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  • 1
    Online Resource
    Online Resource
    Preconditioning of Summer Melt Ponds From Winter Sea Ice Surface Temperature
    American Geophysical Union (AGU) ; 2023
    In:  Geophysical Research Letters Vol. 50, No. 4 ( 2023-02-28)
    Details
    In: Geophysical Research Letters, American Geophysical Union (AGU), Vol. 50, No. 4 ( 2023-02-28)
    Abstract: Winter warm surface temperature anomalies are co‐located with melt pond locations in the following summer Warm anomalies appear in refrozen leads, in refrozen melt ponds, and in troughs between ridges, due to thinner snow and ice We show the potential for prediction of summer melt pond fraction from winter surface temperatures
    Type of Medium: Online Resource
    ISSN: 0094-8276 , 1944-8007
    URL: Article
    DOI: 10.1029/2022GL101493
    Language: English
    Publisher: American Geophysical Union (AGU)
    Publication Date: 2023
    detail.hit.zdb_id: 2021599-X
    detail.hit.zdb_id: 7403-2
    SSG: 16,13
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  • 2
    Online Resource
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    Sea Ice Remote Sensing—Recent Developments in Methods and Climate Data Sets
    Springer Science and Business Media LLC ; 2023
    In:  Surveys in Geophysics Vol. 44, No. 5 ( 2023-10), p. 1653-1689
    Details
    In: Surveys in Geophysics, Springer Science and Business Media LLC, Vol. 44, No. 5 ( 2023-10), p. 1653-1689
    Abstract: Sea ice monitoring by polar orbiting satellites has been developed over more than four decades and is today one of the most well-established applications of space observations. This article gives an overview of data product development from the first sensors to the state-of-the-art regarding retrieval methods, new products and operational data sets serving climate monitoring as well as daily operational services including ice charting and forecasting. Passive microwave data has the longest history and represents the backbone of global ice monitoring with already more than four decades of consistent observations of ice concentration and extent. Time series of passive microwave data is the primary climate data set to document the sea ice decline in the Arctic. Scatterometer data is a valuable supplement to the passive microwave data, in particular to retrieve ice displacement and distinguish between firstyear and multiyear ice. Radar and laser altimeter data has become the main method to estimate sea ice thickness and thereby fill a gap in the observation of sea ice as an essential climate variable. Data on ice thickness allows estimation of ice volume and masses as well as improvement of the ice forecasts. The use of different altimetric frequencies also makes it possible to measure the depth of the snow covering the ice. Synthetic Aperture Radar (SAR) has become the work horse in operational ice observation on regional scale because high-resolution radar images are delivered year-round in nearly all regions where national ice services produce ice charts. Synthetic Aperture Radar data are also important for sea ice research because the data can be used to observe a number of sea ice processes and phenomena, like ice type development and sea ice dynamics, and thereby contribute to new knowledge about sea ice. The use of sea ice data products in modelling and forecasting services as well as in ice navigation is discussed. Finally, the article describes future plans for new satellites and sensors to be used in sea ice observation.
    Type of Medium: Online Resource
    ISSN: 0169-3298 , 1573-0956
    URL: Article
    DOI: 10.1007/s10712-023-09781-0
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
    detail.hit.zdb_id: 2017797-5
    SSG: 16,13
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  • 3
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    Evidence of Arctic sea ice thinning from direct observations
    American Geophysical Union (AGU) ; 2014
    In:  Geophysical Research Letters Vol. 41, No. 14 ( 2014-07-28), p. 5029-5036
    Details
    In: Geophysical Research Letters, American Geophysical Union (AGU), Vol. 41, No. 14 ( 2014-07-28), p. 5029-5036
    Abstract: We present a time series of sea ice thickness in Fram Strait from in situ data Fram Strait sea ice thickness has decreased by over 50% in 2003–2012 The thinning independent from the source region indicates Arctic‐wide decline
    Type of Medium: Online Resource
    ISSN: 0094-8276 , 1944-8007
    URL: Issue
    URL: Article
    DOI: 10.1002/grl.v41.14
    DOI: 10.1002/2014GL060369
    Language: English
    Publisher: American Geophysical Union (AGU)
    Publication Date: 2014
    detail.hit.zdb_id: 2021599-X
    detail.hit.zdb_id: 7403-2
    SSG: 16,13
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  • 4
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    Robust Multiseasonal Ice Classification From High-Resolution X-Band SAR
    Institute of Electrical and Electronics Engineers (IEEE) ; 2022
    In:  IEEE Transactions on Geoscience and Remote Sensing Vol. 60 ( 2022), p. 1-12
    Details
    In: IEEE Transactions on Geoscience and Remote Sensing, Institute of Electrical and Electronics Engineers (IEEE), Vol. 60 ( 2022), p. 1-12
    Type of Medium: Online Resource
    ISSN: 0196-2892 , 1558-0644
    URL: Article
    DOI: 10.1109/TGRS.2022.3144731
    Language: Unknown
    Publisher: Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2022
    detail.hit.zdb_id: 2027520-1
    SSG: 16,13
    SSG: 13
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  • 5
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    Relevance of warm air intrusions for Arctic satellite sea ice concentration time series
    Copernicus GmbH ; 2023
    In:  The Cryosphere Vol. 17, No. 9 ( 2023-09-06), p. 3867-3881
    Details
    In: The Cryosphere, Copernicus GmbH, Vol. 17, No. 9 ( 2023-09-06), p. 3867-3881
    Abstract: Abstract. Winter warm air intrusions entering the Arctic region can strongly modify the microwave emission of the snow-covered sea ice system due to temperature-induced snow metamorphism and ice crust formations, e.g., after melt–refreeze events. Common microwave radiometer satellite sea ice concentration retrievals are based on empirical models using the snow-covered sea ice emissivity and thus can be influenced by strong warm air intrusions. Here, we carry out a long-term study analyzing 41 years of winter sea ice concentration observations from different algorithms to investigate the impact of warm air intrusions on the retrieved ice concentration. Our results show that three out of four algorithms underestimate the sea ice concentration during (and up to 10 d after) warm air intrusions which increase the 2 m air temperature (daily maximum) above − 5 ∘C. This can lead to sea ice area underestimations in the order of 104 to 105 km2. If the 2 m temperature during the warm air intrusions crosses − 2 ∘C, all algorithms are impacted. Our analysis shows that the strength of these strong warm air intrusions increased in recent years, especially in April. With a further climate change, such warm air intrusions are expected to occur more frequently and earlier in the season, and their influence on sea ice climate data records will become more important.
    Type of Medium: Online Resource
    ISSN: 1994-0424
    URL: Article
    DOI: 10.5194/tc-17-3867-2023
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2023
    detail.hit.zdb_id: 2393169-3
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  • 6
    Online Resource
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    MOSAiC drift expedition from October 2019 to July 2020: sea ice conditions from space and comparison with previous years
    Copernicus GmbH ; 2021
    In:  The Cryosphere Vol. 15, No. 8 ( 2021-08-20), p. 3897-3920
    Details
    In: The Cryosphere, Copernicus GmbH, Vol. 15, No. 8 ( 2021-08-20), p. 3897-3920
    Abstract: Abstract. We combine satellite data products to provide a first and general overview of the physical sea ice conditions along the drift of the international Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition and a comparison with previous years (2005–2006 to 2018–2019). We find that the MOSAiC drift was around 20 % faster than the climatological mean drift, as a consequence of large-scale low-pressure anomalies prevailing around the Barents–Kara–Laptev sea region between January and March. In winter (October–April), satellite observations show that the sea ice in the vicinity of the Central Observatory (CO; 50 km radius) was rather thin compared to the previous years along the same trajectory. Unlike ice thickness, satellite-derived sea ice concentration, lead frequency and snow thickness during winter months were close to the long-term mean with little variability. With the onset of spring and decreasing distance to the Fram Strait, variability in ice concentration and lead activity increased. In addition, the frequency and strength of deformation events (divergence, convergence and shear) were higher during summer than during winter. Overall, we find that sea ice conditions observed within 5 km distance of the CO are representative for the wider (50 and 100 km) surroundings. An exception is the ice thickness; here we find that sea ice within 50 km radius of the CO was thinner than sea ice within a 100 km radius by a small but consistent factor (4 %) for successive monthly averages. Moreover, satellite acquisitions indicate that the formation of large melt ponds began earlier on the MOSAiC floe than on neighbouring floes.
    Type of Medium: Online Resource
    ISSN: 1994-0424
    URL: Article
    DOI: 10.5194/tc-15-3897-2021
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2021
    detail.hit.zdb_id: 2393169-3
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  • 7
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    Online Resource
    Sea ice classification of TerraSAR-X ScanSAR images for the MOSAiC expedition incorporating per-class incidence angle dependency of image texture
    Copernicus GmbH ; 2023
    In:  The Cryosphere Vol. 17, No. 3 ( 2023-03-16), p. 1279-1297
    Details
    In: The Cryosphere, Copernicus GmbH, Vol. 17, No. 3 ( 2023-03-16), p. 1279-1297
    Abstract: Abstract. We provide sea ice classification maps of a sub-weekly time series of single (horizontal–horizontal, HH) polarization X-band TerraSAR-X scanning synthetic aperture radar (TSX SC) images from November 2019 to March 2020, covering the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. This classified time series benefits from the wide spatial coverage and relatively high spatial resolution of TSX SC data and is a useful basic dataset for future MOSAiC studies on physical sea ice processes and ocean and climate modeling. Sea ice is classified into leads, young ice with different backscatter intensities, and first-year ice (FYI) or multiyear ice (MYI) with different degrees of deformation. We establish the per-class incidence angle (IA) dependencies of TSX SC intensities and gray-level co-occurrence matrix (GLCM) textures and use a classifier that corrects for the class-specific decreasing backscatter with increasing IAs, with both HH intensities and textures as input features. Optimal parameters for texture calculation are derived to achieve good class separation while maintaining maximum spatial detail and minimizing textural collinearity. Class probabilities yielded by the classifier are adjusted by Markov random field contextual smoothing to produce classification results. The texture-based classification process yields an average overall accuracy of 83.70 % and good correspondence to geometric ice surface roughness derived from in situ ice thickness measurements (correspondence consistently close to or higher than 80 %). A positive logarithmic relationship is found between geometric ice surface roughness and TSX SC HH backscatter intensity, similar to previous C- and L-band studies. Areal fractions of classes representing ice openings (leads and young ice) show prominent increases in middle to late November 2019 and March 2020, corresponding well to ice-opening time series derived from in situ data in this study and those derived from satellite synthetic aperture radar (SAR) and optical data in other MOSAiC studies.
    Type of Medium: Online Resource
    ISSN: 1994-0424
    URL: Article
    DOI: 10.5194/tc-17-1279-2023
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2023
    detail.hit.zdb_id: 2393169-3
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  • 8
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    First results of the ARIEL L-band radiometer on the MOSAiC Arctic Expedition during the late summer and autumn period
    University of California Press ; 2022
    In:  Elementa: Science of the Anthropocene Vol. 10, No. 1 ( 2022-09-23)
    Details
    In: Elementa: Science of the Anthropocene, University of California Press, Vol. 10, No. 1 ( 2022-09-23)
    Abstract: Arctic sea ice is changing rapidly. Its retreat significantly impacts Arctic heat fluxes, ocean currents, and ecology, warranting the continuous monitoring and tracking of changes to sea ice extent and thickness. L-band (1.4 GHz) microwave radiometry can measure sea ice thickness for thin ice ≤1 m, depending on salinity and temperature. The sensitivity to thin ice makes L-band measurements complementary to radar altimetry which can measure the thickness of thick ice with reasonable accuracy. During the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, we deployed the mobile ARIEL L-band radiometer on the sea ice floe next to research vessel Polarstern to study the sensitivity of the L-band to different sea ice parameters (e.g., snow and ice thickness, ice salinity, ice and snow temperature), with the aim to help improve/validate current microwave emission models. Our results show that ARIEL is sensitive to different types of surfaces (ice, leads, and melt ponds) and to ice thickness up to 70 cm when the salinity of the sea ice is low. The measurements can be reproduced with the Burke emission model when in situ snow and ice measurements for the autumn transects were used as model input. The correlation coefficient for modeled Burke brightness temperature (BT) versus ARIEL measurements was approximately 0.8. The discrepancy between the measurements and the model is about 5%, depending on the transects analyzed. No explicit dependence on snow depth was detected. We present a qualitative analysis for thin ice observations on leads. We have demonstrated that the ARIEL radiometer is an excellent field instrument for quantifying the sensitivity of L-band radiometry to ice and snow parameters, leading to insights that can enhance sea ice thickness retrievals from L-band radiometer satellites (such as Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP)) and improve estimates of Arctic sea-ice thickness changes on a larger scale.
    Type of Medium: Online Resource
    ISSN: 2325-1026
    URL: Article
    DOI: 10.1525/elementa.2022.00031
    Language: English
    Publisher: University of California Press
    Publication Date: 2022
    detail.hit.zdb_id: 2745461-7
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  • 9
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    Polynya Signature Simulation Method polynya area in comparison to AMSR-E 89GHz sea-ice concentrations in the Ross Sea and off the Adélie Coast, Antarctica, for 2002–05: first results
    International Glaciological Society ; 2007
    In:  Annals of Glaciology Vol. 46 ( 2007), p. 409-418
    Details
    In: Annals of Glaciology, International Glaciological Society, Vol. 46 ( 2007), p. 409-418
    Abstract: The Polynya Signature Simulation Method (PSSM) is applied to Special Sensor Microwave/Imager observations from different Defense Meteorological Satellite Program spacecraft for 2002–05 to analyze the polynya area in the Ross Sea (Ross Ice Shelf polynya (RISP) and Terra Nova Bay polynya (TNBP)) and off the Adélie Coast (Mertz Glacier polynya (MGP)), Antarctica, on a sub-daily scale. The RISP and the MGP exhibit similar average total polynya areas. Major area changes ( 〉 10000km 2 ; TNPB: 〉 2000km 2 ) occur over a range of 2–3 to 20 days in all regions. Sub-daily area changes are largest for the MGP (5800km 2 ) and smallest for the TNBP (800km 2 ), underlining the persistence of the forcing of the latter. ARTIST sea-ice (ASI) algorithm concentration maps obtained using 89 GHz Advanced Microwave Scanning Radiometer (AMSR-E) data are compared to PSSM maps, yielding convincing agreement in the average, similarly detailed winter polynya distribution. Average ASI algorithm ice concentrations take values of 25–40% and 65–80% for the PSSM open-water and thin-ice class, respectively. The discrepancy with expected values (0% and 100%) can be explained by the different spatial resolution and frequency used by the methods. A new land mask and a mask to flag icebergs are introduced. Comparison of PSSM maps with thermal ice thickness based on AVHRR infrared temperature and ECMWF ERA-40 data suggests an upper thickness limit for the PSSM thin-ice class of 20–25 cm.
    Type of Medium: Online Resource
    ISSN: 0260-3055 , 1727-5644
    URL: Article
    DOI: 10.3189/172756407782871585
    Language: English
    Publisher: International Glaciological Society
    Publication Date: 2007
    detail.hit.zdb_id: 2122400-6
    SSG: 14
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  • 10
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    Snow and Ice Thickness Retrievals Using GNSS-R: Preliminary Results of the MOSAiC Experiment
    MDPI AG ; 2020
    In:  Remote Sensing Vol. 12, No. 24 ( 2020-12-10), p. 4038-
    Details
    In: Remote Sensing, MDPI AG, Vol. 12, No. 24 ( 2020-12-10), p. 4038-
    Abstract: The FSSCat mission was the 2017 ESA Sentinel Small Satellite (S⌃3) Challenge winner and the Copernicus Masters competition overall winner. It was successfully launched on 3 September 2020 onboard the VEGA SSMS PoC (VV16). FSSCat aims to provide coarse and downscaled soil moisture data and over polar regions, sea ice cover, and coarse resolution ice thickness using a combined L-band microwave radiometer and GNSS-Reflectometry payload. As part of the calibration and validation activities of FSSCat, a GNSS-R instrument was deployed as part of the MOSAiC polar expedition. The Multidisciplinary drifting Observatory for the Study of Arctic Climate expedition was an international one-year-long field experiment led by the Alfred Wegener Institute to study the climate system and the impact of climate change in the Arctic Ocean. This paper presents the first results of the PYCARO-2 instrument, focused on the GNSS-R techniques used to measure snow and ice thickness of an ice floe. The Interference Pattern produced by the combination of the GNSS direct and reflected signals over the sea-ice has been modeled using a four-layer model. The different thicknesses of the substrate layers (i.e., snow and ice) are linked to the position of the fringes of the interference pattern. Data collected by MOSAiC GNSS-R instrument between December 2019 and January 2020 for different GNSS constellations and frequencies are presented and analyzed, showing that under general conditions, sea ice and snow thickness can be retrieved using multiangular and multifrequency data.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    URL: Article
    DOI: 10.3390/rs12244038
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2513863-7
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