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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: ICOS RI; Bergamaschi, Peter; Colomb, Aurélie; Emmenegger, Lukas; +50 Authors

    This data package contains high accuracy N2O dry air mole fractions from 32 ICOS and non-ICOS European observatories at in total 73 observation levels, collected by the ICOS Atmosphere Thematic Centre (ATC) and provided by the station contributors. The package is the first release of the N2O European Obspack data product (version 10.0), and is intended for use in carbon cycle inverse modeling, model evaluation, and satellite validation studies. Please report errors and send comments regarding this product to the ObsPack originators. Please read carefully the ObsPack Fair Use statement and cite appropriately. Metadata for this product are available at https://commons.datacite.org/doi.org/10.18160/6ZXD-BAAZ. Please visit http://www.gml.noaa.gov/ccgg/obspack/ for more information.

    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/ ICOS Carbon Portalarrow_drop_down
    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/
    ICOS Carbon Portal
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
    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/
    ICOS Carbon Portal
    Dataset . 2024
    Data sources: B2FIND
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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/ ICOS Carbon Portalarrow_drop_down
      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/
      ICOS Carbon Portal
      Dataset . 2024
      License: CC BY
      Data sources: Datacite
      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/
      ICOS Carbon Portal
      Dataset . 2024
      Data sources: B2FIND
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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: ICOS RI; Bergamaschi, Peter; Colomb, Aurélie; Emmenegger, Lukas; +50 Authors

    This data package contains high accuracy N2O dry air mole fractions from 32 ICOS and non-ICOS European observatories at in total 73 observation levels, collected by the ICOS Atmosphere Thematic Centre (ATC) and provided by the station contributors. The package is the first release of the N2O European Obspack data product (version 10.0), and is intended for use in carbon cycle inverse modeling, model evaluation, and satellite validation studies. Please report errors and send comments regarding this product to the ObsPack originators. Please read carefully the ObsPack Fair Use statement and cite appropriately. Metadata for this product are available at https://commons.datacite.org/doi.org/10.18160/6ZXD-BAAZ. Please visit http://www.gml.noaa.gov/ccgg/obspack/ for more information.

    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/ ICOS Carbon Portalarrow_drop_down
    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/
    ICOS Carbon Portal
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
    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/
    ICOS Carbon Portal
    Dataset . 2024
    Data sources: B2FIND
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    This Research product is the result of merged Research products in OpenAIRE.

    You have already added works in your ORCID record related to the merged Research product.
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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/ ICOS Carbon Portalarrow_drop_down
      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/
      ICOS Carbon Portal
      Dataset . 2024
      License: CC BY
      Data sources: Datacite
      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/
      ICOS Carbon Portal
      Dataset . 2024
      Data sources: B2FIND
      addClaim

      This Research product is the result of merged Research products in OpenAIRE.

      You have already added works in your ORCID record related to the merged Research product.
  • 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: Brian Oney; Brian Oney; Markus Leuenberger; Nicolas Gruber; +6 Authors

    Abstract. We describe a new rural network of four densely placed (< 100 km apart), continuous atmospheric carbon (CO2, CH4, and CO) measurement sites in north-central Switzerland and analyze their suitability for regional-scale (~ 100 to 500 km) carbon flux studies. We characterize each site by analyzing surrounding land cover, observed local meteorology, and sensitivity to surface fluxes, as simulated with the Lagrangian particle dispersion model FLEXPART-COSMO. The Beromünster measurements are made on a tall tower (212 m) located on a gentle hill. At Beromünster, regional CO2 signals (measurement minus background) vary diurnally from −4 to +4 ppmv on average, and are simulated to come from nearly the entire Swiss Plateau, where 50% of surface influence is simulated to be within 130 to 260 km distance. The Früebüel site measurements are made 4 m above ground on the flank of a gently sloping mountain. Nearby (< 50 km) pasture and forest fluxes exert the most simulated surface influence, except during convective summertime days when the site is mainly influenced by the eastern Swiss Plateau, which results in summertime regional CO2 signals varying diurnally from −5 to +12 ppmv and elevated summer daytime CH4 signals (+30 ppbv above other sites). The Gimmiz site measurements are made on a small tower (32 m) in flat terrain. Here, strong summertime regional signals (−5 to +60 ppmv CO2) stem from large, nearby (< 50 km) crop and anthropogenic fluxes of the Seeland region, except during warm or windy days when simulated surface influence is of regional scale (< 250 km). The Lägern-Hochwacht measurements are made on a small tower (32 m) on top of the steep Lägern crest, where simulated surface influence is typically of regional scale (130 to 300 km) causing summertime regional signals to vary from −5 to +8 ppmv CO2. Here, considerable anthropogenic influence from the nearby industrialized region near Zurich cause the average wintertime regional CO2 signals to be 5 ppmv above the regional signals simultaneously measured at Früebüel site. We find that the suitability of the datasets from our current observation network for regional carbon budgeting studies largely depends on the ability of the high-resolution (2 km) atmospheric transport model to correctly capture the temporal dynamics of the stratification of the lower atmosphere at the different sites. The current version of the atmospheric transport model captures these dynamics well, but it clearly reaches its limits at the sites in steep topography, and at the sites that generally remain in the surface layer. Trace gas transport and inverse modeling studies will be necessary to determine the impact of these limitations on our ability to derive reliable regional-scale carbon flux estimates in the complex Swiss landscape.

    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/ Bern Open Repository...arrow_drop_down
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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/
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    https://doi.org/10.5194/acpd-1...
    Article . 2015 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
    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://www.atmos-chem-phys.ne...
    Article
    License: CC BY
    Data sources: UnpayWall
    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/
    Atmospheric Chemistry and Physics (ACP)
    Article . 2015 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
    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/
    Atmospheric Chemistry and Physics (ACP)
    Article
    License: CC BY
    Data sources: UnpayWall
    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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    Atmospheric Chemistry and Physics (ACP)
    Other literature type . 2018
    Data sources: Copernicus
    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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    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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    Research Collection
    Article . 2015
    License: CC BY
    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/
    Research Collection
    Research . 2015
    License: CC BY
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    http://www.atmos-chem-phys.net...
    Article . 2015 . Peer-reviewed
    Data sources: SNSF P3 Database
    https://dx.doi.org/10.60692/gp...
    Other literature type . 2015
    Data sources: Datacite
    Research Collection
    Article . 2015
    License: CC BY
    Data sources: Datacite
    https://dx.doi.org/10.60692/hc...
    Other literature type . 2015
    Data sources: Datacite
    Research Collection
    Research . 2015
    License: CC BY
    Data sources: Datacite
    Copernicus Publications
    Other literature type . 2018
    addClaim

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    citations34
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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/ Bern Open Repository...arrow_drop_down
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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/
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      https://doi.org/10.5194/acpd-1...
      Article . 2015 . Peer-reviewed
      License: CC BY
      Data sources: Crossref
      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://www.atmos-chem-phys.ne...
      Article
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      Data sources: UnpayWall
      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/
      Atmospheric Chemistry and Physics (ACP)
      Article . 2015 . Peer-reviewed
      License: CC BY
      Data sources: Crossref
      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/
      Atmospheric Chemistry and Physics (ACP)
      Article
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      Data sources: UnpayWall
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      Atmospheric Chemistry and Physics (ACP)
      Other literature type . 2018
      Data sources: Copernicus
      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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      Research Collection
      Article . 2015
      License: CC BY
      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/
      Research Collection
      Research . 2015
      License: CC BY
      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/
      http://www.atmos-chem-phys.net...
      Article . 2015 . Peer-reviewed
      Data sources: SNSF P3 Database
      https://dx.doi.org/10.60692/gp...
      Other literature type . 2015
      Data sources: Datacite
      Research Collection
      Article . 2015
      License: CC BY
      Data sources: Datacite
      https://dx.doi.org/10.60692/hc...
      Other literature type . 2015
      Data sources: Datacite
      Research Collection
      Research . 2015
      License: CC BY
      Data sources: Datacite
      Copernicus Publications
      Other literature type . 2018
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      This Research product is the result of merged Research products in OpenAIRE.

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    Authors: Brian Oney; Brian Oney; Markus Leuenberger; Nicolas Gruber; +6 Authors

    Abstract. We describe a new rural network of four densely placed (< 100 km apart), continuous atmospheric carbon (CO2, CH4, and CO) measurement sites in north-central Switzerland and analyze their suitability for regional-scale (~ 100 to 500 km) carbon flux studies. We characterize each site by analyzing surrounding land cover, observed local meteorology, and sensitivity to surface fluxes, as simulated with the Lagrangian particle dispersion model FLEXPART-COSMO. The Beromünster measurements are made on a tall tower (212 m) located on a gentle hill. At Beromünster, regional CO2 signals (measurement minus background) vary diurnally from −4 to +4 ppmv on average, and are simulated to come from nearly the entire Swiss Plateau, where 50% of surface influence is simulated to be within 130 to 260 km distance. The Früebüel site measurements are made 4 m above ground on the flank of a gently sloping mountain. Nearby (< 50 km) pasture and forest fluxes exert the most simulated surface influence, except during convective summertime days when the site is mainly influenced by the eastern Swiss Plateau, which results in summertime regional CO2 signals varying diurnally from −5 to +12 ppmv and elevated summer daytime CH4 signals (+30 ppbv above other sites). The Gimmiz site measurements are made on a small tower (32 m) in flat terrain. Here, strong summertime regional signals (−5 to +60 ppmv CO2) stem from large, nearby (< 50 km) crop and anthropogenic fluxes of the Seeland region, except during warm or windy days when simulated surface influence is of regional scale (< 250 km). The Lägern-Hochwacht measurements are made on a small tower (32 m) on top of the steep Lägern crest, where simulated surface influence is typically of regional scale (130 to 300 km) causing summertime regional signals to vary from −5 to +8 ppmv CO2. Here, considerable anthropogenic influence from the nearby industrialized region near Zurich cause the average wintertime regional CO2 signals to be 5 ppmv above the regional signals simultaneously measured at Früebüel site. We find that the suitability of the datasets from our current observation network for regional carbon budgeting studies largely depends on the ability of the high-resolution (2 km) atmospheric transport model to correctly capture the temporal dynamics of the stratification of the lower atmosphere at the different sites. The current version of the atmospheric transport model captures these dynamics well, but it clearly reaches its limits at the sites in steep topography, and at the sites that generally remain in the surface layer. Trace gas transport and inverse modeling studies will be necessary to determine the impact of these limitations on our ability to derive reliable regional-scale carbon flux estimates in the complex Swiss landscape.

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    Authors: Erkan Ibraim; Erkan Ibraim; Longfei Yu; Sarah Eggleston; +12 Authors

    Abstract. Nitrous oxide (N2O) is the primary atmospheric constituent involved in stratospheric ozone depletion and contributes strongly to changes in the climate system through a positive radiative forcing mechanism. The atmospheric abundance of N2O has increased from 270 ppb (parts per billion, 10−9 mole mole−1) during the pre-industrial era to approx. 330 ppb in 2018. Even though it is well known that microbial processes in agricultural and natural soils are the major N2O source, the contribution of specific soil processes is still uncertain. The relative abundance of N2O isotopocules (14N14N16N, 14N15N16O, 15N14N16O, and 14N14N18O) carries process-specific information and thus can be used to trace production and consumption pathways. While isotope ratio mass spectroscopy (IRMS) was traditionally used for high-precision measurement of the isotopic composition of N2O, quantum cascade laser absorption spectroscopy (QCLAS) has been put forward as a complementary technique with the potential for on-site analysis. In recent years, pre-concentration combined with QCLAS has been presented as a technique to resolve subtle changes in ambient N2O isotopic composition. From the end of May until the beginning of August 2016, we investigated N2O emissions from an intensively managed grassland at the study site Fendt in southern Germany. In total, 612 measurements of ambient N2O were taken by combining pre-concentration with QCLAS analyses, yielding δ15Nα, δ15Nβ, δ18O, and N2O concentration with a temporal resolution of approximately 1 h and precisions of 0.46 ‰, 0.36 ‰, 0.59 ‰, and 1.24 ppb, respectively. Soil δ15N-NO3- values and concentrations of NO3- and NH4+ were measured to further constrain possible N2O-emitting source processes. Furthermore, the concentration footprint area of measured N2O was determined with a Lagrangian particle dispersion model (FLEXPART-COSMO) using local wind and turbulence observations. These simulations indicated that night-time concentration observations were largely sensitive to local fluxes. While bacterial denitrification and nitrifier denitrification were identified as the primary N2O-emitting processes, N2O reduction to N2 largely dictated the isotopic composition of measured N2O. Fungal denitrification and nitrification-derived N2O accounted for 34 %–42 % of total N2O emissions and had a clear effect on the measured isotopic source signatures. This study presents the suitability of on-site N2O isotopocule analysis for disentangling source and sink processes in situ and found that at the Fendt site bacterial denitrification or nitrifier denitrification is the major source for N2O, while N2O reduction acted as a major sink for soil-produced N2O.

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    Authors: Erkan Ibraim; Erkan Ibraim; Longfei Yu; Sarah Eggleston; +12 Authors

    Abstract. Nitrous oxide (N2O) is the primary atmospheric constituent involved in stratospheric ozone depletion and contributes strongly to changes in the climate system through a positive radiative forcing mechanism. The atmospheric abundance of N2O has increased from 270 ppb (parts per billion, 10−9 mole mole−1) during the pre-industrial era to approx. 330 ppb in 2018. Even though it is well known that microbial processes in agricultural and natural soils are the major N2O source, the contribution of specific soil processes is still uncertain. The relative abundance of N2O isotopocules (14N14N16N, 14N15N16O, 15N14N16O, and 14N14N18O) carries process-specific information and thus can be used to trace production and consumption pathways. While isotope ratio mass spectroscopy (IRMS) was traditionally used for high-precision measurement of the isotopic composition of N2O, quantum cascade laser absorption spectroscopy (QCLAS) has been put forward as a complementary technique with the potential for on-site analysis. In recent years, pre-concentration combined with QCLAS has been presented as a technique to resolve subtle changes in ambient N2O isotopic composition. From the end of May until the beginning of August 2016, we investigated N2O emissions from an intensively managed grassland at the study site Fendt in southern Germany. In total, 612 measurements of ambient N2O were taken by combining pre-concentration with QCLAS analyses, yielding δ15Nα, δ15Nβ, δ18O, and N2O concentration with a temporal resolution of approximately 1 h and precisions of 0.46 ‰, 0.36 ‰, 0.59 ‰, and 1.24 ppb, respectively. Soil δ15N-NO3- values and concentrations of NO3- and NH4+ were measured to further constrain possible N2O-emitting source processes. Furthermore, the concentration footprint area of measured N2O was determined with a Lagrangian particle dispersion model (FLEXPART-COSMO) using local wind and turbulence observations. These simulations indicated that night-time concentration observations were largely sensitive to local fluxes. While bacterial denitrification and nitrifier denitrification were identified as the primary N2O-emitting processes, N2O reduction to N2 largely dictated the isotopic composition of measured N2O. Fungal denitrification and nitrification-derived N2O accounted for 34 %–42 % of total N2O emissions and had a clear effect on the measured isotopic source signatures. This study presents the suitability of on-site N2O isotopocule analysis for disentangling source and sink processes in situ and found that at the Fendt site bacterial denitrification or nitrifier denitrification is the major source for N2O, while N2O reduction acted as a major sink for soil-produced N2O.

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    https://doi.org/10.5194/bg-201...
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    Authors: Ioannis Katharopoulos; Dominik Brunner; Lukas Emmenegger; Markus Leuenberger; +1 Authors

    AbstractLagrangian particle dispersion models (LPDMs) are frequently used for regional-scale inversions of greenhouse gas emissions. However, the turbulence parameterizations used in these models were developed for coarse resolution grids, hence, when moving to the kilometre-scale the validity of these descriptions should be questioned. Here, we analyze the influence of the turbulence parameterization employed in the LPDM FLEXPART-COSMO model. Comparisons of the turbulence kinetic energy between the turbulence schemes of FLEXPART-COSMO and the underlying Eulerian model COSMO suggest that the dispersion in FLEXPART-COSMO suffers from a double-counting of turbulent elements when run at a high resolution of $$1 \times 1 \,\hbox {km}^2$$ 1 × 1 km 2 . Such turbulent elements are represented in both COSMO, by the resolved grid-scale winds, and FLEXPART, by its stochastic parameterizations. Therefore, we developed a new parametrization for the variations of the winds and the Lagrangian time scales in FLEXPART in order to harmonize the amount of turbulence present in both models. In a case study for a power plant plume, the new scheme results in improved plume representation when compared with in situ flight observations and with a tracer transported in COSMO. Further in-depth validation of the LPDM against methane observations at a tall tower site in Switzerland shows that the model’s ability to predict the observed tracer variability and concentration at different heights above ground is considerably enhanced using the updated turbulence description. The high-resolution simulations result in a more realistic and pronounced diurnal cycle of the tracer concentration peaks and overall improved correlation with observations when compared to previously used coarser resolution simulations (at 7 km $$\times $$ × 7 km). Our results indicate that the stochastic turbulence schemes of LPDMs, developed in the past for coarse resolution models, should be revisited to include a resolution dependency and resolve only the part of the turbulence spectrum that is a subgrid process at each different mesh size. Although our new scheme is specific to COSMO simulations at $$1 \times 1 \,\hbox {km}^2$$ 1 × 1 km 2 resolution, the methodology for deriving the scheme can easily be applied to different resolutions and other regional models.

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    Boundary-Layer Meteorology
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    Authors: Ioannis Katharopoulos; Dominik Brunner; Lukas Emmenegger; Markus Leuenberger; +1 Authors

    AbstractLagrangian particle dispersion models (LPDMs) are frequently used for regional-scale inversions of greenhouse gas emissions. However, the turbulence parameterizations used in these models were developed for coarse resolution grids, hence, when moving to the kilometre-scale the validity of these descriptions should be questioned. Here, we analyze the influence of the turbulence parameterization employed in the LPDM FLEXPART-COSMO model. Comparisons of the turbulence kinetic energy between the turbulence schemes of FLEXPART-COSMO and the underlying Eulerian model COSMO suggest that the dispersion in FLEXPART-COSMO suffers from a double-counting of turbulent elements when run at a high resolution of $$1 \times 1 \,\hbox {km}^2$$ 1 × 1 km 2 . Such turbulent elements are represented in both COSMO, by the resolved grid-scale winds, and FLEXPART, by its stochastic parameterizations. Therefore, we developed a new parametrization for the variations of the winds and the Lagrangian time scales in FLEXPART in order to harmonize the amount of turbulence present in both models. In a case study for a power plant plume, the new scheme results in improved plume representation when compared with in situ flight observations and with a tracer transported in COSMO. Further in-depth validation of the LPDM against methane observations at a tall tower site in Switzerland shows that the model’s ability to predict the observed tracer variability and concentration at different heights above ground is considerably enhanced using the updated turbulence description. The high-resolution simulations result in a more realistic and pronounced diurnal cycle of the tracer concentration peaks and overall improved correlation with observations when compared to previously used coarser resolution simulations (at 7 km $$\times $$ × 7 km). Our results indicate that the stochastic turbulence schemes of LPDMs, developed in the past for coarse resolution models, should be revisited to include a resolution dependency and resolve only the part of the turbulence spectrum that is a subgrid process at each different mesh size. Although our new scheme is specific to COSMO simulations at $$1 \times 1 \,\hbox {km}^2$$ 1 × 1 km 2 resolution, the methodology for deriving the scheme can easily be applied to different resolutions and other regional models.

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    Authors: ICOS RI; Bergamaschi, Peter; Colomb, Aurélie; De Mazière, Martine; +91 Authors

    This data package contains high accuracy CO2 dry air mole fractions from 69 ICOS and non-ICOS European observatories at in total 152 observation levels, collected by the ICOS Atmosphere Thematic Centre (ATC) and provided by the station contributors. The package is the 2024 update of the Globalview EU data product (version 10) and is intended for use in carbon cycle inverse modeling, model evaluation, and satellite validation studies. Please report errors and send comments regarding this product to the ObsPack originators. Please read carefully the ObsPack Fair Use statement and cite appropriately. Please review the release notes for the associated Obspack product at www.esrl.noaa.gov/gmd/ccgg/obspack/release_notes.html. Metadata for this product are available at https://commons.datacite.org/doi.org/10.18160/FSS8-53NX. Please visit http://www.gml.noaa.gov/ccgg/obspack/ for more information on Obspack.

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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/ ICOS Carbon Portalarrow_drop_down
      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/
      ICOS Carbon Portal
      Dataset . 2024
      License: CC BY
      Data sources: Datacite
      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/
      ICOS Carbon Portal
      Dataset . 2024
      Data sources: B2FIND
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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: ICOS RI; Bergamaschi, Peter; Colomb, Aurélie; De Mazière, Martine; +91 Authors

    This data package contains high accuracy CO2 dry air mole fractions from 69 ICOS and non-ICOS European observatories at in total 152 observation levels, collected by the ICOS Atmosphere Thematic Centre (ATC) and provided by the station contributors. The package is the 2024 update of the Globalview EU data product (version 10) and is intended for use in carbon cycle inverse modeling, model evaluation, and satellite validation studies. Please report errors and send comments regarding this product to the ObsPack originators. Please read carefully the ObsPack Fair Use statement and cite appropriately. Please review the release notes for the associated Obspack product at www.esrl.noaa.gov/gmd/ccgg/obspack/release_notes.html. Metadata for this product are available at https://commons.datacite.org/doi.org/10.18160/FSS8-53NX. Please visit http://www.gml.noaa.gov/ccgg/obspack/ for more information on Obspack.

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    ICOS Carbon Portal
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
    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/
    ICOS Carbon Portal
    Dataset . 2024
    Data sources: B2FIND
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      ICOS Carbon Portal
      Dataset . 2024
      License: CC BY
      Data sources: Datacite
      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/
      ICOS Carbon Portal
      Dataset . 2024
      Data sources: B2FIND
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5 Research products
  • 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: ICOS RI; Bergamaschi, Peter; Colomb, Aurélie; Emmenegger, Lukas; +50 Authors

    This data package contains high accuracy N2O dry air mole fractions from 32 ICOS and non-ICOS European observatories at in total 73 observation levels, collected by the ICOS Atmosphere Thematic Centre (ATC) and provided by the station contributors. The package is the first release of the N2O European Obspack data product (version 10.0), and is intended for use in carbon cycle inverse modeling, model evaluation, and satellite validation studies. Please report errors and send comments regarding this product to the ObsPack originators. Please read carefully the ObsPack Fair Use statement and cite appropriately. Metadata for this product are available at https://commons.datacite.org/doi.org/10.18160/6ZXD-BAAZ. Please visit http://www.gml.noaa.gov/ccgg/obspack/ for more information.

    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/ ICOS Carbon Portalarrow_drop_down
    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/
    ICOS Carbon Portal
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
    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/
    ICOS Carbon Portal
    Dataset . 2024
    Data sources: B2FIND
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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/ ICOS Carbon Portalarrow_drop_down
      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/
      ICOS Carbon Portal
      Dataset . 2024
      License: CC BY
      Data sources: Datacite
      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/
      ICOS Carbon Portal
      Dataset . 2024
      Data sources: B2FIND
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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: ICOS RI; Bergamaschi, Peter; Colomb, Aurélie; Emmenegger, Lukas; +50 Authors

    This data package contains high accuracy N2O dry air mole fractions from 32 ICOS and non-ICOS European observatories at in total 73 observation levels, collected by the ICOS Atmosphere Thematic Centre (ATC) and provided by the station contributors. The package is the first release of the N2O European Obspack data product (version 10.0), and is intended for use in carbon cycle inverse modeling, model evaluation, and satellite validation studies. Please report errors and send comments regarding this product to the ObsPack originators. Please read carefully the ObsPack Fair Use statement and cite appropriately. Metadata for this product are available at https://commons.datacite.org/doi.org/10.18160/6ZXD-BAAZ. Please visit http://www.gml.noaa.gov/ccgg/obspack/ for more information.

    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/ ICOS Carbon Portalarrow_drop_down
    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/
    ICOS Carbon Portal
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
    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/
    ICOS Carbon Portal
    Dataset . 2024
    Data sources: B2FIND
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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/ ICOS Carbon Portalarrow_drop_down
      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/
      ICOS Carbon Portal
      Dataset . 2024
      License: CC BY
      Data sources: Datacite
      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/
      ICOS Carbon Portal
      Dataset . 2024
      Data sources: B2FIND
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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: Brian Oney; Brian Oney; Markus Leuenberger; Nicolas Gruber; +6 Authors

    Abstract. We describe a new rural network of four densely placed (< 100 km apart), continuous atmospheric carbon (CO2, CH4, and CO) measurement sites in north-central Switzerland and analyze their suitability for regional-scale (~ 100 to 500 km) carbon flux studies. We characterize each site by analyzing surrounding land cover, observed local meteorology, and sensitivity to surface fluxes, as simulated with the Lagrangian particle dispersion model FLEXPART-COSMO. The Beromünster measurements are made on a tall tower (212 m) located on a gentle hill. At Beromünster, regional CO2 signals (measurement minus background) vary diurnally from −4 to +4 ppmv on average, and are simulated to come from nearly the entire Swiss Plateau, where 50% of surface influence is simulated to be within 130 to 260 km distance. The Früebüel site measurements are made 4 m above ground on the flank of a gently sloping mountain. Nearby (< 50 km) pasture and forest fluxes exert the most simulated surface influence, except during convective summertime days when the site is mainly influenced by the eastern Swiss Plateau, which results in summertime regional CO2 signals varying diurnally from −5 to +12 ppmv and elevated summer daytime CH4 signals (+30 ppbv above other sites). The Gimmiz site measurements are made on a small tower (32 m) in flat terrain. Here, strong summertime regional signals (−5 to +60 ppmv CO2) stem from large, nearby (< 50 km) crop and anthropogenic fluxes of the Seeland region, except during warm or windy days when simulated surface influence is of regional scale (< 250 km). The Lägern-Hochwacht measurements are made on a small tower (32 m) on top of the steep Lägern crest, where simulated surface influence is typically of regional scale (130 to 300 km) causing summertime regional signals to vary from −5 to +8 ppmv CO2. Here, considerable anthropogenic influence from the nearby industrialized region near Zurich cause the average wintertime regional CO2 signals to be 5 ppmv above the regional signals simultaneously measured at Früebüel site. We find that the suitability of the datasets from our current observation network for regional carbon budgeting studies largely depends on the ability of the high-resolution (2 km) atmospheric transport model to correctly capture the temporal dynamics of the stratification of the lower atmosphere at the different sites. The current version of the atmospheric transport model captures these dynamics well, but it clearly reaches its limits at the sites in steep topography, and at the sites that generally remain in the surface layer. Trace gas transport and inverse modeling studies will be necessary to determine the impact of these limitations on our ability to derive reliable regional-scale carbon flux estimates in the complex Swiss landscape.

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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/
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    https://doi.org/10.5194/acpd-1...
    Article . 2015 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
    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://www.atmos-chem-phys.ne...
    Article
    License: CC BY
    Data sources: UnpayWall
    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/
    Atmospheric Chemistry and Physics (ACP)
    Article . 2015 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
    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/
    Atmospheric Chemistry and Physics (ACP)
    Article
    License: CC BY
    Data sources: UnpayWall
    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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    Atmospheric Chemistry and Physics (ACP)
    Other literature type . 2018
    Data sources: Copernicus
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    Research Collection
    Article . 2015
    License: CC BY
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    Research Collection
    Research . 2015
    License: CC BY
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    http://www.atmos-chem-phys.net...
    Article . 2015 . Peer-reviewed
    Data sources: SNSF P3 Database
    https://dx.doi.org/10.60692/gp...
    Other literature type . 2015
    Data sources: Datacite
    Research Collection
    Article . 2015
    License: CC BY
    Data sources: Datacite
    https://dx.doi.org/10.60692/hc...
    Other literature type . 2015
    Data sources: Datacite
    Research Collection
    Research . 2015
    License: CC BY
    Data sources: Datacite
    Copernicus Publications
    Other literature type . 2018
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    citations34
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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/ Bern Open Repository...arrow_drop_down
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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/
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      https://doi.org/10.5194/acpd-1...
      Article . 2015 . Peer-reviewed
      License: CC BY
      Data sources: Crossref
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      https://www.atmos-chem-phys.ne...
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      Data sources: UnpayWall
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      Atmospheric Chemistry and Physics (ACP)
      Article . 2015 . Peer-reviewed
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      http://www.atmos-chem-phys.net...
      Article . 2015 . Peer-reviewed
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    Authors: Brian Oney; Brian Oney; Markus Leuenberger; Nicolas Gruber; +6 Authors

    Abstract. We describe a new rural network of four densely placed (< 100 km apart), continuous atmospheric carbon (CO2, CH4, and CO) measurement sites in north-central Switzerland and analyze their suitability for regional-scale (~ 100 to 500 km) carbon flux studies. We characterize each site by analyzing surrounding land cover, observed local meteorology, and sensitivity to surface fluxes, as simulated with the Lagrangian particle dispersion model FLEXPART-COSMO. The Beromünster measurements are made on a tall tower (212 m) located on a gentle hill. At Beromünster, regional CO2 signals (measurement minus background) vary diurnally from −4 to +4 ppmv on average, and are simulated to come from nearly the entire Swiss Plateau, where 50% of surface influence is simulated to be within 130 to 260 km distance. The Früebüel site measurements are made 4 m above ground on the flank of a gently sloping mountain. Nearby (< 50 km) pasture and forest fluxes exert the most simulated surface influence, except during convective summertime days when the site is mainly influenced by the eastern Swiss Plateau, which results in summertime regional CO2 signals varying diurnally from −5 to +12 ppmv and elevated summer daytime CH4 signals (+30 ppbv above other sites). The Gimmiz site measurements are made on a small tower (32 m) in flat terrain. Here, strong summertime regional signals (−5 to +60 ppmv CO2) stem from large, nearby (< 50 km) crop and anthropogenic fluxes of the Seeland region, except during warm or windy days when simulated surface influence is of regional scale (< 250 km). The Lägern-Hochwacht measurements are made on a small tower (32 m) on top of the steep Lägern crest, where simulated surface influence is typically of regional scale (130 to 300 km) causing summertime regional signals to vary from −5 to +8 ppmv CO2. Here, considerable anthropogenic influence from the nearby industrialized region near Zurich cause the average wintertime regional CO2 signals to be 5 ppmv above the regional signals simultaneously measured at Früebüel site. We find that the suitability of the datasets from our current observation network for regional carbon budgeting studies largely depends on the ability of the high-resolution (2 km) atmospheric transport model to correctly capture the temporal dynamics of the stratification of the lower atmosphere at the different sites. The current version of the atmospheric transport model captures these dynamics well, but it clearly reaches its limits at the sites in steep topography, and at the sites that generally remain in the surface layer. Trace gas transport and inverse modeling studies will be necessary to determine the impact of these limitations on our ability to derive reliable regional-scale carbon flux estimates in the complex Swiss landscape.

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    https://doi.org/10.5194/acpd-1...
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    Atmospheric Chemistry and Physics (ACP)
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    http://www.atmos-chem-phys.net...
    Article . 2015 . Peer-reviewed
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      https://doi.org/10.5194/acpd-1...
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      http://www.atmos-chem-phys.net...
      Article . 2015 . Peer-reviewed
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    Authors: Erkan Ibraim; Erkan Ibraim; Longfei Yu; Sarah Eggleston; +12 Authors

    Abstract. Nitrous oxide (N2O) is the primary atmospheric constituent involved in stratospheric ozone depletion and contributes strongly to changes in the climate system through a positive radiative forcing mechanism. The atmospheric abundance of N2O has increased from 270 ppb (parts per billion, 10−9 mole mole−1) during the pre-industrial era to approx. 330 ppb in 2018. Even though it is well known that microbial processes in agricultural and natural soils are the major N2O source, the contribution of specific soil processes is still uncertain. The relative abundance of N2O isotopocules (14N14N16N, 14N15N16O, 15N14N16O, and 14N14N18O) carries process-specific information and thus can be used to trace production and consumption pathways. While isotope ratio mass spectroscopy (IRMS) was traditionally used for high-precision measurement of the isotopic composition of N2O, quantum cascade laser absorption spectroscopy (QCLAS) has been put forward as a complementary technique with the potential for on-site analysis. In recent years, pre-concentration combined with QCLAS has been presented as a technique to resolve subtle changes in ambient N2O isotopic composition. From the end of May until the beginning of August 2016, we investigated N2O emissions from an intensively managed grassland at the study site Fendt in southern Germany. In total, 612 measurements of ambient N2O were taken by combining pre-concentration with QCLAS analyses, yielding δ15Nα, δ15Nβ, δ18O, and N2O concentration with a temporal resolution of approximately 1 h and precisions of 0.46 ‰, 0.36 ‰, 0.59 ‰, and 1.24 ppb, respectively. Soil δ15N-NO3- values and concentrations of NO3- and NH4+ were measured to further constrain possible N2O-emitting source processes. Furthermore, the concentration footprint area of measured N2O was determined with a Lagrangian particle dispersion model (FLEXPART-COSMO) using local wind and turbulence observations. These simulations indicated that night-time concentration observations were largely sensitive to local fluxes. While bacterial denitrification and nitrifier denitrification were identified as the primary N2O-emitting processes, N2O reduction to N2 largely dictated the isotopic composition of measured N2O. Fungal denitrification and nitrification-derived N2O accounted for 34 %–42 % of total N2O emissions and had a clear effect on the measured isotopic source signatures. This study presents the suitability of on-site N2O isotopocule analysis for disentangling source and sink processes in situ and found that at the Fendt site bacterial denitrification or nitrifier denitrification is the major source for N2O, while N2O reduction acted as a major sink for soil-produced N2O.

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    Biogeosciences (BG)
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    https://doi.org/10.5194/bg-201...
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    Authors: Erkan Ibraim; Erkan Ibraim; Longfei Yu; Sarah Eggleston; +12 Authors

    Abstract. Nitrous oxide (N2O) is the primary atmospheric constituent involved in stratospheric ozone depletion and contributes strongly to changes in the climate system through a positive radiative forcing mechanism. The atmospheric abundance of N2O has increased from 270 ppb (parts per billion, 10−9 mole mole−1) during the pre-industrial era to approx. 330 ppb in 2018. Even though it is well known that microbial processes in agricultural and natural soils are the major N2O source, the contribution of specific soil processes is still uncertain. The relative abundance of N2O isotopocules (14N14N16N, 14N15N16O, 15N14N16O, and 14N14N18O) carries process-specific information and thus can be used to trace production and consumption pathways. While isotope ratio mass spectroscopy (IRMS) was traditionally used for high-precision measurement of the isotopic composition of N2O, quantum cascade laser absorption spectroscopy (QCLAS) has been put forward as a complementary technique with the potential for on-site analysis. In recent years, pre-concentration combined with QCLAS has been presented as a technique to resolve subtle changes in ambient N2O isotopic composition. From the end of May until the beginning of August 2016, we investigated N2O emissions from an intensively managed grassland at the study site Fendt in southern Germany. In total, 612 measurements of ambient N2O were taken by combining pre-concentration with QCLAS analyses, yielding δ15Nα, δ15Nβ, δ18O, and N2O concentration with a temporal resolution of approximately 1 h and precisions of 0.46 ‰, 0.36 ‰, 0.59 ‰, and 1.24 ppb, respectively. Soil δ15N-NO3- values and concentrations of NO3- and NH4+ were measured to further constrain possible N2O-emitting source processes. Furthermore, the concentration footprint area of measured N2O was determined with a Lagrangian particle dispersion model (FLEXPART-COSMO) using local wind and turbulence observations. These simulations indicated that night-time concentration observations were largely sensitive to local fluxes. While bacterial denitrification and nitrifier denitrification were identified as the primary N2O-emitting processes, N2O reduction to N2 largely dictated the isotopic composition of measured N2O. Fungal denitrification and nitrification-derived N2O accounted for 34 %–42 % of total N2O emissions and had a clear effect on the measured isotopic source signatures. This study presents the suitability of on-site N2O isotopocule analysis for disentangling source and sink processes in situ and found that at the Fendt site bacterial denitrification or nitrifier denitrification is the major source for N2O, while N2O reduction acted as a major sink for soil-produced N2O.

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    Authors: Ioannis Katharopoulos; Dominik Brunner; Lukas Emmenegger; Markus Leuenberger; +1 Authors

    AbstractLagrangian particle dispersion models (LPDMs) are frequently used for regional-scale inversions of greenhouse gas emissions. However, the turbulence parameterizations used in these models were developed for coarse resolution grids, hence, when moving to the kilometre-scale the validity of these descriptions should be questioned. Here, we analyze the influence of the turbulence parameterization employed in the LPDM FLEXPART-COSMO model. Comparisons of the turbulence kinetic energy between the turbulence schemes of FLEXPART-COSMO and the underlying Eulerian model COSMO suggest that the dispersion in FLEXPART-COSMO suffers from a double-counting of turbulent elements when run at a high resolution of $$1 \times 1 \,\hbox {km}^2$$ 1 × 1 km 2 . Such turbulent elements are represented in both COSMO, by the resolved grid-scale winds, and FLEXPART, by its stochastic parameterizations. Therefore, we developed a new parametrization for the variations of the winds and the Lagrangian time scales in FLEXPART in order to harmonize the amount of turbulence present in both models. In a case study for a power plant plume, the new scheme results in improved plume representation when compared with in situ flight observations and with a tracer transported in COSMO. Further in-depth validation of the LPDM against methane observations at a tall tower site in Switzerland shows that the model’s ability to predict the observed tracer variability and concentration at different heights above ground is considerably enhanced using the updated turbulence description. The high-resolution simulations result in a more realistic and pronounced diurnal cycle of the tracer concentration peaks and overall improved correlation with observations when compared to previously used coarser resolution simulations (at 7 km $$\times $$ × 7 km). Our results indicate that the stochastic turbulence schemes of LPDMs, developed in the past for coarse resolution models, should be revisited to include a resolution dependency and resolve only the part of the turbulence spectrum that is a subgrid process at each different mesh size. Although our new scheme is specific to COSMO simulations at $$1 \times 1 \,\hbox {km}^2$$ 1 × 1 km 2 resolution, the methodology for deriving the scheme can easily be applied to different resolutions and other regional models.

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    Authors: Ioannis Katharopoulos; Dominik Brunner; Lukas Emmenegger; Markus Leuenberger; +1 Authors

    AbstractLagrangian particle dispersion models (LPDMs) are frequently used for regional-scale inversions of greenhouse gas emissions. However, the turbulence parameterizations used in these models were developed for coarse resolution grids, hence, when moving to the kilometre-scale the validity of these descriptions should be questioned. Here, we analyze the influence of the turbulence parameterization employed in the LPDM FLEXPART-COSMO model. Comparisons of the turbulence kinetic energy between the turbulence schemes of FLEXPART-COSMO and the underlying Eulerian model COSMO suggest that the dispersion in FLEXPART-COSMO suffers from a double-counting of turbulent elements when run at a high resolution of $$1 \times 1 \,\hbox {km}^2$$ 1 × 1 km 2 . Such turbulent elements are represented in both COSMO, by the resolved grid-scale winds, and FLEXPART, by its stochastic parameterizations. Therefore, we developed a new parametrization for the variations of the winds and the Lagrangian time scales in FLEXPART in order to harmonize the amount of turbulence present in both models. In a case study for a power plant plume, the new scheme results in improved plume representation when compared with in situ flight observations and with a tracer transported in COSMO. Further in-depth validation of the LPDM against methane observations at a tall tower site in Switzerland shows that the model’s ability to predict the observed tracer variability and concentration at different heights above ground is considerably enhanced using the updated turbulence description. The high-resolution simulations result in a more realistic and pronounced diurnal cycle of the tracer concentration peaks and overall improved correlation with observations when compared to previously used coarser resolution simulations (at 7 km $$\times $$ × 7 km). Our results indicate that the stochastic turbulence schemes of LPDMs, developed in the past for coarse resolution models, should be revisited to include a resolution dependency and resolve only the part of the turbulence spectrum that is a subgrid process at each different mesh size. Although our new scheme is specific to COSMO simulations at $$1 \times 1 \,\hbox {km}^2$$ 1 × 1 km 2 resolution, the methodology for deriving the scheme can easily be applied to different resolutions and other regional models.

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    Boundary-Layer Meteorology
    Article . 2022 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
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    Research Collection
    Article . 2022
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    Article . 2022
    Data sources: Datacite
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    Authors: ICOS RI; Bergamaschi, Peter; Colomb, Aurélie; De Mazière, Martine; +91 Authors

    This data package contains high accuracy CO2 dry air mole fractions from 69 ICOS and non-ICOS European observatories at in total 152 observation levels, collected by the ICOS Atmosphere Thematic Centre (ATC) and provided by the station contributors. The package is the 2024 update of the Globalview EU data product (version 10) and is intended for use in carbon cycle inverse modeling, model evaluation, and satellite validation studies. Please report errors and send comments regarding this product to the ObsPack originators. Please read carefully the ObsPack Fair Use statement and cite appropriately. Please review the release notes for the associated Obspack product at www.esrl.noaa.gov/gmd/ccgg/obspack/release_notes.html. Metadata for this product are available at https://commons.datacite.org/doi.org/10.18160/FSS8-53NX. Please visit http://www.gml.noaa.gov/ccgg/obspack/ for more information on Obspack.

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    Authors: ICOS RI; Bergamaschi, Peter; Colomb, Aurélie; De Mazière, Martine; +91 Authors

    This data package contains high accuracy CO2 dry air mole fractions from 69 ICOS and non-ICOS European observatories at in total 152 observation levels, collected by the ICOS Atmosphere Thematic Centre (ATC) and provided by the station contributors. The package is the 2024 update of the Globalview EU data product (version 10) and is intended for use in carbon cycle inverse modeling, model evaluation, and satellite validation studies. Please report errors and send comments regarding this product to the ObsPack originators. Please read carefully the ObsPack Fair Use statement and cite appropriately. Please review the release notes for the associated Obspack product at www.esrl.noaa.gov/gmd/ccgg/obspack/release_notes.html. Metadata for this product are available at https://commons.datacite.org/doi.org/10.18160/FSS8-53NX. Please visit http://www.gml.noaa.gov/ccgg/obspack/ for more information on Obspack.

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