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37 Research products

  • European Marine Science
  • 2014-2023
  • Research software
  • Other research products
  • European Commission
  • CH
  • European Marine Science

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Wolff, Eric William; Mulvaney, Robert; Grieman, Mackenzie M; Hoffmann, Helene; +1 Authors

    We present an age model for the 651 m deep Skytrain Ice Rise ice core (79°44.5'S, 78°32.7'W). The top 2000 years have previously been dated using age markers interpolated through annual layer counting. Below this, we align the Skytrain core to the AICC2012 age model using tie points in the ice and air phase, and apply the Paleochrono program to obtain the best fit to the tie points and glaciological constraints. In the gas phase, ties are made using methane and, in critical sections, δ18Oair; in the ice phase ties are through 10Be across the Laschamps Event, and through ice chemistry related to long-range dust transport and deposition. This strategy provides a good outcome to about 108 ka (~605 m). Beyond that there are signs of flow disturbance, with a section of ice probably repeated. Nonetheless values of CH4 and δ18Oair confirm that part of the last interglacial (LIG), from about 117-126 ka (617-628 m), is present and in chronological order. Below this there are clear signs of stratigraphic disturbance, with rapid oscillation of values in both the ice and gas phase at the base of the LIG section. Based on methane values, the warmest part of the LIG and the coldest part of the penultimate glacial are missing from our record. Ice below 631 m appears to be of age >150 ka.

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    Authors: Brugnara, Yuri; Horn, Michael; Salvador, Isabella;

    We provide two instrumental records of air pressure and temperature for the Alpine cities of Rovereto and Bolzano/Bozen, covering the periods 1800-1839 and 1842-1873, respectively. They were measured by local physics teachers and digitized at the University of Bern from a handwritten weather diary and a local newspaper. In addition to the raw (sub-daily) data, we provide daily and monthly means together with a quantitative estimation of their uncertainty. The data were converted to modern units, quality controlled, and homogenized.

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    https://doi.org/10.1594/pangae...
    Collection . 2023
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      https://doi.org/10.1594/pangae...
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    Authors: Brandon, Margaux; Duchamp-Alphonse, Stéphanie; Michel, Elisabeth; Landais, Amaëlle; +6 Authors

    Micropaleontological (coccolith, planktonic foraminifera) and geochemical (CaCO3, CaXRF, δ18O N. pachyderma, δ13C N. pachyderma) analyses from sediment core MD04-2718 retrieved from the Subantarctic zone (SAZ) of the Indian Southern Ocean covering the time interval from Marine Isotope Stage (MIS) 12 to MIS 10 (440,000– 360,000 years). Coccolith abundances and masses were performed using SYRACO software at Geoscience Paris-Saclay Laboratory (GEOPS). CaCO3 percentages were also measured at GEOPS. Foraminifera abundances and masses and stable oxygen and carbon isotopes were performed at Laboratoire des Sciences du Climat et de l'Environnement (LSCE). SST were calculated using two methods : the Modern Analogue Technique (Haddam et al., 2016) and the percentage of N. pachyderma s. (Govin et al., 2009). CaXRF measurements were performed at ETH, Zurich. These approaches allowed to decipher the variations in Carbonate Counter Pump and upwelling strength in the Indian Sector of the Southern Ocean between MIS 12 and MIS 10, including the Termination V and interglacial MIS 11.

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    Authors: Lundstad, Elin; Brugnara, Yuri; Brönnimann, Stefan;

    There is a growing need for past weather and climate data to support science and decision-making. This paper describes the compilation and the construction of a global multivariable (air temperature, pressure, precipitation sum, number of precipitation days) monthly instrumental climate database that encompasses a substantial body of the known early instrumental time series. The dataset contains series compiled from existing databases that start before 1890 (though continuing to the present) as well as a large amount of newly rescued data. All series underwent a quality control procedure and subdaily series were processed to monthly mean values. An inventory was compiled, and the collection was deduplicated based on coordinates and mutual correlations. The data are provided in a common format accompanied by the inventory. The collection totals 12452 meteorological records in 118 countries. The data has been merged from 18250 original data files. The data can be used for climate reconstructions and analyses. It is the most comprehensive global monthly climate data set for the preindustrial period.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ https://doi.org/10.1...arrow_drop_down
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    https://doi.org/10.1594/pangae...
    Collection . 2022
    License: CC BY
    Data sources: Sygma
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      https://doi.org/10.1594/pangae...
      Collection . 2022
      License: CC BY
      Data sources: Sygma
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    Authors: Benedetti, Fabio;
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    Authors: Kopp, Robert E.; Rasmussen, D. J.;

    This MATLAB code is intended to help end-users who wish to work with the sea-level rise projections of Kopp et al. (2014) and successor papers in greater detail than provided by the supplementary tables accompanying that table but without re-running the full global analysis using the supplementary code accompanying the paper. Key functionality these routines provide include: 1. Local sea-level rise projections at decadal time points and arbitrary quantiles 2. Localized Monte Carlo samples, disaggregatable by contributory process 3. Localized variance decomposition plots This code was originally developed to accompany the results of R. E. Kopp, R. M. Horton, C. M. Little, J. X. Mitrovica, M. Oppenheimer, D. J. Rasmussen, B. H. Strauss, and C. Tebaldi (2014). Probabilistic 21st and 22nd century sea-level projections at a global network of tide gauge sites. Earth's Future 2: 287–306, doi:10.1002/2014EF000239. Please cite that paper, along with the paper(s) associated with the specific projections you are using, when using any sea-level rise projections generated with this code.

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    Authors: Plach, Andreas; Vinther, Bo M.; Nisancioglu, Kerim H.; Vudayagiri, Sindhu; +1 Authors

    This study presents simulations of Greenland surface melt for the Eemian interglacial period (∼130 000 to 115 000 years ago) derived from regional climate simulations with a coupled surface energy balance model. Surface melt is of high relevance due to its potential effect on ice core observations, e.g., lowering the preserved total air content (TAC) used to infer past surface elevation. An investigation of surface melt is particularly interesting for warm periods with high surface melt, such as the Eemian interglacial period. Furthermore, Eemian ice is the deepest and most compressed ice preserved on Greenland, resulting in our inability to identify melt layers visually. Therefore, simulating Eemian melt rates and associated melt layers is beneficial to improve the reconstruction of past surface elevation. Estimated TAC, based on simulated melt during the Eemian, could explain the lower TAC observations. The simulations show Eemian surface melt at all deep Greenland ice core locations and an average of up to ∼30 melt days per year at Dye-3, corresponding to more than 600 mm water equivalent (w.e.) of annual melt. For higher ice sheet locations, between 60 and 150 mmw.e.yr-1 on average are simulated. At the summit of Greenland, this yields a refreezing ratio of more than 25 % of the annual accumulation. As a consequence, high melt rates during warm periods should be considered when interpreting Greenland TAC fluctuations as surface elevation changes. In addition to estimating the influence of melt on past TAC in ice cores, the simulated surface melt could potentially be used to identify coring locations where Greenland ice is best preserved.

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    Authors: Vogt, Meike; Benedetti, Fabio; Righetti, Damiano; O'Brien, Colleen; +3 Authors
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    Authors: Erhardt, Tobias; Bigler, Matthias; Federer, Urs; Gfeller, Gideon; +20 Authors

    Records of chemical impurities from ice cores enable us to reconstruct the past deposition of aerosols onto polar ice sheets and alpine glaciers. Through this they allow us to gain insight into changes of the source, transport and deposition processes that ultimately determine the deposition flux at the coring location. However, the low concentrations of the aerosol species in the ice and the resulting high risk of contamination pose a formidable analytical challenge, especially if long, continuous and highly resolved records are needed. Continuous flow analysis, CFA, the continuous melting, decontamination and analysis of ice-core samples has mostly overcome this issue and has quickly become the de facto standard to obtain high-resolution aerosol records from ice cores after its inception at the University of Bern in the mid-1990s. Here, we present continuous records of calcium (Ca2+), sodium (Na+), ammonium (NH4+), nitrate (NO3-) and electrolytic conductivity at 1 mm depth resolution from the NGRIP (North Greenland Ice Core Project) and NEEM (North Greenland Eemian Ice Drilling) ice cores produced by the Bern Continuous Flow Analysis group in the years 2000 to 2011 (Erhardt et al., 2021). Both of the records were previously used in a number of studies but were never published in full 1 mm resolution. Alongside the 1 mm datasets we provide decadal averages, a detailed description of the methods, relevant references, an assessment of the quality of the data and its usable resolution. Along the way we will also give some historical context on the development of the Bern CFA system. The data is available in full 1 mm and 10-year-averaged resolution on PANGAEA (https://doi.org/10.1594/PANGAEA.935838, Erhardt et al., 2021)

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    Authors: Macfarlane, Amy R; Schneebeli, Martin; Dadic, Ruzica; Wagner, David N; +18 Authors

    This dataset captures the yearlong evolution of physical properties of the snow cover over Arctic sea ice during the MOSAiC expedition (October 2019-September 2020). It also includes the surface scattering layer that is typical of the melting summer sea ice surface. This dataset is specifically for measurements that were logged as “snowpit events” during MOSAiC. The snowpit events were either detailed point-measurements of vertical snow profiles or horizontally repeated transects, measured at selected locations in designated undisturbed areas. One snowpit event corresponds to one site visit. The snowpits are often co-located with measurements from other MOSAiC teams to improve our understanding of how snow cover affects and interacts with the atmosphere-sea ice-ocean-ecology system. Most snowpits were measured at least bi-weekly to capture the temporal evolution of physical properties of snow. Some snowpits were one-off events to capture interesting and unplanned-for surface conditions. This dataset includes 576 snowpit events, and describes the snow conditions during the entire expedition. Please direct inquiries to; David Wagner (PS122/1), Martin Schneebeli (PS122/2), Amy Macfarlane (PS122/3 and PS122/4), Ruzica Dadic (PS122/5).

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Wolff, Eric William; Mulvaney, Robert; Grieman, Mackenzie M; Hoffmann, Helene; +1 Authors

    We present an age model for the 651 m deep Skytrain Ice Rise ice core (79°44.5'S, 78°32.7'W). The top 2000 years have previously been dated using age markers interpolated through annual layer counting. Below this, we align the Skytrain core to the AICC2012 age model using tie points in the ice and air phase, and apply the Paleochrono program to obtain the best fit to the tie points and glaciological constraints. In the gas phase, ties are made using methane and, in critical sections, δ18Oair; in the ice phase ties are through 10Be across the Laschamps Event, and through ice chemistry related to long-range dust transport and deposition. This strategy provides a good outcome to about 108 ka (~605 m). Beyond that there are signs of flow disturbance, with a section of ice probably repeated. Nonetheless values of CH4 and δ18Oair confirm that part of the last interglacial (LIG), from about 117-126 ka (617-628 m), is present and in chronological order. Below this there are clear signs of stratigraphic disturbance, with rapid oscillation of values in both the ice and gas phase at the base of the LIG section. Based on methane values, the warmest part of the LIG and the coldest part of the penultimate glacial are missing from our record. Ice below 631 m appears to be of age >150 ka.

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    Authors: Brugnara, Yuri; Horn, Michael; Salvador, Isabella;

    We provide two instrumental records of air pressure and temperature for the Alpine cities of Rovereto and Bolzano/Bozen, covering the periods 1800-1839 and 1842-1873, respectively. They were measured by local physics teachers and digitized at the University of Bern from a handwritten weather diary and a local newspaper. In addition to the raw (sub-daily) data, we provide daily and monthly means together with a quantitative estimation of their uncertainty. The data were converted to modern units, quality controlled, and homogenized.

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    https://doi.org/10.1594/pangae...
    Collection . 2023
    License: CC BY
    Data sources: Sygma
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      https://doi.org/10.1594/pangae...
      Collection . 2023
      License: CC BY
      Data sources: Sygma
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    Authors: Brandon, Margaux; Duchamp-Alphonse, Stéphanie; Michel, Elisabeth; Landais, Amaëlle; +6 Authors

    Micropaleontological (coccolith, planktonic foraminifera) and geochemical (CaCO3, CaXRF, δ18O N. pachyderma, δ13C N. pachyderma) analyses from sediment core MD04-2718 retrieved from the Subantarctic zone (SAZ) of the Indian Southern Ocean covering the time interval from Marine Isotope Stage (MIS) 12 to MIS 10 (440,000– 360,000 years). Coccolith abundances and masses were performed using SYRACO software at Geoscience Paris-Saclay Laboratory (GEOPS). CaCO3 percentages were also measured at GEOPS. Foraminifera abundances and masses and stable oxygen and carbon isotopes were performed at Laboratoire des Sciences du Climat et de l'Environnement (LSCE). SST were calculated using two methods : the Modern Analogue Technique (Haddam et al., 2016) and the percentage of N. pachyderma s. (Govin et al., 2009). CaXRF measurements were performed at ETH, Zurich. These approaches allowed to decipher the variations in Carbonate Counter Pump and upwelling strength in the Indian Sector of the Southern Ocean between MIS 12 and MIS 10, including the Termination V and interglacial MIS 11.

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    Authors: Lundstad, Elin; Brugnara, Yuri; Brönnimann, Stefan;

    There is a growing need for past weather and climate data to support science and decision-making. This paper describes the compilation and the construction of a global multivariable (air temperature, pressure, precipitation sum, number of precipitation days) monthly instrumental climate database that encompasses a substantial body of the known early instrumental time series. The dataset contains series compiled from existing databases that start before 1890 (though continuing to the present) as well as a large amount of newly rescued data. All series underwent a quality control procedure and subdaily series were processed to monthly mean values. An inventory was compiled, and the collection was deduplicated based on coordinates and mutual correlations. The data are provided in a common format accompanied by the inventory. The collection totals 12452 meteorological records in 118 countries. The data has been merged from 18250 original data files. The data can be used for climate reconstructions and analyses. It is the most comprehensive global monthly climate data set for the preindustrial period.

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    https://doi.org/10.1594/pangae...
    Collection . 2022
    License: CC BY
    Data sources: Sygma
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      https://doi.org/10.1594/pangae...
      Collection . 2022
      License: CC BY
      Data sources: Sygma
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    Authors: Benedetti, Fabio;
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    Authors: Kopp, Robert E.; Rasmussen, D. J.;

    This MATLAB code is intended to help end-users who wish to work with the sea-level rise projections of Kopp et al. (2014) and successor papers in greater detail than provided by the supplementary tables accompanying that table but without re-running the full global analysis using the supplementary code accompanying the paper. Key functionality these routines provide include: 1. Local sea-level rise projections at decadal time points and arbitrary quantiles 2. Localized Monte Carlo samples, disaggregatable by contributory process 3. Localized variance decomposition plots This code was originally developed to accompany the results of R. E. Kopp, R. M. Horton, C. M. Little, J. X. Mitrovica, M. Oppenheimer, D. J. Rasmussen, B. H. Strauss, and C. Tebaldi (2014). Probabilistic 21st and 22nd century sea-level projections at a global network of tide gauge sites. Earth's Future 2: 287–306, doi:10.1002/2014EF000239. Please cite that paper, along with the paper(s) associated with the specific projections you are using, when using any sea-level rise projections generated with this code.

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    Authors: Plach, Andreas; Vinther, Bo M.; Nisancioglu, Kerim H.; Vudayagiri, Sindhu; +1 Authors

    This study presents simulations of Greenland surface melt for the Eemian interglacial period (∼130 000 to 115 000 years ago) derived from regional climate simulations with a coupled surface energy balance model. Surface melt is of high relevance due to its potential effect on ice core observations, e.g., lowering the preserved total air content (TAC) used to infer past surface elevation. An investigation of surface melt is particularly interesting for warm periods with high surface melt, such as the Eemian interglacial period. Furthermore, Eemian ice is the deepest and most compressed ice preserved on Greenland, resulting in our inability to identify melt layers visually. Therefore, simulating Eemian melt rates and associated melt layers is beneficial to improve the reconstruction of past surface elevation. Estimated TAC, based on simulated melt during the Eemian, could explain the lower TAC observations. The simulations show Eemian surface melt at all deep Greenland ice core locations and an average of up to ∼30 melt days per year at Dye-3, corresponding to more than 600 mm water equivalent (w.e.) of annual melt. For higher ice sheet locations, between 60 and 150 mmw.e.yr-1 on average are simulated. At the summit of Greenland, this yields a refreezing ratio of more than 25 % of the annual accumulation. As a consequence, high melt rates during warm periods should be considered when interpreting Greenland TAC fluctuations as surface elevation changes. In addition to estimating the influence of melt on past TAC in ice cores, the simulated surface melt could potentially be used to identify coring locations where Greenland ice is best preserved.

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    Authors: Vogt, Meike; Benedetti, Fabio; Righetti, Damiano; O'Brien, Colleen; +3 Authors