden)

    G. Heygster

    2012-12-01

    Full Text Available In the Arctic, global warming is particularly pronounced so that we need to monitor its development continuously. On the other hand, the vast and hostile conditions make in situ observation difficult, so that available satellite observations should be exploited in the best possible way to extract geophysical information. Here, we give a résumé of the sea ice remote sensing efforts of the European Union's (EU project DAMOCLES (Developing Arctic Modeling and Observing Capabilities for Long-term Environmental Studies. In order to better understand the seasonal variation of the microwave emission of sea ice observed from space, the monthly variations of the microwave emissivity of first-year and multi-year sea ice have been derived for the frequencies of the microwave imagers like AMSR-E (Advanced Microwave Scanning Radiometer on EOS and sounding frequencies of AMSU (Advanced Microwave Sounding Unit, and have been used to develop an optimal estimation method to retrieve sea ice and atmospheric parameters simultaneously. In addition, a sea ice microwave emissivity model has been used together with a thermodynamic model to establish relations between the emissivities from 6 GHz to 50 GHz. At the latter frequency, the emissivity is needed for assimilation into atmospheric circulation models, but is more difficult to observe directly. The size of the snow grains on top of the sea ice influences both its albedo and the microwave emission. A method to determine the effective size of the snow grains from observations in the visible range (MODIS is developed and demonstrated in an application on the Ross ice shelf. The bidirectional reflectivity distribution function (BRDF of snow, which is an essential input parameter to the retrieval, has been measured in situ on Svalbard during the DAMOCLES campaign, and a BRDF model assuming aspherical particles is developed. Sea ice drift and deformation is derived from satellite observations with the scatterometer

  3. Modeling the summertime evolution of sea-ice melt ponds

    DEFF Research Database (Denmark)

    Lüthje, Mikael; Feltham, D.L.; Taylor, P.D.;

    2006-01-01

    We present a mathematical model describing the summer melting of sea ice. We simulate the evolution of melt ponds and determine area coverage and total surface ablation. The model predictions are tested for sensitivity to the melt rate of unponded ice, enhanced melt rate beneath the melt ponds......, vertical seepage, and horizontal permeability. The model is initialized with surface topographies derived from laser altimetry corresponding to first-year sea ice and multiyear sea ice. We predict that there are large differences in the depth of melt ponds and the area of coverage between the two types...... of ice. We also find that the vertical seepage rate and the melt rate of unponded ice are important in determining the total surface ablation and area covered by melt ponds....

  4. Modeling the summertime evolution of sea-ice melt ponds

    DEFF Research Database (Denmark)

    Lüthje, Mikael; Feltham, D.L.; Taylor, P.D.

    2006-01-01

    We present a mathematical model describing the summer melting of sea ice. We simulate the evolution of melt ponds and determine area coverage and total surface ablation. The model predictions are tested for sensitivity to the melt rate of unponded ice, enhanced melt rate beneath the melt ponds......, vertical seepage, and horizontal permeability. The model is initialized with surface topographies derived from laser altimetry corresponding to first-year sea ice and multiyear sea ice. We predict that there are large differences in the depth of melt ponds and the area of coverage between the two types...... of ice. We also find that the vertical seepage rate and the melt rate of unponded ice are important in determining the total surface ablation and area covered by melt ponds....

  5. Community-based sea ice thickness observatories in the Arctic

    Science.gov (United States)

    Gearheard, S.; Mahoney, A. R.; Huntington, H.; Oshima, T.; Qillaq, T.; Barry, R. G.

    2007-12-01

    The thickness of sea ice is a fundamental diagnostic variable for assessing the state of the ice cover. At the scale of the Arctic Basin, the ice thickness distribution determines the volume of the ice pack and its susceptibility to a warming climate as well as affecting the exchange of heat between the ocean and atmosphere. At the local scale, it dictates where and when it is safe to travel on the ice or through the water. Measuring the thickness of sea ice is challenging both technically and logistically and any measurement program strikes a balance between cost and coverage accordingly. Accurately measuring the thickness of large areas of sea ice generally requires airplanes, ice breakers or submarines and electromagnetic or acoustic devices. In this study, we use one of the least technical methods combined with support from remote communities to establish a set of sea ice observation stations in Barrow (Alaska), Clyde River (Baffin Island, Nunavut) and Qaanaaq (northwest Greenland). We employ hunters from these communities, who are experts in traveling and working on the ice, and train them to deploy ice observation stations and take measurements. Each station consists of snow stakes and hot-wire ice thickness gauges and the local observers take measurements on a weekly basis. Involvement of the community is fundamental to the success of these measurement programs and ensures the data collected are relevant to the local use of the sea ice. Community elders and hunters chose the station locations according to where they hunt and travel and to be representative of local variability. As partners in research, the scientists and local hunters are able to share and synthesize their knowledge; the scientific community gains a better understanding of the extraordinary depth of traditional knowledge and the communities improve their understanding of global changes and ability to adapt. Here we present data from observation stations near Clyde River and Qaanaaq. At Clyde

  6. The sea ice in Young Sound: Implications for carbon cycling

    DEFF Research Database (Denmark)

    Glud, Ronnie Nøhr; Rysgaard, Søren; Kühl, Michael

    2007-01-01

    , and 7 of the longest sea-ice-free periods observed in 50 years were recorded after 1990. The snow and sea-ice cover regulates the activity of the light-limited marine ecosystem of Young Sound. As the snow cover melts during late May and June, the irradiance refl ectance decreases, especially for red...... and near infrared light. Differences in snow cover thickness and patchy distribution of dry snow, wet snow and melting ponds on the sea-ice surface result in a very heterogeneous light environment at the underside of the ice. In areas with suffi cient light, sea-ice algae begin to fl ourish......–30 μg Chl a l-1 sea ice at the underside of the ice and with maximum area integrated values of c. 3 mg Chl a m-2. We speculate that the extreme dynamics in sea-ice appearance, structure and brine percolation, which is driven primarily by large but variable freshwater inputs during snow melt...

  7. Antartic sea ice, 1973 - 1976: Satellite passive-microwave observations

    Science.gov (United States)

    Zwally, H. J.; Comiso, J. C.; Parkinson, C. L.; Campbell, W. J.; Carsey, F. D.; Gloersen, P.

    1983-01-01

    Data from the Electrically Scanning Microwave Radiometer (ESMR) on the Nimbus 5 satellite are used to determine the extent and distribution of Antarctic sea ice. The characteristics of the southern ocean, the mathematical formulas used to obtain quantitative sea ice concentrations, the general characteristics of the seasonal sea ice growth/decay cycle and regional differences, and the observed seasonal growth/decay cycle for individual years and interannual variations of the ice cover are discussed. The sea ice data from the ESMR are presented in the form of color-coded maps of the Antarctic and the southern oceans. The maps show brightness temperatures and concentrations of pack ice averaged for each month, 4-year monthly averages, and month-to-month changes. Graphs summarizing the results, such as areas of sea ice as a function of time in the various sectors of the southern ocean are included. The images demonstrate that satellite microwave data provide unique information on large-scale sea ice conditions for determining climatic conditions in polar regions and possible global climatic changes.

  8. The sea ice in Young Sound: Implications for carbon cycling

    DEFF Research Database (Denmark)

    Glud, Ronnie Nøhr; Rysgaard, Søren; Kühl, Michael

    2007-01-01

    , and 7 of the longest sea-ice-free periods observed in 50 years were recorded after 1990. The snow and sea-ice cover regulates the activity of the light-limited marine ecosystem of Young Sound. As the snow cover melts during late May and June, the irradiance refl ectance decreases, especially for red...... and near infrared light. Differences in snow cover thickness and patchy distribution of dry snow, wet snow and melting ponds on the sea-ice surface result in a very heterogeneous light environment at the underside of the ice. In areas with suffi cient light, sea-ice algae begin to fl ourish......–30 μg Chl a l-1 sea ice at the underside of the ice and with maximum area integrated values of c. 3 mg Chl a m-2. We speculate that the extreme dynamics in sea-ice appearance, structure and brine percolation, which is driven primarily by large but variable freshwater inputs during snow melt...

  9. 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.

  10. Characterizing Arctic sea ice topography using high-resolution IceBridge data

    OpenAIRE

    Petty, Alek A.; Tsamados, Michel C.; Kurtz, Nathan T.; Farrell, Sinead L.; Newman, Thomas; Harbeck, Jeremy P.; FELTHAM, DANIEL L.; Richter-Menge, Jackie A.

    2015-01-01

    We present an analysis of Arctic sea ice topography using high resolution, three-dimensional, surface elevation data from the Airborne Topographic Mapper, flown as part of NASA's Operation IceBridge mission. Surface features in the sea ice cover are detected using a newly developed surface feature picking algorithm. We derive information regarding the height, volume and geometry of surface features from 2009–2014 within the Beaufort/Chukchi and Central Arcti...

  11. On large outflows of Arctic sea ice into the Barents Sea

    Science.gov (United States)

    Kwok, Ron; Maslowski, Wieslaw; Laxon, Seymour W.

    2005-01-01

    Winter outflows of Arctic sea ice into the Barents Sea are estimated using a 10-year record of satellite ice motion and thickness. The mean winter volume export through the Svalbard/Franz Josef Land passage is 40 km3, and ranges from -280 km3 to 340 km3. A large outflow in 2003 is preconditioned by an unusually high concentration of thick perennial ice over the Nansen Basin at the end of the 2002 summer. With a deep atmospheric low situated over the eastern Barents Sea in winter, the result is an increased export of Arctic ice. The Oct-Mar ice area flux, at 110 x 10 to the third power km3, is not only unusual in magnitude but also remarkable in that >70% of the area is multiyear ice; the ice volume flux at340 km3 is almost one-fifth of the ice flux through the Fram Strait. Another large outflow of Arctic sea ice through this passage, comparable to that in 2003, is found in 1996. This southward flux of sea ice represents one of two major sources of freshwater in the Barents Sea; the other is the eastward flux of water via the Norwegian Coastal Current. The possible consequences of variable freshwater input on the Barents Sea hydrography and its impact on transformation of Atlantic Water en route to the Arctic Ocean are examined with a 25-year coupled ice-ocean model.

  12. Greenland Ice Sheet response to mid-Pliocene summer Arctic sea ice-free conditions

    Science.gov (United States)

    Koenig, S. J.; DeConto, R.; Pollard, D.

    2011-12-01

    A critical uncertainty in future predictions of climate and sea level is the response of the cryosphere. Proxy reconstructions for the mid-Pliocene Arctic Ocean (~ 3 Ma) are indicative of summer Arctic ice-free conditions and higher than modern sea surface temperatures, conditions that are analogous to projections for the end of the 21st century. We implement available mid-Pliocene boundary conditions into a fully-coupled Global Circulation Model with interactive vegetation. We use a 3-D thermo-mechanical ice sheet-shelf model to simulate the equilibrated response of the Greenland Ice Sheet (GIS) to the combined effect of reduced sea ice conditions and increased sea surface temperatures during the mid-Pliocene Warm Period. Reductions in Arctic sea ice are shown to enhance ocean/land-to-atmosphere fluxes, increasing heat and moisture transport in the high latitudes. In particular, changes in the North Atlantic exert a strong influence on the storm track and seasonal temperatures and precipitation over Greenland. Despite increased precipitation, warmer temperatures generally reduce snow mass balance. As a result, an initial present-day ice sheet forced by Pliocene climate undergoes rapid melting, limiting the ice sheet to the only highest elevations in South and East Greenland. Once the ice sheet is lost, local surface characteristics and associated feedbacks dominates Greenland climate, precluding the regrowth of the ice sheet. Depending on the initial state of the ice sheet, the equilibrated ice sheet loss is equivalent to between 5.8 to 6.4 m of sea level. We assess the sensitivity of the GIS to Pliocene forcing and internal feedbacks, adding to the understanding of land-ice sea-ice hysteresis in a world warmer than today.

  13. Spring Snow Depth on Arctic Sea Ice using the IceBridge Snow Depth Product (Invited)

    Science.gov (United States)

    Webster, M.; Rigor, I. G.; Nghiem, S. V.; Kurtz, N. T.; Farrell, S. L.

    2013-12-01

    Snow has dual roles in the growth and decay of Arctic sea ice. In winter, it insulates sea ice from colder air temperatures, slowing its growth. From spring into summer, the albedo of snow determines how much insolation is transmitted through the sea ice and into the underlying ocean, ultimately impacting the progression of the summer ice melt. Knowing the snow thickness and distribution are essential for understanding and modeling sea ice thermodynamics and the surface heat budget. Therefore, an accurate assessment of the snow cover is necessary for identifying its impacts in the changing Arctic. This study assesses springtime snow conditions on Arctic sea ice using airborne snow thickness measurements from Operation IceBridge (2009-2012). The 2012 data were validated with coordinated in situ measurements taken in March 2012 during the BRomine, Ozone, and Mercury EXperiment field campaign. We find a statistically significant correlation coefficient of 0.59 and RMS error of 5.8 cm. The comparison between the IceBridge snow thickness product and the 1937, 1954-1991 Soviet drifting ice station data suggests that the snow cover has thinned by 33% in the western Arctic and 44% in the Beaufort and Chukchi Seas. A rudimentary estimation shows that a thinner snow cover in the Beaufort and Chukchi Seas translates to a mid-December surface heat flux as high as 81 W/m2 compared to 32 W/m2. The relationship between the 2009-2012 thinner snow depth distribution and later sea ice freeze-up is statistically significant, with a correlation coefficient of 0.59. These results may help us better understand the surface energy budget in the changing Arctic, and may improve our ability to predict the future state of the sea ice cover.

  14. The Importance of Snow Distribution on Sea Ice

    Science.gov (United States)

    Butler, B.; Polashenski, C.; Divine, D.; King, J.; Liston, G. E.; Nicolaus, M.; Rösel, A.

    2015-12-01

    Snow's insulating and reflective properties substantially influence Arctic sea ice growth and decay. A particularly important, but under-appreciated, aspect of snow on sea ice is its fine-scale spatial distribution. Snow redistribution into dunes and drifts controls the effective thermal conductivity of a snowpack and dictates the locations of melt pond formation, exerting considerable control over ice mass balance. The effective thermal conductivity of snow distributions created on sea ice, for example, is often considerably greater than a uniform snowpack of equivalent mean thickness. During the N-ICE 2015 campaign north of Svalbard, we studied snow distributions across multiple ice types and the impacts these have on thermal fluxes and ice mass balance. We used terrestrial LiDAR to observe the snow surface topography over km2 areas, conducted many thousands of manual snow depth measurements, and collected hundreds of observations of the snow physical properties in snow pits. We find that the wind driven redistribution of snow can alter the net effect of a constant snow cover volume on ice mass balance as strongly as inter-annual variability in the amount and timing of snowfall. Further comparison with snow depth distributions from field campaigns in other parts of the Arctic highlights regional and inter-annual differences in snow distribution. We quantify the impact of this variability on ice mass balance and demonstrate the need for considering snow distributions and redistribution processes in sea ice models.

  15. Influence of ice thickness and surface properties on light transmission through Arctic sea ice.

    Science.gov (United States)

    Katlein, Christian; Arndt, Stefanie; Nicolaus, Marcel; Perovich, Donald K; Jakuba, Michael V; Suman, Stefano; Elliott, Stephen; Whitcomb, Louis L; McFarland, Christopher J; Gerdes, Rüdiger; Boetius, Antje; German, Christopher R

    2015-09-01

    The observed changes in physical properties of sea ice such as decreased thickness and increased melt pond cover severely impact the energy budget of Arctic sea ice. Increased light transmission leads to increased deposition of solar energy in the upper ocean and thus plays a crucial role for amount and timing of sea-ice-melt and under-ice primary production. Recent developments in underwater technology provide new opportunities to study light transmission below the largely inaccessible underside of sea ice. We measured spectral under-ice radiance and irradiance using the new Nereid Under-Ice (NUI) underwater robotic vehicle, during a cruise of the R/V Polarstern to 83°N 6°W in the Arctic Ocean in July 2014. NUI is a next generation hybrid remotely operated vehicle (H-ROV) designed for both remotely piloted and autonomous surveys underneath land-fast and moving sea ice. Here we present results from one of the first comprehensive scientific dives of NUI employing its interdisciplinary sensor suite. We combine under-ice optical measurements with three dimensional under-ice topography (multibeam sonar) and aerial images of the surface conditions. We investigate the influence of spatially varying ice-thickness and surface properties on the spatial variability of light transmittance during summer. Our results show that surface properties such as melt ponds dominate the spatial distribution of the under-ice light field on small scales (ice-thickness is the most important predictor for light transmission on larger scales. In addition, we propose the use of an algorithm to obtain histograms of light transmission from distributions of sea ice thickness and surface albedo.

  16. Physically-based Ice Thickness and Surface Roughness Retrievals over Rough Deformed Sea Ice

    Science.gov (United States)

    Li, Li; Gaiser, Peter; Allard, Richard; Posey, Pamela; Hebert, David; Richter-Menge, Jacqueline; Polashenski, Christopher; Claffey, Keran

    2016-04-01

    The observations of sea ice thickness and ice surface roughness are critical for our understanding of the state of the changing Arctic. Currently, the Radar and/or LiDAR data of sea ice freeboard are used to infer sea ice thickness via isostasy. The underlying assumption is that the LiDAR signal returns at the air/snow interface and radar signal at the snow/ice interface. The elevations of these interfaces are determined based on LiDAR/Radar return waveforms. However, the commonly used threshold-based surface detection techniques are empirical in nature and work well only over level/smooth sea ice. Rough sea ice surfaces can modify the return waveforms, resulting in significant Electromagnetic (EM) bias in the estimated surface elevations, and thus large errors in the ice thickness retrievals. To understand and quantify such sea ice surface roughness effects, a combined EM rough surface and volume scattering model was developed to simulate radar returns from the rough sea ice 'layer cake' structure. A waveform matching technique was also developed to fit observed waveforms to a physically-based waveform model and subsequently correct the roughness induced EM bias in the estimated freeboard. This new EM Bias Corrected (EMBC) algorithm was able to better retrieve surface elevations and estimate the surface roughness parameter simultaneously. Both the ice thickness and surface roughness retrievals are validated using in-situ data. For the surface roughness retrievals, we applied this EMBC algorithm to co-incident LiDAR/Radar measurements collected during a Cryosat-2 under-flight by the NASA IceBridge missions. Results show that not only does the waveform model fit very well to the measured radar waveform, but also the roughness parameters derived independently from the LiDAR and radar data agree very well for both level and deformed sea ice. For sea ice thickness retrievals, validation based on in-situ data from the coordinated CRREL/NRL field campaign demonstrates

  17. Linking the northern hemisphere sea-ice reduction trend and the quasi-decadal arctic sea-ice oscillation

    Energy Technology Data Exchange (ETDEWEB)

    Wang, J. [University of Alaska Fairbanks, International Arctic Research Center, Alaska (United States); Ikeda, M. [Hokkaido University, Graduate School of Environmental Earth Science, Sapporo (Japan); Zhang, S. [University of Alaska Fairbanks Fairbanks, Department of Mathematical Sciences, Alaska (United States); Gerdes, R. [Alfred-Wegener Institute for Polar Research, Bremerhaven (Germany)

    2005-02-01

    The nature of the reduction trend and quasi-decadal oscillation in Northern Hemisphere sea-ice extent is investigated. The trend and oscillation that seem to be two separate phenomena have been found in data. This study examines a hypothesis that the Arctic sea-ice reduction trend in the last three decades amplified the quasi-decadal Arctic sea-ice oscillation (ASIO) due to a positive ice/ocean-albedo feedback, based on data analysis and a conceptual model proposed by Ikeda et al. The theoretical, conceptual model predicts that the quasi-decadal oscillation is amplified by the thinning sea-ice, leading to the ASIO, which is driven by the strong positive feedback between the atmosphere and ice-ocean systems. Such oscillation is predicted to be out-of-phase between the Arctic Basin and the Nordic Seas with a phase difference of 3{pi}/4, with the Nordic Seas leading the Arctic. The wavelet analysis of the sea ice data reveals that the quasi-decadal ASIO occurred actively since the 1970s following the trend starting in the 1960s (i.e., as sea-ice became thinner and thinner), as the atmosphere experienced quasi-decadal oscillations during the last century. The wavelet analysis also confirms the prediction of such out-of-phase feature between these two basins, which varied from 0.62{pi} in 1960 to 0.25{pi} in 1995. Furthermore, a coupled ice-ocean general circulation model (GCM) was used to simulate two scenarios, one without the greenhouse gas warming and the other having realistic atmospheric forcing along with the warming that leads to sea-ice reduction trend. The quasi-decadal ASIO is excited in the latter case compared to the no-warming case. The wavelet analyses of the simulated ice volume were also conducted to derive decadal ASIO and similar phase relationship between the Arctic Ocean and the Nordic Seas. An independent data source was used to confirm such decadal oscillation in the upper layer (or freshwater) thickness, which is consistent with the model

  18. Application of the HY-1 satellite to sea ice monitoring and forecasting

    Institute of Scientific and Technical Information of China (English)

    LUO Yawei; WU Huiding; ZHANG Yunfei; SUN Congrong; LIU Yu

    2004-01-01

    The HY-1A satellite is the first oceanic satellite of China. During the winter of 2002~2003, the data of the HY-1A were applied to the sea ice monitoring and forecasting for the Bohai Sea of China for the first time. The sea ice retrieval system of the HY-1A has been constructed. It receives 1B data from the satellite, outputs sea ice images and provides digital products of ice concentration, ice thickness and ice edge, which can be used as important information for sea ice monitoring and the initial fields of the numeric sea ice forecast and as one of the reference data for the sea ice forecasting verification. The sea ice retrieval system of the satellite is described, including its processes, methods and parameters. The retrieving results and their application to the sea ice monitoring and forecasting for the Bohai Sea are also discussed.

  19. Skill improvement of dynamical seasonal Arctic sea ice forecasts

    Science.gov (United States)

    Krikken, Folmer; Schmeits, Maurice; Vlot, Willem; Guemas, Virginie; Hazeleger, Wilco

    2016-05-01

    We explore the error and improve the skill of the outcome from dynamical seasonal Arctic sea ice reforecasts using different bias correction and ensemble calibration methods. These reforecasts consist of a five-member ensemble from 1979 to 2012 using the general circulation model EC-Earth. The raw model reforecasts show large biases in Arctic sea ice area, mainly due to a differently simulated seasonal cycle and long term trend compared to observations. This translates very quickly (1-3 months) into large biases. We find that (heteroscedastic) extended logistic regressions are viable ensemble calibration methods, as the forecast skill is improved compared to standard bias correction methods. Analysis of regional skill of Arctic sea ice shows that the Northeast Passage and the Kara and Barents Sea are most predictable. These results show the importance of reducing model error and the potential for ensemble calibration in improving skill of seasonal forecasts of Arctic sea ice.

  20. Can regional climate engineering save the summer Arctic sea ice?

    Science.gov (United States)

    Tilmes, S.; Jahn, Alexandra; Kay, Jennifer E.; Holland, Marika; Lamarque, Jean-Francois

    2014-02-01

    Rapid declines in summer Arctic sea ice extent are projected under high-forcing future climate scenarios. Regional Arctic climate engineering has been suggested as an emergency strategy to save the sea ice. Model simulations of idealized regional dimming experiments compared to a business-as-usual greenhouse gas emission simulation demonstrate the importance of both local and remote feedback mechanisms to the surface energy budget in high latitudes. With increasing artificial reduction in incoming shortwave radiation, the positive surface albedo feedback from Arctic sea ice loss is reduced. However, changes in Arctic clouds and the strongly increasing northward heat transport both counteract the direct dimming effects. A 4 times stronger local reduction in solar radiation compared to a global experiment is required to preserve summer Arctic sea ice area. Even with regional Arctic dimming, a reduction in the strength of the oceanic meridional overturning circulation and a shut down of Labrador Sea deep convection are possible.

  1. Trajectories of arctic sea ice under anthropogenic warming scenarios

    Science.gov (United States)

    Zhang, J.; Steele, M.; Schweiger, A. J.

    2010-12-01

    A series of numerical experiments are conducted to study the possible trajectories of arctic sea ice in response to varying levels of future anthropogenic warming and climate variability using a sea ice-ocean model. A summer ice-free Arctic Ocean is likely by the mid-2040s if arctic surface air temperature (SAT) increases 4C by 2050 and climate variability is similar to the past relatively warm two decades. Summer ice volume decreases to very low levels (10-37% of the 1978-2009 summer mean) as early as 2025 and remains low in the following years, while summer ice extent continues to fluctuate annually. The rate of annual mean ice volume decrease relaxes approaching 2050. The causes of the reduced ice volume loss are examined.

  2. Use of ERTS data for mapping Arctic sea ice

    Science.gov (United States)

    Barnes, J. C. (Principal Investigator); Bowley, C. J.

    1973-01-01

    The author has identified the following significant results. Data from ERTS passes crossing the Bering Sea in early March have been correlated with ice observations collected in the Bering Sea Experiment (BESEX). On two flights of the NASA CV-990 aircraft, the ice conditions in the vicinity of St. Lawrence Island reported by the onboard observer are in close agreement with the ice conditions mapped from the corresponding ERTS imagery. The ice features identified in ERTS imagery and substantiated by the aerial observer include the locations of boundaries between areas consisting of mostly grey ice and of mostly first and multi-year ice, the existence of shearing leads, and the occurrence of open water with the associated development of stratus cloud streaks. The BESEX correlative ice formation verifies the potential of practical applications of ERTS data.

  3. IceMap250—Automatic 250 m Sea Ice Extent Mapping Using MODIS Data

    Directory of Open Access Journals (Sweden)

    Charles Gignac

    2017-01-01

    Full Text Available The sea ice cover in the North evolves at a rapid rate. To adequately monitor this evolution, tools with high temporal and spatial resolution are needed. This paper presents IceMap250, an automatic sea ice extent mapping algorithm using MODIS reflective/emissive bands. Hybrid cloud-masking using both the MOD35 mask and a visibility mask, combined with downscaling of Bands 3–7 to 250 m, are utilized to delineate sea ice extent using a decision tree approach. IceMap250 was tested on scenes from the freeze-up, stable cover, and melt seasons in the Hudson Bay complex, in Northeastern Canada. IceMap250 first product is a daily composite sea ice presence map at 250 m. Validation based on comparisons with photo-interpreted ground-truth show the ability of the algorithm to achieve high classification accuracy, with kappa values systematically over 90%. IceMap250 second product is a weekly clear sky map that provides a synthesis of 7 days of daily composite maps. This map, produced using a majority filter, makes the sea ice presence map even more accurate by filtering out the effects of isolated classification errors. The synthesis maps show spatial consistency through time when compared to passive microwave and national ice services maps.

  4. On the characteristics of sea ice divergence/convergence in the Southern Beaufort Sea

    Directory of Open Access Journals (Sweden)

    J. V. Lukovich

    2014-07-01

    Full Text Available An understanding of spatial gradients in sea ice motion, or deformation, is essential to understanding of ocean-sea-ice-atmosphere interactions and realistic representations of sea ice in models used for the purposes of prediction. This is particularly true for the southern Beaufort Sea, where significant offshore hydrocarbon resource development increases the risk of oil and other contaminants dispersing into the marginal ice zone. In this study, sea ice deformation is examined through evaluation of ice beacon triplets from September to November 2009 in the southern Beaufort Sea (SBS, defined according to distance from the coastline on deployment. Results from this analysis illustrate that ice beacon triplets in the SBS demonstrate spatiotemporal differences in their evolution at the periphery and interior of the ice pack. The time rate of change in triplet area highlights two intervals of enhanced divergence and convergence in fall, 2009. Investigation of sea ice and atmospheric conditions during these intervals shows that until mid-September, all triplets respond to northerly flow, while during the second interval of enhanced divergence/convergence in October only one triplet responds to persistent northeasterly flow due to its proximity to the ice edge, in contrast to triplets located at the interior of the pack. Differences in sea ice deformation and dispersion near the pack ice edge and interior are further demonstrated in the behavior of triplets B and C in late October/early November. The results from this analysis highlight differences in dispersion and deformation characteristics based on triplet proximity to the southernmost ice edge and coastline, with implications for modeling studies pertaining to sea ice dynamics and dispersion.

  5. Environmental predictors of ice seal presence in the Bering Sea.

    Science.gov (United States)

    Miksis-Olds, Jennifer L; Madden, Laura E

    2014-01-01

    Ice seals overwintering in the Bering Sea are challenged with foraging, finding mates, and maintaining breathing holes in a dark and ice covered environment. Due to the difficulty of studying these species in their natural environment, very little is known about how the seals navigate under ice. Here we identify specific environmental parameters, including components of the ambient background sound, that are predictive of ice seal presence in the Bering Sea. Multi-year mooring deployments provided synoptic time series of acoustic and oceanographic parameters from which environmental parameters predictive of species presence were identified through a series of mixed models. Ice cover and 10 kHz sound level were significant predictors of seal presence, with 40 kHz sound and prey presence (combined with ice cover) as potential predictors as well. Ice seal presence showed a strong positive correlation with ice cover and a negative association with 10 kHz environmental sound. On average, there was a 20-30 dB difference between sound levels during solid ice conditions compared to open water or melting conditions, providing a salient acoustic gradient between open water and solid ice conditions by which ice seals could orient. By constantly assessing the acoustic environment associated with the seasonal ice movement in the Bering Sea, it is possible that ice seals could utilize aspects of the soundscape to gauge their safe distance to open water or the ice edge by orienting in the direction of higher sound levels indicative of open water, especially in the frequency range above 1 kHz. In rapidly changing Arctic and sub-Arctic environments, the seasonal ice conditions and soundscapes are likely to change which may impact the ability of animals using ice presence and cues to successfully function during the winter breeding season.

  6. Environmental predictors of ice seal presence in the Bering Sea.

    Directory of Open Access Journals (Sweden)

    Jennifer L Miksis-Olds

    Full Text Available Ice seals overwintering in the Bering Sea are challenged with foraging, finding mates, and maintaining breathing holes in a dark and ice covered environment. Due to the difficulty of studying these species in their natural environment, very little is known about how the seals navigate under ice. Here we identify specific environmental parameters, including components of the ambient background sound, that are predictive of ice seal presence in the Bering Sea. Multi-year mooring deployments provided synoptic time series of acoustic and oceanographic parameters from which environmental parameters predictive of species presence were identified through a series of mixed models. Ice cover and 10 kHz sound level were significant predictors of seal presence, with 40 kHz sound and prey presence (combined with ice cover as potential predictors as well. Ice seal presence showed a strong positive correlation with ice cover and a negative association with 10 kHz environmental sound. On average, there was a 20-30 dB difference between sound levels during solid ice conditions compared to open water or melting conditions, providing a salient acoustic gradient between open water and solid ice conditions by which ice seals could orient. By constantly assessing the acoustic environment associated with the seasonal ice movement in the Bering Sea, it is possible that ice seals could utilize aspects of the soundscape to gauge their safe distance to open water or the ice edge by orienting in the direction of higher sound levels indicative of open water, especially in the frequency range above 1 kHz. In rapidly changing Arctic and sub-Arctic environments, the seasonal ice conditions and soundscapes are likely to change which may impact the ability of animals using ice presence and cues to successfully function during the winter breeding season.

  7. Larsen C Ice Shelf rheology inferred by combining InSAR observations and numerical modeling

    Science.gov (United States)

    Khazendar, A.; Rignot, E. J.; Larour, E. Y.

    2009-12-01

    Larsen C Ice Shelf presents a valuable setting for investigating the many connected processes involved in the evolution of ice shelves in a warming climate. The stability of this ice shelf has become a topic of keen interest, especially following the disintegration of Larsen B and other Peninsular ice shelves, and the consequent increase in continental ice flow to the ocean. We are addressing this complex question in a multi-disciplinary manner by combining remote sensing and numerical modeling. Thus, we analyzed satellite InSAR observations of Larsen C obtained in the years 2000 and 2007 which revealed that ice shelf flow velocity in some areas have had some changes. We then applied inverse modeling, combining the observed velocity field with numerical flow models, to infer a spatial distribution of the flow parameter for the ice shelf, which is indispensable for accurately modeling ice shelf flow and evolution. The inferred rheology field allowed us to detect zones of weakness, including a large area in the middle of the ice shelf, many of which are associated with fracture features. Our similar previous analysis of Larsen B at the eve of its disintegration in 2002 emphasizes the significant interaction and interdependence among frontal calving, flow acceleration, variable rheology including fracture zones, and the ultimate destabilization of the ice shelf. Therefore, this work, by measuring any recent acceleration in the flow of Larsen C and inferring its rheology provides essential tools to evaluate its stability and long-term prospects. This work was performed at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration, Cryospheric Sciences Program.

  8. The potential transport of pollutants by Arctic sea ice

    OpenAIRE

    Pfirman, S. L.; Eicken, H.; Bauch, Dorothea; Weeks, W. F.

    1995-01-01

    Drifting sea ice in the Arctic may transport contaminants from coastal areas across the pole and release them during melting far from the source areas. Arctic sea ice often contains sediments entrained on the Siberian shelves and receives atmospheric deposition from Arctic haze. Elevated levels of some heavy metals (e.g. lead, iron, copper and cadmium) and organochlorines (e.g. PCBs and DDTs) have been observed in ice sampled in the Siberian seas, north of Svalbard, and in Baffin Bay. In orde...

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

    OpenAIRE

    Notz, Dirk

    2009-01-01

    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, w...

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

    Science.gov (United States)

    2012-12-06

    physical features such as snow topography and hydraulic meltwater transport rates both laterally and vertically. Departing from the cellular automaton...parameterizations before, or are mod- eled here in a different manner from prior work. When meltwater forms with snow still on the ice, the water is...thickest ice, near Greenland and the Canadian Arctic. A larger fraction of this thicker sea ice is ridged, less level ice is available for ponding, and

  11. Simulation of the crystal growth of platelet sea ice with diffusive heat and mass transfer

    NARCIS (Netherlands)

    Wangpan, Pat; Langhorne, Patricia J.; Dempsey, David E.; Hahn-Woernle, L.; Sun, Zhifa

    2015-01-01

    Antarctic coastal sea ice often grows in water that has been supercooled by interaction with an ice shelf. In these situations, ice crystals can form at depth, rise and deposit under the sea-ice cover to form a porous layer that eventually consolidates near the base of the existing sea ice. The leas

  12. Simulation of the crystal growth of platelet sea ice with diffusive heat and mass transfer

    NARCIS (Netherlands)

    Wangpan, Pat; Langhorne, Patricia J.; Dempsey, David E.; Hahn-Woernle, L.; Sun, Zhifa

    2015-01-01

    Antarctic coastal sea ice often grows in water that has been supercooled by interaction with an ice shelf. In these situations, ice crystals can form at depth, rise and deposit under the sea-ice cover to form a porous layer that eventually consolidates near the base of the existing sea ice. The leas

  13. Comparison of Quad-Polarimetric and Dual-Polarimetric SAR Data Capabilities for River Ice Classification

    Science.gov (United States)

    Los, H.; Pawlowski, B.; Osinska-Skotak, K.; Pluto-Kossakowska, J.

    2016-08-01

    River ice is one of the largest challenges of flood prevention during the winter. In the last decade, significant progress has been made on river ice research based on Earth observation data, especially with Synthetic Aperture Radar (SAR) systems. In this study, we compare the capabilities of quad-polarimetric and dual-polarimetric RADARSAT-2 data for river ice classification on the Lower Vistula. Dual-polarized datasets are generated by reducing polarization channels in original fully-polarized data. To classify images, we use supervised classification based on a maximum- likelihood algorithm. The results show that even with a reduced number of polarization channels, the classification result still presented satisfactory overall accuracy of above 85%.

  14. Wave Processes in Arctic Seas, Observed from TerraSAR-X

    Science.gov (United States)

    2015-09-30

    and validate modelling data for the spatial and temporal evolution of sea state in the MIZ. Further goals are the development of near-real time... spatial and temporal variability of the wave field in the emerging ice-free regions; • investigate wave damping in sea ice and the related ice breakup...the reason for the somewhat reduced wave heights in the southern region of the swath. The most pronounced drop in wave height is observed in the

  15. Sea ice contribution to the air-sea CO(2) exchange in the Arctic and Southern Oceans

    DEFF Research Database (Denmark)

    Rysgaard...[], Søren; Bendtsen, Jørgen; Delille, B.

    2011-01-01

    Although salt rejection from sea ice is a key process in deep-water formation in ice-covered seas, the concurrent rejection of CO(2) and the subsequent effect on air-sea CO(2) exchange have received little attention. We review the mechanisms by which sea ice directly and indirectly controls the a......-sea CO(2) exchange during winter, and (3) release of CO(2)-depleted melt water with excess total alkalinity during sea-ice decay and (4) biological CO(2) drawdown during primary production in sea ice and surface oceanic waters.......Although salt rejection from sea ice is a key process in deep-water formation in ice-covered seas, the concurrent rejection of CO(2) and the subsequent effect on air-sea CO(2) exchange have received little attention. We review the mechanisms by which sea ice directly and indirectly controls the air......-sea CO(2) exchange and use recent measurements of inorganic carbon compounds in bulk sea ice to estimate that oceanic CO(2) uptake during the seasonal cycle of sea-ice growth and decay in ice-covered oceanic regions equals almost half of the net atmospheric CO(2) uptake in ice-free polar seas. This sea-ice...

  16. Loss of sea ice during winter north of Svalbard

    Directory of Open Access Journals (Sweden)

    Ingrid H. Onarheim

    2014-06-01

    Full Text Available Sea ice loss in the Arctic Ocean has up to now been strongest during summer. In contrast, the sea ice concentration north of Svalbard has experienced a larger decline during winter since 1979. The trend in winter ice area loss is close to 10% per decade, and concurrent with a 0.3°C per decade warming of the Atlantic Water entering the Arctic Ocean in this region. Simultaneously, there has been a 2°C per decade warming of winter mean surface air temperature north of Svalbard, which is 20–45% higher than observations on the west coast. Generally, the ice edge north of Svalbard has retreated towards the northeast, along the Atlantic Water pathway. By making reasonable assumptions about the Atlantic Water volume and associated heat transport, we show that the extra oceanic heat brought into the region is likely to have caused the sea ice loss. The reduced sea ice cover leads to more oceanic heat transferred to the atmosphere, suggesting that part of the atmospheric warming is driven by larger open water area. In contrast to significant trends in sea ice concentration, Atlantic Water temperature and air temperature, there is no significant temporal trend in the local winds. Thus, winds have not caused the long-term warming or sea ice loss. However, the dominant winds transport sea ice from the Arctic Ocean into the region north of Svalbard, and the local wind has influence on the year-to-year variability of the ice concentration, which correlates with surface air temperatures, ocean temperatures, as well as the local wind.

  17. Atmospheric Response to Variations in Arctic Sea Ice Conditions

    Science.gov (United States)

    Bhatt, U.; Alexander, M.; Walsh, J.; Timlin, M.; Miller, J.

    2001-12-01

    While it is generally accepted that changes in air temperature and circulation determine sea ice conditions, it is not understood how the atmosphere is influenced by changes in sea ice. We employ the NCAR CCM 3.6 with specified ice extent and sea surface temperatures (sst). The overarching question addressed in this study is: how do variations in sea ice influence the atmosphere? We are particularly interested in the summer time response to highlight this unique aspect of this research. A control experiment has been integrated for 55 years by repeating the mean annual cycle of observed sea ice extent (either 0% or 100% ice cover) and sst, based on the period 1979-99. Sets of 50 member ensemble experiments were constructed by integrating the CCM from October to April using climatological sst (same as control) and observed sea ice extent from the winters of 1982-83 (ice maximum) and 1995-96 (ice minimum). Similar summertime sensitivity experiments were performed using ice extent conditions from April to October during 1982 (maximum) and 1995 (minimum). While responses were found both in winter and summer, the results described below refer to the summer of 1995. A set of 50 ensembles was also integrated for the summer of 1995 using sea ice concentration instead of extent. During the summer of 1995, negative sea ice anomalies were particularly large in the Siberian Arctic. Sea ice reductions result in increased surface and air temperatures and enhanced latent, sensible, and longwave fluxes out of the ocean. However, the net heat flux out of the ocean decreases because the changes are dominated by increased absorption of solar radiation over the low-albedo ocean. Cloud feedbacks are important in the Arctic and the downwelling solar at the surface decreases. The total cloud amount decreases due to reductions in low level clouds, however, convective cloud amounts increased. The net cloud radiative (shortwave and longwave) forcing is smaller in the experiment than the

  18. Albedo parametrization and reversibility of sea ice decay

    Science.gov (United States)

    Müller-Stoffels, M.; Wackerbauer, R.

    2012-02-01

    The Arctic's sea ice cover has been receding rapidly in recent years, and global climate models typically predict a further decline over the next century. It is an open question whether a possible loss of Arctic sea ice is reversible. We study the stability of Arctic model sea ice in a conceptual, two-dimensional energy-based regular network model of the ice-ocean layer that considers ARM's longwave radiative budget data and SHEBA albedo measurements. Seasonal ice cover, perennial ice and perennial open water are asymptotic states accessible by the model. We show that the shape of albedo parameterization near the melting temperature differentiates between reversible continuous sea ice decrease under atmospheric forcing and hysteresis behavior. Fixed points induced solely by the surface energy budget are essential for understanding the interaction of surface energy with the radiative forcing and the underlying body of ice/water, particularly close to a bifurcation point. Future studies will explore ice edge stability and reversibility in this lattice model, generalized to a latitudinal transect with spatiotemporal lateral atmospheric heat transfer and high spatial resolution.

  19. Albedo parametrization and reversibility of sea ice decay

    Directory of Open Access Journals (Sweden)

    M. Müller-Stoffels

    2012-02-01

    Full Text Available The Arctic's sea ice cover has been receding rapidly in recent years, and global climate models typically predict a further decline over the next century. It is an open question whether a possible loss of Arctic sea ice is reversible. We study the stability of Arctic model sea ice in a conceptual, two-dimensional energy-based regular network model of the ice-ocean layer that considers ARM's longwave radiative budget data and SHEBA albedo measurements. Seasonal ice cover, perennial ice and perennial open water are asymptotic states accessible by the model. We show that the shape of albedo parameterization near the melting temperature differentiates between reversible continuous sea ice decrease under atmospheric forcing and hysteresis behavior. Fixed points induced solely by the surface energy budget are essential for understanding the interaction of surface energy with the radiative forcing and the underlying body of ice/water, particularly close to a bifurcation point. Future studies will explore ice edge stability and reversibility in this lattice model, generalized to a latitudinal transect with spatiotemporal lateral atmospheric heat transfer and high spatial resolution.

  20. 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.

  1. Effects of Mackenzie River Discharge and Bathymetry on Sea Ice in the Beaufort Sea

    Science.gov (United States)

    Nghiem, S. V.; Hall, D. K.; Rigor, I. G; Li, P.; Neumann, G.

    2014-01-01

    Mackenzie River discharge and bathymetry effects on sea ice in the Beaufort Sea are examined in 2012 when Arctic sea ice extent hit a record low. Satellite-derived sea surface temperature revealed warmer waters closer to river mouths. By 5 July 2012, Mackenzie warm waters occupied most of an open water area about 316,000 sq km. Surface temperature in a common open water area increased by 6.5 C between 14 June and 5 July 2012, before and after the river waters broke through a recurrent landfast ice barrier formed over the shallow seafloor offshore the Mackenzie Delta. In 2012, melting by warm river waters was especially effective when the strong Beaufort Gyre fragmented sea ice into unconsolidated floes. The Mackenzie and other large rivers can transport an enormous amount of heat across immense continental watersheds into the Arctic Ocean, constituting a stark contrast to the Antarctic that has no such rivers to affect sea ice.

  2. NOAA/NMC/CAC Arctic and Antarctic Monthly Sea Ice Extent, 1973-1990

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Sea ice extent from January 1973 through August 1990 was digitized from weekly operational sea ice charts produced by the Navy/NOAA Joint Ice Center. Charts were...

  3. Guide to Sea Ice Information and Sea Ice Data Online - the Sea Ice Knowledge and Data Platform www.meereisportal.de and www.seaiceportal.de

    Science.gov (United States)

    Treffeisen, R. E.; Nicolaus, M.; Bartsch, A.; Fritzsch, B.; Grosfeld, K.; Haas, C.; Hendricks, S.; Heygster, G.; Hiller, W.; Krumpen, T.; Melsheimer, C.; Ricker, R.; Weigelt, M.

    2016-12-01

    The combination of multi-disciplinary sea ice science and the rising demand of society for up-to-date information and user customized products places emphasis on creating new ways of communication between science and society. The new knowledge platform is a contribution to the cross-linking of scientifically qualified information on climate change, and focuses on the theme: `sea ice' in both Polar Regions. With this platform, the science opens to these changing societal demands. It is the first comprehensive German speaking knowledge platform on sea ice; the platform went online in 2013. The web site delivers popularized information for the general public as well as scientific data meant primarily for the more expert readers and scientists. It also provides various tools allowing for visitor interaction. The demand for the web site indicates a high level of interest from both the general public and experts. It communicates science-based information to improve awareness and understanding of sea ice related research. The principle concept of the new knowledge platform is based on three pillars: (1) sea ice knowledge and background information, (2) data portal with visualizations, and (3) expert knowledge, latest research results and press releases. Since then, the content and selection of data sets increased and the data portal received increasing attention, also from the international science community. Meanwhile, we are providing near-real time and archived data of many key parameters of sea ice and its snow cover. The data sets result from measurements acquired by various platforms as well as numerical simulations. Satellite observations (e.g., AMSR2, CryoSat-2 and SMOS) of sea ice concentration, freeboard, thickness and drift are available as gridded data sets. Sea ice and snow temperatures and thickness as well as atmospheric parameters are available from autonomous ice-tethered platforms (buoys). Additional ship observations, ice station measurements, and

  4. Applicability of highly branched isoprenoids as a sea ice proxy in the Ross Sea

    Science.gov (United States)

    Kim, Jung-Hyun; Lee, Jae Il; Belt, Simon T.; Gal, Jong-Ku; Smik, Lukas; Shin, Kyung-Hoon

    2016-04-01

    Sea ice is an integral component of the polar climate system, constraining the effect of changing surface albedo, ocean-atmosphere heat exchanges, the formation of deep and intermediate waters that participate in driving the meridional overturning circulation and thus global climate. In recent years, a mono-unsaturated highly branched isoprenoid (HBI) alkene which is biosynthesised by certain sea ice diatoms during the spring bloom and, upon ice melt, deposited into underlying sediments, has been uniquely observed in Arctic sea ice and in Arctic sediments. Hence, the term IP25 (ice proxy with 25 carbon atoms) was proposed to distinguish this compound from other HBI isomers and has become an established proxy for the reconstruction of Arctic sea ice. In contrast, a monounsaturated HBI alkene, i.e. IP25, has not been observed in sea ice or sediments from the Antarctic. Hence, the application of diene and triene HBI concentrations and the resulting diene/triene (D/T) ratio was alternatively introduced as sea ice/open water indicators in the Southern Ocean. However, there is still lack of data covering the wide areas around the Antarctic, especially from the Ross Sea. Hence, we investigated surface sediment samples from the Ross Sea (n=14) collected during the R/V ARAON cruise in 2015 as well as from the Antarctic Peninsula (n=17) collected during several R/V ARAON cruises between 2001 and 2013. We will present our preliminary results and will discuss the applicability of the HBI in the Ross Sea.

  5. Improving Surface Mass Balance Over Ice Sheets and Snow Depth on Sea Ice

    Science.gov (United States)

    Koenig, Lora Suzanne; Box, Jason; Kurtz, Nathan

    2013-01-01

    Surface mass balance (SMB) over ice sheets and snow on sea ice (SOSI) are important components of the cryosphere. Large knowledge gaps remain in scientists' abilities to monitor SMB and SOSI, including insufficient measurements and difficulties with satellite retrievals. On ice sheets, snow accumulation is the sole mass gain to SMB, and meltwater runoff can be the dominant single loss factor in extremely warm years such as 2012. SOSI affects the growth and melt cycle of the Earth's polar sea ice cover. The summer of 2012 saw the largest satellite-recorded melt area over the Greenland ice sheet and the smallest satellite-recorded Arctic sea ice extent, making this meeting both timely and relevant.

  6. Antarctic last interglacial isotope peak in response to sea ice retreat not ice-sheet collapse.

    Science.gov (United States)

    Holloway, Max D; Sime, Louise C; Singarayer, Joy S; Tindall, Julia C; Bunch, Pete; Valdes, Paul J

    2016-08-16

    Several studies have suggested that sea-level rise during the last interglacial implies retreat of the West Antarctic Ice Sheet (WAIS). The prevalent hypothesis is that the retreat coincided with the peak Antarctic temperature and stable water isotope values from 128,000 years ago (128 ka); very early in the last interglacial. Here, by analysing climate model simulations of last interglacial WAIS loss featuring water isotopes, we show instead that the isotopic response to WAIS loss is in opposition to the isotopic evidence at 128 ka. Instead, a reduction in winter sea ice area of 65±7% fully explains the 128 ka ice core evidence. Our finding of a marked retreat of the sea ice at 128 ka demonstrates the sensitivity of Antarctic sea ice extent to climate warming.

  7. Dependence of NAO variability on coupling with sea ice

    Science.gov (United States)

    Strong, Courtenay; Magnusdottir, Gudrun

    2011-05-01

    The variance of the North Atlantic Oscillation index (denoted N) is shown to depend on its coupling with area-averaged sea ice concentration anomalies in and around the Barents Sea (index denoted B). The observed form of this coupling is a negative feedback whereby positive N tends to produce negative B, which in turn forces negative N. The effects of this feedback in the system are examined by modifying the feedback in two modeling frameworks: a statistical vector autoregressive model ( F VAR) and an atmospheric global climate model ( F CAM) customized so that sea ice anomalies on the lower boundary are stochastic with adjustable sensitivity to the model's evolving N. Experiments show that the variance of N decreases nearly linearly with the sensitivity of B to N, where the sensitivity is a measure of the negative feedback strength. Given that the sea ice concentration field has anomalies, the variance of N goes down as these anomalies become more sensitive to N. If the sea ice concentration anomalies are entirely absent, the variance of N is even smaller than the experiment with the most sensitive anomalies. Quantifying how the variance of N depends on the presence and sensitivity of sea ice anomalies to N has implications for the simulation of N in global climate models. In the physical system, projected changes in sea ice thickness or extent could alter the sensitivity of B to N, impacting the within-season variability and hence predictability of N.

  8. Export of Algal Biomass from the Melting Arctic Sea Ice

    OpenAIRE

    A. Boetius; S. Albrecht; Bakker, K; Bienhold, C.; J. Felden; Fernandez-Mendez, M; Hendricks, S.; C. Katlein; C Lalande; Krumpen, T.; M. Nicolaus; Peeken, I.; Rabe, B.; Rogacheva, A.; Rybakova, E.

    2013-01-01

    In the Arctic, under-ice primary production is limited to summer months and is restricted not only by ice thickness and snow cover but also by the stratification of the water column, which constrains nutrient supply for algal growth. Research Vessel Polarstern visited the ice-covered eastern-central basins between 82° to 89°N and 30° to 130°E in summer 2012, when Arctic sea ice declined to a record minimum. During this cruise, we observed a widespread deposition of ice algal biomass of on ave...

  9. Fabric and crystal characteristics of Bohai and Arctic sea ice

    Institute of Scientific and Technical Information of China (English)

    李志军; 康建成; 蒲毅彬

    2002-01-01

    The fabrics and crystals of Bohai one-year ice show that the noncontinuous ice growth rate enables the level ice layers with different amount of air bubbles to be formed in lower part of an ice sheet which was clearly seen from CT technology; typical grain ice and columnar ice occur in the grey ice which grows in stable water; thaw-refrozen ice and rafted ice have their specific crystal characters. On the Arctic sea ice, the ice core located at 72°24.037′N, 153°33.994′W and 2.2 m in length was a 3-year ice floe and a new sort of crystal was found, which is defined as refrozen clastic pieces. The crystal profile of the ice core 4.86 m in length located at 74°58.614′N, 160°31.830′W shows the evidence that ice ridge changed into hummock.

  10. Sea Surface Wakes Observed by Spaceborne SAR in the Offshore Wind Farms

    Science.gov (United States)

    Li, Xiaoming; Lehner, Susanne; Jacobsen, Sven

    2014-11-01

    In the paper, we present some X-band spaceborne synthetic aperture radar (SAR) TerraSAR-X (TS-X) images acquired at the offshore wind farms in the North Sea and the East China Sea. The high spatial resolution SAR images show different sea surface wake patterns downstream of the offshore wind turbines. The analysis suggests that there are major two types of wakes among the observed cases. The wind turbine wakes generated by movement of wind around wind turbines are the most often observed cases. In contrast, due to the strong local tidal currents in the near shore wind farm sites, the tidal current wakes induced by tidal current impinging on the wind turbine piles are also observed in the high spatial resolution TS-X images. The discrimination of the two types of wakes observed in the offshore wind farms is also described in the paper.

  11. Relating Regional Arctic Sea Ice and climate extremes over Europe

    Science.gov (United States)

    Ionita-Scholz, Monica; Grosfeld, Klaus; Lohmann, Gerrit; Scholz, Patrick

    2016-04-01

    The potential increase of temperature extremes under climate change is a major threat to society, as temperature extremes have a deep impact on environment, hydrology, agriculture, society and economy. Hence, the analysis of the mechanisms underlying their occurrence, including their relationships with the large-scale atmospheric circulation and sea ice concentration, is of major importance. At the same time, the decline in Arctic sea ice cover during the last 30 years has been widely documented and it is clear that this change is having profound impacts at regional as well as planetary scale. As such, this study aims to investigate the relation between the autumn regional sea ice concentration variability and cold winters in Europe, as identified by the numbers of cold nights (TN10p), cold days (TX10p), ice days (ID) and consecutive frost days (CFD). We analyze the relationship between Arctic sea ice variation in autumn (September-October-November) averaged over eight different Arctic regions (Barents/Kara Seas, Beaufort Sea, Chukchi/Bering Seas, Central Arctic, Greenland Sea, Labrador Sea/Baffin Bay, Laptev/East Siberian Seas and Northern Hemisphere) and variations in atmospheric circulation and climate extreme indices in the following winter season over Europe using composite map analysis. Based on the composite map analysis it is shown that the response of the winter extreme temperatures over Europe is highly correlated/connected to changes in Arctic sea ice variability. However, this signal is not symmetrical for the case of high and low sea ice years. Moreover, the response of temperatures extreme over Europe to sea ice variability over the different Arctic regions differs substantially. The regions which have the strongest impact on the extreme winter temperature over Europe are: Barents/Kara Seas, Beaufort Sea, Central Arctic and the Northern Hemisphere. For the years of high sea ice concentration in the Barents/Kara Seas there is a reduction in the number

  12. Remote Oil Spill Detection and Monitoring Beneath Sea Ice

    Science.gov (United States)

    Polak, Adam; Marshall, Stephen; Ren, Jinchang; Hwang, Byongjun (Phil); Hagan, Bernard; Stothard, David J. M.

    2016-08-01

    The spillage of oil in Polar Regions is particularly serious due to the threat to the environment and the difficulties in detecting and tracking the full extent of the oil seepage beneath the sea ice. Development of fast and reliable sensing techniques is highly desirable. In this paper hyperspectral imaging combined with signal processing and classification techniques are proposed as a potential tool to detect the presence of oil beneath the sea ice. A small sample, lab based experiment, serving as a proof of concept, resulted in the successful identification of oil presence beneath the thin ice layer as opposed to the other sample with ice only. The paper demonstrates the results of this experiment that granted a financial support to execute full feasibility study of this technology for oil spill detection beneath the sea ice.

  13. Introduction of parameterized sea ice drag coefficients into ice free-drift modeling

    Institute of Scientific and Technical Information of China (English)

    LU Peng; LI Zhijun; HAN Hongwei

    2016-01-01

    Many interesting characteristics of sea ice drift depend on the atmospheric drag coefficient (Ca) and oceanic drag coefficient (Cw). Parameterizations of drag coefficients rather than constant values provide us a way to look insight into the dependence of these characteristics on sea ice conditions. In the present study, the parameterized ice drag coefficients are included into a free-drift sea ice dynamic model, and the wind factorα and the deflection angleθ between sea ice drift and wind velocity as well as the ratio ofCa toCw are studied to investigate their dependence on the impact factors such as local drag coefficients, floe and ridge geometry. The results reveal that in an idealized steady ocean,Ca/Cw increases obviously with the increasing ice concentration for small ice floes in the marginal ice zone, while it remains at a steady level (0.2–0.25) for large floes in the central ice zone. The wind factorα increases rapidly at first and approaches a steady level of 0.018 whenA is greater than 20%. And the deflection angleθ drops rapidly from an initial value of approximate 80° and decreases slowly asA is greater than 20% without a steady level likeα. The values of these parameters agree well with the previously reported observations in Arctic. The ridging intensity is an important parameter to determine the dominant contribution of the ratio of skin friction drag coefficient (Cs’/Cs) and the ratio of ridge form drag coefficient (Cr’/Cr) to the value of Ca/Cw,α, andθ, because of the dominance of ridge form drag for large ridging intensity and skin friction for small ridging intensity among the total drag forces. Parameterization of sea ice drag coefficients has the potential to be embedded into ice dynamic models to better account for the variability of sea ice in the transient Arctic Ocean.

  14. The Satellite Passive-Microwave Record of Sea Ice in the Ross Sea Since Late 1978

    Science.gov (United States)

    Parkinson, Claire L.

    2009-01-01

    Satellites have provided us with a remarkable ability to monitor many aspects of the globe day-in and day-out and sea ice is one of numerous variables that by now have quite substantial satellite records. Passive-microwave data have been particularly valuable in sea ice monitoring, with a record that extends back to August 1987 on daily basis (for most of the period), to November 1970 on a less complete basis (again for most of the period), and to December 1972 on a less complete basis. For the period since November 1970, Ross Sea sea ice imagery is available at spatial resolution of approximately 25 km. This allows good depictions of the seasonal advance and retreat of the ice cover each year, along with its marked interannual variability. The Ross Sea ice extent typically reaches a minimum of approximately 0.7 x 10(exp 6) square kilometers in February, rising to a maximum of approximately 4.0 x 10(exp 6) square kilometers in September, with much variability among years for both those numbers. The Ross Sea images show clearly the day-by-day activity greatly from year to year. Animations of the data help to highlight the dynamic nature of the Ross Sea ice cover. The satellite data also allow calculation of trends in the ice cover over the period of the satellite record. Using linear least-squares fits, the Ross Sea ice extent increased at an average rate of 12,600 plus or minus 1,800 square kilometers per year between November 1978 and December 2007, with every month exhibiting increased ice extent and the rates of increase ranging from a low of 7,500 plus or minus 5,000 square kilometers per year for the February ice extents to a high of 20,300 plus or minus 6,100 kilometers per year for the October ice extents. On a yearly average basis, for 1979-2007 the Ross Sea ice extent increased at a rate of 4.8 plus or minus 1.6 % per decade. Placing the Ross Sea in the context of the Southern Ocean as a whole, over the November 1978-December 2007 period the Ross Sea had

  15. Arctic Sea Ice Charts from Danish Meteorological Institute, 1893 - 1956

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — From 1893 to 1956, the Danish Meteorological Institute (DMI) created charts of observed and inferred sea ice extent for each summer month. These charts are based on...

  16. Sea Ice Prediction Has Easy and Difficult Years

    Science.gov (United States)

    Hamilton, Lawrence C.; Bitz, Cecilia M.; Blanchard-Wrigglesworth, Edward; Cutler, Matthew; Kay, Jennifer; Meier, Walter N.; Stroeve, Julienne; Wiggins, Helen

    2014-01-01

    Arctic sea ice follows an annual cycle, reaching its low point in September each year. The extent of sea ice remaining at this low point has been trending downwards for decades as the Arctic warms. Around the long-term downward trend, however, there is significant variation in the minimum extent from one year to the next. Accurate forecasts of yearly conditions would have great value to Arctic residents, shipping companies, and other stakeholders and are the subject of much current research. Since 2008 the Sea Ice Outlook (SIO) (http://www.arcus.org/search-program/seaiceoutlook) organized by the Study of Environmental Arctic Change (SEARCH) (http://www.arcus.org/search-program) has invited predictions of the September Arctic sea ice minimum extent, which are contributed from the Arctic research community. Individual predictions, based on a variety of approaches, are solicited in three cycles each year in early June, July, and August. (SEARCH 2013).

  17. Global warming releases microplastic legacy frozen in Arctic Sea ice

    National Research Council Canada - National Science Library

    Obbard, Rachel W; Sadri, Saeed; Wong, Ying Qi; Khitun, Alexandra A; Baker, Ian; Thompson, Richard C

    2014-01-01

    .... Here we show that Arctic Sea ice from remote locations contains concentrations of microplastics at least two orders of magnitude greater than those that have been previously reported in highly...

  18. Sea Ice Melt Pond Data from the Canadian Arctic

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set contains observations of albedo, depth, and physical characteristics of melt ponds on sea ice, taken during the summer of 1994. The melt ponds studied...

  19. Large-Scale Surveys of Snow Depth on Arctic Sea Ice from Operation IceBridge

    Science.gov (United States)

    Kurtz, Nathan T.; Farrell, Sinead L.

    2011-01-01

    We show the first results of a large ]scale survey of snow depth on Arctic sea ice from NASA fs Operation IceBridge snow radar system for the 2009 season and compare the data to climatological snow depth values established over the 1954.1991 time period. For multiyear ice, the mean radar derived snow depth is 33.1 cm and the corresponding mean climatological snow depth is 33.4 cm. The small mean difference suggests consistency between contemporary estimates of snow depth with the historical climatology for the multiyear ice region of the Arctic. A 16.5 cm mean difference (climatology minus radar) is observed for first year ice areas suggesting that the increasingly seasonal sea ice cover of the Arctic Ocean has led to an overall loss of snow as the region has transitioned away from a dominantly multiyear ice cover.

  20. Modelling sea ice formation in the Terra Nova Bay polynya

    Science.gov (United States)

    Sansiviero, M.; Morales Maqueda, M. Á.; Fusco, G.; Aulicino, G.; Flocco, D.; Budillon, G.

    2017-02-01

    Antarctic sea ice is constantly exported from the shore by strong near surface winds that open leads and large polynyas in the pack ice. The latter, known as wind-driven polynyas, are responsible for significant water mass modification due to the high salt flux into the ocean associated with enhanced ice growth. In this article, we focus on the wind-driven Terra Nova Bay (TNB) polynya, in the western Ross Sea. Brine rejected during sea ice formation processes that occur in the TNB polynya densifies the water column leading to the formation of the most characteristic water mass of the Ross Sea, the High Salinity Shelf Water (HSSW). This water mass, in turn, takes part in the formation of Antarctic Bottom Water (AABW), the densest water mass of the world ocean, which plays a major role in the global meridional overturning circulation, thus affecting the global climate system. A simple coupled sea ice-ocean model has been developed to simulate the seasonal cycle of sea ice formation and export within a polynya. The sea ice model accounts for both thermal and mechanical ice processes. The oceanic circulation is described by a one-and-a-half layer, reduced gravity model. The domain resolution is 1 km × 1 km, which is sufficient to represent the salient features of the coastline geometry, notably the Drygalski Ice Tongue. The model is forced by a combination of Era Interim reanalysis and in-situ data from automatic weather stations, and also by a climatological oceanic dataset developed from in situ hydrographic observations. The sensitivity of the polynya to the atmospheric forcing is well reproduced by the model when atmospheric in situ measurements are combined with reanalysis data. Merging the two datasets allows us to capture in detail the strength and the spatial distribution of the katabatic winds that often drive the opening of the polynya. The model resolves fairly accurately the sea ice drift and sea ice production rates in the TNB polynya, leading to

  1. 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.

  2. Processes controlling surface, bottom and lateral melt of Arctic sea ice in a state of the art sea ice model.

    Science.gov (United States)

    Tsamados, Michel; Feltham, Daniel; Petty, Alek; Schroeder, David; Flocco, Daniela

    2015-10-13

    We present a modelling study of processes controlling the summer melt of the Arctic sea ice cover. We perform a sensitivity study and focus our interest on the thermodynamics at the ice-atmosphere and ice-ocean interfaces. We use the Los Alamos community sea ice model CICE, and additionally implement and test three new parametrization schemes: (i) a prognostic mixed layer; (ii) a three equation boundary condition for the salt and heat flux at the ice-ocean interface; and (iii) a new lateral melt parametrization. Recent additions to the CICE model are also tested, including explicit melt ponds, a form drag parametrization and a halodynamic brine drainage scheme. The various sea ice parametrizations tested in this sensitivity study introduce a wide spread in the simulated sea ice characteristics. For each simulation, the total melt is decomposed into its surface, bottom and lateral melt components to assess the processes driving melt and how this varies regionally and temporally. Because this study quantifies the relative importance of several processes in driving the summer melt of sea ice, this work can serve as a guide for future research priorities. © 2015 The Author(s).

  3. Seasonal cycle of solar energy fluxes through Arctic sea ice

    Directory of Open Access Journals (Sweden)

    S. Arndt

    2014-06-01

    Full Text Available Arctic sea ice has not only decreased considerably during the last decades, but also changed its physical properties towards a thinner and more seasonal cover. These changes strongly impact the energy budget and might affect the ice-associated ecosystem of the Arctic. But until now, it is not possible to quantify shortwave energy fluxes through sea ice sufficiently well over large regions and during different seasons. Here, we present a new parameterization of light transmittance through sea ice for all seasons as a function of variable sea ice properties. The annual maximum solar heat flux of 30 × 105 J m−2 occurs in June, then also matching the under ice ocean heat flux. Furthermore, our results suggest that 96% of the total annual solar heat input occurs from May to August, during four months only. Applying the new parameterization on remote sensing and reanalysis data from 1979 to 2011, we find an increase in light transmission of 1.5% a−1 for all regions. Sensitivity studies reveal that the results strongly depend on the timing of melt onset and the correct classification of ice types. Hence, these parameters are of great importance for quantifying under-ice radiation fluxes and the uncertainty of this parameterization. Assuming a two weeks earlier melt onset, the annual budget increases by 20%. Continuing the observed transition from Arctic multi- to first year sea ice could increase light transmittance by another 18%. Furthermore, the increase in light transmission directly contributes to an increase in internal and bottom melt of sea ice, resulting in a positive transmittance-melt feedback process.

  4. Ice gouge processes in the Alaskan Beaufort Sea

    Science.gov (United States)

    Rearic, Douglas M.; Ticken, Edward J.

    1988-01-01

    A generalized picture of ice gouge characteristics from shallow inshore depths to the outer shelf at about 60 m of water is presented. Data from recent studies show that the size and quantity of gouging increases in an offshore direction to depths of about 45 m where this trend then reverses and the features decrease in size and quantity as the shelf break is approached. Ice gouges are oriented east-west and this suggests that most gouging is caused by ice approaching from the east, possibly driven by the Beaufort Sea gyre. The most intense gouging occurs in the stamukhi zone, between 20 and 40 m of water, and is caused by a high rate of ice keel production owing to shearing forces between mobile and stable sea ice. Inshore of the stamukhi zone, ice gouging still presents a significant hazard but their greatly decreased size and number make it possible to design against this hazard.

  5. Antarctic Sea Ice-a Habitat for Extremophiles

    Science.gov (United States)

    Thomas, D. N.; Dieckmann, G. S.

    2002-01-01

    The pack ice of Earth's polar oceans appears to be frozen white desert, devoid of life. However, beneath the snow lies a unique habitat for a group of bacteria and microscopic plants and animals that are encased in an ice matrix at low temperatures and light levels, with the only liquid being pockets of concentrated brines. Survival in these conditions requires a complex suite of physiological and metabolic adaptations, but sea-ice organisms thrive in the ice, and their prolific growth ensures they play a fundamental role in polar ecosystems. Apart from their ecological importance, the bacterial and algae species found in sea ice have become the focus for novel biotechnology, as well as being considered proxies for possible life forms on ice-covered extraterrestrial bodies.

  6. Role for Atlantic inflows and sea ice loss on shifting phytoplankton blooms in the Barents Sea

    Science.gov (United States)

    Oziel, L.; Neukermans, G.; Ardyna, M.; Lancelot, C.; Tison, J.-L.; Wassmann, P.; Sirven, J.; Ruiz-Pino, D.; Gascard, J.-C.

    2017-06-01

    Phytoplankton blooms in the Barents Sea are highly sensitive to seasonal and interannual changes in sea ice extent, water mass distribution, and oceanic fronts. With the ongoing increase of Atlantic Water inflows, we expect an impact on these blooms. Here, we use a state-of-the-art collection of in situ hydrogeochemical data for the period 1998-2014, which includes ocean color satellite-derived proxies for the biomass of calcifying and noncalcifying phytoplankton. Over the last 17 years, sea ice extent anomalies were evidenced having direct consequences for the spatial extent of spring blooms in the Barents Sea. In years of minimal sea ice extent, two spatially distinct blooms were clearly observed: one along the ice edge and another in ice-free water. These blooms are thought to be triggered by different stratification mechanisms: heating of the surface layers in ice-free waters and melting of the sea ice along the ice edge. In years of maximal sea ice extent, no such spatial delimitation was observed. The spring bloom generally ended in June when nutrients in the surface layer were depleted. This was followed by a stratified and oligotrophic summer period. A coccolithophore bloom generally developed in August, but was confined only to Atlantic Waters. In these same waters, a late summer bloom of noncalcifying algae was observed in September, triggered by enhanced mixing, which replenishes surface waters with nutrients. Altogether, the 17 year time-series revealed a northward and eastward shift of the spring and summer phytoplankton blooms.

  7. Impact of declining Arctic sea ice on winter snowfall

    OpenAIRE

    Liu, Jiping; Curry, Judith A.; Wang, Huijun; Song, Mirong; Radley M. Horton

    2012-01-01

    While the Arctic region has been warming strongly in recent decades, anomalously large snowfall in recent winters has affected large parts of North America, Europe, and east Asia. Here we demonstrate that the decrease in autumn Arctic sea ice area is linked to changes in the winter Northern Hemisphere atmospheric circulation that have some resemblance to the negative phase of the winter Arctic oscillation. However, the atmospheric circulation change linked to the reduction of sea ice shows mu...

  8. "Rotten Ice": Characterizing the Physical Properties of Arctic Sea Ice Under Conditions of Extreme Summer Melt

    Science.gov (United States)

    Light, B.; Frantz, C. M.; Junge, K.; Orellana, M. V.; Carpenter, S.; Farley, S. M.; Lieb-Lappen, R.; Courville, Z.

    2016-12-01

    The microstructural properties of sea ice are central to understanding the mechanical, thermal, electrical, and optical properties of a sea ice cover. Over the course of an annual cycle, this small scale structure routinely evolves from a network of mostly isolated brine and gas inclusions prevalent in cold ice, to a more connected, more permeable structure as the ice endures summer melt processes. In the case of extreme summer melt, sea ice can become "rotten", and it is expected that such rotten ice may become more prevalent as melt seasons lengthen. Rotten ice is approximately isothermal, largely drained of brine, and is typified by the presence of large multi-cm-scale void spaces that contribute to its high permeability and low structural integrity. These properties are expected to alter the ice cover response to dynamic forcing, ability to backscatter incident light, and its melt rate. An interdisciplinary effort to characterize the physical properties of rotten first-year ice, in concert with some of its chemical and biological properties, is being carried out both in the field and in the laboratory. Time-series samples focusing on the evolution of ice microstructure were acquired and analyzed for shore-fast first-year sea ice near Barrow, Alaska in May - July of 2015. Laboratory studies have focused on assessing the seasonal evolution of optical properties of this ice, as well as the measurement of melt rates of ice grown under carefully controlled laboratory conditions. Preliminary results from these studies illuminate some of the physical and biophysical controls on late summer ice melt.

  9. Floating Ice-Algal Aggregates below melting Arctic Sea Ice

    OpenAIRE

    Philipp Assmy; Jens K. Ehn; Mar Fernández-Méndez; Haakon Hop; Christian Katlein; Arild Sundfjord; Katrin Bluhm; Malin Daase; Anja Engel; Agneta Fransson; Granskog, Mats A.; Hudson, Stephen R.; Svein Kristiansen; Marcel Nicolaus; Ilka Peeken

    2013-01-01

    During two consecutive cruises to the Eastern Central Arctic in late summer 2012, we observed floating algal aggregates in the melt-water layer below and between melting ice floes of first-year pack ice. The macroscopic (1 – 15 cm in diameter) aggregates had a mucous consistency and were dominated by typical ice-associated pennate diatoms embedded within the mucous matrix. Aggregates maintained buoyancy and accumulated just above a strong pycnocline that separated meltwater and seawater layer...

  10. Atmospheric forcing of sea ice anomalies in the Ross Sea Polynya region

    Science.gov (United States)

    Dale, Ethan; McDonald, Adrian; Rack, Wolfgang

    2016-04-01

    Despite warming trends in global temperatures, sea ice extent in the southern hemisphere has shown an increasing trend over recent decades. Wind-driven sea ice export from coastal polynyas is an important source of sea ice production. Areas of major polynyas in the Ross Sea, the region with largest increase in sea ice extent, have been suggested to produce the vast amount of the sea ice in the region. We investigate the impacts of strong wind events on polynyas and the subsequent sea ice production. We utilize Bootstrap sea ice concentration (SIC) measurements derived from satellite based, Special Sensor Microwave Imager (SSM/I) brightness temperature images. These are compared with surface wind measurements made by automatic weather stations of the University of Wisconsin-Madison Antarctic Meteorology Program. Our analysis focusses on the winter period defined as 1st April to 1st November in this study. Wind data was used to classify each day into characteristic regimes based on the change of wind speed. For each regime, a composite of SIC anomaly was formed for the Ross Sea region. We found that persistent weak winds near the edge of the Ross Ice Shelf are generally associated with positive SIC anomalies in the Ross Sea polynya area (RSP). Conversely we found negative SIC anomalies in this area during persistent strong winds. By analyzing sea ice motion vectors derived from SSM/I brightness temperatures, we find significant sea ice motion anomalies throughout the Ross Sea during strong wind events. These anomalies persist for several days after the strong wing event. Strong, negative correlations are found between SIC within the RSP and wind speed indicating that strong winds cause significant advection of sea ice in the RSP. This rapid decrease in SIC is followed by a more gradual recovery in SIC. This increase occurs on a time scale greater than the average persistence of strong wind events and the resulting Sea ice motion anomalies, highlighting the production

  11. A Modified NASA Team Sea Ice Algorithm for the Antarctic

    Science.gov (United States)

    Cavalieri, Donald J.; Markus, Thorsten

    1998-01-01

    A recent comparative study of the NASA Team and Bootstrap passive microwave sea ice algorithms revealed significantly different sea ice concentration retrievals in some parts of the Antarctic. The study identified potential reasons for the discrepancies including the influence of sea ice temperature variability on the Bootstrap retrievals and the influence of ice surface reflectivity on the horizontally polarized emissivity in the NASA Team retrievals. In this study, we present a modified version of the NASA Team algorithm which reduces the error associated with the use of horizontally polarized radiance data, while retaining the relative insensitivity to ice temperature variations provided by radiance ratios. By retaining the 19 GHz polarization as an independent variable, we also maintain a relatively large dynamic range in sea ice concentration. The modified algorithm utilizes the 19 GHz polarization (PR19) and both gradient ratios, GRV and GRH defined by (37V-19V)/(37V+19V) and (37H-19H)/(37H+19H), respectively, rather than just GRV used in the current NASA Team algorithm. A plot of GRV versus GRH shows that the preponderance of points lie along a quadratic curve, whereas those points affected by surface reflectivity anomalies deviate from this curve. This serves as a method of identifying the problems points. The 19H brightness temperature of these problem points is increased so they too fall along quadratic curve. Sea ice concentrations derived from AVHRR imagery illustrate the extent to which this method reduces the error associated with surface layering.

  12. Forecasting Future Sea Ice Conditions: A Lagrangian Approach

    Science.gov (United States)

    2015-09-30

    are preceded by a pulse of heat of Atlantic origin into the Arctic Ocean , causing an increase in open water area, and absorbed solar radiation at the...Transport in Sea Ice and Ocean Surface Waters from Ten Potential Spill Sites Marine Pollution Bulletin, Marine Pollution Bulletin, 2015. 12 3- Hata...keywhich factors most important in explaining the promotion of first year ice into multi- year ice, including ocean heat fluxes, radiative and

  13. Model resolution influence on simulated sea ice decline

    OpenAIRE

    Sewall, J.O.

    2008-01-01

    Satellite observations and model predictions of recent and future Arctic sea ice decline have raised concerns over the timing and potential impacts of a seasonally ice-free Arctic Ocean. Model predictions of seasonally ice-free Arctic conditions are, however, highly variable. Here I present results from fourteen climate system models from the World Climate Research Programme's (WCRP's) Coupled Model Intercomparison Project phase 3 (CMIP3) multi-model dataset that indicate modeled Ar...

  14. Large sea ice outflow into the Nares Strait in 2007

    DEFF Research Database (Denmark)

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

    2010-01-01

    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......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...

  15. A Validation Dataset for CryoSat Sea Ice Investigators

    DEFF Research Database (Denmark)

    Julia, Gaudelli,; Baker, Steve; Haas, Christian;

    Since its launch in April 2010 Cryosat has been collecting valuable sea ice data over the Arctic region. Over the same period ESA’s CryoVEx and NASA IceBridge validation campaigns have been collecting a unique set of coincident airborne measurements in the Arctic. The CryoVal-SI project has colla...

  16. Arctic sea ice reaches second lowest in satellite record

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    Xinhua reports that the blanket of sea ice that floats on the Arctic Ocean appears to have reached its lowest extent for 2011, the second lowest recorded since satellites began measuring it in 1979, according to a report released on September 15 by the University of Colorado Boulder's National Snow and Ice Data Center (NSIDC).

  17. Numerical modelling of thermodynamics and dynamics of sea ice in the Baltic Sea

    Directory of Open Access Journals (Sweden)

    A. Herman

    2011-01-01

    Full Text Available In this paper, a numerical dynamic-thermodynamic sea-ice model for the Baltic Sea is used to analyze the variability of ice conditions in three winter seasons. The modelling results are validated with station (water temperature and satellite data (ice concentration as well as by qualitative comparisons with the Swedish Meteorological and Hydrological Institute ice charts. Analysis of the results addresses two major questions. One concerns effects of meteorological forcing on the spatio-temporal distribution of ice concentration in the Baltic. Patterns of correlations between air temperature, wind speed, and ice-covered area are demonstrated to be different in larger, more open sub-basins (e.g., the Bothnian Sea than in the smaller ones (e.g., the Bothnian Bay. Whereas the correlations with the air temperature are positive in both cases, the influence of wind is pronounced only in large basins, leading to increase/decrease of areas with small/large ice concentrations, respectively. The other question concerns the role of ice dynamics in the evolution of the ice cover. By means of simulations with the dynamic model turned on and off, the ice dynamics is shown to play a crucial role in interactions between the ice and the upper layers of the water column, especially during periods with highly varying wind speeds and directions. In particular, due to the fragmentation of the ice cover and the modified surface fluxes, the ice dynamics influences the rate of change of the total ice volume, in some cases by as much as 1 km3 per day. As opposed to most other numerical studies on the sea-ice in the Baltic Sea, this work concentrates on the short-term variability of the ice cover and its response to the synoptic-scale forcing.

  18. Numerical modelling of thermodynamics and dynamics of sea ice in the Baltic Sea

    Directory of Open Access Journals (Sweden)

    A. Herman

    2011-04-01

    Full Text Available In this paper, a numerical dynamic-thermo-dynamic sea-ice model for the Baltic Sea is used to analyze the variability of ice conditions in three winter seasons. The modelling results are validated with station (water temperature and satellite data (ice concentration as well as by qualitative comparisons with the Swedish Meteorological and Hydrological Institute ice charts. Analysis of the results addresses two major questions. One concerns effects of meteorological forcing on the spatio-temporal distribution of ice concentration in the Baltic. Patterns of correlations between air temperature, wind speed, and ice-covered area are demonstrated to be different in larger, more open sub-basins (e.g., the Bothnian Sea than in the smaller ones (e.g., the Bothnian Bay. Whereas the correlations with the air temperature are positive in both cases, the influence of wind is pronounced only in large basins, leading to increase/decrease of areas with small/large ice concentrations, respectively. The other question concerns the role of ice dynamics in the evolution of the ice cover. By means of simulations with the dynamic model turned on and off, the ice dynamics is shown to play a crucial role in interactions between the ice and the upper layers of the water column, especially during periods with highly varying wind speeds and directions. In particular, due to the fragmentation of the ice cover and the modified surface fluxes, the ice dynamics influences the rate of change of the total ice volume, in some cases by as much as 1 km3 per day. As opposed to most other numerical studies on the sea-ice in the Baltic Sea, this work concentrates on the short-term variability of the ice cover and its response to the synoptic-scale forcing.

  19. Global Daily Sea Ice Concentration Reprocessing Data Set for 1978-2007 from the EUMETSAT Ocean and Sea Ice Satellite Application Facility (NCEI Accession 0068294)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — These data constitute the reprocessed sea ice concentration data set from the EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI SAF), covering the...

  20. Arctic Ocean sea ice drift origin derived from artificial radionuclides.

    Science.gov (United States)

    Cámara-Mor, P; Masqué, P; Garcia-Orellana, J; Cochran, J K; Mas, J L; Chamizo, E; Hanfland, C

    2010-07-15

    Since the 1950s, nuclear weapon testing and releases from the nuclear industry have introduced anthropogenic radionuclides into the sea, and in many instances their ultimate fate are the bottom sediments. The Arctic Ocean is one of the most polluted in this respect, because, in addition to global fallout, it is impacted by regional fallout from nuclear weapon testing, and indirectly by releases from nuclear reprocessing facilities and nuclear accidents. Sea-ice formed in the shallow continental shelves incorporate sediments with variable concentrations of anthropogenic radionuclides that are transported through the Arctic Ocean and are finally released in the melting areas. In this work, we present the results of anthropogenic radionuclide analyses of sea-ice sediments (SIS) collected on five cruises from different Arctic regions and combine them with a database including prior measurements of these radionuclides in SIS. The distribution of (137)Cs and (239,240)Pu activities and the (240)Pu/(239)Pu atom ratio in SIS showed geographical differences, in agreement with the two main sea ice drift patterns derived from the mean field of sea-ice motion, the Transpolar Drift and Beaufort Gyre, with the Fram Strait as the main ablation area. A direct comparison of data measured in SIS samples against those reported for the potential source regions permits identification of the regions from which sea ice incorporates sediments. The (240)Pu/(239)Pu atom ratio in SIS may be used to discern the origin of sea ice from the Kara-Laptev Sea and the Alaskan shelf. However, if the (240)Pu/(239)Pu atom ratio is similar to global fallout, it does not provide a unique diagnostic indicator of the source area, and in such cases, the source of SIS can be constrained with a combination of the (137)Cs and (239,240)Pu activities. Therefore, these anthropogenic radionuclides can be used in many instances to determine the geographical source area of sea-ice.

  1. Bellingshausen Sea ice extent recorded in an Antarctic Peninsula ice core

    Science.gov (United States)

    Porter, Stacy E.; Parkinson, Claire L.; Mosley-Thompson, Ellen

    2016-12-01

    Annual net accumulation (An) from the Bruce Plateau (BP) ice core retrieved from the Antarctic Peninsula exhibits a notable relationship with sea ice extent (SIE) in the Bellingshausen Sea. Over the satellite era, both BP An and Bellingshausen SIE are influenced by large-scale climatic factors such as the Amundsen Sea Low, Southern Annular Mode, and Southern Oscillation. In addition to the direct response of BP An to Bellingshausen SIE (e.g., more open water as a moisture source), these large-scale climate phenomena also link the BP and the Bellingshausen Sea indirectly such that they exhibit similar responses (e.g., northerly wind anomalies advect warm, moist air to the Antarctic Peninsula and neighboring Bellingshausen Sea, which reduces SIE and increases An). Comparison with a time series of fast ice at South Orkney Islands reveals a relationship between BP An and sea ice in the northern Weddell Sea that is relatively consistent over the twentieth century, except when it is modulated by atmospheric wave patterns described by the Trans-Polar Index. The trend of increasing accumulation on the Bruce Plateau since 1970 agrees with other climate records and reconstructions in the region and suggests that the current rate of sea ice loss in the Bellingshausen Sea is unrivaled in the twentieth century.

  2. On using numerical sea-ice prediction and indigenous observations to improve operational sea-ice forecasts during spring in the bering sea

    Science.gov (United States)

    Deemer, Gregory Joseph

    Impacts of a rapidly changing climate are amplified in the Arctic. The most notorious change has come in the form of record-breaking summertime sea-ice retreat. Larger areas of open water and a prolonged ice-free season create opportunity for some industries, but bring new challenges to indigenous populations that rely on sea-ice cover for subsistence. Observed and projected increases in maritime activities require accurate sea-ice forecasts on the weather timescale, which are currently lacking. Motivated by this need, this study explores how new modeling developments and local-scale observations can contribute to improving sea-ice forecasts. The Arctic Cap Nowcast/Forecast System, a research sea-ice forecast model developed by the U.S. Navy, is evaluated for forecast skill. Forecasts of ice concentration, thickness, and drift speed produced by the model from April through June 2011 in the Bering Sea were investigated to determine how the model performs relative to persistence and climatology. Results show that model forecasts can outperform forecasts based on climatology or persistence. However, predictive skill is less consistent during powerful, synoptic-scale events and near the Bering Slope. Forecast case studies in Western Alaska were presented. Community-based observations from recognized indigenous sea-ice experts have been analyzed to gauge the prospect of using local observations in the operational sea-ice monitoring and prediction process. Local observations were discussed in the context of cross-validating model guidance, data sources used in operational ice monitoring, and public sea-ice information products issued by the U.S. National Weather Service. Instrumentation for observing sea-ice and weather at the local scale was supplied to key observers. The instrumentation shows utility in the field and may help translate the context of indigenous observations and provide ground-truth data for use by forecasters.

  3. Arctic autumn sea ice decline and Asian winter temperature anomaly

    Institute of Scientific and Technical Information of China (English)

    LIU Na; LIN Lina; WANG Yingjie; KONG Bin; ZHANG Zhanhai; CHEN Hongxia

    2016-01-01

    Associations between the autumn Arctic sea ice concentration (SIC) and Asian winter temperature are discussed using the singular value decomposition analysis. Results show that in recent 33 years reduced autumn Arctic sea ice is accompanied by Asian winter temperature decrease except in the Tibetan plateau and the Arctic Ocean and the North Pacific Ocean coast. The autumn SIC reduction excites two geopotential height centers in Eurasia and the north Arctic Ocean, which are persistent from autumn to winter. The negative center is in Barents Sea/Kara Sea. The positive center is located in Mongolia. The anomalous winds are associated with geopotential height centers, providing favorable clod air for the Asian winter temperature decreasing in recent 33 years. This relationship indicates a potential long-term outlook for the Asian winter temperature decrease as the decline of the autumn sea ice in the Arctic Ocean is expected to continue as climate warms.

  4. Sea ice occurrence predicts genetic isolation in the Arctic fox.

    Science.gov (United States)

    Geffen, Eli; Waidyaratne, Sitara; Dalén, Love; Angerbjörn, Anders; Vila, Carles; Hersteinsson, Pall; Fuglei, Eva; White, Paula A; Goltsman, Michael; Kapel, Christian M O; Wayne, Robert K

    2007-10-01

    Unlike Oceanic islands, the islands of the Arctic Sea are not completely isolated from migration by terrestrial vertebrates. The pack ice connects many Arctic Sea islands to the mainland during winter months. The Arctic fox (Alopex lagopus), which has a circumpolar distribution, populates numerous islands in the Arctic Sea. In this study, we used genetic data from 20 different populations, spanning the entire distribution of the Arctic fox, to identify barriers to dispersal. Specifically, we considered geographical distance, occurrence of sea ice, winter temperature, ecotype, and the presence of red fox and polar bear as nonexclusive factors that influence the dispersal behaviour of individuals. Using distance-based redundancy analysis and the BIOENV procedure, we showed that occurrence of sea ice is the key predictor and explained 40-60% of the genetic distance among populations. In addition, our analysis identified the Commander and Pribilof Islands Arctic populations as genetically unique suggesting they deserve special attention from a conservation perspective.

  5. Climate change and ice hazards in the Beaufort Sea

    Directory of Open Access Journals (Sweden)

    D. G. Barber

    2014-03-01

    Full Text Available Abstract 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 and gas deposits known to occur throughout the Arctic. Here we show that hazardous ice features remain a threat to stationary and mobile infrastructure in the southern Beaufort Sea. With the opening up of the ice pack, forecasting of high-frequency oscillations or local eddy-driven ice motion 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 fields ‘up-stream’ from drilling and extraction operations.

  6. Wind waves in ice-free areas of Arctic seas.

    Science.gov (United States)

    Golubkin, Pavel; Chapron, Bertrand; Kudryavtsev, Vladimir

    Wind-generated waves in Kara, Laptev and East Siberian Seas are investigated using altimeter data from ENVISAT and SARAL-AltiKa. Only the “isolated” ice-free areas had been selected for analysis. In this case wind seas can be treated as pure wind-generated waves without any contamination by the swell. The isolated ice-free areas are identified using National Snow & Ice Data Center (NSIDC) ice concentration data generated from brightness temperatures derived from Special Sensor Microwave/Imager (SSM/I) and Special Sensor Microwave Imager/Sounder (SSMIS) on board the Defense Meteorological Satellite Program (DMSP) F13 and F17 satellites, respectively. The altimeter data, both significant wave height (SWH) and wind speed which were accompanied with ASCAT scatterometer wind velocity field (since 2007), have been selected for these areas in the time period 2002-2013. This data set is analyzed in terms of dimensionless SWH and dimensionless ice-free area. Either of these quantities is scaled using “standard” dimension analysis based on wind speed and gravity acceleration. Universal empirical dependences of dimensionless SWH on dimensionless ice-free areas are established. At smallest ice-free areas they are consistent with known universal dependences for wind wave generation at fetch limited conditions. At the largest ice-free areas the established dependences are consistent with field data for the open ocean conditions. Impact of climate change and ice melting in the Arctic areas on wind seas is discussed.

  7. Sensitivity of ocean circulation and sea-ice conditions to loss of West Antarctic ice shelves and ice sheet

    Science.gov (United States)

    Bougamont, Marion; Hunke, Elizabeth C.; Tulaczyk, Slawek

    We use a global coupled ocean-sea ice model to test the hypothesis that the disintegration of the West Antarctic ice sheet (WAIS), or just its ice shelves, may modify ocean circulation and sea-ice conditions in the Southern Ocean. We compare the results of three model runs: (1) a control run with a standard (modern) configuration of landmask in West Antarctica, (2) a no-shelves run with West Antarctic ice shelves removed and (3) a no-WAIS run. In the latter two runs, up to a few million square kilometres of new sea surface area opens to sea-ice formation, causing the volume and extent of Antarctic sea-ice cover to increase compared with the control run. In general, near-surface waters are cooler around Antarctica in the no-shelves and no-WAIS model runs than in the control run, while warm intermediate and deep waters penetrate further south, increasing poleward heat transport. Varying regional responses to the imposed changes in landmask configuration are determined by the fact that Antarctic polynyas and fast ice develop in different parts of the model domain in each run. Model results suggest that changes in the extent of WAIS may modify oceanographic conditions in the Southern Ocean.

  8. Arctic Autumn Air-Ice-Ocean Interactions Resulting from Recent Sea-ice Decline

    Science.gov (United States)

    Persson, Ola; Blomquist, Byron; Fairall, Christopher; Guest, Peter; Stammerjohn, Sharon; Rainville, Luc; Thomson, Jim; Smith, Madison; Tjernström, Michael; Solomon, Amy

    2017-04-01

    The recent decline in Arctic sea-ice extent has produced large areas of open water in September that were previously ice covered. Autumn air-ice-ocean interactions in these regions are now characterized by ice-edge or marginal ice zone (MIZ) processes rather than by primarily air-ice refreezing processes. This study will utilize field program measurements to illustrate this change in processes, provide examples of new processes, and to quantify changes in energy fluxes resulting from some of the key processes. Observations from SHEBA (1998) and near the North Pole during ASCOS (2008) are used to illustrate freeze-up over existing sea ice ("old Arctic" processes) while observations from ACSE (2014), Mirai (2014), and Sea State (2015), supplemented with mesoscale model output, are used to illustrate "new Arctic" processes. In the "old Arctic", energy budgets show that freeze-up over remaining end-of-season sea ice occurred in late August, primarily because of the high albedo of the ice enhanced by snowfall events. In the "new Arctic" with extensive open water, summertime upper-ocean heating, formation of atmospheric ice-edge fronts, atmospheric thermal circulations, formation of thin new ice, ocean waves, and upper-ocean mixing all play a role in the autumn freeze-up process. These new processes also significantly impact the temporal extent and magnitude of the ocean heat loss to the atmosphere during this critical season from September to November, and possibly beyond. The magnitude of this heat loss plays an important role in various hypotheses regarding the impact of Arctic sea-ice loss on mid-latitude atmospheric circulations. While these hypotheses will not be discussed, the observations directly provide estimates of heat loss magnitudes in the "old Arctic" and the "new Arctic", thereby quantifying changes in heat loss, which can then be used to assess the accuracy of the various models and reanalyses.

  9. The deformation of ice-debris landforms in the Khumbu Region from InSAR

    Science.gov (United States)

    Schmidt, D. A.; Barker, A. D.; Hallet, B.

    2014-12-01

    We present new interferometric synthetic aperture radar (InSAR) results for the Khumbu region, Nepal, using PALSAR data from the ALOS1 satellite. Glaciers and ice-debris landforms represent a critical water resource to communities in the Himalayas and other relatively arid alpine environments. Changes in climate have impacted this resource as the volume of ice decreases. The monitoring of rock glaciers and debris covered glaciers is critical to the assessment of these natural resources and associated hazards (e.g. Glacial Lake Outburst Floods--GLOFs). Satellite data provide one means to monitor ice-containing landforms over broad regions. InSAR measures the subtle deformation of the surface, with mm precision, that is related to deformation or changes in ice volume within rock glaciers and debris-covered glaciers. While previous work in the region had used C-band (6 cm wavelength) SAR data from the ERS satellite, we utilize L-band data (24 cm) from the ALOS satellite, which provides better coherence, especially where the phase gradient is large. After processing 20 differential interferograms that span from 2008 to 2011, we focus on the 5 interferograms with the best overall coherence. Based on three 45-day interferograms and two 3-year interferograms, all of which have relatively small perpendicular baselines (glaciers. From the 3-year interferograms, we map the boundary of active movement along the perimeter of the debris-covered toe of Khumbu Glacier. Movement over this longer time period leads to a loss of coherence, clearly delimiting actively moving areas. Of particular note, active movement is detected in the glacier-moraine dam of Imja Lake, which has implications for GLOF hazard. The significant vertical relief in the Himalaya region poses a challenge for doing differential radar interferometry, as artifacts in the digital elevation model (DEM) can propagate into the differential interferograms. Additionally, large changes in topography or glacier surfaces

  10. Evaluation of the sea ice proxy IP against observational and diatom proxy data in the SW Labrador Sea

    DEFF Research Database (Denmark)

    Weckström, K.; Andersen, M.L.; Kuijpers, A.

    2013-01-01

    The recent rapid decline in Arctic sea ice cover has increased the need to improve the accuracy of the sea ice component in climate models and to provide detailed long-term sea ice concentration records, which are only available via proxy data. Recently, the highly branched isoprenoid IP25...... established sea ice proxy (sea ice diatom abundance in sediments) in the South-West (SW) Labrador Sea. Furthermore, our study location at the southern margin of Arctic sea ice drift provided a new environmental setting in which to further test the novel PIP25 index. Our two study sites are located North......-East (NE) and South-East (SE) of Newfoundland where box cores covering the last ca 100-150 years were collected. IP25 concentrations are nearly an order of magnitude higher and sea ice diatoms more abundant in sediments from NE of Newfoundland, where sea ice prevails 2-4 months per year compared...

  11. Spatial and temporal variability of sea ice in the southern Beaufort Sea and Amundsen Gulf: 1980-2004

    Science.gov (United States)

    Galley, R. J.; Key, E.; Barber, D. G.; Hwang, B. J.; Ehn, J. K.

    2008-05-01

    Changing extent, location, and motion of the Arctic perennial pack affect the annual evolution of seasonal ice zones. Canadian Ice Service digital ice charts covering the southern Beaufort Sea and Amundsen Gulf are used to illustrate summer and winter conditions and trends between 1980 and 2004 for several sea ice stages of development. Results illustrate average sea ice conditions within the region in summer and winter for predominant sea ice types and changes in the relative concentration of sea ice types in summer and winter. In summer, a trend toward increased old sea ice concentration occurred near the mouth of Amundsen Gulf, with a trend toward decreasing summer first-year sea ice farther west. In winter, increasing thick first-year sea ice extent appears to be replacing young sea ice within the flaw lead system in the region. The dynamically driven breakup of sea ice in spring in the Amundsen Gulf is a highly variable event taking anywhere between 2 and 22 weeks to completely remove ice from the gulf. The timing and duration of the open water season depends upon the extent and timing of old ice influx. Freezeup occurs very quickly, proceeding from west to east with little temporal variability. The results of this paper are used to set the context for the Canadian Arctic Shelf Exchange Study (CASES) in terms of sea ice dynamic and thermodynamic processes.

  12. Satellite information of sea ice for model validation

    Science.gov (United States)

    Saheed, P. P.; Mitra, Ashis K.; Momin, Imranali M.; Mahapatra, Debasis K.; Rajagopal, E. N.

    2016-05-01

    Emergence of extensively large computational facilities have enabled the scientific world to use earth system models for understating the prevailing dynamics of the earth's atmosphere, ocean and cryosphere and their inter relations. The sea ice in the arctic and the Antarctic has been identified as one of the main proxies to study the climate changes. The rapid sea-ice melting in the Arctic and disappearance of multi-year sea ice has become a matter of concern. The earth system models couple the ocean, atmosphere and sea-ice in order to bring out the possible inter connections between these three very important components and their role in the changing climate. The Indian monsoon is seen to be subjected to nonlinear changes in the recent years. The rapid ice melt in the Arctic sea ice is apparently linked to the changes in the weather and climate of the Indian subcontinent. The recent findings reveal the relation between the high events occurs in the Indian subcontinent and the Arctic sea ice melt episodes. The coupled models are being used in order to study the depth of these relations. However, the models have to be validated extensively by using measured parameters. The satellite measurements of sea-ice starts from way back in 1979. There have been many data sets available since then. Here in this study, an evaluation of the existing data sets is conducted. There are some uncertainties in these data sets. It could be associated with the absence of a single sensor for a long period of time and also the absence of accurate in-situ measurements in order to validate the satellite measurements.

  13. A microwave technique for mapping thin sea ice

    Science.gov (United States)

    Cavalieri, Donald J.

    1994-01-01

    A technique is presented for mapping the distribution of new, young and first-year sea ice in seasonal sea ice zones that utilizes microwave spectral and polarization information from the Defense Meteorological Satellite Program Special Sensor Microwave/Imager (DMSP SSM/I). The motivation for this work stems from the need for accurate estimates of open water and thin ice within the Arctic ice pack. The technique utilizes the microwave polarization and spectral characteristics of these three ice types through two microwave radiance ratios: the 19.4 GHz polarization and the spectral gradient ratio, which is a measure of the spectral difference between the 19.4-GHz and the 37.0-GHz vertically polarized radiance components. The combined use of the spectral gradient ratio and polarization reduces the low ice concentration bias generally associated with the presence of thin ice types. The microwave polarization, which is sensitive to changes in ice thickness and ice surface characteristics, is used to classify new, young, and first-year ice types.

  14. Microwave signature of sea-ice for GCOM-W1/AMSR2

    Science.gov (United States)

    Naoki, K.; Nishio, F.; Yoshikawa, M.

    2011-12-01

    The lowest Arctic sea-ice cover has been recorded in September 2007. After that, though it has increased in 2008 and 2009, it has decreased again in 2010. The factor of the sea-ice change is researched in various fields. Monitoring of a thin sea-ice thickness is important as these researches because the sea-ice thickness has influences for the heat budget. However the retrieval of thin sea-ice thickness is difficult because thin sea-ice brightness temperature (TB) depends on the salinity and temperature, and there exist the snow over the thin sea-ice. In order to know the relationship between sea-ice TB and sea-ice parameters, we observed thin sea-ice TB using Polarimetric Scanning Radiometer (PSR) and measured ice thickness by ship. The effect of sea-ice parameters on the TB was examined by model. The brightness temperature of the thin sea-ice was observed using PSR on board an aircraft in the Okhotsk on February 7, 2003. The sea-ice thickness was measured from the icebreaker synchronizing with the aircraft. The TB calculated the variation at the sea-ice with/without of the snow, thickness, and the density of the snow. The calculated result was consistent with the observed one in the 18GHz-Hpol. We show the snow density influenced the increased brightness temperature.

  15. 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

    2016-07-01

    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 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.

  16. 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.

  17. Assessment of Sea Surface Temperature and Sea Ice Initial Conditions on Coupled Model Forecasts

    Science.gov (United States)

    Intrieri, J. M.; Solomon, A.; Persson, O. P. G.; Capotondi, A.; LaFontaine, F.; Jedlovec, G.

    2016-12-01

    We present weather-scale (0-10 day) sea ice forecast validation and skill results from an experimental coupled ice-ocean-atmosphere model during the fall freeze-up periods for 2015 and 2016. The model is a mesoscale, coupled atmosphere-ice-ocean mixed-layer model, termed RASM-ESRL, that was developed from the larger-scale Regional Arctic System Model (RASM) architecture. The atmospheric component of RASM-ESRL consists of the Weather Research and Forecasting (WRF) model, the sea-ice component is the Los Alamos CICE model, and the ocean model is POP. Experimental 5-day forecasts were run daily with RASM-ESRL from July through mid-November in 2015 and 2016. Our project focuses on how the modeled sea ice evolution compares to observed physical processes including atmospheric forcing of sea ice movement, melt, and freeze-up through energy fluxes. Model hindcast output is validated against buoy observations, satellite measurements, and concurrent in situ flux observations made from the R/V Sikuliaq in the fall of 2015. Model skill in predicting atmospheric state variables, wind and boundary layer structures, synoptic features, cloud microphysical and ocean properties will be discussed. We will show results of using different initializations of ocean sea surface temperature and sea ice extent and the impacts on sea ice edge prediction.

  18. Remote sensing of sea ice: advances during the DAMOCLES project

    Directory of Open Access Journals (Sweden)

    G. Heygster

    2012-01-01

    Full Text Available In the Arctic, global warming is particularly pronounced so that we need to monitor its development continuously. On the other hand, the vast and hostile conditions make in situ observation difficult, so that available satellite observations should be exploited in the best possible way to extract geophysical information. Here, we give a résumé of the sea ice remote sensing efforts of the EU project DAMOCLES (Developing Arctic Modeling and Observing Capabilities for Long-term Environmental Studies. The monthly variation of the microwave emissivity of first-year and multiyear sea ice has been derived for the frequencies of the microwave imagers like AMSR-E and sounding frequencies of AMSU, and has been used to develop an optimal estimation method to retrieve sea ice and atmospheric parameters simultaneously. A sea ice microwave emissivity model has been used together with a thermodynamic model to establish relations between the emisivities at 6 GHz and 50 GHz. At the latter frequency, the emissivity is needed for assimilation into atmospheric circulation models, but more difficult to observe directly. A method to determine the effective size of the snow grains from observations in the visible range (MODIS is developed and applied. The bidirectional reflectivity distribution function (BRDF of snow, which is an essential input parameter to the retrieval, has been measured in situ on Svalbard during the DAMOCLES campaign, and a BRDF model assuming aspherical particles is developed. Sea ice drift and deformation is derived from satellite observations with the scatterometer 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

  19. Sea ice contribution to the air-sea CO{sub 2} exchange in the Arctic and Southern Oceans

    Energy Technology Data Exchange (ETDEWEB)

    Rysgaard, Soeren (Greenland Climate Research Centre, Greenland Inst. of Natural Resources, Nuuk, Greenland (Denmark); Centre for Earth Observation Science, CHR Faculty of Environment Earth and Resources, Univ. of Manitoba, Winnipeg (Canada)), e-mail: rysgaard@natur.gl; Bendtsen, Joergen (Greenland Climate Research Centre, Greenland Inst. of Natural Resources, Nuuk, Greenland (Denmark); Centre for Ice and Climate, Niels Bohr Inst., Univ. of Copenhagen, Copenhagen O (Denmark)); Delille, Bruno (Unit' e d' Oceanographie Chimique, Interfacultary Centre for Marine Research, Universite de Liege, Liege (Belgium)); Dieckmann, Gerhard S. (Alfred Wegener Inst. for Polar and Marine Research, Bremerhaven (Germany)); Glud, Ronnie N. (Greenland Climate Research Centre, Greenland Inst. of Natural Resources, Nuuk, Greenland (Denmark); Scottish Association of Marine Sciences, Scotland UK, Southern Danish Univ. and NordCee, Odense M (Denmark)); Kennedy, Hilary; Papadimitriou, Stathys (School of Ocean Sciences, Bangor Univ., Menai Bridge, Anglesey, Wales (United Kingdom)); Mortensen, John (Greenland Climate Research Centre, Greenland Inst. of Natural Resources, Nuuk, Greenland (Denmark)); Thomas, David N. (School of Ocean Sciences, Bangor Univ., Menai Bridge, Anglesey, Wales (United Kingdom); Finnish Environment Inst. (SYKE), Marine Research Centre, Helsinki (Finland)); Tison, Jean-Louis (Glaciology Unit, Dept. of Earth and Environmental Sciences, Universite Libre de Bruxelles, Bruxelles, (Belgium))

    2011-11-15

    Although salt rejection from sea ice is a key process in deep-water formation in ice-covered seas, the concurrent rejection of CO{sub 2} and the subsequent effect on air-sea CO{sub 2} exchange have received little attention. We review the mechanisms by which sea ice directly and indirectly controls the air-sea CO{sub 2} exchange and use recent measurements of inorganic carbon compounds in bulk sea ice to estimate that oceanic CO{sub 2} uptake during the seasonal cycle of sea-ice growth and decay in ice-covered oceanic regions equals almost half of the net atmospheric CO{sub 2} uptake in ice-free polar seas. This sea-ice driven CO{sub 2} uptake has not been considered so far in estimates of global oceanic CO{sub 2} uptake. Net CO{sub 2} uptake in sea-ice-covered oceans can be driven by; (1) rejection during sea-ice formation and sinking of CO{sub 2}-rich brine into intermediate and abyssal oceanic water masses, (2) blocking of air-sea CO{sub 2} exchange during winter, and (3) release of CO{sub 2}-depleted melt water with excess total alkalinity during sea-ice decay and (4) biological CO{sub 2} drawdown during primary production in sea ice and surface oceanic waters

  20. Summer and Fall Sea Ice Processes in the Amundsen Sea: Bottom melting, surface flooding and snow ice formation

    Science.gov (United States)

    Ackley, S. F.; Perovich, D. K.; Weissling, B.; Elder, B. C.

    2011-12-01

    Two ice mass balance buoys were deployed on the Amundsen Sea, Antarctica, ice pack near January 1, 2011. Below freezing air and snow temperatures and sea ice and seawater temperatures at the freezing point at this time indicated that summer melt had not yet commenced. Over the next two months, however, while snow depths changed by less than 0.1m, ice thickness decreased, from bottom melting, by 0.9-1.0m. As snow temperature records did not show temperatures ever reaching the melting point, no surface melt was recorded during the summer period and the small snow depth changes were presumed to occur by consolidation or wind scouring. Water temperatures above the freezing point caused the observed bottom melting from mid January to late February. During the ice loss periods, progressive flooding by sea water at the base of the snow pack was recorded by temperature sensors, showing an increase in the depth of flooded snow pack of 0.4m by the end of the summer period in late February. We hypothesize that progressive flooding of the surface snow pack gives a mechanism for nutrient replenishment in these upper layers, and continuous high algal growth can therefore occur in the flooded snow layer during summer. An underice radiometer recorded light transmission through the ice and snow at selective wavelengths sensitive to chlorophyll. These radiometric results will be presented to examine this algal growth hypothesis. This flooded layer then refroze from the top down into snow ice as air temperatures dropped during March and April, showing that the layer had refrozen as snow ice on the top surface of the ice. Refreezing of the flooded layer gives an ice growth mechanism at the end of summer of 0.2 m to 0.4m of new ice growth over the majority of the ice pack. The snow ice growth in areas covered with pack ice gives salt fluxes commensurate with new ice growth in the autumn expansion of the ice edge over open water. These high salt fluxes therefore represent a marked

  1. [Comparative analysis of sea-ice diatom species composition in the seas of Russian Arctic].

    Science.gov (United States)

    Il'iash, L V; Zhitina, L S

    2009-01-01

    Comparative analysis of species composition of ice diatom algae (IDA) of the White, Barents, Kara, Laptev, East Siberian, Chukchi Seas and the Basin of the Arctic Ocean was conducted on the basis of both original and published data. Species composition of IDA counts 567 taxa including 122 centric and 446 pennate diatoms. The freshwater algae composed about 18% of the total species number. In the White Sea, IDA were the most numerous (272 taxa), in the Kara Sea they are the least numerous (57 taxa). The species compositions in different seas differ significantly from each other. Similarity of IDA was consistent with the Arctic Ocean circulation and ice drift. IDA of Chukchi, East Siberian and Laptev Seas are the most similar, as are IDA of White and Kara Seas. Similarity of IDA of Chukchi Sea to those of other seas decrease in the west direction. IDA species differences between regions within one sea could be greater than those between different seas.

  2. Windows in Arctic sea ice: Light transmission and ice algae in a refrozen lead

    Science.gov (United States)

    Kauko, Hanna M.; Taskjelle, Torbjørn; Assmy, Philipp; Pavlov, Alexey K.; Mundy, C. J.; Duarte, Pedro; Fernández-Méndez, Mar; Olsen, Lasse M.; Hudson, Stephen R.; Johnsen, Geir; Elliott, Ashley; Wang, Feiyue; Granskog, Mats A.

    2017-06-01

    The Arctic Ocean is rapidly changing from thicker multiyear to thinner first-year ice cover, with significant consequences for radiative transfer through the ice pack and light availability for algal growth. A thinner, more dynamic ice cover will possibly result in more frequent leads, covered by newly formed ice with little snow cover. We studied a refrozen lead (≤0.27 m ice) in drifting pack ice north of Svalbard (80.5-81.8°N) in May-June 2015 during the Norwegian young sea ICE expedition (N-ICE2015). We measured downwelling incident and ice-transmitted spectral irradiance, and colored dissolved organic matter (CDOM), particle absorption, ultraviolet (UV)-protecting mycosporine-like amino acids (MAAs), and chlorophyll a (Chl a) in melted sea ice samples. We found occasionally very high MAA concentrations (up to 39 mg m-3, mean 4.5 ± 7.8 mg m-3) and MAA to Chl a ratios (up to 6.3, mean 1.2 ± 1.3). Disagreement in modeled and observed transmittance in the UV range let us conclude that MAA signatures in CDOM absorption spectra may be artifacts due to osmotic shock during ice melting. Although observed PAR (photosynthetically active radiation) transmittance through the thin ice was significantly higher than that of the adjacent thicker ice with deep snow cover, ice algal standing stocks were low (≤2.31 mg Chl a m-2) and similar to the adjacent ice. Ice algal accumulation in the lead was possibly delayed by the low inoculum and the time needed for photoacclimation to the high-light environment. However, leads are important for phytoplankton growth by acting like windows into the water column.

  3. Sea ice thickness analyses for the Bohai Sea using MODIS thermal infrared imagery

    Institute of Scientific and Technical Information of China (English)

    ZENG Tao; SHI Lijian; MARKO Makynen; CHENG Bin; ZOU Juhong; ZHANG Zhiping

    2016-01-01

    Level ice thickness distribution pattern in the Bohai Sea in the winter of 2009–2010 was investigated in this paper using MODIS night-time thermal infrared imagery. The cloud cover in the imagery was masked out manually. Level ice thickness was calculated using MODIS ice surface temperature and an ice surface heat balance equation. Weather forcing data was from the European Centre for Medium-Range Weather Forecasts (ECMWF) analyses. The retrieved ice thickness agreed reasonable well within situ observations from two off-shore oil platforms. The overall bias and the root mean square error of the MODIS ice thickness are –1.4 cm and 3.9 cm, respectively. The MODIS results under cold conditions (air temperature < –10°C) also agree with the estimated ice growth from Lebedev and Zubov models. The MODIS ice thickness is sensitive to the changes of the sea ice and air temperature, in particular when the sea ice is relatively thin. It is less sensitive to the wind speed. Our method is feasible for the Bohai Sea operational ice thickness analyses during cold freezing seasons.

  4. Surface and basal sea ice melt from autonomous buoy arrays during the 2014 sea ice retreat in the Beaufort/Chukchi Seas

    Science.gov (United States)

    Maksym, T. L.; Wilkinson, J.; Hwang, P. B.

    2014-12-01

    As the Arctic continues its transition to a seasonal ice cover, the nature and role of the processes driving sea ice retreat are expected to change. Key questions revolve around how the coupling between dynamics and thermodynamic processes and potential changes in the role of melt ponds contribute to an accelerated seasonal ice retreat. To address these issues, 44 autonomous platforms were deployed in four arrays in the Beaufort Sea in March, 2014, with an additional array deployed in August in the Chukchi Sea to monitor the evolution of ice conditions during the seasonal sea ice retreat. Each "5-dice" array included four or five co-sited ice mass balance buoys (IMB) and wave buoys with digital cameras, and one automatic weather station (AWS) at the array center. The sensors on these buoys, combined with satellite imagery monitoring the large-scale evolution of the ice cover, provide a near-complete history of the processes involved in the seasonal melt of sea ice. We present a preliminary analysis of the contributions of several key processes to the seasonal ice decay. The evolution of surface ponding was observed at several sites with differing ice types and surface morphologies. The records of surface melt and ice thickness demonstrate a key role of ice type in driving the evolution of the ice cover. Analysis of the surface forcing and estimates of solar energy partitioning between the surface and upper ocean is compared to the surface and basal mass balance from the IMBs. The role of ice divergence and deformation in driving sea ice decay - in particular its role in accelerating thermodynamic melt processes - is discussed.

  5. A recent bifurcation in Arctic sea-ice cover

    CERN Document Server

    Livina, Valerie N

    2012-01-01

    There is ongoing debate over whether Arctic sea-ice has already passed a 'tipping point', or whether it will do so in future, with several recent studies arguing that the loss of summer sea ice does not involve a bifurcation because it is highly reversible in models. Recently developed methods can detect and sometimes forewarn of bifurcations in time-series data, hence we applied them to satellite data for Arctic sea-ice cover. Here we show that a new low ice cover state has appeared from 2007 onwards, which is distinct from the normal state of seasonal sea ice variation, suggesting a bifurcation has occurred from one attractor to two. There was no robust early warning signal of critical slowing down prior to this bifurcation, consistent with it representing the appearance of a new ice cover state rather than the loss of stability of the existing state. The new low ice cover state has been sampled predominantly in summer-autumn and seasonal forcing combined with internal climate variability are likely respons...

  6. New IceTracker Tool Depicts Forward and Backward Arctic Sea Ice Trajectories

    Science.gov (United States)

    Pfirman, S. L.; Campbell, G.; Tremblay, B.; Newton, R.; Meier, W.

    2013-12-01

    The IceTracker allows researchers, educators and the public to depict the forward drift trajectories of sea ice, as well as back trajectories showing the path the ice took to the specified location. Users enter in the location and date of an ice parcel - or parcels -- of interest, then select a later or earlier date, depending on whether they want to see the forward or the backward trajectory. The database for the IceTracker contains ice motion vectors based upon a pattern recognition algorithm applied to images of sea ice derived from microwave satellite data. Ice motion vector plots are single day motion estimates. The available database starts November 1978 and runs to the present with ca. 1 month delay. IceTracker output includes both an image of the ice motion path as well as a data file that has quasi-daily date, latitude, longitude, estimated sea ice age, ice drift speed, mean air temperature, and water depth. One can overlay different days on the same plot in different colors for comparing different seasons. This presentation highlights research, education, and outreach applications of the tool. Research applications include estimating the origin and melt location of sediment and contaminants sampled on or in sea ice, assessing potential trajectories oil spilled in ice-infested waters, documenting seasonal and interannual variability in ice drift trajectories from specific locations, defining the typical origins of ice that tend to melt in an area of interest, such as a polynya, and assessing the deviation from drift of polar bear foraging. The IceTracker can also be used in the social sciences, for example recreating Nansen's historic 1893-1896 trans-Arctic drift with the Fram under modern conditions and considering the implications of alternative fates. Educational purposes include teaching students about ice dynamics and interannual variability by setting up team competitions to be the first to reach the North Pole or some other location. Applications

  7. Increased Land Use by Chukchi Sea Polar Bears in Relation to Changing Sea Ice Conditions.

    Directory of Open Access Journals (Sweden)

    Karyn D Rode

    Full Text Available Recent observations suggest that polar bears (Ursus maritimus are increasingly using land habitats in some parts of their range, where they have minimal access to their preferred prey, likely in response to loss of their sea ice habitat associated with climatic warming. We used location data from female polar bears fit with satellite radio collars to compare land use patterns in the Chukchi Sea between two periods (1986-1995 and 2008-2013 when substantial summer sea-ice loss occurred. In both time periods, polar bears predominantly occupied sea-ice, although land was used during the summer sea-ice retreat and during the winter for maternal denning. However, the proportion of bears on land for > 7 days between August and October increased between the two periods from 20.0% to 38.9%, and the average duration on land increased by 30 days. The majority of bears that used land in the summer and for denning came to Wrangel and Herald Islands (Russia, highlighting the importance of these northernmost land habitats to Chukchi Sea polar bears. Where bears summered and denned, and how long they spent there, was related to the timing and duration of sea ice retreat. Our results are consistent with other studies supporting increased land use as a common response of polar bears to sea-ice loss. Implications of increased land use for Chukchi Sea polar bears are unclear, because a recent study observed no change in body condition or reproductive indices between the two periods considered here. This result suggests that the ecology of this region may provide a degree of resilience to sea ice loss. However, projections of continued sea ice loss suggest that polar bears in the Chukchi Sea and other parts of the Arctic may increasingly use land habitats in the future, which has the potential to increase nutritional stress and human-polar bear interactions.

  8. Measurements of sea ice by satellite and airborne altimetry

    DEFF Research Database (Denmark)

    Kildegaard Rose, Stine

    A changing sea ice cover in the Arctic Ocean is an early indicator of a climate in transition, the sea ice has in addition a large impact on the climate. The annual and interannual variations of the sea ice cover have been observed by satellites since the start of the satellite era in 1979......, and it has been in retreat every since. The mass balance of the sea ice is an important input to climate models, where the ice thickness is the most uncertain parameter. In this study, data from the CryoSat-2 radar altimeter satellite are used. CryoSat-2 has been measuring the sea ice in the Arctic Ocean...... freeboard is found to be 35 cm for both the airborne and satellite data implying, that the radar signal is here reflected from the snow surface, probably due to weather conditions. CryoSat-2 is very sensitive to returns from specular surfaces, even if they appear o_-nadir. This contaminates the “true...

  9. 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.

  10. Arctic Sea Ice Simulation in the PlioMIP Ensemble

    Science.gov (United States)

    Howell, Fergus W.; Haywood, Alan M.; Otto-Bliesner, Bette L.; Bragg, Fran; Chan, Wing-Le; Chandler, Mark A.; Contoux, Camille; Kamae, Youichi; Abe-Ouchi, Ayako; Rosenbloom, Nan A.; Stepanek, Christian; Zhang, Zhongshi

    2016-01-01

    Eight general circulation models have simulated the mid-Pliocene warm period (mid-Pliocene, 3.264 to 3.025 Ma) as part of the Pliocene Modelling Intercomparison Project (PlioMIP). Here, we analyse and compare their simulation of Arctic sea ice for both the pre-industrial period and the mid-Pliocene. Mid-Pliocene sea ice thickness and extent is reduced, and the model spread of extent is more than twice the pre-industrial spread in some summer months. Half of the PlioMIP models simulate ice-free conditions in the mid-Pliocene. This spread amongst the ensemble is in line with the uncertainties amongst proxy reconstructions for mid-Pliocene sea ice extent. Correlations between mid-Pliocene Arctic temperatures and sea ice extents are almost twice as strong as the equivalent correlations for the pre-industrial simulations. The need for more comprehensive sea ice proxy data is highlighted, in order to better compare model performances.

  11. Regional variability in sea ice melt in a changing Arctic.

    Science.gov (United States)

    Perovich, Donald K; Richter-Menge, Jacqueline A

    2015-07-13

    In recent years, the Arctic sea ice cover has undergone a precipitous decline in summer extent. The sea ice mass balance integrates heat and provides insight on atmospheric and oceanic forcing. The amount of surface melt and bottom melt that occurs during the summer melt season was measured at 41 sites over the time period 1957 to 2014. There are large regional and temporal variations in both surface and bottom melting. Combined surface and bottom melt ranged from 16 to 294 cm, with a mean of 101 cm. The mean ice equivalent surface melt was 48 cm and the mean bottom melt was 53 cm. On average, surface melting decreases moving northward from the Beaufort Sea towards the North Pole; however interannual differences in atmospheric forcing can overwhelm the influence of latitude. Substantial increases in bottom melting are a major contributor to ice losses in the Beaufort Sea, due to decreases in ice concentration. In the central Arctic, surface and bottom melting demonstrate interannual variability, but show no strong temporal trends from 2000 to 2014. This suggests that under current conditions, summer melting in the central Arctic is not large enough to completely remove the sea ice cover. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

  12. Passive microwave remote sensing for sea ice research

    Science.gov (United States)

    1984-01-01

    Techniques for gathering data by remote sensors on satellites utilized for sea ice research are summarized. Measurement of brightness temperatures by a passive microwave imager converted to maps of total sea ice concentration and to the areal fractions covered by first year and multiyear ice are described. Several ancillary observations, especially by means of automatic data buoys and submarines equipped with upward looking sonars, are needed to improve the validation and interpretation of satellite data. The design and performance characteristics of the Navy's Special Sensor Microwave Imager, expected to be in orbit in late 1985, are described. It is recommended that data from that instrument be processed to a form suitable for research applications and archived in a readily accessible form. The sea ice data products required for research purposes are described and recommendations for their archival and distribution to the scientific community are presented.

  13. Periodic fluctuations in deep water formation due to sea ice

    CERN Document Server

    Saha, Raj

    2015-01-01

    During the last ice age several quasi-periodic abrupt warming events took place. Known as Dansgaard-Oeschger (DO) events their effects were felt globally, although the North Atlantic experienced the largest temperature anomalies. Paleoclimate data shows that the fluctuations often occurred right after massive glacial meltwater releases in the North Atlantic and in bursts of three or four with progressively decreasing strengths. In this study a simple dynamical model of an overturning circulation and sea ice is developed with the goal of understanding the fundamental mechanisms that could have caused the DO events. Interaction between sea ice and the overturning circulation in the model produces self-sustained oscillations. Analysis and numerical experiments reveal that the insulating effect of sea ice causes the ocean to periodically vent out accumulated heat in the deep ocean into the atmosphere. Subjecting the model to idealized freshwater forcing mimicking Heinrich events causes modulation of the natural p...

  14. Sea ice dynamics and the role of wind forcing over the Beaufort Sea

    Science.gov (United States)

    Petty, A.; Hutchings, J. K.; Farrell, S. L.; Richter-Menge, J.; Tschudi, M. A.

    2014-12-01

    Both the ocean circulation and overlying sea ice cover of the Beaufort and Chukchi seas have experienced significant change in recent decades. We use sea ice drift estimates from satellite feature tracking (NSIDC/CERSAT), wind forcing from atmospheric reanalysis products (NCEP-R2/ERA-I/JRA-55), and ice type information from satellite and direct ship-based observations (obtained during the Beaufort Gyre Exploration Project), to investigate the role of wind forcing and ice mechanics in driving these changes. An assessment of ice drift shows reasonable agreement across the different products, revealing interannual variability in the ice flux around the Beaufort Sea. However, clear uncertainties remain in determining the magnitude of these fluxes, especially in regions of low ice concentration. We find an increase in ice export out of the southern Beaufort Sea (into the Chukchi Sea) across all seasons. We find slight differences in the strength of the decadal (1980-2013) trends in the mean seasonal wind curl over the Beaufort Sea, although all reanalysis products indicate a strong and significant increase in anti-cyclonic winds in summer. Analysis of ice drift curl suggests increasing anti-cyclonic drift across all seasons, despite the wind curl showing a similar trend in summer only. The strongest trend in ice drift curl appears to be in autumn, however recent years have seen a strong reduction in this anti-cyclonic drift, likely due to a combination of changes in the wind forcing and sea ice state. The implication of this finding is an enhanced response of the ocean circulation to shifts in atmospheric circulation compared to that experienced prior to 2000.

  15. COMPARISON OF C-BAND AND X-BAND POLARIMETRIC SAR DATA FOR RIVER ICE CLASSIFICATION ON THE PEACE RIVER

    OpenAIRE

    Łoś, H.; Osińska-Skotak, K.; J. Pluto-Kossakowska; Bernier, M; Y. Gauthier; M. Jasek; A. Roth

    2016-01-01

    In this study, synthetic aperture radar (SAR) data from TerraSAR-X were compared with RADARSAT-2 data to evaluate their effectiveness for river ice monitoring on the Peace River. For several years RADARSAT-2 data have been successfully used for river ice observation. However, it is important to take into account data from other satellites as they may provide solutions when it is not possible to obtain images from the preferred system (e.g., in the case of acquisition priority conflicts). In t...

  16. Primary production calculations for sea ice from bio-optical observations in the Baltic Sea

    Directory of Open Access Journals (Sweden)

    Susann Müller

    2016-09-01

    Full Text Available Abstract Bio-optics is a powerful approach for estimating photosynthesis rates, but has seldom been applied to sea ice, where measuring photosynthesis is a challenge. We measured absorption coefficients of chromophoric dissolved organic matter (CDOM, algae, and non-algal particles along with solar radiation, albedo and transmittance at four sea-ice stations in the Gulf of Finland, Baltic Sea. This unique compilation of optical and biological data for Baltic Sea ice was used to build a radiative transfer model describing the light field and the light absorption by algae in 1-cm increments. The maximum quantum yields and photoadaptation of photosynthesis were determined from 14C-incorporation in photosynthetic-irradiance experiments using melted ice. The quantum yields were applied to the radiative transfer model estimating the rate of photosynthesis based on incident solar irradiance measured at 1-min intervals. The calculated depth-integrated mean primary production was 5 mg C m–2 d–1 for the surface layer (0–20 cm ice depth at Station 3 (fast ice and 0.5 mg C m–2 d–1 for the bottom layer (20–57 cm ice depth. Additional calculations were performed for typical sea ice in the area in March using all ice types and a typical light spectrum, resulting in depth-integrated mean primary production rates of 34 and 5.6 mg C m–2 d–1 in surface ice and bottom ice, respectively. These calculated rates were compared to rates determined from 14C incorporation experiments with melted ice incubated in situ. The rate of the calculated photosynthesis and the rates measured in situ at Station 3 were lower than those calculated by the bio-optical algorithm for typical conditions in March in the Gulf of Finland by the bio-optical algorithm. Nevertheless, our study shows the applicability of bio-optics for estimating the photosynthesis of sea-ice algae.

  17. Albedo changes of the Arctic sea ice cover

    Science.gov (United States)

    Perovich, D. K.; Light, B.; Jones, K. F.; Eicken, H.; Runciman, K.; Nghiem, S. V.; Stroeve, J.; Markus, T.

    2008-12-01

    The summer extent of the Arctic sea ice cover has decreased in recent decades and there have been alterations in the timing and duration of the summer melt season. This has resulted in changes in the evolution of albedo of the Arctic sea ice cover, and consequently in the partitioning of solar energy. These changes are examined on a pan-Arctic scale on a 25 x 25 km Equal Area Scalable Earth Grid for the years 1979 - 2007. Daily values of incident solar irradiance are obtained from ERA-40 reanalysis products and ice concentrations are determined from passive microwave satellite data. The albedo of the ice is modeled by a five-phase process that includes dry snow, melting snow, melt pond formation, melt pond evolution, and freezeup. The timing of these phases is governed by the onset dates of summer melt and fall freezeup, which are determined from satellite observations. Results indicate a general trend of increasing solar heat input to the Arctic ice-ocean system due to reductions in ice concentration and longer melt seasons. This trend may accelerate the loss of sea ice through the ice-albedo feedback. The evolution of albedo, and hence the total solar heating of the ocean, is more sensitive to the date of melt onset than the date of fall freezeup.

  18. Air-sea interactions in the marginal ice zone

    Directory of Open Access Journals (Sweden)

    Seth Zippel

    2016-03-01

    Full Text Available Abstract The importance of waves in the Arctic Ocean has increased with the significant retreat of the seasonal sea-ice extent. Here, we use wind, wave, turbulence, and ice measurements to evaluate the response of the ocean surface to a given wind stress within the marginal ice zone, with a focus on the local wind input to waves and subsequent ocean surface turbulence. Observations are from the Beaufort Sea in the summer and early fall of 2014, with fractional ice cover of up to 50%. Observations showed strong damping and scattering of short waves, which, in turn, decreased the wind energy input to waves. Near-surface turbulent dissipation rates were also greatly reduced in partial ice cover. The reductions in waves and turbulence were balanced, suggesting that a wind-wave equilibrium is maintained in the marginal ice zone, though at levels much less than in open water. These results suggest that air-sea interactions are suppressed in the marginal ice zone relative to open ocean conditions at a given wind forcing, and this suppression may act as a feedback mechanism in expanding a persistent marginal ice zone throughout the Arctic.

  19. Sea ice characteristics between the middle Weddell Sea and the Prydz Bay, Antarctica during the austral summer of 2003

    Institute of Scientific and Technical Information of China (English)

    TANG Shulin; KANG Jiancheng; ZHOU Shangzhe; LI Zhijun

    2005-01-01

    The antarctic sea ice was investigated upon five occasions between January 4 and February 15, 2003. The investigations included: (1)estimation of sea ice distribution by ship-based observations between the middle Weddell Sea and the Prydz Bay; (2) estimation of sea ice distribution by aerial photography in the Prydz Bay; (3) direct measurements of fast ice thickness and snow cover, as well as ice core sampling in Nella Fjord; (4) estimation of melting sea ice distribution near the Zhongshan Station; and (5) observation of sea ice early freeze near the Zhongshan Station. On average, sea ice covered 14.4% of the study area. The highest sea ice concentration (80%)was observed in the Weddell Sea. First-year ice was dominant (99.7%~99.8%). Sea ice distributions in the Prydz Bay were more variable due to complex inshore topography, proximity of the Larsemann Hills, and/or grounded icebergs. The average thickness of landfast ice in Nella Fjord was 169.5 cm. Wind-blown snow redistribution plays an important role in affecting the ice thickness in Nella Fjord. Preliminary freezing of sea ice near the Zhongshan Station follows the first two phases of the pancake cycle.

  20. High resolution Holocene sea ice records from Herald Canyon, Chukchi Sea

    Science.gov (United States)

    Pearce, Christof; Jakobsson, Martin; O'Regan, Matt; Rattray, Jayne; Barrientos, Natalia; Muchitiello, Francesco; Smittenburg, Rienk; Cronin, Tom; Coxall, Helen; Semiletov, Igor

    2016-04-01

    Arctic Ocean sea ice plays a critical role in the Earth's climate system because of the positive ice-albedo feedback mechanisms as well as its control on ocean-atmospheric heat exchange and potential influence on the thermohaline circulation. Key to improving our understanding of Arctic sea ice cover and its reaction to external forcing is the reconstruction of past variability through paleo-records such as marine sediment cores. Although the observed recent sea ice loss seems to be the strongest of the last millennia, it is still uncertain whether the shift from perennial to seasonal ice cover expected for the near future was unprecedented during the current interglacial. High resolution sea ice reconstructions from the Arctic Ocean are rare, and specifically records from the Russian Arctic are underrepresented. In this study, we present results from marine sediment cores from the Herald Canyon in the East Siberian Sea. The area is one of the major conduits of Pacific water entering the Arctic Ocean basin from the Bering Strait and is thus an ideal place to study past variability of the inflow of these nutrient rich waters. Radiocarbon dating of mollusks indicates very high sedimentation rates at the coring sites which allowed for analyses at centennial resolution up to decadal resolution in the late Holocene. Core samples were analyzed for the biomarker IP25, which is produced by diatoms living in sea ice and is used as a proxy of past seasonal sea ice concentrations. Preliminary results indicate the presence of seasonal sea ice during the entire Late Holocene and show a significant increase of sea ice concentrations during the last millennia.

  1. Export of algal biomass from the melting Arctic sea ice.

    Science.gov (United States)

    Boetius, Antje; Albrecht, Sebastian; Bakker, Karel; Bienhold, Christina; Felden, Janine; Fernández-Méndez, Mar; Hendricks, Stefan; Katlein, Christian; Lalande, Catherine; Krumpen, Thomas; Nicolaus, Marcel; Peeken, Ilka; Rabe, Benjamin; Rogacheva, Antonina; Rybakova, Elena; Somavilla, Raquel; Wenzhöfer, Frank

    2013-03-22

    In the Arctic, under-ice primary production is limited to summer months and is restricted not only by ice thickness and snow cover but also by the stratification of the water column, which constrains nutrient supply for algal growth. Research Vessel Polarstern visited the ice-covered eastern-central basins between 82° to 89°N and 30° to 130°E in summer 2012, when Arctic sea ice declined to a record minimum. During this cruise, we observed a widespread deposition of ice algal biomass of on average 9 grams of carbon per square meter to the deep-sea floor of the central Arctic basins. Data from this cruise will contribute to assessing the effect of current climate change on Arctic productivity, biodiversity, and ecological function.

  2. Peopling of the high Arctic - induced by sea ice?

    Science.gov (United States)

    Funder, Svend

    2010-05-01

    'We travelled in the winter after the return of daylight and did not go into fixed camp until spring, when the ice broke up. There was good hunting on the way, seals, beluga, walrus, bear.' (From Old Merkrusârk's account of his childhood's trek from Baffin Island to Northwest Greenland, told to Knud Rasmussen on Saunders Island in 1904) Five thousand years ago people moving eastwards from Beringia spread over the barrens of the Canadian high Arctic. This was the first of three waves of prehistoric Arctic 'cultures', which eventually reached Greenland. The passage into Greenland has to go through the northernmost and most hostile part of the country with a 5 month Polar night, and to understand this extraordinary example of human behaviour and endurance, it has been customary to invoke a more favourable (warmer) climate. This presentation suggests that land-fast sea ice, i.e. stationary sea ice anchored to the coast, is among the most important environmental factors behind the spread of prehistoric polar cultures. The ice provides the road for travelling and social communion - and access to the most important