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  • 2020-2024  (72,472)
  • 1985-1989  (12)
  • 2021  (72,472)
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  • 1
    Publication Date: 2024-05-30
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
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  • 2
    Publication Date: 2024-05-29
    Description: Data of apparent ice thickness from airborne electromagnetic (AEM) surveys of fast ice in McMurdo Sound, Antarctica, carried out in Nov/Dec 2009, 2011, 2013, 2016, and 2017. Values are given for apparent thicknesses derived from both, in-phase and quadrature signals. The difference between both thicknesses is a scaled measure of sub-ice platelet layer thickness. Data are from east-west transects across McMurdo Sound, at fixed latitudes. Data were smoothed and interpolated onto a regular longitude grid (0.001 degree increments). More information can be found in Haas et al. (2021).
    Keywords: AC; AEM_survey_McMurdo; airborne electromagnetic induction measurement; Aircraft; Antarctica; Cape Adare; C-GJKB; DEEP SOUTH NATIONAL SCIENCE CHALLENGE: Targeted observation and process-informed modelling of Antarctic sea ice; Electro-magnetic Bird (EM-Bird); Electromagnetic induction/laser; EMB; EML; Ice thickness; K063_2011; K063_2013; K066_2016; K066_2016a; K066_2017; K066-1718-A; K066-1718-A_1109; K066-1718-A_1111; LONGITUDE; McMurdo Sound; TOPIMASI
    Type: Dataset
    Format: text/tab-separated-values, 73052 data points
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  • 3
    Publication Date: 2024-05-29
    Description: Sea ice thickness and sub-ice platelet layer thickness under sea ice was measured in regular intervals. Holes were drilled into sea ice at measurement sites about 5 km apart. The thickness was measured using measurement tapes. Snow depth on sea ice was also measured at sites.
    Keywords: Antarctica; Date/Time of event; Event label; Fast ice; Freeboard; ICEDRILL; Ice drill; Identification; Latitude of event; Longitude of event; McMurdo-2009_1; McMurdo-2009_10; McMurdo-2009_11; McMurdo-2009_12; McMurdo-2009_13; McMurdo-2009_14; McMurdo-2009_15; McMurdo-2009_16; McMurdo-2009_17; McMurdo-2009_18; McMurdo-2009_19; McMurdo-2009_2; McMurdo-2009_20; McMurdo-2009_21; McMurdo-2009_3; McMurdo-2009_4; McMurdo-2009_5; McMurdo-2009_6; McMurdo-2009_7; McMurdo-2009_8; McMurdo-2009_9; McMurdo Sound; Sea ice thickness; Snow layer; Snow thickness; Sub-ice platelet layer; Sub-ice platelet-layer thickness
    Type: Dataset
    Format: text/tab-separated-values, 103 data points
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  • 4
    Publication Date: 2024-05-29
    Description: Data of apparent ice thickness from airborne electromagnetic (AEM) surveys of fast ice in McMurdo Sound, Antarctica, carried out in Nov/Dec 2009, 2011, 2013, 2016, and 2017. Values are given for apparent thicknesses derived from both, in-phase and quadrature signals. The difference between both thicknesses is a scaled measure of sub-ice platelet layer thickness. Data are from east-west transects across McMurdo Sound, at fixed latitudes. Data were smoothed and interpolated onto a regular longitude grid (0.001 degree increments). More information can be found in Haas et al. (2021).
    Keywords: AC; AEM_survey_McMurdo; airborne electromagnetic induction measurement; Aircraft; Antarctica; Cape Adare; C-GJKB; DATE/TIME; DEEP SOUTH NATIONAL SCIENCE CHALLENGE: Targeted observation and process-informed modelling of Antarctic sea ice; Distance; Electro-magnetic Bird (EM-Bird); Electromagnetic induction/laser; EMB; EML; Identification; K063_2011; K063_2013; K066_2016; K066_2016a; K066_2017; K066-1718-A; K066-1718-A_1109; K066-1718-A_1111; LATITUDE; Latitude description; LONGITUDE; McMurdo Sound; Sub-ice platelet-layer thickness; TOPIMASI; Type
    Type: Dataset
    Format: text/tab-separated-values, 149 data points
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  • 5
    Publication Date: 2024-05-29
    Description: The thicknesses of sea ice and sub-ice platelet layer were measured at regular intervals on fast ice in McMurdo Sound, Antarctica in November of 2016. Thirty-metre cross-profiles were established at each site, and snow depths were measured at 0.5 m intervals along the transect lines with a MagnaProbe. A mean snow depth for each site was derived from these 120 measurements. Freeboard, sea ice thickness and sub-ice platelet layer thickness were recorded at five locations at each site - at the central crossing point and at the end points of each transect. The mean of these was then calculated and taken as representative of the site. Ice thicknesses were measured by using a tape measure with a brass T-anchor attached at the zero mark. This was deployed vertically through the drill-hole and allowed to rotate to a horizontal alignment when exiting the bottom of the drill-hole at the ice-ocean interface. From this position the anchor is slowly pulled upwards until some resistance is met and the first measurement is taken. This resistance is taken to mark the sub-ice platelet layer/ocean interface. The tape measure is then pulled harder, forcing the bar to pass through the sub-ice platelet layer until it sits flush against the sea ice/sub-ice platelet layer interface where a second measurement is taken. Measurement sites were about 10 km apart.
    Keywords: Antarctica; Date/Time of event; Deep South National Science Challenge: Targeted observations and process-informed modeling of Antarctic sea ice; Event label; Fast ice; Freeboard; ICEDRILL; Ice drill; Identification; Latitude of event; Longitude of event; McMurdo-2016_1; McMurdo-2016_10; McMurdo-2016_11; McMurdo-2016_12; McMurdo-2016_13; McMurdo-2016_14; McMurdo-2016_15; McMurdo-2016_16; McMurdo-2016_17; McMurdo-2016_18; McMurdo-2016_19; McMurdo-2016_2; McMurdo-2016_3; McMurdo-2016_4; McMurdo-2016_5; McMurdo-2016_6; McMurdo-2016_7; McMurdo-2016_8; McMurdo-2016_9; McMurdo Sound; PIPERS; Polynyas, ice production, and seasonal evolution in the Ross Sea; Sea ice thickness; Snow layer; Snow thickness; Sub-ice platelet layer; Sub-ice platelet-layer thickness; TOPOMASI
    Type: Dataset
    Format: text/tab-separated-values, 95 data points
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  • 6
    Publication Date: 2024-05-29
    Description: The thicknesses of sea ice and sub-ice platelet layer were measured at regular intervals on fast ice in McMurdo Sound, Antarctica in November of 2017. Thirty-metre cross-profiles were established at each site, and snow depths were measured at 0.5 m intervals along the transect lines with a MagnaProbe. A mean snow depth for each site was derived from these 120 measurements. Freeboard, sea ice thickness and sub-ice platelet layer thickness were recorded at five locations at each site - at the central crossing point and at the end points of each transect. The mean of these was then calculated and taken as representative of the site. Ice thicknesses were measured by using a tape measure with a brass T-anchor attached at the zero mark. This was deployed vertically through the drill-hole and allowed to rotate to a horizontal alignment when exiting the bottom of the drill-hole at the ice-ocean interface. From this position the anchor is slowly pulled upwards until some resistance is met and the first measurement is taken. This resistance is taken to mark the sub-ice platelet layer/ocean interface. The tape measure is then pulled harder, forcing the bar to pass through the sub-ice platelet layer until it sits flush against the sea ice/sub-ice platelet layer interface where a second measurement is taken. Measurement sites were about 10 km apart.
    Keywords: Antarctica; Date/Time of event; Deep South National Science Challenge: Targeted observations and process-informed modeling of Antarctic sea ice; Event label; Fast ice; Freeboard; ICEDRILL; Ice drill; Identification; Latitude of event; Longitude of event; McMurdo-2017_1; McMurdo-2017_11; McMurdo-2017_2; McMurdo-2017_20; McMurdo-2017_21; McMurdo-2017_22; McMurdo-2017_23; McMurdo-2017_24; McMurdo-2017_3; McMurdo-2017_4; McMurdo-2017_5; McMurdo-2017_6; McMurdo-2017_7; McMurdo-2017_70; McMurdo-2017_71; McMurdo-2017_72; McMurdo-2017_73; McMurdo-2017_74; McMurdo-2017_75; McMurdo-2017_76; McMurdo-2017_77; McMurdo-2017_EM31_1; McMurdo-2017_EM31_2; McMurdo Sound; PIPERS; Polynyas, ice production, and seasonal evolution in the Ross Sea; Sea ice thickness; Snow layer; Snow thickness; Sub-ice platelet layer; Sub-ice platelet-layer thickness; TOPOMASI
    Type: Dataset
    Format: text/tab-separated-values, 115 data points
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  • 7
    Publication Date: 2024-05-29
    Description: Sea ice thickness and sub-ice platelet layer thickness under fast ice were measured at regular intervals at two North-South oriented profiles and four east-west oriented profiles in McMurdo Sound, Antarctica in November 2013. Holes were drilled at regular intervals into sea ice at measurement sites about 10 km apart. The thickness was measured using measurement tapes. Snow depth on sea ice was also measured at all sites.
    Keywords: Antarctica; Antarctic sea ice thickness: Harbinger of change in the Southern Ocean; AntSeaIce; Date/Time of event; Event label; Fast ice; Freeboard; ICEDRILL; Ice drill; Identification; Latitude of event; Longitude of event; McMurdo-2013_1; McMurdo-2013_10; McMurdo-2013_11; McMurdo-2013_12; McMurdo-2013_13; McMurdo-2013_14; McMurdo-2013_15; McMurdo-2013_16; McMurdo-2013_17; McMurdo-2013_18; McMurdo-2013_19; McMurdo-2013_2; McMurdo-2013_20; McMurdo-2013_21; McMurdo-2013_22; McMurdo-2013_23; McMurdo-2013_24; McMurdo-2013_25; McMurdo-2013_26; McMurdo-2013_27; McMurdo-2013_28; McMurdo-2013_29; McMurdo-2013_3; McMurdo-2013_30; McMurdo-2013_31; McMurdo-2013_32; McMurdo-2013_33; McMurdo-2013_4; McMurdo-2013_5; McMurdo-2013_6; McMurdo-2013_7; McMurdo-2013_8; McMurdo-2013_9; McMurdo Sound; Sea ice thickness; Snow layer; Snow thickness; Sub-ice platelet layer; Sub-ice platelet-layer thickness
    Type: Dataset
    Format: text/tab-separated-values, 165 data points
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  • 8
    Publication Date: 2024-05-29
    Description: The thicknesses of sea ice and sub-ice platelet layer were measured at regular intervals on fast ice in McMurdo Sound, Antarctica in November and December of 2011. Thirty-metre cross-profiles were established at each site, and snow depths were measured at 0.5 m intervals along the transect lines with a metal ruler. A mean snow depth for each site was derived from these 120 measurements. Freeboard, sea ice thickness and sub-ice platelet layer thickness were recorded at five locations at each site - at the central crossing point and at the end points of each transect. The mean of these was then calculated and taken as representative of the site. Ice thicknesses were measured by using a tape measure with a brass T-anchor attached at the zero mark. This was deployed vertically through the drill-hole and allowed to rotate to a horizontal alignment when exiting the bottom of the drill-hole at the ice-ocean interface. From this position the anchor is slowly pulled upwards until some resistance is met and the first measurement is taken. This resistance is taken to mark the sub-ice platelet layer/ocean interface. The tape measure is then pulled harder, forcing the bar to pass through the sub-ice platelet layer until it sits flush against the sea ice/sub-ice platelet layer interface where a second measurement is taken. Measurement sites were about 5 km apart.
    Keywords: Antarctica; Antarctic sea ice thickness: Harbinger of change in the Southern Ocean; AntSeaIce; Date/Time of event; Event label; Fast ice; Freeboard; ICEDRILL; Ice drill; Identification; Latitude of event; Longitude of event; McMurdo-2011_1; McMurdo-2011_10; McMurdo-2011_11; McMurdo-2011_12; McMurdo-2011_13; McMurdo-2011_14; McMurdo-2011_15; McMurdo-2011_16; McMurdo-2011_17; McMurdo-2011_18; McMurdo-2011_19; McMurdo-2011_2; McMurdo-2011_20; McMurdo-2011_21; McMurdo-2011_22; McMurdo-2011_23; McMurdo-2011_24; McMurdo-2011_25; McMurdo-2011_26; McMurdo-2011_27; McMurdo-2011_28; McMurdo-2011_29; McMurdo-2011_3; McMurdo-2011_30; McMurdo-2011_31; McMurdo-2011_32; McMurdo-2011_33; McMurdo-2011_34; McMurdo-2011_35; McMurdo-2011_36; McMurdo-2011_37; McMurdo-2011_38; McMurdo-2011_39; McMurdo-2011_4; McMurdo-2011_40; McMurdo-2011_5; McMurdo-2011_6; McMurdo-2011_7; McMurdo-2011_8; McMurdo-2011_9; McMurdo-2011_CGPS; McMurdo-2011_EGPS; McMurdo-2011_WGPS; McMurdo Sound; Sea ice thickness; Snow layer; Snow thickness; Sub-ice platelet layer; Sub-ice platelet-layer thickness
    Type: Dataset
    Format: text/tab-separated-values, 215 data points
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  • 9
    Publication Date: 2024-05-29
    Description: Pelagic video transects with the Pelagic In-Situ Observation System (PELAGIOS, (Hoving et al., 2019a)) were conducted during the cruises MSM49 (Christiansen et al., 2016) (transects between 30 and 1000 m, total towing duration 〉 80h), MSM61 (Fiedler et al., 2020) (transects between 80 and 1200 m, total hours of observations 〉 32h), POS520 (Hoving et al., 2018, p. 520) (transects between 30 and 2500 m, total hours of observations 27h), POS532 (Hoving et al., 2019b) (transects between 30 and 990 m, total hours of observations 19h) and M119 (Brandt, 2016) (transects between 50 and 700 m, total hours of observations 〉 20h) between 2015 and 2019 (Figure 1). PELAGIOS is a battery powered, high-definition camera system that is towed horizontally via a single-wired conductive sea-cable at 0.5 m s -1. Around 0.45 m2 of the water column in front of the camera is illuminated with an LED array. The attached depth sensor and/or a sensor for conductivity, temperature and depth (CTD) with oxygen sensor allows for hydrographic measurements and depth monitoring during transects. Pelagic video transects were conducted between 11-33 minutes per depth, towing the camera horizontally at specified depths. A deep-sea telemetry system allows for transmission of a low-resolution preview of the recorded video. During the cruises POS520 and POS532 the manned submersible JAGO (GEOMAR, Helmholtz Centre for Ocean Research) was used for 30 deployments of about four hours each between the surface and 350 m water depth. During the dives, video was recorded by a high-resolution camera. The videos taken during the PELAGIOS and JAGO dives were annotated manually using the Video Annotation and Reference System (VARS) developed at the Monterey Bay Aquarium Research Institute, which allows annotation and congruent collection of video frames. We also provide raw data on environmental DNA samples taken during POS532 in February 2019 at five stations. The stations off the islands Santo Antão and Fogo were close to the coast (maximum sampled depth 2500 m), CVOO was a reference station in the open ocean (maximum sampled depth 3000 m) and the stations Cyclone and Anticyclone were located eddies that had formed in the wake of Fogo and had propagated southwards (maximum sampled depths 2200 and 600 m, respectively). Per sampled depth, three biological replicates of two liters of seawater each were collected from three different 10 liter Niskin bottles mounted on a CTD rosette. For filtration, 0.22 µm pore size Sterivex-GP filter (Merck Millipore) were directly connected to the Niskin bottle with sterile tubing. The weight of the water in the Niskin bottles was sufficient to filter two liters of seawater per filter. The filters were closed with sterile plastic caps and stored at -80°C until further processing in the laboratory.
    Keywords: Cabo Verde; Cephalopods; Comment; CT; Day-Night indicator; Depth, nominal; environmental DNA; Event label; Gear; in situ observations; JAGO; LATITUDE; LONGITUDE; M119; M119_694-1; M119_705-1; M119_710-1; Maria S. Merian; Metabarcoding; Meteor (1986); MSM49; MSM49_583-4; MSM49_585-8; MSM49_604-12; MSM49-track; MSM61; MSM61_471-3; MSM61-track; Pelagic In situ Observation System PELAGIOS; PELAGIOS; POS520; POS520_12-1; POS520_14-1; POS520_17-2; POS520_21-1; POS520_24-1; POS520_25-1; POS520_26-1; POS520_28-2; POS520_29-2; POS520_33-1; POS520_34-2; POS520_37-1; POS520_44-1; POS520_49-1; POS520_64-1; POS520_CVOO; POS520_eddy; POS532; POS532_11-1; POS532_12-1; POS532_15-1; POS532_20-1; POS532_26-1; POS532_29-1; POS532_31-1; POS532_47-1; POS532_65-1; POS532_65-3; Poseidon; Sample code/label; South Atlantic Ocean; Species; Station label; Submersible JAGO; Underway cruise track measurements
    Type: Dataset
    Format: text/tab-separated-values, 1195 data points
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  • 10
    Publication Date: 2024-05-28
    Description: Foraminifera are a species-rich phylum of rhizarian protists that are highly abundant in many marine environments and play a major role in global carbon cycling. Species recognition in Foraminifera is mainly based on morphological characters and nuclear 18S ribosomal RNA barcoding. The 18S rRNA contains variable sequence regions that allow for the identification of most foraminiferal species. Still, some species show limited variability, while others contain high levels of intragenomic polymorphisms, thereby complicating species identification. The use of additional, easily obtainable molecular markers other than 18S rRNA will enable more detailed investigation of evolutionary history, population genetics and speciation in Foraminifera. Here we present the first mitochondrial cytochrome c oxidase subunit 1 (COI) gene sequences (“barcodes”) of Foraminifera. We applied shotgun sequencing to single foraminiferal specimens, assembled COI, and developed primers that allow amplification of COI in a wide range of foraminiferal species. We obtained COI sequences of 49 specimens from 17 species from the orders Rotaliida and Miliolida. Phylogenetic analysis showed that the COI tree is largely congruent with previously published 18S rRNA phylogenies. Furthermore, species delimitation with ASAP and ABGD algorithms showed that foraminiferal species can be identified based on COI barcodes.
    Repository Name: National Museum of Natural History, Netherlands
    Type: info:eu-repo/semantics/article
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  • 11
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    Copernicus GmbH
    In:  Earth System Science Data vol. 13 no. 9, pp. 4313-4329
    Publication Date: 2024-05-28
    Description: Marine Isotope Stage 5e (MIS 5e; the Last Interglacial, 125 ka) represents a process analog for a warmer world. Analysis of sea-level proxies formed in this period helps in constraining both regional and global drivers of sea-level change. In Southeast Asia, several studies have reported elevation and age information on MIS 5e sea-level proxies, such as fossil coral reef terraces or tidal notches, but a standardized database of such data was hitherto missing. In this paper, we produced such a sea-level database using the framework of the World Atlas of Last Interglacial Shorelines (WALIS; https://warmcoasts.eu/world-atlas.html). Overall, we screened and reviewed 14 studies on Last Interglacial sea-level indicators in Southeast Asia, from which we report 43 proxies (42 coral reef terraces and 1 tidal notch) that were correlated to 134 dated samples. Five data points date to MIS 5a (80 ka), six data points are MIS 5c (100 ka), and the rest are dated to MIS 5e. The database compiled in this study is available at https://doi.org/10.5281/zenodo.5040784 (Maxwell et al., 2021).
    Repository Name: National Museum of Natural History, Netherlands
    Type: info:eu-repo/semantics/article
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  • 12
    Publication Date: 2024-05-28
    Description: Here we present the experimental design and results from a new mid-Pliocene simulation using the latest version of the UK's physical climate model, HadGEM3-GC31-LL, conducted under the auspices of CMIP6/PMIP4/PlioMIP2. Although two other palaeoclimate simulations have been recently run using this model, they both focused on more recent periods within the Quaternary, and therefore this is the first time this version of the UK model has been run this far back in time. The mid-Pliocene Warm Period, ∼3 Ma, is of particular interest because it represents a time period when the Earth was in equilibrium with CO2 concentrations roughly equivalent to those of today, providing a possible analogue for current and future climate change. The implementation of the Pliocene boundary conditions is firstly described in detail, based on the PRISM4 dataset, including CO2, ozone, orography, ice mask, lakes, vegetation fractions and vegetation functional types. These were incrementally added into the model, to change from a pre-industrial setup to a Pliocene setup. The results of the simulation are then presented, which are firstly compared with the model's pre-industrial simulation, secondly with previous versions of the same model and with available proxy data, and thirdly with all other models included in PlioMIP2. Firstly, the comparison with the pre-industrial simulation suggests that the Pliocene simulation is consistent with current understanding and existing work, showing warmer and wetter conditions, and with the greatest warming occurring over high-latitude and polar regions. The global mean surface air temperature anomaly at the end of the Pliocene simulation is 5.1 ∘C, which is the second highest of all models included in PlioMIP2 and is consistent with the fact that HadGEM3-GC31-LL has one of the highest Effective Climate Sensitivities of all CMIP6 models. Secondly, the comparison with previous generation models and with proxy data suggests a clear increase in global sea surface temperatures as the model has undergone development. Up to a certain level of warming, this results in a better agreement with available proxy data, and the “sweet spot” appears to be the previous CMIP5 generation of the model, HadGEM2-AO. The most recent simulation presented here, however, appears to show poorer agreement with the proxy data compared with HadGEM2 and may be overly sensitive to the Pliocene boundary conditions, resulting in a climate that is too warm. Thirdly, the comparison with other models from PlioMIP2 further supports this conclusion, with HadGEM3-GC31-LL being one of the warmest and wettest models in all of PlioMIP2, and if all the models are ordered according to agreement with proxy data, HadGEM3-GC31-LL ranks approximately halfway among them. A caveat to these results is the relatively short run length of the simulation, meaning the model is not in full equilibrium. Given the computational cost of the model it was not possible to run it for a longer period; a Gregory plot analysis indicates that had it been allowed to come to full equilibrium, the final global mean surface temperature could have been approximately 1.5 ∘C higher.
    Repository Name: National Museum of Natural History, Netherlands
    Type: info:eu-repo/semantics/article
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  • 13
    Publication Date: 2024-05-28
    Description: Despite increasing recognition of the need for more diverse and equitable representation in the sciences, it is unclear whether measurable progress has been made. Here, we examine trends in authorship in coral reef science from 1,677 articles published over the past 16 years (2003–2018) and find that while representation of authors that are women (from 18 to 33%) and from non-OECD nations (from 4 to 13%) have increased over time, progress is slow in achieving more equitable representation. For example, at the current rate, it would take over two decades for female representation to reach 50%. Given that there are more coral reef non-OECD countries, at the current rate, truly equitable representation of non-OECD countries would take even longer. OECD nations also continue to dominate authorship contributions in coral reef science (89%), in research conducted in both OECD (63%) and non-OECD nations (68%). We identify systemic issues that remain prevalent in coral reef science (i.e., parachute science, gender bias) that likely contribute to observed trends. We provide recommendations to address systemic biases in research to foster a more inclusive global science community. Adoption of these recommendations will lead to more creative, innovative, and impactful scientific approaches urgently needed for coral reefs and contribute to environmental justice efforts.
    Keywords: coral reef science ; gender ; equity ; inclusion ; representation ; diversity
    Repository Name: National Museum of Natural History, Netherlands
    Type: info:eu-repo/semantics/article
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  • 14
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    PANGAEA
    In:  Izaña Atmospheric Research Center, Meteorological State Agency of Spain
    Publication Date: 2024-05-28
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, maximum; Diffuse radiation, minimum; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, maximum; Direct radiation, minimum; Direct radiation, standard deviation; EKO Instruments, MR-60, SN S15115.07, WRMC No. 61013; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; IZA; Izaña; Long-wave downward radiation; Long-wave downward radiation, maximum; Long-wave downward radiation, minimum; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Long-wave upward radiation, maximum; Long-wave upward radiation, minimum; Long-wave upward radiation, standard deviation; Monitoring station; MONS; Net radiation; Net radiation, maximum; Net radiation, minimum; Net radiation, standard deviation; Pyranometer, EKO, MS-802F, SN F15508FR, WRMC No. 61010; Pyranometer, EKO, MS-802F, SN F15509FR, WRMC No. 61011; Pyrgeometer, Kipp & Zonen, CGR4, SN 050783, WRMC No. 61008; Pyrheliometer, EKO, MS-56, SN P15048, WRMC No. 61012; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, maximum; Short-wave downward (GLOBAL) radiation, minimum; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Short-wave upward (REFLEX) radiation, maximum; Short-wave upward (REFLEX) radiation, minimum; Short-wave upward (REFLEX) radiation, standard deviation; Station pressure; Tenerife, Spain; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 1195351 data points
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  • 15
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    PANGAEA
    In:  Izaña Atmospheric Research Center, Meteorological State Agency of Spain
    Publication Date: 2024-05-28
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, maximum; Diffuse radiation, minimum; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, maximum; Direct radiation, minimum; Direct radiation, standard deviation; EKO Instruments, MR-60, SN S15115.07, WRMC No. 61013; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; IZA; Izaña; Long-wave downward radiation; Long-wave downward radiation, maximum; Long-wave downward radiation, minimum; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Long-wave upward radiation, maximum; Long-wave upward radiation, minimum; Long-wave upward radiation, standard deviation; Monitoring station; MONS; Net radiation; Net radiation, maximum; Net radiation, minimum; Net radiation, standard deviation; Pyranometer, EKO, MS-802F, SN F15508FR, WRMC No. 61010; Pyranometer, EKO, MS-802F, SN F15509FR, WRMC No. 61011; Pyrgeometer, Kipp & Zonen, CGR4, SN 050783, WRMC No. 61008; Pyrheliometer, EKO, MS-56, SN P15048, WRMC No. 61012; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, maximum; Short-wave downward (GLOBAL) radiation, minimum; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Short-wave upward (REFLEX) radiation, maximum; Short-wave upward (REFLEX) radiation, minimum; Short-wave upward (REFLEX) radiation, standard deviation; Station pressure; Tenerife, Spain; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 1189200 data points
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  • 16
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    Unknown
    PANGAEA
    In:  Izaña Atmospheric Research Center, Meteorological State Agency of Spain
    Publication Date: 2024-05-28
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, maximum; Diffuse radiation, minimum; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, maximum; Direct radiation, minimum; Direct radiation, standard deviation; EKO Instruments, MR-60, SN S15115.07, WRMC No. 61013; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; IZA; Izaña; Long-wave downward radiation; Long-wave downward radiation, maximum; Long-wave downward radiation, minimum; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Long-wave upward radiation, maximum; Long-wave upward radiation, minimum; Long-wave upward radiation, standard deviation; Monitoring station; MONS; Net radiation; Net radiation, maximum; Net radiation, minimum; Net radiation, standard deviation; Pyranometer, EKO, MS-802F, SN F15508FR, WRMC No. 61010; Pyranometer, EKO, MS-802F, SN F15509FR, WRMC No. 61011; Pyrgeometer, Kipp & Zonen, CGR4, SN 050783, WRMC No. 61008; Pyrheliometer, EKO, MS-56, SN P15048, WRMC No. 61012; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, maximum; Short-wave downward (GLOBAL) radiation, minimum; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Short-wave upward (REFLEX) radiation, maximum; Short-wave upward (REFLEX) radiation, minimum; Short-wave upward (REFLEX) radiation, standard deviation; Station pressure; Tenerife, Spain; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 1343594 data points
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  • 17
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    PANGAEA
    In:  Izaña Atmospheric Research Center, Meteorological State Agency of Spain
    Publication Date: 2024-05-28
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, maximum; Diffuse radiation, minimum; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, maximum; Direct radiation, minimum; Direct radiation, standard deviation; EKO Instruments, MR-60, SN S15115.07, WRMC No. 61013; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; IZA; Izaña; Long-wave downward radiation; Long-wave downward radiation, maximum; Long-wave downward radiation, minimum; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Long-wave upward radiation, maximum; Long-wave upward radiation, minimum; Long-wave upward radiation, standard deviation; Monitoring station; MONS; Net radiation; Net radiation, maximum; Net radiation, minimum; Net radiation, standard deviation; Pyranometer, EKO, MS-802F, SN F15508FR, WRMC No. 61010; Pyranometer, EKO, MS-802F, SN F15509FR, WRMC No. 61011; Pyrgeometer, Kipp & Zonen, CGR4, SN 050783, WRMC No. 61008; Pyrheliometer, EKO, MS-56, SN P15048, WRMC No. 61012; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, maximum; Short-wave downward (GLOBAL) radiation, minimum; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Short-wave upward (REFLEX) radiation, maximum; Short-wave upward (REFLEX) radiation, minimum; Short-wave upward (REFLEX) radiation, standard deviation; Station pressure; Tenerife, Spain; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 1295097 data points
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  • 18
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    PANGAEA
    In:  Izaña Atmospheric Research Center, Meteorological State Agency of Spain
    Publication Date: 2024-05-28
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, maximum; Diffuse radiation, minimum; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, maximum; Direct radiation, minimum; Direct radiation, standard deviation; EKO Instruments, MR-60, SN S15115.07, WRMC No. 61013; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; IZA; Izaña; Long-wave downward radiation; Long-wave downward radiation, maximum; Long-wave downward radiation, minimum; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Long-wave upward radiation, maximum; Long-wave upward radiation, minimum; Long-wave upward radiation, standard deviation; Monitoring station; MONS; Net radiation; Net radiation, maximum; Net radiation, minimum; Net radiation, standard deviation; Pyranometer, EKO, MS-802F, SN F15508FR, WRMC No. 61010; Pyranometer, EKO, MS-802F, SN F15509FR, WRMC No. 61011; Pyrgeometer, Kipp & Zonen, CGR4, SN 60882, WRMC No. 61014; Pyrheliometer, EKO, MS-56, SN P15048, WRMC No. 61012; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, maximum; Short-wave downward (GLOBAL) radiation, minimum; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Short-wave upward (REFLEX) radiation, maximum; Short-wave upward (REFLEX) radiation, minimum; Short-wave upward (REFLEX) radiation, standard deviation; Station pressure; Tenerife, Spain; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 1337371 data points
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  • 19
    Publication Date: 2024-05-28
    Description: Raw secondary low frequency (SLF) echo sounding data initially retrieved during POLARSTERN cruise PS87 (ARK-XXVIII/4) were converted to standard SGY format for further visualization in geophysical software. Conversion was performed using the PS32SGY tool by Hanno Keil, University of Bremen. Navigation was converted to UKOOA format with coordinates in WGS84. SGY and UKOOA fils are named using the starting date and time of the profile (YYYY_MMDD_HHMMSS). Due to the 12-digits-restriction of profile names in the UKOOA format, the first column of the UKOOA file contains a shortened version of the SGY file name (YYMMDDHHMMSS). This publication contains data from the Lomonosov Ridge/Amundsen Basin.
    Keywords: ARK-XXVIII/4 ALEX2014; ASCII file; Binary Object; CT; DATE/TIME; LATITUDE; Latitude 2; LONGITUDE; Longitude 2; PARASOUND; Polarstern; PS87; PS87-track; SGY; Underway cruise track measurements
    Type: Dataset
    Format: text/tab-separated-values, 56 data points
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  • 20
    Publication Date: 2024-05-28
    Description: Raw secondary low frequency (SLF) echo sounding data initially retrieved during POLARSTERN cruise PS19 (ARK-VIII/3) were converted to standard SGY format for further visualization in geophysical software. Conversion was performed using the PS32SGY tool by Hanno Keil, University of Bremen. Navigation was converted to UKOOA format with coordinates in WGS84. SGY and UKOOA fils are named using the starting date and time of the profile (YYYY_MMDD_HHMMSS). Due to the 12-digits-restriction of profile names in the UKOOA format, the first column of the UKOOA file contains a shortened version of the SGY file name (YYMMDDHHMMSS). This publication contains data from the Lomonosov Ridge/Amundsen Basin.
    Keywords: ARK-VIII/3; ASCII file; Binary Object; CT; DATE/TIME; LATITUDE; Latitude 2; LONGITUDE; Longitude 2; PARASOUND; Polarstern; PS19/3-track; PS19 ARCTIC91; SGY; Underway cruise track measurements
    Type: Dataset
    Format: text/tab-separated-values, 36 data points
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  • 21
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    PANGAEA
    In:  Izaña Atmospheric Research Center, Meteorological State Agency of Spain
    Publication Date: 2024-05-28
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, maximum; Diffuse radiation, minimum; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, maximum; Direct radiation, minimum; Direct radiation, standard deviation; EKO Instruments, MR-60, SN S15115.07, WRMC No. 61013; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; IZA; Izaña; Long-wave downward radiation; Long-wave downward radiation, maximum; Long-wave downward radiation, minimum; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Long-wave upward radiation, maximum; Long-wave upward radiation, minimum; Long-wave upward radiation, standard deviation; Monitoring station; MONS; Net radiation; Net radiation, maximum; Net radiation, minimum; Net radiation, standard deviation; Pyranometer, EKO, MS-802F, SN F15508FR, WRMC No. 61010; Pyranometer, EKO, MS-802F, SN F15509FR, WRMC No. 61011; Pyrgeometer, Kipp & Zonen, CGR4, SN 050783, WRMC No. 61008; Pyrheliometer, EKO, MS-56, SN P15048, WRMC No. 61012; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, maximum; Short-wave downward (GLOBAL) radiation, minimum; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Short-wave upward (REFLEX) radiation, maximum; Short-wave upward (REFLEX) radiation, minimum; Short-wave upward (REFLEX) radiation, standard deviation; Station pressure; Tenerife, Spain; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 1224033 data points
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  • 22
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    PANGAEA
    In:  Izaña Atmospheric Research Center, Meteorological State Agency of Spain
    Publication Date: 2024-05-28
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, maximum; Diffuse radiation, minimum; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, maximum; Direct radiation, minimum; Direct radiation, standard deviation; EKO Instruments, MR-60, SN S15115.07, WRMC No. 61013; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; IZA; Izaña; Long-wave downward radiation; Long-wave downward radiation, maximum; Long-wave downward radiation, minimum; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Long-wave upward radiation, maximum; Long-wave upward radiation, minimum; Long-wave upward radiation, standard deviation; Monitoring station; MONS; Net radiation; Net radiation, maximum; Net radiation, minimum; Net radiation, standard deviation; Pyranometer, EKO, MS-802F, SN F15508FR, WRMC No. 61010; Pyranometer, EKO, MS-802F, SN F15509FR, WRMC No. 61011; Pyrgeometer, Kipp & Zonen, CGR4, SN 050783, WRMC No. 61008; Pyrheliometer, EKO, MS-56, SN P15048, WRMC No. 61012; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, maximum; Short-wave downward (GLOBAL) radiation, minimum; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Short-wave upward (REFLEX) radiation, maximum; Short-wave upward (REFLEX) radiation, minimum; Short-wave upward (REFLEX) radiation, standard deviation; Station pressure; Tenerife, Spain; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 1331703 data points
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  • 23
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    PANGAEA
    In:  Izaña Atmospheric Research Center, Meteorological State Agency of Spain
    Publication Date: 2024-05-28
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, maximum; Diffuse radiation, minimum; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, maximum; Direct radiation, minimum; Direct radiation, standard deviation; EKO Instruments, MR-60, SN S15115.07, WRMC No. 61013; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; IZA; Izaña; Long-wave downward radiation; Long-wave downward radiation, maximum; Long-wave downward radiation, minimum; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Long-wave upward radiation, maximum; Long-wave upward radiation, minimum; Long-wave upward radiation, standard deviation; Monitoring station; MONS; Net radiation; Net radiation, maximum; Net radiation, minimum; Net radiation, standard deviation; Pyranometer, EKO, MS-802F, SN F15508FR, WRMC No. 61010; Pyranometer, EKO, MS-802F, SN F15509FR, WRMC No. 61011; Pyrgeometer, Kipp & Zonen, CGR4, SN 050783, WRMC No. 61008; Pyrheliometer, EKO, MS-56, SN P15048, WRMC No. 61012; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, maximum; Short-wave downward (GLOBAL) radiation, minimum; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Short-wave upward (REFLEX) radiation, maximum; Short-wave upward (REFLEX) radiation, minimum; Short-wave upward (REFLEX) radiation, standard deviation; Station pressure; Tenerife, Spain; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 1316808 data points
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  • 24
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    PANGAEA
    In:  Izaña Atmospheric Research Center, Meteorological State Agency of Spain
    Publication Date: 2024-05-28
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, maximum; Diffuse radiation, minimum; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, maximum; Direct radiation, minimum; Direct radiation, standard deviation; EKO Instruments, MR-60, SN S15115.07, WRMC No. 61013; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; IZA; Izaña; Long-wave downward radiation; Long-wave downward radiation, maximum; Long-wave downward radiation, minimum; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Long-wave upward radiation, maximum; Long-wave upward radiation, minimum; Long-wave upward radiation, standard deviation; Monitoring station; MONS; Net radiation; Net radiation, maximum; Net radiation, minimum; Net radiation, standard deviation; Pyranometer, EKO, MS-802F, SN F15508FR, WRMC No. 61010; Pyranometer, EKO, MS-802F, SN F15509FR, WRMC No. 61011; Pyrgeometer, Kipp & Zonen, CGR4, SN 050783, WRMC No. 61008; Pyrheliometer, EKO, MS-56, SN P15048, WRMC No. 61012; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, maximum; Short-wave downward (GLOBAL) radiation, minimum; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Short-wave upward (REFLEX) radiation, maximum; Short-wave upward (REFLEX) radiation, minimum; Short-wave upward (REFLEX) radiation, standard deviation; Station pressure; Tenerife, Spain; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 1331440 data points
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  • 25
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    PANGAEA
    In:  Izaña Atmospheric Research Center, Meteorological State Agency of Spain
    Publication Date: 2024-05-28
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, maximum; Diffuse radiation, minimum; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, maximum; Direct radiation, minimum; Direct radiation, standard deviation; EKO Instruments, MR-60, SN S15115.07, WRMC No. 61013; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; IZA; Izaña; Long-wave downward radiation; Long-wave downward radiation, maximum; Long-wave downward radiation, minimum; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Long-wave upward radiation, maximum; Long-wave upward radiation, minimum; Long-wave upward radiation, standard deviation; Monitoring station; MONS; Net radiation; Net radiation, maximum; Net radiation, minimum; Net radiation, standard deviation; Pyranometer, EKO, MS-802F, SN F15508FR, WRMC No. 61010; Pyranometer, EKO, MS-802F, SN F15509FR, WRMC No. 61011; Pyrgeometer, Kipp & Zonen, CGR4, SN 050783, WRMC No. 61008; Pyrheliometer, EKO, MS-56, SN P15048, WRMC No. 61012; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, maximum; Short-wave downward (GLOBAL) radiation, minimum; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Short-wave upward (REFLEX) radiation, maximum; Short-wave upward (REFLEX) radiation, minimum; Short-wave upward (REFLEX) radiation, standard deviation; Station pressure; Tenerife, Spain; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 1300233 data points
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  • 26
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    PANGAEA
    In:  Izaña Atmospheric Research Center, Meteorological State Agency of Spain
    Publication Date: 2024-05-28
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, maximum; Diffuse radiation, minimum; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, maximum; Direct radiation, minimum; Direct radiation, standard deviation; EKO Instruments, MR-60, SN S15115.07, WRMC No. 61013; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; IZA; Izaña; Long-wave downward radiation; Long-wave downward radiation, maximum; Long-wave downward radiation, minimum; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Long-wave upward radiation, maximum; Long-wave upward radiation, minimum; Long-wave upward radiation, standard deviation; Monitoring station; MONS; Net radiation; Net radiation, maximum; Net radiation, minimum; Net radiation, standard deviation; Pyranometer, EKO, MS-802F, SN F15509FR, WRMC No. 61011; Pyranometer, Kipp & Zonen, CM21, SN 080032, WRMC No. 61002; Pyrgeometer, Kipp & Zonen, CGR4, SN 60882, WRMC No. 61014; Pyrheliometer, EKO, MS-56, SN P15048, WRMC No. 61012; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, maximum; Short-wave downward (GLOBAL) radiation, minimum; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Short-wave upward (REFLEX) radiation, maximum; Short-wave upward (REFLEX) radiation, minimum; Short-wave upward (REFLEX) radiation, standard deviation; Station pressure; Tenerife, Spain; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 1278759 data points
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  • 27
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    PANGAEA
    In:  Izaña Atmospheric Research Center, Meteorological State Agency of Spain
    Publication Date: 2024-05-28
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, maximum; Diffuse radiation, minimum; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, maximum; Direct radiation, minimum; Direct radiation, standard deviation; EKO Instruments, MR-60, SN S15115.07, WRMC No. 61013; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; IZA; Izaña; Long-wave downward radiation; Long-wave downward radiation, maximum; Long-wave downward radiation, minimum; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Long-wave upward radiation, maximum; Long-wave upward radiation, minimum; Long-wave upward radiation, standard deviation; Monitoring station; MONS; Net radiation; Net radiation, maximum; Net radiation, minimum; Net radiation, standard deviation; Pyranometer, EKO, MS-802F, SN F15508FR, WRMC No. 61010; Pyranometer, EKO, MS-802F, SN F15509FR, WRMC No. 61011; Pyrgeometer, Kipp & Zonen, CGR4, SN 050783, WRMC No. 61008; Pyrheliometer, EKO, MS-56, SN P15048, WRMC No. 61012; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, maximum; Short-wave downward (GLOBAL) radiation, minimum; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Short-wave upward (REFLEX) radiation, maximum; Short-wave upward (REFLEX) radiation, minimum; Short-wave upward (REFLEX) radiation, standard deviation; Station pressure; Tenerife, Spain; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 1297325 data points
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  • 28
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    PANGAEA
    In:  Izaña Atmospheric Research Center, Meteorological State Agency of Spain
    Publication Date: 2024-05-28
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, maximum; Diffuse radiation, minimum; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, maximum; Direct radiation, minimum; Direct radiation, standard deviation; EKO Instruments, MR-60, SN S15115.07, WRMC No. 61013; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; IZA; Izaña; Long-wave downward radiation; Long-wave downward radiation, maximum; Long-wave downward radiation, minimum; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Long-wave upward radiation, maximum; Long-wave upward radiation, minimum; Long-wave upward radiation, standard deviation; Monitoring station; MONS; Net radiation; Net radiation, maximum; Net radiation, minimum; Net radiation, standard deviation; Pyranometer, EKO, MS-802F, SN F15508FR, WRMC No. 61010; Pyranometer, EKO, MS-802F, SN F15509FR, WRMC No. 61011; Pyrgeometer, Kipp & Zonen, CGR4, SN 050783, WRMC No. 61008; Pyrheliometer, EKO, MS-56, SN P15048, WRMC No. 61012; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, maximum; Short-wave downward (GLOBAL) radiation, minimum; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Short-wave upward (REFLEX) radiation, maximum; Short-wave upward (REFLEX) radiation, minimum; Short-wave upward (REFLEX) radiation, standard deviation; Station pressure; Tenerife, Spain; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 1259302 data points
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  • 29
    Publication Date: 2024-05-28
    Description: The spatial pattern of Antarctic surface air temperature variability on multi–decadal to multi–centennial time scales is poorly known because of the short instrumental records, the relatively small number of high–resolution paleoclimate observations, and biases in climate models. Here, changes in surface air temperature over Antarctica are reconstructed over the past two millennia using data assimilation constrained by different ice core water isotope records in order to identify robust signals. The comparison between previous statistically based temperature reconstructions and simulations covering the full Common Era driven by natural and anthropogenic forcings shows major discrepancies occurring in the period 1–1000 CE over East Antarctica, with the reconstructions displaying a warming over 1–500 CE that is not reproduced by the simulations. This suggests that the trends in the first millennium deduced from the statistically based reconstructions are unlikely to be entirely forced by external forcings. Our reconstructions show the high sensitivity of the 500-year temperature trend in Antarctica and its spatial distribution to selection of the records for the reconstructions, especially during 1–500 CE. A robust cooling over Antarctica during 501–1000 CE has been obtained in three data assimilation–based reconstructions with a larger magnitude in the WAIS than elsewhere over Antarctica, in agreement with previous estimates with the larger changes than simulated in climate models. The reconstructions for atmospheric circulation indicate that the pattern of temperature changes over 501–1000 CE is related to the positive trend of Southern Annular Mode and a deepening of Amundsen Sea Low. This confirms the role of internal variability in the temperature trends on multi–centennial scales.
    Type: Article , PeerReviewed
    Format: text
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  • 30
    Publication Date: 2024-05-28
    Description: Until now, proxy records have been the primary tool for quantitative reconstructions of the physical world of the ancient and late antique Mediterranean. This chapter demonstrates the combined use of proxy datasets and the hitherto underutilized potential of earth system models in the scientific and historical study of past environmental variations and impacts on human societies. Results from model simulations are able to explain hydroclimatic anomalies observed in the proxy records and provide links to relevant mechanisms. The Late Roman Dry Period and the Late Roman Wet Period of the mid-fourth to early eighth centuries AD are each associated with the increase in the frequency of subsistence crises and with the accelerated infrastructural adaptations of communities and agricultural expansion, respectively. The chapter concludes with an examination of the historical and climatic contexts behind one such anomaly, a subsistence crisis in Cappadocia in the late 300s AD.
    Type: Book chapter , NonPeerReviewed
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  • 31
    Publication Date: 2024-05-28
    Type: Article , PeerReviewed
    Format: text
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  • 32
    Publication Date: 2024-05-28
    Description: Arabian Sea upwelling in the past has been generally studied based on the sediment records. We apply two earth system models and analyze the simulated water vertical velocity to investigate coastal upwelling in the western Arabian Sea over the last millennium. In addition, two models with slightly different configurations are also employed to study the upwelling in the 21st century under the strongest and the weakest greenhouse gas emission scenarios. With a negative long-term trend caused by the orbital forcing of the models, the upwelling over the last millennium is found to be closely correlated with the sea surface temperature, the Indian summer Monsoon and the sediment records. The future upwelling under the Representative Concentration Pathway (RCP) 8.5 scenario reveals a negative trend, in contrast with the positive trend displayed by the upwelling favorable along-shore winds. Therefore, it is likely that other factors, like water stratification in the upper ocean layers caused by the stronger surface warming, overrides the effect from the upwelling favorable wind. No significant trend is found for the upwelling under the RCP2.6 scenario, which is likely due to a compensation between the opposing effects of the increase in upwelling favorable winds and the water stratification.
    Type: Article , PeerReviewed
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  • 33
    Publication Date: 2024-05-28
    Description: We investigate the effects of solar forcing on the North Atlantic (NA) summer climate, in climate simulations with Earth System Models (ESMs), over the preindustrial past millennium (AD 850–1849). We use one simulation and a four-member ensemble performed with the MPI-ESM-P and CESM-LME models, respectively, forced only by low-scaling variations in Total Solar Irradiance (TSI). We apply linear methods (correlation and regression) and composite analysis to estimate the NA surface and tropospheric climatic responses to decadal solar variability. Linear methods in the CESM ensemble indicate a weak summer response in sea-level pressure (SLP) and 500-hPa geopotential height to TSI, with decreased values over Greenland and increased values over the NA subtropics. Composite analysis indicates that, during high-TSI periods, SLP decreases over eastern Canada and the geopotential height at 500-hPa increases over the subtropical NA. The possible summer response of SSTs is overlapped by model internal variability. Therefore, for low-scaling TSI changes, state-of-the-art ESMs disagree on the NA surface climatic effect of solar forcing indicated by proxy-based studies during the preindustrial millennium. The analysis of control simulations indicates that, in all climatic variables studied, spurious patterns of apparent solar response may arise from the analysis of single model simulations.
    Type: Article , PeerReviewed
    Format: text
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  • 34
    Publication Date: 2024-05-27
    Description: Ocean acidification (OA) appears to have diverse impacts on calcareous coccolithophores, but the cellular processes underlying these responses are not well understood. Here we use stable boron and carbon isotopes, B/Ca ratios, as well as inorganic and organic carbon production rates to investigate the carbon utilization and the internal pH regulation at the site of calcification in Emiliania huxleyi, Pleurochrysis carterae and Calcidiscus leptoporus cultured over a wide pCO2 range (180 to 1000 μatm). Despite large variability, the geochemistry data indicate species-specific modes of pH control and differences in the utilization of inorganic carbon. Boron isotope data suggest that all three species generally upregulate the pH of the calcification fluid (pHCF) compared to surrounding seawater, which coincides with relatively constant growth rates and cellular ratios of inorganic to organic carbon. Furthermore, species exhibit different strategies in regulating their pHCF, i.e., two species maintain homeostasis (pHCF = ∼ 8.7), while one species shows a constant offset to the surrounding seawater (ΔpH = ∼0.6 units) over the entire tested pCO2 range. In addition to these different strategies, carbon isotope data suggests that high plasticity in the utilization of dissolved inorganic carbon might be an explanation for species-specific differences in coccolithophore responses to OA.
    Keywords: Acid-base regulation; Alkalinity, total; Alkalinity, total, standard deviation; Aragonite saturation state; Bicarbonate ion; Biomass/Abundance/Elemental composition; Boron/Calcium ratio; Boron/Calcium ratio, standard deviation; Bottles or small containers/Aquaria (〈20 L); Calcidiscus leptoporus; Calcification/Dissolution; Calcifying fluid, pH; Calcifying fluid, pH, standard deviation; Calcite saturation state; Calculated using CO2SYS; Calculated using seacarb after Nisumaa et al. (2010); Carbon, inorganic, dissolved; Carbon, inorganic, dissolved, standard deviation; Carbon, inorganic, particulate, per cell; Carbon, inorganic, particulate, production per cell; Carbon, organic, particulate, per cell; Carbon, organic, particulate, production per cell; Carbon, organic, particulate, standard deviation; Carbonate ion; Carbonate system computation flag; Carbon dioxide; Chromista; Difference δ13C, particulate inorganic carbon and dissolved inorganic carbon; Difference δ13C, particulate inorganic carbon and dissolved inorganic carbon, standard deviation; Difference δ13C, particulate organic carbon and dissolved inorganic carbon; Difference δ13C, particulate organic carbon and dissolved inorganic carbon, standard deviation; Emiliania huxleyi; Fugacity of carbon dioxide (water) at sea surface temperature (wet air); Growth/Morphology; Growth rate; Growth rate, standard deviation; Haptophyta; Identification; Iron/Calcium ratio; Iron/Calcium ratio, standard deviation; Laboratory experiment; Laboratory strains; Magnesium/Calcium ratio; Magnesium/Calcium ratio, standard deviation; Not applicable; OA-ICC; Ocean Acidification International Coordination Centre; Other studied parameter or process; Partial pressure of carbon dioxide (water) at sea surface temperature (wet air); Particulate inorganic carbon/particulate organic carbon ratio; Particulate inorganic carbon/particulate organic carbon ratio, standard deviation; Particulate inorganic carbon per cell, standard deviation; Pelagos; pH; pH, difference; pH, difference, standard deviation; pH, standard deviation; Phytoplankton; Pleurochrysis carterae; Potentiometric; Potentiometric titration; Primary production/Photosynthesis; Registration number of species; Salinity; Single species; Species; Temperature, water; Temperature, water, standard deviation; Type; Uniform resource locator/link to reference; δ11B; δ11B, standard deviation; δ13C, dissolved inorganic carbon; δ13C, dissolved inorganic carbon, standard deviation; δ13C, particulate inorganic carbon; δ13C, particulate inorganic carbon, standard deviation; δ13C, particulate organic carbon; δ13C, particulate organic carbon, standard deviation
    Type: Dataset
    Format: text/tab-separated-values, 1945 data points
    Location Call Number Expected Availability
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  • 35
    Publication Date: 2024-05-27
    Description: A literature retrieval was performed for whole rock geochemical analyses of sedimentary, magmatic and metamorphic rocks in the catchment of River Thuringian Saale for the past 600 Ma. Considering availability and coincidence with paleontological an facies data the following indicators seem suitable to detect environmental and climatic changes: biogenic P for Paleoproductivity, STI Index for weathering intensity, Ni/Co-ratio for redox conditions, relative enrichments of Co, Ba and Rb versus crustal values for volcanic activity at varying differentiation. The Mg/Ca-ratio as proxy for salinity is applicable in evaporites. The binary plot Nb/Y versus Zr/TiO2 indicates a presently eroded volcanic level of the Bohemian Massif as catchment area for the Middle Bunter, whereas higly differentiated volcanics provided source material for Neoproterozoic greywackes. A positive Eu-anomaly is limited to the Lower Bunter and implies mafic source rocks perhaps formerly located in the Bohemian Massif.
    Keywords: AGE; Aluminium; Aluminium oxide; Antimony; Arsenic; Barium; Beryllium; Bismuth; Boron; Cadmium; Caesium; Calcium; Calcium oxide; Carbon, organic, total; Carbon, total; Carbon dioxide; Cerium; Chlorine; Chromium; Cobalt; Copper; Dysprosium; environmental change; Erbium; Europium; Gadolinium; Gallium; Germanium; Gold; Hafnium; Holmium; Indium; inorganic geochemistry; Iodine; Iron; Iron oxide, Fe2O3; Iron oxide, FeO; Lanthanum; Lead; Lithium; Loss on ignition; Lutetium; Magnesium; Magnesium oxide; Manganese; Manganese oxide; Median values; Mercury; Molybdenum; MULT; Multiple investigations; Neodymium; Nickel; Niobium; Nitrogen, total; Number of analyses; Palladium; Phosphorus; Phosphorus pentoxide; Platinum; Potassium; Potassium oxide; Praseodymium; provenance study; proxies; Recalculated; Rhenium; Rubidium; Saale; Saale catchment; Samarium; Scandium; Selenium; Silicon; Silicon dioxide; Silver; Sodium; Sodium oxide; Stratigraphy; Strontium; Sulfur, total; Sulfur trioxide; Tantalum; Tellurium; Terbium; Thallium; Thorium; Thulium; Tin; Titanium; Titanium dioxide; Tungsten; Uranium; Vanadium; Water in rock; Ytterbium; Yttrium; Zinc; Zirconium
    Type: Dataset
    Format: text/tab-separated-values, 2994 data points
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  • 36
    Publication Date: 2024-05-27
    Description: Extreme rainfall generated by storms and atmospheric instability causes innumerable damage to coastal areas and their marine ecosystems. This chapter describes some of the processes that generate critical precipitation events in coastal areas. Among these, the typical synoptic conditions combine with the increase in sea surface temperature and air temperature, coastal geomorphology, and sea breeze. Coastal and regional rainfall events should be studied to understand the meteorological, oceanographic, and geomorphological conditions that cause the extreme events, to later relate them with the consequences on coasts. The effects of the interaction of storms with tides originating storm surges and the effect of sea-level rise are described as well as the main consequences of extreme rainfall events such as beach erosion, decrease in water quality, changes in plankton and fish species that inhabit coastal waters, among others.
    Type: Book chapter , PeerReviewed
    Format: text
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  • 37
    Publication Date: 2024-05-25
    Description: This dataset contains occurrence records (i.e., species name, latitude, longitude, depth (where available), and metadata) for six species of the demosponge genus Geodia Lamarck, 1815, belonging to the Geodiidae family: Geodia atlantica (Stephens, 1915); Geodia barretti Bowerbank, 1858; Geodia macandrewii Bowerbank, 1858; Geodia phlegraei (Sollas, 1880); Geodia hentscheli Cárdenas et al. 2010; and Geodia parva Hansen, 1885. The records fall in the North Atlantic and Arctic Oceans, and are used/described in the linked article by Roberts et al. (2021). Note that the dataset provided has not been subjected to any of the filtering stages applied in that manuscript for the purposes of various novel biogeographical analyses (i.e., it is original and complete), and the taxonomic identifications have been rigorously checked (as described therein). Definitions of institution abbreviations used in the 'Museum Specimen / Picture Information' column of the dataset spreadsheet have been provided in an accompanying table (see Comment field below). Where records are derived from earlier literature sources, full references for citations given in the 'Campaign / Source' column (and further general information on many of the records) may be found in the articles by Cárdenas et al. (2010; 2013) and Cárdenas & Rapp (2015). An earlier version of this dataset may be accessed at the DRYAD repository: Cárdenas P, Rapp HT, Klitgaard AB, Best M, Thollesson M, Tendal OS (2013), Data from: Taxonomy, biogeography and DNA barcodes of Geodia species (Porifera, Demospongiae, Tetractinellida) in the Atlantic boreo-arctic region, Dryad, Dataset, doi:10.5061/dryad.td8sb
    Keywords: 87PA0028; 87PA0067; 87PA0078; 92PA0160002; 92PA0160005; 92PA0160014; 92PA0160028; 92PA0160050; 92PA0160052; 94PA0090001; 94PA0090002; 94PA0090009; 94PA0090010; 94PA0090019; 94PA0090020; 94PA0090026; 94PA0090039; 94PA0090041; 94PA0090043; 94PA0090045; 94PA0090049; 94PA0090062; Agassiz Trawl; AGT; Arctic Ocean; ARK-VII/2; ARK-XXII/1a; Barents Sea; BEAM; Beam trawl; BIODEEP2007_Dredge2; BIODEEP2007_ROV10; BIODEEP2007_ROV9; BIOFAR_St117; BIOFAR_St119; BIOFAR_St120; BIOFAR_St122; BIOFAR_St234; BIOFAR_St279; BIOFAR_St287; BIOFAR_St297; BIOFAR_St298; BIOFAR_St375; BIOFAR_St379; BIOFAR_St389; BIOFAR_St43; BIOFAR_St451; BIOFAR_St452; BIOFAR_St486; BIOFAR_St487; BIOFAR_St498; BIOFAR_St526; BIOFAR_St530; BIOFAR_St531; BIOFAR_St535; BIOFAR_St540; BIOFAR_St550; BIOFAR_St69; BIOFAR_St734; BIOFAR_St756; BIOFAR_St89; BIOFAR_St901; BIOICE_St2022; BIOICE_St2023; BIOICE_St2218; BIOICE_St2292; BIOICE_St2293; BIOICE_St2368; BIOICE_St2374; BIOICE_St2499; BIOICE_St2501; BIOICE_St2516; BIOICE_St2518; BIOICE_St2700; BIOICE_St2728; BIOICE_St2747; BIOICE_St2756; BIOICE_St2768; BIOICE_St2769; BIOICE_St2923; BIOICE_St2926; BIOICE_St2928; BIOICE_St3227; BIOICE_St3659; BIOICE_St3661; BIOSKAG2006_St20; BIOSYS2006_DR182; BIOSYS2006_VG20-1; Blacker1957_11; Blacker1957_130; Blacker1957_131; Blacker1957_14; Blacker1957_16; Blacker1957_164; Blacker1957_165; Blacker1957_168; Blacker1957_20; Blacker1957_21; Blacker1957_22; Blacker1957_24; Blacker1957_25; Blacker1957_27; Blacker1957_28; Blacker1957_33; Blacker1957_35; Blacker1957_36; Blacker1957_44; Blacker1957_45; Blacker1957_46; Blacker1957_53; Blacker1957_55; Blacker1957_56; Blacker1957_60; Blacker1957_61; Blacker1957_62; Blacker1957_68; Blacker1957_75; Blacker1957_8; Blacker1957_80; Blacker1957_81; Blacker1957_84; Blacker1957_9; Blacker1957_94; BMT19; Boury-Esnaultetal1994_CP62; Boury-Esnaultetal1994_CP63; Boury-Esnaultetal1994_CP92; Boury-Esnaultetal1994_CP98; Bowerbank1872a_Vikna; Bowerbank1872aPlateXI_Vikna; Brattholmen_St230407; Breitfuss1930_St1237; Breitfuss1930_St1347; Breitfuss1930_St1385; Burton1934_St548; Burton1959_EIceland; Burton1959_SEIceland; Campaign; CD80_St178; CD80_St18; CD80_St91; CE13008; CE13008_ROV32; CE2008-11_M11GHaul22; CE2008-11_M11GHaul23; Celtic Explorer; Celtic Sea; CENTOBBiogasII_DS33; CGB2011_11c-16-DR01; CGB2011_11c-19-ROV05; CGB2011_11c-30-DR05; CGB2011_11c-31-DR06; Comment; CorSeaCan_B12_CG_ACH_P01_20100809; CorSeaCan_B13_MOI-ACH-P06; CV13012_51; Dana_St6001; Davis Strait; Deep-sea Sponge Grounds Ecosystems of the North Atlantic; Depth, bottom/max; Depth, top/min; DEPTH, water; Dyrelivihavet2008_SandsfjordRogaland; E17044_SP17E44001; EBS; EcosystemBarentsSea2007_St2562; Epibenthic sledge; Event label; FRVScotia2012_S12_469; FRVScotia2012_S12/469; FRVScotia2012_S12-469; G. O. Sars (2003); Giant box corer; GKG; Greenland Sea; GS06/112; GS112_BMT19; GS14; GS14-AGT03; GS14-AGT07; GS14-DR02; GS14-DR09; GS14-DR12; H2DEEP2008_ROV5; HakonMosby_St237; HakonMosby_St242; HakonMosby_St245; HakonMosby_St86072701; HakonMosby_St93060602; HakonMosby_St93060612; HakonMosby_St93060613; HakonMosby_St93061106; Hentschel1929_St40; Hentschel1929_St41; Hentschel1929_St42; Howelletal2010_WSC11; Howelletal2010_WSCE10B; Howelletal2010_WSCE3; Howelletal2010_WSCE4; HUD2007-025_DiveR1059; HUD2010-029; HUD2010-029_R1335; HUD2010-029_R1336-07; HUD2010-029_R1339-10; HUD2010-029_R1340-12; HUD2010-029_R1340-4; HUD2010-029_R1341-18; HUD2013/29; HUD2013-029_DS1-I; Hudson; Iceland Sea; Identification; IngolfExpdt_St1; IngolfExpdt_St125; IngolfExpdt_St21; IngolfExpdt_St78; IngolfExpdt_St90; IngolfExpdt_St92; JAGO; Kara Sea; Kingstonetal1979_LabradorCoast; Koltun1964_St1; Koltun1964_St10; Koltun1964_St11; Koltun1964_St26; Koltun1964_St46; Koltun1964_St7; Koltun1964_St8; Koltun1964_St9; Koltun1966_NofFranzJosephLand; Koltun1966_NofKaraSea; Koltun1966_NWofLaptevSea; Labrador Sea; Langenuen_SteinnesetSt31; Laptev Sea; LATITUDE; LONGITUDE; Lundbeck1909_Angmagsalik; Lynch_St1971; Lynch_St1972; Lynch_St1973; Lynch_St721008; Lysefjord_Uksen; M85/3; M85/3_1123; M85/3_1132; M85/3_1136; M85/3_1219; M85/3_1223; MA0200057_St90; MagnusHeinason_St150990; MAR310_St1; Mareano_StR228-12; Mareano_StR262VL282; Mareano_StR828; Mareano_StR863; Mareano2009_StR469VL491; Mareano2011_StR729VL756; Mareano2011_StR731VL759; Mareano2011_StR744VL772; Mareano2011_StR758VL786; MAR-Eco2004_St50-373; MAR-Eco2004_St70_385; MAR-Eco2004_St70-385; MAR-Eco2004_St72-386; MedSeaCan_B7_MG_PO2_20090523; MedSeaCan_B7_PA_ACH_P02_20090519; Meteor (1986); More2005_St46; MULT; Multiple investigations; NEREIDA0609_BC89; NEREIDA0710_BC237; Nereida2009-2010_BC04; Nereida2009-2010_DR04-001; Nereida2009-2010_DR07-025; Nereida2009-2010_DR10; Nereida2009-2010_DR12; Nereida2009-2010_DR18; Nereida2009-2010_DR19; Nereida2009-2010_DR20; Nereida2009-2010_DR22; Nereida2009-2010_DR23; Nereida2009-2010_DR24; Nereida2009-2010_DR3; Nereida2009-2010_DR32; Nereida2009-2010_DR38; Nereida2009-2010_DR4; Nereida2009-2010_DR6; Nereida2009-2010_DR64; Nereida2009-2010_DR66; Nereida2009-2010_DR7; Nereida2009-2010_DR70; Nereida2009-2010_DR70_BOTTOM; Nereida2009-2010_DR74; Nereida2009-2010_DR74_BOTTOM; North Greenland Sea; North Sea; Norwegian Sea; PA2010-009_Set075; PA2010-009_Set104; PA2010-009_Set105; PA2010-009_Set108; PA2010-009_Set109; PA2010-009_Set111; PA2010-009_Set113; PA2010-009_Set114; PA2010-009_Set115; PA2010-009_Set116; PA2010-009_Set126; PA2010-009_Set141; PA2010-009_Set155; PA2010-009_Set156; PA2010-009_Set157; PA2010-009_Set159; PA2010-009_Set160; PA2010-009_Set161; PA2010-009_Set162; PA2010-009_Set163; PA2010-009_Set164; PA2010-009_Set167; PA2010-009_Set168; PAA2011007; PAA2011007_127_39; PAA2011007_225_114; PAA2011007_255_126; PAA2011007_262_128; PAA2011007_533_23; PAA2011007_634_139; PAA2013008; PAA2013008_157_44; PAA2013008_169_46; PAA2013008_174_47; PAA2013008_176_48; PAA2013008_177_50; PAA2013008_302_141; PAA2013008_305_142; PAA2013008_31_10; PAA2014007; PAA2014007_278_125; PAA2014007_286_127; PAA2014007_321_136; PAA2014007_514_152; PAA2015007; PAA2015007_126_32; PAA2015007_289_60; PAA2015007_299_62; PAA2015007_303_64; Paamiut; Polarstern; PS17; PS17/223; PS70; PS70/002-2; PS70/006-1; PS70/014-4; PS70/015-1; PS70/016-1; PS70/027-1; PS70/040-4; RVMichaelSars_St102; RVMichaelSars_St76; RVMichaelSars_St85; S10176_SP10176001; S11073_SP11073001; S11471_SP11471001; S12135_SP12135001; S12444_SP12444001; S12446_SP12446001; S12447; S15A13; S16185_SP16185001; S16379_SP16379003; S16A03_SP16A03017; S16A03_SP16A03029; S16A03_SP16A03039; S16A03_SP16A03041; S18A02; S18A03; Scotland Sea; ShinkaiMaru_St004; ShinkaiMaru_St109; ShinkaiMaru_St110; ShinkaiMaru_St15; ShinkaiMaru_St18; ShinkaiMaru_St1976; ShinkaiMaru_St21; ShinkaiMaru_St26; ShinkaiMaru_St29; ShinkaiMaru_St3; ShinkaiMaru_St32; ShinkaiMaru_St43; ShinkaiMaru_St50; ShinkaiMaru_St63; ShinkaiMaru_St70; ShinkaiMaru_St79; ShinkaiMaru_St9; ShinkaiMaru1987_St104; ShinkaiMaru1987_St67; Skagerrak; South Atlantic Ocean; Species; SponGES; St89SI0240086; Station label; Submersible JAGO; SwedishArcticExp1871_St37; T0406066; T8903301; T8905093; T8905125; T8905127; T8905185; T9405259; T9405264; T9405276; T9405305; T9405315; T9405317; T9406031; T9406032; T9406036; T9406066; ThalassaZ_Z407; ThalassaZ_Z408; Traena Deep; Trollholmflua; Tromso_Haugbernes; Western Basin; WH_St569; WH47566; WH47572; ZoolPolarExp1900_St30
    Type: Dataset
    Format: text/tab-separated-values, 2307 data points
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  • 38
    Publication Date: 2024-05-24
    Description: In the marine realm, microorganisms are responsible for the bulk of primary production, thereby sustaining marine life across all trophic levels. Longhurst provinces have distinct microbial fingerprints; however, little is known about how microbial diversity and primary productivity change at finer spatial scales. Here, we sampled the Atlantic Ocean from south to north (~50°S–50°N), every ~0.5° latitude. We conducted measurements of primary productivity, chlorophyll-a and relative abundance of 16S and 18S rRNA genes, alongside analyses of the physicochemical and hydrographic environment. We analysed the diversity of autotrophs, mixotrophs and heterotrophs, and noted distinct patterns among these guilds across provinces with high and low chlorophyll-a conditions. Eukaryotic autotrophs and prokaryotic heterotrophs showed a shared inter-province diversity pattern, distinct from the diversity pattern shared by mixotrophs, cyanobacteria and eukaryotic heterotrophs. Additionally, we calculated samplewise productivity-specific length scales, the potential horizontal displacement of microbial communities by surface currents to an intrinsic biological rate (here, specific primary productivity). This scale provides key context for our trophically disaggregated diversity analysis that we could relate to underlying oceanographic features. We integrate this element to provide more nuanced insights into the mosaic-like nature of microbial provincialism, linking diversity patterns to oceanographic transport through primary production.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , peerRev
    Format: application/pdf
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  • 39
    Publication Date: 2024-05-24
    Description: The St1 Deep Heat Project was started in 2014 by the Finnish energy companies St1 and Fortum. This site is at Fortum's district heating plant at the Aalto University campus, west of Helsinki. The project began with the drilling of a cored 2015 m pilot hole, which encountered a few meters of alluvium over the expected crystalline basement. Follow-on ~6000 m deviated injection-andproduction wells were completed in 2018 and 2020. These wells were extensively logged, and the deep wells were stimulated after completion. In Oct 2018 the ~2500 m to ~5000 m vertical portion of the injection well was profiled with the GFZ German Geoscience Center 17 level, 10 m spaced Sercel borehole geophone array (a Vertical Seismic Profile - VSP). Near-surface shots at 4 offset and 1 near-well shot-points were used as sources. These data were analyzed and compared to (a) drilling data, (b) logging data, (c) surface geology, and (d) a short run of Seismic While Drilling (SWD) data recorded in the pilot hole using hammer-drill signals from the production hole. The VSP data establishes that a seismic velocity reversal - from a P-velocity of ~6.5 to ~6.1 km/s - extends from ~3000 m down at least to the bottom VSP position at 5000 m and is also seen in the well logs. Aside from several shallower structures, the most significant reflection feature found in these data is a ~400 m thick horizon that intersects the ~6000 m wells at ~5000 m. This horizon includes internal reflections that appear to correlate with a drilling-encountered and loginterpreted fracture zone. Owing to complex surrounding velocity structure, this feature's lateral continuation and ultimate attitude have been difficult to resolve. In one interpretation it appears as a 45 ENE dipping extension of a shallower reflector seen in the SWD data. The productionwell's trajectory was based on this interpretation - which drilling seems to confirm. Its consequences for the EGS project will be tested with a circulation campaign over the next months.
    Type: info:eu-repo/semantics/conferenceObject
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  • 40
    Publication Date: 2024-05-24
    Description: Large-scale physics-based groundwater flow models are indispensable tools to contribute to an understanding required to manage our present and future water resources. For instance, large finite-element-based models can encompass up to 108 finite elements and require high performance computing environments to run. To effectively use such models for prediction and scenario analysis, proper calibrations against observation data are required. For calibration, two major challenges arise: 1) the high amount of time and computational resources required for the numerous model runs, and, 2) the high complexity of parameter optimization for heterogeneous domains that translates into multiple potentially suitable calibrations. Here, we provide a solution by integrating data science methods for meta modeling with Bayesian optimization and visual analytics into calibration workflows for physics-based groundwater flow models. With the open source simulator OpenGeoSys we developed a virtual aquifer (VA) model that serves as ground truth. From this we derived groundwater flow models with perturbed parameters for calibration. In our calibration method, we use machine-learning algorithms (e.g. Gaussian process regression) to build fast meta (surrogate) models of the physics-based groundwater flow model in order to explore the calibration parameter space in a step-wise interactive Bayesian optimization routine. In this routine, visual analytic tools (e.g. GCex) provide insights into the calibration progress and parameter sensitivities, which allow the modeler to analyze potential solutions and/or adjusting further steps in the optimization routine. In this way we are able to effectively combine the modelers expert knowledge with an intelligent parameter optimization strategy that allows the calibration of large and complex groundwater flow models with a minimum of computational resources.
    Type: info:eu-repo/semantics/conferenceObject
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  • 41
    Publication Date: 2024-05-24
    Description: The presented dataset contains chamber measurements of methane transport (mg CH₄ g dry plant mass-1 day-1) through individual aerenchymous peatland plants and the ancillary data for these measurements. Chamber measurements were performed for 7 plant species at two peatland sites, an oligotrophic fen and an ombrotrophic bog part of Siikaneva peatland complex in Southern Finland (61.8249° N, 24.1390° E, altitude 170 m a.s.l.) , during growing seasons 2013 and 2014 (between 1st of May and 28th of October). The ancillary data contains measurements of water table depth from the moss surface, air and peat temperature during the measurement as well as leaf area, dry mass of plant material, specific leaf area, number of leaves and the proportion of brown leaves in each sample that was measured. The dataset was collected to quantify the impact of plant species, plant properties and environmental factors on methane transport through aerenchymous plants. Plant CH₄ transport rate was measured using custom-made cylinder-shaped chambers that varied in volume between 0.7 and 5.0 liters. A plant sample of 2–104 leaves (depending on the growth form of the measured plant) belonging to the same species was separated from the peat and moss underneath by two plexiglass plates that were attached together with a hinge and had a smooth rubber seal between them to avoid compression of the plant. The proportion of green leaves in the sample varied from 0 to 100 % depending on the phase of the growing season. The sample was then covered with an opaque plastic chamber that was sealed with the plate by a smooth rubber seal attached to the bottom of the chamber. Airtightness of the system was ensured by tightening a belt that extended from one plate to the other over the chamber. Finally, a rubber stopper was used to seal a vent hole in the top of the chamber. Each plant sample was measured for 35 minutes, during which four 20 ml air samples were drawn from the chamber with a syringe through the rubber stopper in the top of the chamber at 5, 15, 25 and 35 minutes after chamber closure. The air samples were then injected into evacuated 12 ml glass vials (Labco Limited, UK). Simultaneous to the flux measurements, temperatures in the chamber (air) and peat at 5, 15 and 30 cm depth were recorded. WT was measured from a perforated plastic tube installed into the peat next to the sample after the WT level in the tube had stabilized for at least 30 minutes. After the flux measurement, the plant sample was cut with scissors and transported to the laboratory in a plastic bag. In each plant sample, the number of leaves was counted, the leaf area of brown and green leaf parts was measured with a scanner, and the dry weight was obtained for brown and green leaf parts separately after oven drying the sample at 60 °C for 24 hours. Using these data, specific leaf area (SLA, m²/g) was calculated for each sample. CH₄ concentration in the glass vials was analyzed with an Agilent Technologies 7890A gas chromatograph and Gilson GX-271 liquid handler. The CH₄ flux was calculated as the linear change in CH~4~ concentration in relation to time, chamber volume and temperature. Nonlinear changes in CH₄ concentration that were visually detected, were surmised to have resulted from a leak in the chamber or in the vial and were excluded from the analysis. In total 6 % of the measurements were excluded from the final dataset due to such nonlinearities.
    Keywords: Aerenchymous_peatland_plants-experiment; aerenchymous plant; Brown leaf area/leaf area, total, ratio; DATE/TIME; Day of the year; Gas chromatography on an Agilent Technologies 7890A GC; Green plant, biomass as dry weight; In situ incubation chamber; ISCHAM; Leaf area; Methane efflux, CH4, per dry mass plant; Methane emissions; Methane flux; Number of leaves; Peatland; Plant; Plant, biomass as dry weight; Sample code/label; sedge; Site; Southern Finland; Specific leaf area; Temperature, air; Temperature, peat; Water table depth; wetland
    Type: Dataset
    Format: text/tab-separated-values, 9026 data points
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  • 42
    facet.materialart.
    Unknown
    PANGAEA
    In:  Meteorology Climatology Remote Sensing, Dep. Umweltwissenschaften, Universität Basel
    Publication Date: 2024-05-24
    Description: In Gobabeb, Namibia SWD, LWD and DIR are each measured redundant with two instruments of the same make (not in this data base). The differences between the pairs are used in the quality control. This is done manually by inspecting plots of half-day diurnal courses of the pairs and their differences. Values are removed mostly in the morning due to daily cleaning. Other reasons for larger differences are birds, insects, or people at the station. There are regular fog events varying in frequency over the year. Usually, the fog appears in the second half of the night and disappears a few hours after sunrise. The case temperatures of pyrgeometers practically never drop below dewpoint but there can be water deposition of the dome.
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, standard deviation; GOB; Gobabeb; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; Long-wave downward radiation; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Monitoring station; MONS; Namib Desert, Namibia; Pyranometer, Kipp & Zonen, CMP22, SN 110315, WRMC No. 20100; Pyranometer, Kipp & Zonen, CMP22, SN 110316, WRMC No. 20101; Pyranometer, Kipp & Zonen, CMP22, SN 120330, WRMC No. 20102; Pyrgeometer, Kipp & Zonen, CGR4, SN 110408, WRMC No. 20200; Pyrgeometer, Kipp & Zonen, CGR4, SN 120457, WRMC No. 20201; Pyrheliometer, Kipp & Zonen, CHP 1, SN 110764, WRMC No. 20000; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Station pressure; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 561328 data points
    Location Call Number Expected Availability
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  • 43
    facet.materialart.
    Unknown
    PANGAEA
    In:  Meteorology Climatology Remote Sensing, Dep. Umweltwissenschaften, Universität Basel
    Publication Date: 2024-05-24
    Description: In Gobabeb, Namibia SWD, LWD and DIR are each measured redundant with two instruments of the same make (not in this data base). The differences between the pairs are used in the quality control. This is done manually by inspecting plots of half-day diurnal courses of the pairs and their differences. Values are removed mostly in the morning due to daily cleaning. Other reasons for larger differences are birds, insects, or people at the station. There are regular fog events varying in frequency over the year. Usually, the fog appears in the second half of the night and disappears a few hours after sunrise. The case temperatures of pyrgeometers practically never drop below dewpoint but there can be water deposition of the dome.
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, standard deviation; GOB; Gobabeb; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; Long-wave downward radiation; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Monitoring station; MONS; Namib Desert, Namibia; Pyranometer, Kipp & Zonen, CMP22, SN 110315, WRMC No. 20100; Pyranometer, Kipp & Zonen, CMP22, SN 110316, WRMC No. 20101; Pyranometer, Kipp & Zonen, CMP22, SN 120330, WRMC No. 20102; Pyrgeometer, Kipp & Zonen, CGR4, SN 110408, WRMC No. 20200; Pyrgeometer, Kipp & Zonen, CGR4, SN 120457, WRMC No. 20201; Pyrheliometer, Kipp & Zonen, CHP 1, SN 110764, WRMC No. 20000; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Station pressure; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 580044 data points
    Location Call Number Expected Availability
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  • 44
    facet.materialart.
    Unknown
    PANGAEA
    In:  Meteorology Climatology Remote Sensing, Dep. Umweltwissenschaften, Universität Basel
    Publication Date: 2024-05-24
    Description: In Gobabeb, Namibia SWD, LWD and DIR are each measured redundant with two instruments of the same make (not in this data base). The differences between the pairs are used in the quality control. This is done manually by inspecting plots of half-day diurnal courses of the pairs and their differences. Values are removed mostly in the morning due to daily cleaning. Other reasons for larger differences are birds, insects, or people at the station. There are regular fog events varying in frequency over the year. Usually, the fog appears in the second half of the night and disappears a few hours after sunrise. The case temperatures of pyrgeometers practically never drop below dewpoint but there can be water deposition of the dome.
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, standard deviation; GOB; Gobabeb; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; Long-wave downward radiation; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Monitoring station; MONS; Namib Desert, Namibia; Pyranometer, Kipp & Zonen, CMP22, SN 110315, WRMC No. 20100; Pyranometer, Kipp & Zonen, CMP22, SN 110316, WRMC No. 20101; Pyranometer, Kipp & Zonen, CMP22, SN 120330, WRMC No. 20102; Pyrgeometer, Kipp & Zonen, CGR4, SN 110408, WRMC No. 20200; Pyrgeometer, Kipp & Zonen, CGR4, SN 120457, WRMC No. 20201; Pyrheliometer, Kipp & Zonen, CHP 1, SN 110764, WRMC No. 20000; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Station pressure; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 580187 data points
    Location Call Number Expected Availability
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  • 45
    facet.materialart.
    Unknown
    PANGAEA
    In:  Meteorology Climatology Remote Sensing, Dep. Umweltwissenschaften, Universität Basel
    Publication Date: 2024-05-24
    Description: In Gobabeb, Namibia SWD, LWD and DIR are each measured redundant with two instruments of the same make (not in this data base). The differences between the pairs are used in the quality control. This is done manually by inspecting plots of half-day diurnal courses of the pairs and their differences. Values are removed mostly in the morning due to daily cleaning. Other reasons for larger differences are birds, insects, or people at the station. There are regular fog events varying in frequency over the year. Usually, the fog appears in the second half of the night and disappears a few hours after sunrise. The case temperatures of pyrgeometers practically never drop below dewpoint but there can be water deposition of the dome.
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, standard deviation; GOB; Gobabeb; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; Long-wave downward radiation; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Monitoring station; MONS; Namib Desert, Namibia; Pyranometer, Kipp & Zonen, CMP22, SN 110315, WRMC No. 20100; Pyranometer, Kipp & Zonen, CMP22, SN 110316, WRMC No. 20101; Pyranometer, Kipp & Zonen, CMP22, SN 120330, WRMC No. 20102; Pyrgeometer, Kipp & Zonen, CGR4, SN 110408, WRMC No. 20200; Pyrgeometer, Kipp & Zonen, CGR4, SN 120457, WRMC No. 20201; Pyrheliometer, Kipp & Zonen, CHP 1, SN 110764, WRMC No. 20000; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Station pressure; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 524000 data points
    Location Call Number Expected Availability
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  • 46
    facet.materialart.
    Unknown
    PANGAEA
    In:  Meteorology Climatology Remote Sensing, Dep. Umweltwissenschaften, Universität Basel
    Publication Date: 2024-05-24
    Description: In Gobabeb, Namibia SWD, LWD and DIR are each measured redundant with two instruments of the same make (not in this data base). The differences between the pairs are used in the quality control. This is done manually by inspecting plots of half-day diurnal courses of the pairs and their differences. Values are removed mostly in the morning due to daily cleaning. Other reasons for larger differences are birds, insects, or people at the station. There are regular fog events varying in frequency over the year. Usually, the fog appears in the second half of the night and disappears a few hours after sunrise. The case temperatures of pyrgeometers practically never drop below dewpoint but there can be water deposition of the dome.
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, standard deviation; GOB; Gobabeb; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; Long-wave downward radiation; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Monitoring station; MONS; Namib Desert, Namibia; Pyranometer, Kipp & Zonen, CMP22, SN 110315, WRMC No. 20100; Pyranometer, Kipp & Zonen, CMP22, SN 110316, WRMC No. 20101; Pyranometer, Kipp & Zonen, CMP22, SN 120330, WRMC No. 20102; Pyrgeometer, Kipp & Zonen, CGR4, SN 110408, WRMC No. 20200; Pyrgeometer, Kipp & Zonen, CGR4, SN 120457, WRMC No. 20201; Pyrheliometer, Kipp & Zonen, CHP 1, SN 110764, WRMC No. 20000; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Station pressure; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 561050 data points
    Location Call Number Expected Availability
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  • 47
    facet.materialart.
    Unknown
    PANGAEA
    In:  Meteorology Climatology Remote Sensing, Dep. Umweltwissenschaften, Universität Basel
    Publication Date: 2024-05-24
    Description: In Gobabeb, Namibia SWD, LWD and DIR are each measured redundant with two instruments of the same make (not in this data base). The differences between the pairs are used in the quality control. This is done manually by inspecting plots of half-day diurnal courses of the pairs and their differences. Values are removed mostly in the morning due to daily cleaning. Other reasons for larger differences are birds, insects, or people at the station. There are regular fog events varying in frequency over the year. Usually, the fog appears in the second half of the night and disappears a few hours after sunrise. The case temperatures of pyrgeometers practically never drop below dewpoint but there can be water deposition of the dome.
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, standard deviation; GOB; Gobabeb; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; Long-wave downward radiation; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Monitoring station; MONS; Namib Desert, Namibia; Pyranometer, Kipp & Zonen, CMP22, SN 110315, WRMC No. 20100; Pyranometer, Kipp & Zonen, CMP22, SN 110316, WRMC No. 20101; Pyranometer, Kipp & Zonen, CMP22, SN 120330, WRMC No. 20102; Pyrgeometer, Kipp & Zonen, CGR4, SN 110408, WRMC No. 20200; Pyrgeometer, Kipp & Zonen, CGR4, SN 120457, WRMC No. 20201; Pyrheliometer, Kipp & Zonen, CHP 1, SN 110764, WRMC No. 20000; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Station pressure; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 580078 data points
    Location Call Number Expected Availability
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  • 48
    facet.materialart.
    Unknown
    PANGAEA
    In:  Meteorology Climatology Remote Sensing, Dep. Umweltwissenschaften, Universität Basel
    Publication Date: 2024-05-24
    Description: In Gobabeb, Namibia SWD, LWD and DIR are each measured redundant with two instruments of the same make (not in this data base). The differences between the pairs are used in the quality control. This is done manually by inspecting plots of half-day diurnal courses of the pairs and their differences. Values are removed mostly in the morning due to daily cleaning. Other reasons for larger differences are birds, insects, or people at the station. There are regular fog events varying in frequency over the year. Usually, the fog appears in the second half of the night and disappears a few hours after sunrise. The case temperatures of pyrgeometers practically never drop below dewpoint but there can be water deposition of the dome.
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, standard deviation; GOB; Gobabeb; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; Long-wave downward radiation; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Monitoring station; MONS; Namib Desert, Namibia; Pyranometer, Kipp & Zonen, CMP22, SN 110315, WRMC No. 20100; Pyranometer, Kipp & Zonen, CMP22, SN 110316, WRMC No. 20101; Pyranometer, Kipp & Zonen, CMP22, SN 120330, WRMC No. 20102; Pyrgeometer, Kipp & Zonen, CGR4, SN 110408, WRMC No. 20200; Pyrgeometer, Kipp & Zonen, CGR4, SN 120457, WRMC No. 20201; Pyrheliometer, Kipp & Zonen, CHP 1, SN 110764, WRMC No. 20000; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Station pressure; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 561280 data points
    Location Call Number Expected Availability
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  • 49
    Publication Date: 2024-05-24
    Description: This study simulated a 9-months warming scenario on the common seagrass Zostera marina from winter into summer (December 2015 - August 2016) in the Western Baltic Sea (Kiel Fijord), using outdoor mesocosms. Two treatments were applied: Ambient temperature regime (Ambient) and Ambient + 3.6C (Heat) over the entire course of the experiment. Temperature regimes were compared to the 22-year temperature average in the area. This dataset shows monthly chlorophyll-a and beta-carotene concentration of one shoot per box. Unit is µg per mg of leaf dry weight. The organization of the data is hierarchical: Treatment (Heat, Ambient), Benthocosms number (6 benthocosms per treatment), Seagrass box number (4 boxes per benthocosm).
    Keywords: Benthocosm_A1; Benthocosm_A2; Benthocosm_B1; Benthocosm_B2; Benthocosm_C1; Benthocosm_C2; Benthocosm_D1; Benthocosm_D2; Benthocosm_E1; Benthocosm_E2; Benthocosm_F1; Benthocosm_F2; beta-Carotene, per dry mass; Chlorophyll a, per dry mass; DATE/TIME; Event label; flowering; Identification; Kiel Fjord; MESO; Mesocosm experiment; Seagrass; seasonality; Sea surface temperature rise; Species; thermal tolerance; Treatment; winter warming; Zostera marina
    Type: Dataset
    Format: text/tab-separated-values, 1906 data points
    Location Call Number Expected Availability
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  • 50
    facet.materialart.
    Unknown
    PANGAEA
    In:  Meteorology Climatology Remote Sensing, Dep. Umweltwissenschaften, Universität Basel
    Publication Date: 2024-05-24
    Description: In Gobabeb, Namibia SWD, LWD and DIR are each measured redundant with two instruments of the same make (not in this data base). The differences between the pairs are used in the quality control. This is done manually by inspecting plots of half-day diurnal courses of the pairs and their differences. Values are removed mostly in the morning due to daily cleaning. Other reasons for larger differences are birds, insects, or people at the station. There are regular fog events varying in frequency over the year. Usually, the fog appears in the second half of the night and disappears a few hours after sunrise. The case temperatures of pyrgeometers practically never drop below dewpoint but there can be water deposition of the dome.
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, standard deviation; GOB; Gobabeb; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; Long-wave downward radiation; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Monitoring station; MONS; Namib Desert, Namibia; Pyranometer, Kipp & Zonen, CMP22, SN 110315, WRMC No. 20100; Pyranometer, Kipp & Zonen, CMP22, SN 110316, WRMC No. 20101; Pyranometer, Kipp & Zonen, CMP22, SN 120330, WRMC No. 20102; Pyrgeometer, Kipp & Zonen, CGR4, SN 110408, WRMC No. 20200; Pyrgeometer, Kipp & Zonen, CGR4, SN 120457, WRMC No. 20201; Pyrheliometer, Kipp & Zonen, CHP 1, SN 110764, WRMC No. 20000; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Station pressure; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 537546 data points
    Location Call Number Expected Availability
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