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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/

    This is a dataset of output from version 4 of the Reading Intermediate Global Circulation Model (IGCM4) that was used in the article: McKenna, C. M., Bracegirdle, T. J., Shuckburgh, E. F., Haynes, P. H., & Joshi, M. M. (2018). Arctic sea ice loss in different regions leads to contrasting Northern Hemisphere impacts. Geophysical Research Letters, 45, 945-954. https://doi.org/10.1002/2017GL076433 Files required to setup the IGCM4 simulations are given in the directory 'IGCM4_setup'. All other directories contain netcdf files of timeseries of various monthly mean fields for each IGCM4 simulation (see paper for details on these simulations). The available variables are: ua: zonal winds zg: geopotential height ts: surface temperature hfls, hfss, rlds, rlus: surface heatfluxes Flat, Fz, divF: Eliassen-Palm flux vectors and their divergence (only for months November-February) The ua and zg variables are given for different pressure levels indicated in the filenames (e.g., ua500 is ua at 500 hPa). ua is additionally given in terms of the zonal mean with latitude and pressure. zg is additionally given in terms of longitude and pressure, averaged over latitudes between 60N-80N. All files follow CF conventions in terms of metadata, variable names, etc. Note that the CTL, ATL, PAC, and ATLandPAC simulations were all run continuously in time (i.e., every year starts from the end of the previous year). The 0.5ATL and 0.5PAC simulations, however, were run for 300 years in three separate 100-year chunks (i.e., the initial conditions used to start each 100-year chunk were different). The three 100-year chunks have been appended together in the netcdf files. 

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    ZENODO
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2022
    License: CC BY
    Data sources: ZENODO
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      ZENODO
      Dataset . 2022
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2022
      License: CC BY
      Data sources: ZENODO
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    Authors: Romero-Alvarez, Johana; Lupaşcu, Aurelia; Lowe, Douglas; Badia, Alba; +4 Authors

    Tropospheric ozone (O3) concentrations depend on a combination of hemispheric, regional, and local-scale processes. Estimates of how much O3 is produced locally vs. transported from further afield are essential in air quality management and regulatory policies. Here, a tagged-ozone mechanism within the Weather Research and Forecasting model coupled with chemistry (WRF-Chem) is used to quantify the contributions to surface O3 in the UK from anthropogenic nitrogen oxide (NOx) emissions from inside and outside the UK during May–August 2015. The contribution of the different source regions to three regulatory O3 metrics is also examined. It is shown that model simulations predict the concentration and spatial distribution of surface O3 with a domain-wide mean bias of −3.7 ppbv. Anthropogenic NOx emissions from the UK and Europe account for 13 % and 16 %, respectively, of the monthly mean surface O3 in the UK, as the majority (71 %) of O3 originates from the hemispheric background. Hemispheric O3 contributes the most to concentrations in the north and the west of the UK with peaks in May, whereas European and UK contributions are most significant in the east, south-east, and London, i.e. the UK's most populated areas, intensifying towards June and July. Moreover, O3 from European sources is generally transported to the UK rather than produced in situ. It is demonstrated that more stringent emission controls over continental Europe, particularly in western Europe, would be necessary to improve the health-related metric MDA8 O3 above 50 and 60 ppbv. Emission controls over larger areas, such as the Northern Hemisphere, are instead required to lessen the impacts on ecosystems as quantified by the AOT40 metric.

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    Authors: Lehmann, Moritz K; Gurlin, Daniela; Pahlevan, Nima; Alikas, Krista; +73 Authors

    Projects include:* Estonian Ministry of Education and Research* Estonian Research Council* European Commission, Award: FP7, H2020, FP7-ENV-2007-1-226224* Federal Ministry for Economic Affairs and Energy, Germany, Award: LAKESAT 50EE1340* Federal Ministry of Education and Research Germany, Award: 03G0218A* Helmholtz Infrastructure Initiative, Award: FRAM* NASA ROSES, Award: 80HQTR19C0015, 80NSSC 21K0499, 80NSSC22K1389* New Zealand Ministry for Business, Innovation & Employment, Award: UOWX1503, UOWX1802, KENTR1601* USGS Landsat Science Team Award, Award: 140G0118C0011* Vietnam National Foundation for Science and Technology Development (NAFOSTED), grant number 105.08-2019.329 The GLObal Reflectance community dataset for Imaging and optical sensing of Aquatic environments (GLORIA) includes 7,572 curated hyperspectral remote sensing reflectance measurements at 1 nm intervals within the 350 to 900 nm wavelength range. In addition, at least one co-located water quality measurement, chlorophyll a, total suspended solids, absorption by dissolved substances, and Secchi depth, is provided. The data were contributed by researchers affiliated with 53 institutions worldwide and come from 450 different water bodies, making GLORIA the de-facto state of knowledge of in situ coastal and inland aquatic optical diversity.

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    PANGAEA
    Dataset . 2022
    Data sources: B2FIND
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    Authors: Bracher, Astrid; Wiegmann, Sonja;

    We present a data set on remote sensing reflectance (RRS) at 1nm resolution from 350 to 800nm obtained from measurements in the North Sea and Sogne Fjord from 30 April to 7 May 2016. For the measurements we used radiometric hyperspectral (3.3 nm sampling, 10 nm FWHM) underwater profile measurements down to the 0.1 % light level using RAMSES (TriOS GmbH, Germany) sensors which measured depth resolved the upwelling radiance and downwelling irradiance, both corrected by incident sunlight fluctuations with a second RAMSES sensor measuring the above water downwelling irradiance. The later sensor data were also used to finally calculate RRS. We followed the protocol by Mueller et al. (2003) further modified by Matsuoka et al. (2007) and Stramski et al. (2008), as described for our instrument set-up in Taylor et al. (2011). Our method is further described and assessed for its uncertainty in Tilstone et al. (2020). The same campaign was sampled for optical constituents hyperspectral absorption data in Bracher et al. (2021a-d) and for phytoplankton pigments in Bracher and Wiegmann (2019).

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    PANGAEA
    Dataset . 2022
    Data sources: B2FIND
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      PANGAEA
      Dataset . 2022
      Data sources: B2FIND
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    Authors: Börner, Nicole; Jochum, Klaus Peter; Stuhr, Marleen; Abstein, Michelle; +5 Authors

    High-resolution multi-proxy records from two lakes on the southern Tibetan Plateau, Nam Co and Tangra Yumco, are used to infer long-term variations in the Asian monsoon system. We examine the moisture evolution during the Late Glacial Maximum and Holocene using the trace element and stable isotope composition of ostracod shells. The sediment records covering the past 24 cal. ka BP and 18 cal. ka BP, respectively, demonstrate the suitability of ostracod shell chemistry as paleoenvironmental proxy. We analysed (i) Mg/Ca, Ba/Ca and Sr/Ca ratios as salinity proxies, (ii) Fe/Ca, Mn/Ca and U/Ca ratios representing redox conditions and microbial activity, and (iii) rare earth elements (REEs) reflecting weathering and changes in provenance.

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    PANGAEA
    Dataset . 2022
    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/ PANGAEA - Data Publi...arrow_drop_down
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      PANGAEA
      Dataset . 2022
      Data sources: B2FIND
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    Authors: González-Dávila, Melchor; Droste, Elise Sayana; Santana-Casiano, Juana Magdalena; Schuller, Daniel; +3 Authors

    A fraction of oceanographic profiles (from CTD casts), the temperature, salinity, oxygen, and nutrient data have already previously been published (https://doi.org/10.1594/PANGAEA.910673). We have included these to maintain consistency with the rest of the profiles in the dataset (for which these variables have not been published yet). In addition to the fact that exactly these data were used in the calculations for the marine carbonate system in Droste et al. (2022), it is also easier for users to work with this dataset in the future. The DOI of the already published data is included in the comment column of the dataset itself. Details on sample collection, analysis methods, and salinity-normalisation of DIC and TA can be found in Droste et al. (2022). Discrete seawater samples in a Weddell Sea coastal polynya along the Ekström Ice Shelf were collected from two sets of repeat CTD casts, capturing tidal variability in the water column. One set was collected during RV POLARSTERN expedition PS89, between 8 and 11 January 2015. The second set was collected during RV POLARSTERN expedition PS117, between 11 and 12 January 2019. Dissolved inorganic carbon (DIC) and total alkalinity (TA) were measured using coulometric titration and potentiometric titration, respectively, on a VINDTA 3C system. DIC and TA have been normalised to salinity: nDIC and nTA. Nutrients were measured with UV-Vis spectrophotometry and a continuous gas-segmented flow auto-analyser.

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    PANGAEA
    Dataset . 2022
    Data sources: B2FIND
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      PANGAEA
      Dataset . 2022
      Data sources: B2FIND
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    Authors: Bracher, Astrid; Cheah, Wee;

    We present a data set on remote sensing reflectance (RRS) at 1nm resolution from 350 to 800nm obtained from measurements in the coastal and open ocean areas of the South China Sea and Sulu Sea from 18 to 27 November 2011. For the measurements we used radiometric hyperspectral (3.3 nm sampling, 10 nm FWHM) underwater profile measurements down to the 0.1 % light level using RAMSES (TriOS GmbH, Germany) sensors which measured depth resolved the upwelling radiance and downwelling irradiance, both corrected by incident sunlight fluctuations with a second RAMSES sensor measuring the above water downwelling irradiance. The later sensor data were also used to finally calculate RRS. We followed the protocol by Mueller et al. (2003) further modified by Matsuoka et al. (2007) and Stramski et al. (2008), as described for our instrument set-up in Taylor et al. (2011). Our method is further described and assessed for its uncertainty in Tilstone et al. (2020). The campaign is described in detail in Cheah et al. (2013) and was also optical constituents hyperspectral absorption data (Bracher et al. 2021a, b) and phytoplankton pigments (Bracher 2014) were measured. We are indebted to Maria Altenburg-Soppa, Sonja Wiegmann and Joseph Palermo for their assistance in the sampling on RV Sonne and acknowledge the help of the chief scientist Birgit Quack, the crew and captain of the RV Sonne during SHIVA-Sonne in performing our measurements.

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    PANGAEA
    Dataset . 2022
    Data sources: B2FIND
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      PANGAEA
      Dataset . 2022
      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: van der Lubbe, Jeroen; Hall, Ian R; Barker, Stephen; Starr, Aidan; +5 Authors

    Abstract: Records of sortable silt (SS) percentages and means from the spliced record of IODP Site U1476 at the Davie Ridge, Mozambique Channel. The age model of this spliced record is based on benthic oxygen isotopes and biostratigraphy. Category: geoscientificInformation Source: Not Available Supplemental Information: Not Availble Coverage: EVENT LABEL: 361-U1476A * LATITUDE: -15.821000 * LONGITUDE: 41.769000 * DATE/TIME: 2016-03-08T07:50:00 * ELEVATION: -2176.8 m * Penetration: 224.2 m * Recovery: 232.9 m * CAMPAIGN: Exp361 * BASIS: Joides Resolution * METHOD/DEVICE: Drilling/drill rig EVENT LABEL: 361-U1476C * LATITUDE: -15.821000 * LONGITUDE: 41.769000 * DATE/TIME: 2016-03-09T20:45:00 * ELEVATION: -2176.6 m * Penetration: 5.7 m * Recovery: 5.72 m * CAMPAIGN: Exp361 * BASIS: Joides Resolution * METHOD/DEVICE: Drilling/drill rig EVENT LABEL: 361-U1476D * LATITUDE: -15.821000 * LONGITUDE: 41.769000 * DATE/TIME: 2016-03-09T21:30:00 * ELEVATION: -2176.6 m * Penetration: 229 m * Recovery: 237.02 m * CAMPAIGN: Exp361 * BASIS: Joides Resolution * METHOD/DEVICE: Drilling/drill rig EVENT LABEL: 361-U1476E * LATITUDE: -15.821000 * LONGITUDE: 41.769000 * DATE/TIME: 2016-03-10T19:50:00 * ELEVATION: -2176.3 m * Penetration: 234.8 m * Recovery: 243.77 m * CAMPAIGN: Exp361 * BASIS: Joides Resolution * METHOD/DEVICE: Drilling/drill rig

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    PANGAEA
    Dataset . 2021
    Data sources: B2FIND
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      PANGAEA
      Dataset . 2021
      Data sources: B2FIND
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    Authors: Vasudeva, Ramakrishnan; Sutter, Andreas; Sales, Kris; Dickinson, Matthew E.; +2 Authors

    Rising and more variable global temperatures pose a challenge for biodiversity, with reproduction and fertility being especially sensitive to heat. Here, we assessed the potential for thermal adaptation in sperm and egg function using Tribolium flour beetles, a warm-temperate-tropical insect model. Following temperature increases through adult development, we found opposing gamete responses, with males producing shorter sperm and females laying larger eggs. Importantly, this gamete phenotypic plasticity was adaptive: thermal translocation experiments showed that both sperm and eggs produced in warmer conditions had superior reproductive performance in warmer environments, and vice versa for cooler production conditions and reproductive environments. In warmer environments, gamete plasticity enabled males to double their reproductive success, and females could increase offspring production by one-third. Our results reveal exciting potential for sensitive but vital traits within reproduction to handle increasing and more variable thermal regimes in the natural environment.

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    DRYAD; ZENODO
    Dataset . 2020
    License: CC 0
    Data sources: Datacite; ZENODO
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      DRYAD; ZENODO
      Dataset . 2020
      License: CC 0
      Data sources: Datacite; ZENODO
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    Authors: Sonne, Jesper; Vizentin-Bugoni, Jeferson; Maruyama, Pietro K.; Araújo, Andréa C.; +25 Authors

    Data consisting of 24 quantitative interaction networks sampled throughout the Americas, in areas mostly or entirely covered with native vegetation (Table ESM2). The networks comprise 106 hummingbird species, 31% of all described hummingbird species in the world according to the IOC World Bird List v.7.3 (ESM3), and 450 plant species belonging to 57 plant families (ESM4, see ESM5a for additional details on sampling). The abundance of plant species was measured as the number of flowers produced per species in each community throughout the entire sampling period. Flowers were counted in plots or transects estimated regularly throughout the sampling period. The abundance of hummingbirds within sites was measured in the field by counting the number of visual and aural detections of individuals across transects (n=12 networks) or point counts (n=4 networks), or the number of individuals captured by mist-netting (n=8 networks; ESM5a). Because the abundance sampling protocols were not standardized among networks, we treated the data as relative abundance, i.e. for all species we calculate their abundance as the proportion of the total number of individuals within a given community. Still, we note that mist nets may be especially efficient for surveying elusive understory species, such as traplining hummingbirds, whereas transects and point counts may be better at surveying species at higher vegetation strata [34]. We recognize that the caveat inherent in using different sampling schemes across networks may influence the outcome of our analyses. However, as we used relative abundances to model interaction frequencies within networks (not between networks), we believe that the different sampling schemes had a minimal influence on our results. The phenology of each plant and hummingbird species in each network was determined as the presence-absence of, respectively, open flowers and individuals at each sampling period (usually months). Flower morphology was characterized by the effective corolla length, measured as the distance from the nectary to the corolla opening. The effective corolla length reflects the minimum length of mouthparts required for pollinators to access the nectar legitimately. Hummingbird bill morphology was measured as the length of the exposed culmen from captured hummingbird individuals (see ESM5b further details on sampling). Interactions between species are influenced by different ecological mechanisms, such as morphological matching, phenological overlap, and species abundances. How these mechanisms explain interaction frequencies across environmental gradients remains poorly understood. Consequently, we also know little about the mechanisms that drive the geographical patterns in network structure, such as complementary specialization and modularity. Here, we use data on morphologies, phenologies and abundances to explain interaction frequencies between hummingbirds and plants at a large geographic scale. For 24 quantitative networks sampled throughout the Americas, we found that the tendency of species to interact with morphologically matching partners contributed to specialized and modular network structures. Morphological matching best explained interaction frequencies in networks found closer to the equator and in areas with low temperature seasonality. When comparing the three ecological mechanisms within networks, we found that both morphological matching and phenological overlap generally outperformed abundances in the explanation of interaction frequencies. Together, these findings provide insights into the ecological mechanisms that underlie geographical patterns in resource specialization. Notably, our results highlight morphological constraints on interactions as a potential explanation for increasing resource specialization towards lower latitudes.

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    DRYAD; ZENODO
    Dataset . 2020
    License: CC 0
    Data sources: Datacite; ZENODO
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      DRYAD; ZENODO
      Dataset . 2020
      License: CC 0
      Data sources: Datacite; ZENODO
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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/

    This is a dataset of output from version 4 of the Reading Intermediate Global Circulation Model (IGCM4) that was used in the article: McKenna, C. M., Bracegirdle, T. J., Shuckburgh, E. F., Haynes, P. H., & Joshi, M. M. (2018). Arctic sea ice loss in different regions leads to contrasting Northern Hemisphere impacts. Geophysical Research Letters, 45, 945-954. https://doi.org/10.1002/2017GL076433 Files required to setup the IGCM4 simulations are given in the directory 'IGCM4_setup'. All other directories contain netcdf files of timeseries of various monthly mean fields for each IGCM4 simulation (see paper for details on these simulations). The available variables are: ua: zonal winds zg: geopotential height ts: surface temperature hfls, hfss, rlds, rlus: surface heatfluxes Flat, Fz, divF: Eliassen-Palm flux vectors and their divergence (only for months November-February) The ua and zg variables are given for different pressure levels indicated in the filenames (e.g., ua500 is ua at 500 hPa). ua is additionally given in terms of the zonal mean with latitude and pressure. zg is additionally given in terms of longitude and pressure, averaged over latitudes between 60N-80N. All files follow CF conventions in terms of metadata, variable names, etc. Note that the CTL, ATL, PAC, and ATLandPAC simulations were all run continuously in time (i.e., every year starts from the end of the previous year). The 0.5ATL and 0.5PAC simulations, however, were run for 300 years in three separate 100-year chunks (i.e., the initial conditions used to start each 100-year chunk were different). The three 100-year chunks have been appended together in the netcdf files. 

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    ZENODO
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2022
    License: CC BY
    Data sources: ZENODO
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      ZENODO
      Dataset . 2022
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2022
      License: CC BY
      Data sources: ZENODO
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    Authors: Romero-Alvarez, Johana; Lupaşcu, Aurelia; Lowe, Douglas; Badia, Alba; +4 Authors

    Tropospheric ozone (O3) concentrations depend on a combination of hemispheric, regional, and local-scale processes. Estimates of how much O3 is produced locally vs. transported from further afield are essential in air quality management and regulatory policies. Here, a tagged-ozone mechanism within the Weather Research and Forecasting model coupled with chemistry (WRF-Chem) is used to quantify the contributions to surface O3 in the UK from anthropogenic nitrogen oxide (NOx) emissions from inside and outside the UK during May–August 2015. The contribution of the different source regions to three regulatory O3 metrics is also examined. It is shown that model simulations predict the concentration and spatial distribution of surface O3 with a domain-wide mean bias of −3.7 ppbv. Anthropogenic NOx emissions from the UK and Europe account for 13 % and 16 %, respectively, of the monthly mean surface O3 in the UK, as the majority (71 %) of O3 originates from the hemispheric background. Hemispheric O3 contributes the most to concentrations in the north and the west of the UK with peaks in May, whereas European and UK contributions are most significant in the east, south-east, and London, i.e. the UK's most populated areas, intensifying towards June and July. Moreover, O3 from European sources is generally transported to the UK rather than produced in situ. It is demonstrated that more stringent emission controls over continental Europe, particularly in western Europe, would be necessary to improve the health-related metric MDA8 O3 above 50 and 60 ppbv. Emission controls over larger areas, such as the Northern Hemisphere, are instead required to lessen the impacts on ecosystems as quantified by the AOT40 metric.

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    Authors: Lehmann, Moritz K; Gurlin, Daniela; Pahlevan, Nima; Alikas, Krista; +73 Authors

    Projects include:* Estonian Ministry of Education and Research* Estonian Research Council* European Commission, Award: FP7, H2020, FP7-ENV-2007-1-226224* Federal Ministry for Economic Affairs and Energy, Germany, Award: LAKESAT 50EE1340* Federal Ministry of Education and Research Germany, Award: 03G0218A* Helmholtz Infrastructure Initiative, Award: FRAM* NASA ROSES, Award: 80HQTR19C0015, 80NSSC 21K0499, 80NSSC22K1389* New Zealand Ministry for Business, Innovation & Employment, Award: UOWX1503, UOWX1802, KENTR1601* USGS Landsat Science Team Award, Award: 140G0118C0011* Vietnam National Foundation for Science and Technology Development (NAFOSTED), grant number 105.08-2019.329 The GLObal Reflectance community dataset for Imaging and optical sensing of Aquatic environments (GLORIA) includes 7,572 curated hyperspectral remote sensing reflectance measurements at 1 nm intervals within the 350 to 900 nm wavelength range. In addition, at least one co-located water quality measurement, chlorophyll a, total suspended solids, absorption by dissolved substances, and Secchi depth, is provided. The data were contributed by researchers affiliated with 53 institutions worldwide and come from 450 different water bodies, making GLORIA the de-facto state of knowledge of in situ coastal and inland aquatic optical diversity.

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    PANGAEA
    Dataset . 2022
    Data sources: B2FIND
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    Authors: Bracher, Astrid; Wiegmann, Sonja;

    We present a data set on remote sensing reflectance (RRS) at 1nm resolution from 350 to 800nm obtained from measurements in the North Sea and Sogne Fjord from 30 April to 7 May 2016. For the measurements we used radiometric hyperspectral (3.3 nm sampling, 10 nm FWHM) underwater profile measurements down to the 0.1 % light level using RAMSES (TriOS GmbH, Germany) sensors which measured depth resolved the upwelling radiance and downwelling irradiance, both corrected by incident sunlight fluctuations with a second RAMSES sensor measuring the above water downwelling irradiance. The later sensor data were also used to finally calculate RRS. We followed the protocol by Mueller et al. (2003) further modified by Matsuoka et al. (2007) and Stramski et al. (2008), as described for our instrument set-up in Taylor et al. (2011). Our method is further described and assessed for its uncertainty in Tilstone et al. (2020). The same campaign was sampled for optical constituents hyperspectral absorption data in Bracher et al. (2021a-d) and for phytoplankton pigments in Bracher and Wiegmann (2019).

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    PANGAEA
    Dataset . 2022
    Data sources: B2FIND
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