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  • 1
    Electronic Resource
    Electronic Resource
    Optical investigations on magnetic and structural phase transitions of (CH"3NH"3)"2CuCl"4 and (C"2H"5NH"3)"2CuCl"4
    Amsterdam : Elsevier
    Physica B+C 89 (1977), S. 165-176 
    Details
    ISSN: 0378-4363
    Source: Elsevier Journal Backfiles on ScienceDirect 1907 - 2002
    Topics: Physics
    Type of Medium: Electronic Resource
    URL: http://linkinghub.elsevier.com/retrieve/pii/0378-4363(77)90074-2
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    Paper (German National Licenses)
    Fulltext
  • 2
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    Melt pond fraction and spectral sea ice albedo retrieval from MERIS data – Part 1: Validation against in situ, aerial, and ship cruise data (2015)
    Copernicus Publications (EGU)
    In:  The Cryosphere, 9 . pp. 1551-1566.
    Details
    Publication Date: 2016-02-23
    Description: The presence of melt ponds on the Arctic sea ice strongly affects the energy balance of the Arctic Ocean in summer. It affects albedo as well as transmittance through the sea ice, which has consequences for the heat balance and mass balance of sea ice. An algorithm to retrieve melt pond fraction and sea ice albedo from Medium Resolution Imaging Spectrometer (MERIS) data is validated against aerial, shipborne and in situ campaign data. The results show the best correlation for landfast and multiyear ice of high ice concentrations. For broadband albedo, R2 is equal to 0.85, with the RMS (root mean square) being equal to 0.068; for the melt pond fraction, R2 is equal to 0.36, with the RMS being equal to 0.065. The correlation for lower ice concentrations, subpixel ice floes, blue ice and wet ice is lower due to ice drift and challenging for the retrieval surface conditions. Combining all aerial observations gives a mean albedo RMS of 0.089 and a mean melt pond fraction RMS of 0.22. The in situ melt pond fraction correlation is R2 = 0.52 with an RMS = 0.14. Ship cruise data might be affected by documentation of varying accuracy within the Antarctic Sea Ice Processes and Climate (ASPeCt) protocol, which may contribute to the discrepancy between the satellite value and the observed value: mean R2 = 0.044, mean RMS = 0.16. An additional dynamic spatial cloud filter for MERIS over snow and ice has been developed to assist with the validation on swath data.
    Type: Article , PeerReviewed
    Format: text
    DOI: 10.5194/tc-9-1551-2015
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 3
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    Empirical sea ice thickness retrieval during the freeze up period from SMOS high incident angle observations (2014)
    Copernicus Publications (EGU)
    In:  The Cryosphere, 8 (2). pp. 439-451.
    Details
    Publication Date: 2016-01-14
    Description: Sea ice thickness information is important for sea ice modelling and ship operations. Here a method to detect the thickness of sea ice up to 50 cm during the freeze-up season based on high incidence angle observations of the Soil Moisture and Ocean Salinity (SMOS) satellite working at 1.4 GHz is suggested. By comparison of thermodynamic ice growth data with SMOS brightness temperatures, a high correlation to intensity and an anticorrelation to the difference between vertically and horizontally polarised brightness temperatures at incidence angles between 40 and 50° are found and used to develop an empirical retrieval algorithm sensitive to thin sea ice up to 50 cm thickness. The algorithm shows high correlation with ice thickness data from airborne measurements and reasonable ice thickness patterns for the Arctic freeze-up period.
    Type: Article , PeerReviewed
    Format: text
    DOI: 10.5194/tc-8-439-2014
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 4
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    Online sea ice knowledge and data platform: www.meereisportal.de (2015)
    In:  [Poster] In: 26. International Congress on Polar Research - High Latitutdes and High Mountains: Driver of or Driven by Global Change?, 06.-11.09.2015, Munich, Germany .
    Details
    Publication Date: 2016-02-26
    Type: Conference or Workshop Item , NonPeerReviewed
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    OceanRep: Poster
  • 5
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    Algorithm to retrieve the melt pond fraction and the spectral albedo of Arctic summer ice from satellite optical data (2015)
    Elsevier
    In:  Remote Sensing of Environment, 163 . pp. 153-164.
    Details
    Publication Date: 2017-01-17
    Description: A new algorithmto retrieve characteristics (albedo and melt pond fraction) of summer ice in the Arctic fromoptical satellite data is described. In contrast to other algorithms this algorithm does not use a priori values of the spectral albedo of the sea-ice constituents (such asmelt ponds,white ice etc.). Instead, it is based on an analytical solution for the reflection from sea ice surface. The algorithm includes the correction of the sought-for ice and ponds characteristics with the iterative procedure based on the Newton–Raphson method. Also, it accounts for the bi-directional reflection from the ice/snow surface, which is particularly important for Arctic regions where the sun is low. The algorithm includes an original procedure for the atmospheric correction, as well. This algorithm is implemented as computer code called Melt Pond Detector (MPD). The input to the current version of the MPD algorithm is the MERIS Level 1B data, including the radiance coefficients at ten wavelengths and the solar and observation angles (zenith and azimuth). Also, specific parameters describing surface and atmospheric state can be set in a configuration input file. The software output is the map of the melt ponds area fraction and the spectral albedo of sea-ice in HDF5 format. The numerical verification shows that theMPD algorithm provides more accurate results for the light ponds than for the dark ones. The spectral albedo is retrieved with high accuracy for any type of ice and ponds.
    Type: Article , PeerReviewed , info:eu-repo/semantics/article
    Format: text
    DOI: 10.1016/j.rse.2015.03.012
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 6
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    A combined radiative transfer model for sea ice, open ocean, and atmosphere (1998)
    AGU (American Geophysical Union)
    In:  Radio Science, 33 (2). pp. 303-316.
    Details
    Publication Date: 2018-03-13
    Description: A radiative transfer model to compute brightness temperatures in the microwave frequency range for polar regions including sea ice, open ocean, and atmosphere has been developed and applied to sensitivity studies and retrieval algorithm development. The radiative transfer within sea ice is incorporated according to the “many layer strong fluctuation theory” of Stogryn [1986, 1987] and T. Grenfell [Winebrenner et al., 1992]. The reflectivity of the open water is computed with the three-scale model of Schrader [1995]. Both surface models supply the bistatic scattering coefficients, which define the lower boundary for the atmospheric model. The atmospheric model computes the gaseous absorption by the Liebe et al. [1993] model. Scattering by hydrometeors is determined by Mie or Rayleigh theory. Simulated brightness temperatures have been compared with special sensor microwave imager (SSM/I) observations. The comparison exhibits shortcomings of the ice model for 37 GHz. Applying a simple ad hoc correction at this frequency gives consistent comparison results within the range of observational accuracy. The simulated brightness temperatures show the strong influence of clouds and variations of wind speed over the open ocean, which will affect the sea ice retrieval even for an ice-covered ocean. Simulated brightness temperatures have been used to train a neural network algorithm for the total sea ice concentration, which accounts for these effects. Sea ice concentrations sensed from the SSM/I data using the network and the NASA sea ice algorithm show systematic differences in dependence on cloudiness.
    Type: Article , PeerReviewed
    Format: text
    DOI: 10.1029/97RS03020
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 7
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    Erratum: Corrigendum: Worldwide variations in artificial skyglow (2015)
    In:  Scientific Reports
    Details
    Publication Date: 2020-02-12
    Type: info:eu-repo/semantics/article
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  • 8
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    Online Sea-Ice Knowledge and Data Platform 〈www.meereisportal.de〉 (2016)
    In:  Polarforschung
    Details
    Publication Date: 2020-02-12
    Description: The combination of multi-disciplinary sea ice science and the rising demand of society for up-to-date information and user customized products on climate change emphasis the need for addressing the challenges posed by environmental change in the Polar Regions by means of creating new ways of communication. The new knowledge platform “meereisportal.de” is a contribution to the cross-linking of scientifically qualified information on climate change and focuses deliberately on the theme: “sea ice” in both Polar Regions. With “meereisportal. de” the science opens to changing societal demands and goes new ways of communication between science and society. “meereisportal. de” is the first comprehensive German speaking knowledge platform on sea ice that went online 2013. It was developed in the frame of the Helmholtz Climate Initiative, Regional Climate Change (REKLIM) as a joint project of the University of Bremen (Institute of Environmental Physics) and the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research under the management of the Helmholtz Regional Climate Office for Polar Regions and Sea Level change. This paper describes the concept and the development of the knowledge platform, different usage examples and user-specific products. Moreover, an outlook on the planned activities in the future will be given.
    Description: Die Kombination der zunehmend multi-disziplinären Meereisforschung und die steigende Nachfrage der Gesellschaft nach aktuellen Informationen und benutzerorientierten Produkten zum Thema Klimawandel erfordert neue Wege der Wissenskommunikation, um den Herausforderungen der zunehmenden Umweltveränderungen, insbesondere in den Polarregionen, zu begegnen. Die neue Wissensplattform “meereisportal.de” ist ein Beitrag zum Vernetzen von wissenschaftlich qualifizierten Fachinformationen zum Thema Klimawandel und fokussiert dabei bewusst auf ein Thema: “Meereis” in beiden Polargebieten. Mit “meereisportal.de” öffnet sich die Wissenschaft gegenüber sich verändernden gesellschaftlichen Anforderungen und geht neue Wege der Kommunikation zwischen Wissenschaft und Gesellschaft. “meereisportal. de” ist 2013 als erste umfassende, deutschsprachige Wissensplattform rund um das Thema Meereis in der Arktis und Antarktis online gegangen. Sie wurde im Rahmen des Helmholtz-Verbundes Regionale Klimaveränderungen (REKLIM) als Gemeinschaftsprojekt der Universität Bremen (Institut für Umweltphysik) und des Alfred-Wegener-Institutes, Helmholtz-Zentrum für Polar- und Meeresforschung unter der Federführung des regionalen Helmholtz Klimabüros für Polargebiete und Meeresspiegelanstieg entwickelt. Dieser Beitrag beschreibt die Entstehung, das Konzept und die Entwicklung der Wissensplattform, verschiedene Anwendungsbeispiele sowie nutzerspezifische Produkte. Darüber hinaus wird ein Ausblick über die in Zukunft geplanten Aktivitäten gegeben.
    Language: English
    Type: info:eu-repo/semantics/article
    Format: application/pdf
    Format: application/pdf
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  • 9
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    Worldwide variations in artificial skyglow (2015)
    In:  Scientific Reports
    Details
    Publication Date: 2020-02-12
    Type: info:eu-repo/semantics/article
    Format: application/pdf
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    GFZ OAI
  • 10
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    Angular distribution of upwelling artificial light in Europe as observed by Suomi–NPP satellite (2020)
    In:  Journal of Quantitative Spectroscopy and Radiative Transfer
    Details
    Publication Date: 2020-12-14
    Description: Measuring the angular distribution of upwelling artificial light is important for modeling light pollution, because the direction of emission affects how light propagates in the atmosphere. We characterize the angular distributions of upwelling artificial light for Europe and northern Africa in 2018, based on night time radiance data for clear nights without twilight and moonlight from the VIIRS–DNB sensor on board the Suomi NPP satellite. We find that in general, suburban areas of major cities emit more light at larger zenith angles, whereas the opposite can be seen at the city centers, where the highest radiance is directed upward. The mean numbers of overflights for the year is 83, meaning that there are on average approximately seven suitable overflights per month. Future analysis may consider using moonlight models to compensate for the retrieval of moonlit scenes and analyzing data from different years in order to expand the amount of available data. As the VIIRS–DNB sensor on board the NOAA–20 satellite (launched 2017) has almost the same design, this method can also be extended to the data taken by NOAA–20.
    Type: info:eu-repo/semantics/article
    Format: application/pdf
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