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  • Copernicus  (12,694)
  • PANGAEA  (9,469)
  • 2015-2019  (22,163)
  • 2018  (22,163)
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  • 2015-2019  (22,163)
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  • 1
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    PANGAEA
    In:  EPIC3Bremerhaven, PANGAEA
    Publication Date: 2018-12-19
    Repository Name: EPIC Alfred Wegener Institut
    Type: PANGAEA Documentation , notRev
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  • 2
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    PANGAEA
    In:  EPIC3Bremerhaven, PANGAEA
    Publication Date: 2018-01-19
    Repository Name: EPIC Alfred Wegener Institut
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  • 3
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    PANGAEA
    In:  EPIC3Bremerhaven, PANGAEA
    Publication Date: 2018-01-19
    Repository Name: EPIC Alfred Wegener Institut
    Type: PANGAEA Documentation , notRev
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  • 4
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    PANGAEA
    In:  EPIC3Bremerhaven, PANGAEA
    Publication Date: 2018-03-15
    Repository Name: EPIC Alfred Wegener Institut
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  • 5
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    PANGAEA
    In:  EPIC3Bremerhaven, PANGAEA
    Publication Date: 2018-03-26
    Repository Name: EPIC Alfred Wegener Institut
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  • 6
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    PANGAEA
    In:  EPIC3Bremerhaven, PANGAEA
    Publication Date: 2018-05-04
    Repository Name: EPIC Alfred Wegener Institut
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  • 7
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    Copernicus
    In:  EPIC3European Geosciences Union EGU General Assembly, Vienna, Austria, 2018-04-08-2018-04-13Copernicus
    Publication Date: 2018-06-18
    Description: We use a comprehensive suite of partially laminated high-resolution sediment cores from the Bering Sea, covering a depth transect from 1100 m to 2700 m to study deglacial surface ocean warming patterns, associated changes in biological productivity, oxygen minimum zone dynamics and continent-ocean links through Yukon river runoff. We apply a combination of planktic and benthic isotopes, x-ray fluorescence (XRF)-derived ele- mental ratios and a multi-proxy assessment of changes in upper ocean temperatures. Severe oxygen depletions occurred during the Bølling/Allerød (B/A) and early Holocene, which is in accordance with other locations in the North Pacific, especially the Alaska margin. Detailed analysis of the timing of lamination occurrence between the different sediment cores revealed that the onset of severe anoxia at the beginning of the B/A and early Holocene is a near-synchronous event, while the disappearance of laminations is a diachronic process. The deglacial Oxygen Minimum Zone(OMZ) strengthening is mainly driven by increased export production, visible in XRF-derived elemental ratios, and corresponding high accumulation rates of biogenic components. The export production in turn is a response to rising sea surface temperatures, decreased sea ice cover and increased thermal stratification, while a major nutrient source was the eastern continental shelf, which was flooded during the deglacial global sea level rise. It is discussed controversially whether oxygenation variations in the deglacial subarctic Pacific were coupled to changes in mid-depth water chemistry, or rather a response to physical processes like deep-intermediate ocean or mixed layer warming, or stratification changes. However, knowledge of the driving forcing mechanism for OMZ strengthening is of particular importance, as these are tightly coupled to the regional marine carbon budget, e.g. via the strength and efficiency of the biological pump. Here, our laminated sediments provided the opportunity to study ocean dynamics in exceptional detail, possible on decadal to annual timescales. Due to the correlation patterns of our records to the NGRIP oxygen isotope record through layer counts we presume that (i) the presence of laminations is tightly coupled to submillennial, short-term warm phases, especially during the Bølling-Allerød (B/A), (ii) that the laminations represent annual layered sediments (varves). The latter point in conjunction with our geochemical proxies strongly supports an atmospheric teleconnection between SE Asia, the North Atlantic and the North Pacific, with observed changes in mid-depth ocean dynamics occurring on fast, nearly decadal timescales. Thus, the Bering Sea OMZ is a highly sensitive system reacting almost instantaneously to small temperature changes and therefore has the potential to influence the global carbon budget on short timescales, in particular during episodes of rapidly warming climate.
    Repository Name: EPIC Alfred Wegener Institut
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  • 8
    Publication Date: 2020-03-05
    Description: The aim of the presented study was to investigate the impact on the radiation budget of a biomass-burning plume, transported from Alaska to the High Arctic region of Ny-Ålesund, Svalbard, in early July 2015. Since the mean aerosol optical depth increased by the factor of 10 above the average summer background values, this large aerosol load event is considered particularly exceptional in the last 25 years. In situ data with hygroscopic growth equations, as well as remote sensing measurements as inputs to radiative transfer models, were used, in order to estimate biases associated with (i) hygroscopicity, (ii) variability of single-scattering albedo profiles, and (iii) plane-parallel closure of the modelled atmosphere. A chemical weather model with satellite-derived biomass-burning emissions was applied to interpret the transport and transformation pathways. The provided MODTRAN radiative transfer model (RTM) simulations for the smoke event (14:00 9 July–11:30 11 July) resulted in a mean aerosol direct radiative forcing at the levels of −78.9 and −47.0 W m ^-2 at the surface and at the top of the atmosphere, respectively, for the mean value of aerosol optical depth equal to 0.64 at 550 nm. This corresponded to the average clear-sky direct radiative forcing of −43.3 W/m ^2, estimated by radiometer and model simulations at the surface. Ultimately, uncertainty associated with the plane-parallel atmosphere approximation altered results by about 2 W m^−2. Furthermore, model-derived aerosol direct radiative forcing efficiency reached on average −126 W m^−2/τ550 and −71 W^m−2/τ550 at the surface and at the top of the atmosphere, respectively. The heating rate, estimated at up to 1.8 K day^−1 inside the biomass-burning plume, implied vertical mixing with turbulent kinetic energy of 0.3 m^2s^−2
    Repository Name: EPIC Alfred Wegener Institut
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  • 9
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    PANGAEA
    In:  EPIC3Bremerhaven, PANGAEA
    Publication Date: 2018-09-14
    Repository Name: EPIC Alfred Wegener Institut
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  • 10
    Publication Date: 2020-09-06
    Description: Recent observations of near-surface soil temperatures over the circumpolar Arctic show accelerated warming of permafrost-affected soils. The availability of a comprehensive near-surface permafrost and active layer dataset is critical to better understanding climate impacts and to constraining permafrost thermal conditions and its spatial distribution in land system models. We compiled a soil temperature dataset from 72 monitoring stations in Alaska using data collected by the US Geological Survey, the National Park Service, and the University of Alaska Fairbanks permafrost monitoring networks. The array of monitoring stations spans a large range of latitudes from 60.9 to 71.3 N and elevations from near sea level to~ 1300 m, comprising tundra and boreal forest regions. This dataset consists of monthly ground temperatures at depths up to 1 m, volumetric soil water content, snow depth, and air temperature during 1997–2016. These data have been quality controlled in collection and processing. Meanwhile, we implemented data harmonization evaluation for the processed dataset. The final product (PF-AK, v0. 1) is available at the Arctic Data Center (https://doi. org/10.18739/A2KG55).
    Repository Name: EPIC Alfred Wegener Institut
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  • 11
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    PANGAEA
    In:  EPIC3Bremerhaven, PANGAEA
    Publication Date: 2018-01-23
    Repository Name: EPIC Alfred Wegener Institut
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  • 12
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    PANGAEA
    In:  EPIC3Bremerhaven, PANGAEA
    Publication Date: 2018-01-22
    Repository Name: EPIC Alfred Wegener Institut
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  • 13
    Publication Date: 2018-01-24
    Repository Name: EPIC Alfred Wegener Institut
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  • 14
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    PANGAEA
    In:  EPIC3Bremerhaven, PANGAEA
    Publication Date: 2018-01-19
    Repository Name: EPIC Alfred Wegener Institut
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  • 15
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    PANGAEA
    In:  EPIC3Bremerhaven, PANGAEA
    Publication Date: 2018-01-23
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  • 16
    Publication Date: 2018-04-05
    Repository Name: EPIC Alfred Wegener Institut
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  • 17
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    PANGAEA
    In:  EPIC3Bremerhaven, PANGAEA
    Publication Date: 2018-04-24
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  • 18
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    PANGAEA
    In:  EPIC3Bremerhaven, PANGAEA
    Publication Date: 2018-04-24
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  • 19
    Publication Date: 2018-04-16
    Description: The denudation history of active orogens is often interpreted in the context of modern climate gradients. Here we address the validity of this approach and ask what are the spatial and temporal variations in palaeoclimate for a latitudinally diverse range of active orogens? We do this using high-resolution (T159, ca. 80 × 80 km at the Equator) palaeoclimate simulations from the ECHAM5 global atmospheric general circulation model and a statistical cluster analysis of climate over different orogens (Andes, Himalayas, SE Alaska, Pacific NW USA). Time periods and boundary conditions considered include the Pliocene (PLIO, ∼3Ma), the Last Glacial Maximum (LGM, ∼21ka), mid-Holocene (MH, ∼6ka), and pre-industrial (PI, reference year 1850). The regional simulated climates of each orogen are described by means of cluster analyses based on the variability in precipitation, 2 m air temperature, the intra-annual amplitude of these values, and monsoonal wind speeds where appropriate. Results indicate the largest differences in the PI climate existed for the LGM and PLIO climates in the form of widespread cooling and reduced precipitation in the LGM and warming and enhanced precipitation during the PLIO. The LGM climate shows the largest deviation in annual precipitation from the PI climate and shows enhanced precipitation in the temperate Andes and coastal regions for both SE Alaska and the US Pacific Northwest. Furthermore, LGM precipitation is reduced in the western Himalayas and enhanced in the eastern Himalayas, resulting in a shift of the wettest regional climates eastward along the orogen. The cluster-analysis results also suggest more climatic variability across latitudes east of the Andes in the PLIO climate than in other time slice experiments conducted here. Taken together, these results highlight significant changes in late Cenozoic regional climatology over the last ∼3Myr. Comparison of simulated climate with proxy-based reconstructions for the MH and LGM reveal satisfactory to good performance of the model in reproducing precipitation changes, although in some cases discrepancies between neighbouring proxy observations highlight contradictions between proxy observations themselves. Finally, we document regions where the largest magnitudes of late Cenozoic changes in precipitation and temperature occur and offer the highest potential for future observational studies that quantify the impact of climate change on denudation and weathering rates.
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  • 20
    Publication Date: 2018-06-05
    Repository Name: EPIC Alfred Wegener Institut
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  • 21
    Publication Date: 2018-07-13
    Repository Name: EPIC Alfred Wegener Institut
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  • 22
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    PANGAEA
    In:  EPIC3Bremerhaven, PANGAEA
    Publication Date: 2018-07-19
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  • 23
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    PANGAEA
    In:  EPIC3Bremerhaven, PANGAEA
    Publication Date: 2018-07-19
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  • 24
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    PANGAEA
    In:  EPIC3Bremerhaven, PANGAEA
    Publication Date: 2018-07-24
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  • 25
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    PANGAEA
    In:  EPIC3Bremerhaven, PANGAEA
    Publication Date: 2018-04-24
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  • 26
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    PANGAEA
    In:  EPIC3Bremerhaven, PANGAEA
    Publication Date: 2018-04-24
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  • 27
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    PANGAEA
    In:  EPIC3Bremerhaven, PANGAEA
    Publication Date: 2018-11-28
    Repository Name: EPIC Alfred Wegener Institut
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  • 28
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    Copernicus
    In:  EPIC3Earth System Dynamics, Copernicus, 9(3), pp. 939-954, ISSN: 2190-4979
    Publication Date: 2018-07-09
    Description: In austral spring 2016 the Antarctic region experienced anomalous sea ice retreat in all sectors, with sea ice extent in October and November 2016 being the lowest in the Southern Hemisphere over the observational period (1979–present). The extreme sea ice retreat was accompanied by widespread warming along the coastal areas as well as in the interior of the Antarctic continent. This exceptional event occurred along with a strong negative phase of the Southern Annular Mode (SAM) and the moistest and warmest spring on record, over large areas covering the Indian Ocean, the Ross Sea and the Weddell Sea. In October 2016, the positive anomalies of the totally integrated water vapor (IWV) and 2 m air temperature (T2m) over the Indian Ocean, western Pacific, Bellingshausen Sea and southern part of Ross Sea were unprecedented in the last 39 years. In October and November 2016, when the largest magnitude of negative daily sea ice concentration anomalies was observed, repeated episodes of poleward advection of warm and moist air took place. These results suggest the importance of moist and warm air intrusions into the Antarctic region as one of the main contributors to this exceptional sea ice retreat event.
    Repository Name: EPIC Alfred Wegener Institut
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  • 29
    Publication Date: 2018-07-13
    Repository Name: EPIC Alfred Wegener Institut
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  • 30
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    PANGAEA
    In:  EPIC3Bremerhaven, PANGAEA
    Publication Date: 2018-07-19
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  • 31
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    PANGAEA
    In:  EPIC3Bremerhaven, PANGAEA
    Publication Date: 2018-07-19
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  • 32
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    PANGAEA
    In:  EPIC3Bremerhaven, PANGAEA
    Publication Date: 2018-07-19
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  • 33
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    PANGAEA
    In:  EPIC3Bremerhaven, PANGAEA
    Publication Date: 2018-07-19
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  • 34
    Publication Date: 2018-08-20
    Description: To resolve the mechanisms behind the major climate reorganisation which occurred between 0.9 and 1.2Ma, the recovery of a suitable 1.5 million-year-old ice core is fundamental. The quest for such an Oldest Ice core requires a number of key boundary conditions, of which the poorly known basal geothermal heat flux (GHF) is lacking. We use a transient thermodynamical 1D vertical model that solves for the rate of change of temperature in the vertical, with surface temperature and modelled GHF as boundary conditions. For each point on the ice sheet, the model is forced with variations in atmospheric conditions over the last 2Ma, and modelled ice-thickness variations. The process is repeated for a range of GHF values to determine the value of GHF that marks the limit between frozen and melting conditions over the whole ice sheet, taking into account 2Ma of climate history. These threshold values of GHF are statistically compared to existing GHF data sets. The new probabilistic GHF fields obtained for the ice sheet thus provide the missing boundary conditions in the search for Oldest Ice. High spatial resolution radar data are examined locally in the Dome Fuji and Dome C regions, as these represent the ice core community's primary drilling sites. GHF, bedrock variability, ice thickness and other essential criteria combined highlight a dozen major potential Oldest Ice sites in the vicinity of Dome Fuji and Dome C, where GHF allows for Oldest Ice.
    Repository Name: EPIC Alfred Wegener Institut
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  • 35
    Publication Date: 2018-09-10
    Description: Polar ice core water isotope records are commonly used to infer past changes in Antarctic temperature, motivating an improved understanding and quantification of the temporal relationship between δ18O and temperature. This can be achieved using simulations performed by atmospheric general circulation models equipped with water stable isotopes. Here, we evaluate the skills of the high-resolution water-isotope-enabled atmospheric general circulation model ECHAM5-wiso (the European Centre Hamburg Model) nudged to European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis using simulations covering the period 1960–2013 over the Antarctic continent. We compare model outputs with field data, first with a focus on regional climate variables and second on water stable isotopes, using our updated dataset of water stable isotope measurements from precipitation, snow, and firn–ice core samples. ECHAM5-wiso simulates a large increase in temperature from 1978 to 1979, possibly caused by a discontinuity in the European Reanalyses (ERA) linked to the assimilation of remote sensing data starting in 1979. Although some model–data mismatches are observed, the (precipitation minus evaporation) outputs are found to be realistic products for surface mass balance. A warm model bias over central East Antarctica and a cold model bias over coastal regions explain first-order δ18O model biases by too strong isotopic depletion on coastal areas and underestimated depletion inland. At the second order, despite these biases, ECHAM5-wiso correctly captures the observed spatial patterns of deuterium excess. The results of model–data comparisons for the inter-annual δ18O standard deviation difer when using precipitation or ice core data. Further studies should explore the importance of deposition and post-deposition processes affecting ice core signals and not resolved in the model. These results build trust in the use of ECHAM5-wiso outputs to investigate the spatial, seasonal, and inter-annual δ18O–temperature relationships. We thus make the first Antarctica-wide synthesis of prior results. First, we show that local spatial or seasonal slopes are not a correct surrogate for inter-annual temporal slopes, leading to the conclusion that the same isotope–temperature slope cannot be applied for the climatic interpretation of Antarctic ice core for all timescales. Finally, we explore the phasing between the seasonal cycles of deuterium excess and δ18O as a source of information on changes in moisture sources affecting the δ18O–temperature relationship. The few available records and ECHAM5-wiso show different phase relationships in coastal, intermediate, and central regions. This work evaluates the use of the ECHAM5-wiso model as a tool for the investigation of water stable isotopes in Antarctic precipitation and calls for extended studies to improve our understanding of such proxies.
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  • 36
    Publication Date: 2018-09-10
    Description: The effect of external forcings on atmospheric circulation is debated. Due to the short observational period, the analysis of the role of external forcings is hampered, making it difficult to assess the sensitivity of atmospheric circulation to external forcings, as well as persistence of the effects. In observations, the average response to tropical volcanic eruptions is a positive North Atlantic Oscillation (NAO) during the following winter. However, past major tropical eruptions exceeding the magnitude of eruptions during the instrumental era could have had more lasting effects. Decadal NAO variability has been suggested to follow the 11-year solar cycle, and linkages have been made between grand solar minima and negative NAO. However, the solar link to NAO found by modeling studies is not unequivocally supported by reconstructions, and is not consistently present in observations for the 20th century. Here we present a reconstruction of atmospheric winter circulation for the North Atlantic region covering the period 1241–1970 CE. Based on seasonally resolved Greenland ice core records and a 1200-year-long simulation with an isotope-enabled climate model, we reconstruct sea level pressure and temperature by matching the spatiotemporal variability in the modeled isotopic composition to that of the ice cores. This method allows us to capture the primary (NAO) and secondary mode (Eastern Atlantic Pattern) of atmospheric circulation in the North Atlantic region, while, contrary to previous reconstructions, preserving the amplitude of observed year-to-year atmospheric variability. Our results show five winters of positive NAO on average following major tropical volcanic eruptions, which is more persistent than previously suggested. In response to decadal minima of solar activity we find a high-pressure anomaly over northern Europe, while a reinforced opposite response in pressure emerges with a 5-year time lag. On centennial timescales we observe a similar response of circulation as for the 5-year time-lagged response, with a high-pressure anomaly across North America and south of Greenland. This response to solar forcing is correlated to the second mode of atmospheric circulation, the Eastern Atlantic Pattern. The response could be due to an increase in blocking frequency, possibly linked to a weakening of the subpolar gyre. The long-term anomalies of temperature during solar minima shows cooling across Greenland, Iceland and western Europe, resembling the cooling pattern during the Little Ice Age (1450–1850 CE). While our results show significant correlation between solar forcing and the secondary circulation pattern on decadal (r = 0.29, p 〈 0.01) and centennial timescales (r = 0.6, p 〈 0.01), we find no consistent relationship between solar forcing and NAO. We conclude that solar and volcanic forcing impacts different modes of our reconstructed atmospheric circulation, which can aid in separating the regional effects of forcings and understanding the underlying mechanisms.
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  • 37
    Publication Date: 2018-10-08
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  • 38
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    PANGAEA
    In:  EPIC3Bremerhaven, PANGAEA
    Publication Date: 2018-02-05
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  • 39
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    Copernicus
    In:  EPIC3European Geosciences Union (EGU) General Assembly, Vienna, Austria, 2018-04-08-2018-04-13Copernicus
    Publication Date: 2018-06-18
    Description: North Pacific Intermediate water (NPIW) is a dominant water mass controlling ∼400-1200m depth North Pacific Ocean, meanwhile there is a cessation of North Pacific deep water (NPDW) formation in in modern observations. In contrast, paleoceanographic evidences have recorded NPDW formations during last glacial periods. This sug- gests either a rapid or gradual shutting down process of NPDW formation during the last deglaciation. Here, we use an Earth System Model to diagnose the physical and corresponding biogeochemical evolutions in the North Pacific Ocean before and after the last deglaciation, as well as potential changes during rapid climate shifts of the last deglaciation. Linked to different background climate conditions and varying Atlantic Meridional Over- turning Circulation states, we characterize the modelled NPIW and NPDW changes and builds up linkages to marine records. Our results further develop our understanding about the deglacial switch from NPDW to modern NPIW-only formation process.
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  • 40
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    PANGAEA
    In:  EPIC3Bremerhaven, PANGAEA
    Publication Date: 2018-07-24
    Repository Name: EPIC Alfred Wegener Institut
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  • 41
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    PANGAEA
    In:  EPIC3Bremerhaven, PANGAEA
    Publication Date: 2018-07-19
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  • 42
    Publication Date: 2018-10-29
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  • 43
    Publication Date: 2019-03-26
    Description: Abstract. When combined, the three-dimensional imaging of different physical properties of architectural monumen- tal structures acquired through different methodologies can highlight with efficiency the characteristics of the stone building materials. In this work, we compound high res- olution Digital Color Images (DCI) and Terrestrial Laser Scanner (TLS) data for a dense 3-D reconstruction of an ancient pillar in a nineteenth century building in the town of Cagliari, Italy. The TLS technique was supported by a digital photogrammetry survey in order to obtain a natural color texturized 3-D model of the studied pillar. Geometri- cal anomaly maps showing interesting analogies were com- puted both from the 3-D model derived from the TLS ap- plication and from the high resolution 3-D model detected with the photogrammetry. Starting from the 3-D reconstruc- tion from previous techniques, an acoustic tomography in a sector of prior interest of the investigated architectural ele- ment was planned and carried out. The ultrasonic tomogra- phy proved to be an effective tool for detecting internal decay or defects, locating the position of the anomalies and estimat- ing their sizes, shapes, and characteristics in terms of elastic- mechanical properties. Finally, the combination of geophysi- cal and petrographical data sets represents a powerful method for understanding the quality of the building stone materials in the shallow and inner parts of the investigated architectural structures.
    Description: Regione Autonoma della Sardegna (RAS) (Sardinian Autonomous Region), Regional Law 7th August 2007, no. 7, Promotion of scientific research and technological innovation in Sardinia (Italy).
    Description: Published
    Description: 57-62
    Description: 5T. Sismologia, geofisica e geologia per l'ingegneria sismica
    Description: JCR Journal
    Keywords: Architectural monumental structures ; Structural Diagnosis ; Digital Color Images ; 3D Terrestrial Laser Scanner ; Acoustic tomography ; Petrographical data ; 3D Modeling ; Cultural Heritage ; Architectural Elements ND Diagnosis
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 44
    Publication Date: 2018-03-12
    Description: The Istituto Nazionale di Geofisica e Vulcanologia runs the Italian National Seismic Network (about 400 stations, seismometers, accelerometers and GPS antennas) and other networks at national scale for monitoring earthquakes and tsunami as a part of the National Civil Protection System coordinated by the Italian Department of Civil Protection. This work summarises the acquisition and the distribution of the data and the analysis that are carried out for seismic surveillance and tsunami alert.
    Description: INGV and DPC
    Description: Published
    Description: 31-38
    Description: 1IT. Reti di monitoraggio
    Description: N/A or not JCR
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 45
    Publication Date: 2018-12-14
    Description: This paper describes ESM-SnowMIP, an international coordinated modelling effort to evaluate current snow schemes, including snow schemes that are included in Earth system models, in a wide variety of settings against local and global observations. The project aims to identify crucial processes and characteristics that need to be improved in snow models in the context of local- and global-scale modelling. A further objective of ESM-SnowMIP is to better quantify snow-related feedbacks in the Earth system. Although it is not part of the sixth phase of the Coupled Model Intercomparison Project (CMIP6), ESM-SnowMIP is tightly linked to the CMIP6-endorsed Land Surface, Snow and Soil Moisture Model Intercomparison (LS3MIP).
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
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  • 46
    Publication Date: 2018-11-30
    Repository Name: EPIC Alfred Wegener Institut
    Type: PANGAEA Documentation , notRev
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  • 47
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    In:  EPIC3Bremerhaven, PANGAEA
    Publication Date: 2018-11-28
    Repository Name: EPIC Alfred Wegener Institut
    Type: PANGAEA Documentation , notRev
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  • 48
  • 49
    Publication Date: 2020-02-12
    Description: The airborne laser scanning (ALS) datasets were acquired at the Arctic tundra site of Trail Valley Creek (TVC), Northwest Territories, Canada, which is underlain by continuous permafrost. Basic processing and filtering steps were applied to the ALS point cloud. Based on a classification into ground and vegetation points, a Digital Terrain Model (DTM) and rasters of mean and maximum vegetation heights are derived. Detailed metadata are included.
    Language: English
    Type: info:eu-repo/semantics/workingPaper
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  • 50
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    In:  Supplement to: Kremer, Anne; Stein, Ruediger; Fahl, Kirsten; Ji, Z; Yang, Z; Wiers, Steffen; Matthiessen, Jens; Forwick, Matthias; Löwemark, Ludvig; O'Regan, Matthew; Chen, Jiaming; Snowball, Ian (2018): Changes in sea ice cover and ice sheet extent at the Yermak Plateau during the last 160 ka - Reconstructions from biomarker records. Quaternary Science Reviews, 182, 93-108, https://doi.org/10.1016/j.quascirev.2017.12.016
    Publication Date: 2023-03-16
    Description: The Yermak Plateau is located north of Svalbard at the entrance to the Arctic Ocean, i.e. in an area highly sensitive to climate change. A multi proxy approach was carried out on Core PS92/039-2 to study glacial-interglacial environmental changes at the northern Barents Sea margin during the last 160 ka. The main emphasis was on the reconstruction of sea ice cover, based on the sea ice proxy IP25 and the related phytoplankton - sea ice index PIP25. Sea ice was present most of the time but showed significant temporal variability decisively affected by movements of the Svalbard Barents Sea Ice Sheet. For the first time, we prove the occurrence of seasonal sea ice at the eastern Yermak Plateau during glacial intervals, probably steered by a major northward advance of the ice sheet and the formation of a coastal polynya in front of it. Maximum accumulation of terrigenous organic carbon, IP25 and the phytoplankton biomarkers (brassicasterol, dinosterol, HBI III) can be correlated to distinct deglaciation events. More severe, but variable sea ice cover prevailed at the Yermak Plateau during interglacials. The general proximity to the sea ice margin is further indicated by biomarker (GDGT) - based sea surface temperatures below 2.5 °C.
    Keywords: Arctic Ocean; ARK-XXIX/1, TRANSSIZ; AWI_Paleo; KAL; Kasten corer; Paleoenvironmental Reconstructions from Marine Sediments @ AWI; Polarstern; PS92; PS92/039-2
    Type: Dataset
    Format: application/zip, 4 datasets
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  • 51
    Publication Date: 2023-03-16
    Description: Past sea ice conditions and open water phytoplankton production were reconstructed from a sediment core taken in Disko Bugt, West Greenland, using the sea ice biomarker IP~25~ and other specific phytoplankton biomarker (i.e., brassicasterol, dinosterol, HBI III) records. Our biomarker record indicates that Disko Bugt experienced a gradual expansion of seasonal sea ice during the last 2.2 kyr. Maximum sea ice extent was reached during the Little Ice Age around 0.2 kyr BP. Superimposed on this longer term trend, we find short-term oscillations in open water primary production and terrigenous input, which may be related to the Atlantic Multidecadal Oscillation and solar activity changes as potential climatic trigger mechanisms. A direct sample-to-sample multiproxy comparison of our new biomarker record with microfossil (i.e., benthic foraminifera, dinocysts, and diatoms) and other geochemical records (i.e., alkenone biomarkers) indicates that different proxies are influenced by the complex environmental system with pronounced seasonal changes and strong oceanographic gradients, e.g., freshwater inflow from the Greenland Ice Sheet. Differences in sea ice reconstructions may indicate that the IP~25~ record reflects only the relatively short sea ice season (spring), whereas other microfossil reconstructions may reflect a longer (spring–autumn) interval.
    Keywords: AWI_Paleo; Paleoenvironmental Reconstructions from Marine Sediments @ AWI
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  • 52
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    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-16
    Description: Using a microprofiler and electrochemical oxygen sensors after Revsbech (1989) in situ oxygen profiles measurements were conducted with a spatial resolution if 100 µm and a temporal resolution of 30 seconds at three stations in Potter Cove in austral summer 2015.
    Type: Dataset
    Format: application/zip, 3 datasets
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  • 53
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    In:  Supplement to: Braeckman, Ulrike; Janssen, Felix; Lavik, Gaute; Elvert, Marcus; Marchant, Hannah K; Buckner, Caroline; Bienhold, Christina; Wenzhöfer, Frank (2018): Carbon and nitrogen turnover in the Arctic deep sea: in situ benthic community response to diatom and coccolithophorid phytodetritus. Biogeosciences, 15(21), 6537-6557, https://doi.org/10.5194/bg-15-6537-2018
    Publication Date: 2023-03-16
    Description: This is a dataset from an in situ experiment at station S2 from the LTER monitoring site HAUSGARTEN, performed in June-July 2013 during Maria S Merian expedition MSM29. The in situ responses of Arctic deep-sea benthos to input of phytodetritus of a diatom (Thalassiosira sp.) as opposed to a coccolithophorid (Emiliania huxleyi) were investigated in incubation chambers of benthic landers. Using 13C and 15N labelled phytodetritus harvested from cultures of these species, we traced the fate of the respective phytodetritus into different parts of the food web (respiration, assimilation by bacteria and infauna 〉250 µm), in a short (4d) and long (14d) term experiment. The benthic landers were lowered to the sea floor, where they enclosed ~ 20cm of sediment and ~10 cm of overlying water. During respectively 4d and 14d, the temperature and concentrations of O2, DIC, 13C-DIC, NHx, NOx, 15N-NH4, 15N-NOx were measured. Upon recovery of the landers, the sediment was retrieved and subsampled in vertical horizons to measure pigment, TOC and TN, 13C-POC and 15N-PN concentrations, pore water concentrations of DIC, 13C-DIC, NHx, NOx, 15N-NH4 and 15N-NOx and the assimilation of 13C in bacterial fatty acids (iC15:0 and aiC15:0) and in fauna 〉 250 µm
    Keywords: Hausgarten; Long-term Investigation at AWI-Hausgarten off Svalbard
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    Format: application/zip, 10 datasets
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  • 54
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    In:  Supplement to: Izett, Robert W; Manning, Cara C M; Hamme, Roberta C; Tortell, Philippe Daniel (2018): Refined Estimates of Net Community Production in the Subarctic Northeast Pacific Derived From ΔO2/Ar Measurements With N2O-Based Corrections for Vertical Mixing. Global Biogeochemical Cycles, 32(3), 326-350, https://doi.org/10.1002/2017GB005792
    Publication Date: 2023-03-16
    Description: We present the first field application of a N2O-based approach to correct for vertical mixing in the estimation of net community production (NCP) from mixed layer O2 measurements. Using new ship-based observations of N2O and biological oxygen saturation anomalies (DeltaO2/Ar) from the Subarctic Northeast Pacific, we provide refined mixed layer NCP estimates across contrasting hydrographic regimes and a comprehensive assessment of the methodological considerations and limitations of the approach. Increased vertical mixing coefficients at the base of the mixed layer, derived using N2O measurements, corresponded with periods of heightened wind speed and coastal upwelling. Corrections were most significant in coastal regions where the vertical supply of low-O2 water can otherwise falsely imply net heterotrophy from negative DeltaO2/Ar measurements. After correcting for the mixing flux, all coastal stations showed autotrophic signatures, with maximum NCP exceeding 100 mmol O2 m-2 day-1 in the spring and summer. Vertical fluxes were lower in off-shelf waters, but often contributed more than 50 % to corrected NCP. At some oceanic stations, however, the co-occurrence of N2O minima and O2 maxima resulted in biased (over-estimated) N2O corrections. Evaluating vertical fluxes in these regions remains a challenge for ship-based studies. Nonetheless, our refined NCP estimates show better coherence with surface chlorophyll, temperature, and mixed layer depth than uncorrected values. Potential mixed layer N2O production introduces some uncertainty in the approach, but errors are likely to be small. Ultimately, this work provides rationale for the adoption of the N2O correction to refine NCP estimates, particularly in coastal waters. Data in this submission include the ancillary components required to replicate all calculations, and conclusions made in the main manuscript.
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  • 55
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    In:  Supplement to: Kruse, Stefan; Epp, Laura Saskia; Wieczorek, Mareike; Pestryakova, Luidmila A; Stoof-Leichsenring, Kathleen Rosmarie; Herzschuh, Ulrike (2018): High gene flow and complex treeline dynamics of Larix Mill. stands on the Taymyr Peninsula (north-central Siberia) revealed by nuclear microsatellites. Tree Genetics & Genomes, 14(2), https://doi.org/10.1007/s11295-018-1235-3
    Publication Date: 2023-03-16
    Description: Arctic treelines are facing a strong temperature increase as a result of recent global warming, causing possible changes in forest extent, which will alter vegetation-climate feedbacks. However, the mode and strength of the response is rather unclear, as potential changes are happening in areas that are very remote and difficult to access, and empirical data are still largely lacking. Here, we assessed the current population structure and genetic differentiation of Larix Mill. tree stands within the northernmost latitudinal treeline reaching ~72° N in the southern lowlands of the Taymyr Peninsula (~100° E). We sampled 743 individuals belonging to different height classes (seedlings, saplings, trees) at eleven locations along a gradient from 'single tree' tundra over 'forest line' to 'dense forest' stands and conducted investigations applying eight highly polymorphic nuclear microsatellites. Results suggest a high diversity within subpopulations (HE=0.826-0.893), coupled, however, with heterozygote deficits in all subpopulations, but pronounced in 'forest line' stands. Overall, genetic differentiation of subpopulations is low (FST=0.005), indicating a region-wide high gene flow, although 'forest line' stands harbour few rare and private alleles, likely indicating greater local reproduction. 'Single tree' stands, located beyond the northern forest line, are currently not involved in treeline expansion, but show signs of a long-term refuge, namely asexual reproduction and change of growth-form from erect to creeping growth, possibly having persisted for thousands of years. The lack of differentiation between the subpopulations points to a sufficiently high dispersal potential, and thus a rapid northward migration of the Siberian arctic treeline under recent global warming seems potentially unconstrained, but observations show it to be unexpectedly slow.
    Keywords: AWI_Envi; Polar Terrestrial Environmental Systems @ AWI
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  • 56
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    In:  Supplement to: Beamish, Alison Leslie; Coops, Nicholas; Chabrillat, Sabine; Heim, Birgit (2017): A phenological approach to spectral differentiation of low-arctic tundra vegetation communities, North Slope, Alaska. Remote Sensing, 9(12), 1200, https://doi.org/10.3390/rs9111200
    Publication Date: 2023-03-16
    Description: Ground-based spectroscopy measurements acquired systematically within the Toolik Vegetation Grid in the 2015 and 2016 growing seasons and within the Imnavait Vegetation Grid in the 2016 growing season. Data were collected in 68 distinct 1 x 1 m long-term monitoring plots representing five distinct vegetation communities. Spectral measurements were acquired two times throughout the season in 2015 representing peak and late season and three times in 2016 representing early, peak and late season. Data were acquired using a GER 1500 field spectrometer (350-1050 nm; 512 bands, spectral resolution 3 nm, spectral sampling 1.5 nm, and 8! field of view). Spectra were collected under clear weather conditions at the highest solar zenith angle between 10:00 and 14:00 local time. Data were collected at nadir approximately 1 m off the ground resulting in a Ground Instantaneous Field of View (GIFOV) of approximately 15 cm in diameter. Nine point measurements of upwelling radiance (Lup) were collected in 1 x 1 m plots representative of the five vegetation communities and averaged to characterize the spectral variability and to reduce noise. Downwelling radiance (Ldown) was measured as the reflectance from a white Spectralon© plate. Surface reflectance (R) was processed as Lup/Ldown x 100 (0-100%). Reflectance spectra were preprocessed with a Savitzky-Golay smoothing filter (n = 11) and subset to 400-985 nm to remove sensor noise at the edges of the radiometer detector.
    Keywords: AWI_Envi; MULT; Multiple investigations; Polar Terrestrial Environmental Systems @ AWI; ToolikL_plot; Toolik Lake, Alaska
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  • 57
    Publication Date: 2023-03-16
    Description: Our data, as part of the OISO (Ocean Indien Service d'Observation) campaign, contributes to a better understanding of the physical and biological factors controlling N2 fixation in the Southern Indian Ocean and the French Southern and Antarctic lands during Austral summer January and February 2017. We measured N2 and C fixation as well as NH4+ and NO3- assimilation in 3-6 replicates per station. Additionally, we measured diagnostic pigment concentrations to evaluate phtosynthetic community composition. For pigment analysis 4L water was filtered through 25mm Whatman GF/F filters (pressure drop 〈10kPa). Samples were stored at -80°C until analysis. Pigments were analysed using High Performance Liquid Chromatography (HPLC). Pigment concentration were calculated according to Kilias et al (2013, doi:10.1111/jpy.12109). N2 fixation experiments were carried out in three to six replicates for each station. Incubations were done in pre-acid washed polycarbonate bottles on deck with ambient light conditions. All polycarbonate incubation bottles were rinsed with deionized water, and seawater prior to incubation. We used the combination of the bubble approach (Montoya et al., 1996) and the dissolution method (Mohr et al., 2010, doi:10.1371/journal.pone.0012583) proposed by Klawonn et al. (2015, doi:10.3389/fmicb.2015.00769). Bottles were filled up to capacity to avoid air contamination. Incubations were initialized by adding a 10 ml 15-15N gas bubble. Bottles were gently rocked for 15 minutes. Finally, the remaining bubble was removed to avoid equilibration between gas and aqueous phase. after 24 hours a water subsample was taken to a 12 ml exetainer and preserved with 100 µl HgCl2 solution for later determination of exact 15N-15N concentration. Natural 15N2 was determined using Membrane Inlet Mass Spectrometry (MIMS; GAM200, IPI) for each station. Analysis of 15N2 incorporated was carried out by the Isotopic Laboratory at the UC Davis, California campus. We used stable isotope tracers (15N) to measure dissolved inorganic nitrogen (DIN) assimilation rates. Experiments were initiated by adding a known concentration of 0.05 of K15NO3 and 15NH4Cl for oligotrophic waters of the IO and 0.625 µmol L-1 for HNLC regions in the ACC and PF (Knap et al., 1994, Waite et al., 2007, doi:10.1016/j.dsr2.2006.12.010) to one litre polycarbonate bottles. For C assimilation experiments, we added 20 µmol L-1 of NaH13CO3 to one of each of N2 fixation, NH4+ and NO3- assimilation experiment bottles. For incubation, we followed the same procedure as for N2 fixation experiments. Findings reveal that N2 fixation occurs throughout the whole sampling area up to 55°S latitude. In addition, variations of N2 fiaxation rates between replicates were relatively high indicating a great heterogeneity of the French Southern and Antarctic waters. References: Montoya 1996: Montoya, Joseph P., et al. "A Simple, High-Precision, High-Sensitivity Tracer Assay for N (inf2) Fixation." Applied and environmental microbiology 62.3 (1996): 986-993. Knap et al 1994: Knap, A., Michaels, A., Close, A., Ducklow, H. & Dickson, A. 1994. Protocols for the Joint Global Ocean Flux Study (JGOFS) Core Measurements, JGOFS, Reprint of the IOC Manuals and Guides No. 29. UNESCO, 19, 1.
    Type: Dataset
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  • 58
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    In:  Supplement to: van der Jagt, Helga; Friese, Carmen A; Stuut, Jan-Berend W; Fischer, Gerhard; Iversen, Morten Hvitfeldt (2018): The ballasting effect of Saharan dust deposition on aggregate dynamics and carbon export: Aggregation, settling, and scavenging potential of marine snow. Limnology and Oceanography, 63(3), 1386-1394, https://doi.org/10.1002/lno.10779
    Publication Date: 2023-03-16
    Description: Lithogenic material such as Saharan dust can be incorporated into organic aggregates and act as ballast, potentially enhancing the marine carbon export via increased sinking velocities of aggregates. We studied the ballasting effects of Saharan dust on the aggregate dynamics in the upwelling region off Cape Blanc (Mauritania). Aggregate formation from a natural plankton community exposed to Saharan dust deposition resulted in higher abundance of aggregates with higher sinking velocities compared to aggregate formation with low dust. This higher aggregate abundance and sinking velocities potentially increased the carbon export 10-fold when the aggregates were ballasted by Saharan dust. After aggregate formation in the surface waters, subsequent sinking through suspended Saharan dust minerals had no influence on aggregate sizes, abundance, and sinking velocities. We found that aggregates formed in the surface ocean off Mauritania were already heavily ballasted with lithogenic material and could therefore not scavenge any additional minerals during their descent. This suggests that carbon export to the deep ocean in regions with high dust deposition is strongly controlled by dust input to the surface ocean while suspended dust particles in deeper water layers do not significantly interact with sinking aggregates.
    Keywords: Center for Marine Environmental Sciences; MARUM; SeaPump; Seasonal and regional food web interactions with the biological pump
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    Format: application/zip, 3 datasets
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  • 59
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    In:  Supplement to: Beamish, Alison Leslie; Coops, Nicholas; Hermosilla, T; Chabrillat, Sabine; Heim, Birgit (2018): Monitoring pigment-driven vegetation changes in a low-Arctic tundra ecosystem using digital cameras. Ecosphere, 9(2), e02123, https://doi.org/10.1002/ecs2.2123
    Publication Date: 2023-03-16
    Description: Ground-based spectroscopy measurements acquired systematically within the Toolik Vegetation Grid in the 2016 growing season. All data were collected in a subset of 1 x 1 m long-term monitoring plots representing three distinct vegetation communities three times representing early, peak and late season. Spectral data were acquired using a GER 1500 field spectrometer (350-1050 nm; 512 bands, spectral resolution 3 nm, spectral sampling 1.5 nm, and 8! field of view). Spectra were collected under clear weather conditions at the highest solar zenith angle between 10:00 and 14:00 local time. Data were collected at nadir approximately 1 m off the ground resulting in a Ground Instantaneous Field of View (GIFOV) of approximately 15 cm in diameter. Nine point measurements of upwelling radiance (Lup) were collected in each plot and averaged to characterize the spectral variability and to reduce noise. Downwelling radiance (Ldown) was measured as the reflectance from a white Spectralon© plate. Surface reflectance (R) was processed as Lup/Ldown x 100 (0-100%). Reflectance spectra were preprocessed with a Savitzky-Golay smoothing filter (n = 11) and subset to 400-985 nm to remove sensor noise at the edges of the radiometer detector. Digital camera data were acquired using a consumer-grade camera (Panasonic DM3 LMX, Japan) approximately 1 m off the ground with a white frame for registration of off nadir images. For detailed definitions of the RGB indices see metadata.docx. Leaves and stems of the dominant vascular species in a subset of the sampled plots were collected at early, peak, and late season for chlorophyll and carotenoid analysis.Samples were placed in porous tea bags and preserved in a silica gel desiccant in an opaque container for up to 3 months until pigment extraction (Esteban et al. 2009, doi:10.1007/s11120-009-9468-5). Each sample was homogenized by grinding with a mortar and pestle. Approximately 1.00 mg (+/- 0.05 mg) of homogenized sample was placed into a vial with 2 ml of dimethylformamide (DMF). Vials were then wrapped in aluminum foil to eliminate any degradation of pigments due to UV light and stored in a fridge (4C) for 24 hrs. Samples were measured into a cuvette prior to spectrophotometric analysis. Bulk pigments concentrations were then estimated using a spectrophotometer measuring absorption at 646.8, 663.8 and 480 nm (Porra et al. 1989, doi:10.1016/S0005-2728(89)80347-0) . Absorbance (A) values at specific wavelengths were transformed into µg/mg concentrations of chlorophyll a, Chla, chlorophyll b, Chlb, total chlorophyll, Chl, carotenoids, Car (for equations see metadata.docx). Pigment concentration was calculated as the average concentration of the dominant species in each plot. mean_"pigment" represents the mean of all biomass from each vegetation community and sd_"pigment" represents the standard deviation of each vegetation community.
    Keywords: AWI_Envi; MULT; Multiple investigations; Polar Terrestrial Environmental Systems @ AWI; ToolikL_plot; Toolik Lake, Alaska
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    Format: application/zip, 3 datasets
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  • 60
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    In:  Supplement to: Park, Eunmi; Hefter, Jens; Fischer, Gerhard; Mollenhauer, Gesine (2018): TEX86 in sinking particles in three eastern Atlantic upwelling regimes. Organic Geochemistry, 124, 151-163, https://doi.org/10.1016/j.orggeochem.2018.07.015
    Publication Date: 2023-03-16
    Description: Seasonal variations in fluxes of isoprenoid glycerol dialkyl glycerol tetraethers (GDGTs) and the estimated temperatures based on TEX86 are examined in sinking particles collected using moored sediment traps in the eastern Atlantic upwelling regions. In the equatorial Guinea Basin, GDGT fluxes show a correlation with opal fluxes, implying that GDGTs are mainly transported via aggregation with diatoms. The flux-weighted TEXH86 temperatures derived from particles collected both at 853 m and 3,921 m depth correspond to the water temperature (24.1 °C) of ca. 50 m depth, where nitrate concentration starts to increase, potentially as a consequence of nitrification by Thaumarchaeota. This suggests that nutrient concentrations may affect the depth habitat of Thaumarchaeota, and it determines at which water depth the TEXH86 temperature is recorded. In the coastal upwelling off Namibia, TEXH86 temperatures are similar to satellite-derived sea surface temperature (SST) during the warm season, but the record derived from the trap is delayed relative to the SST by approximately 26 days. Warm biases, however, occur during the cold season, similar to what has previously been observed in the filamentous upwelling region off Cape Blanc. In both coastal upwelling regions, oxygen minimum zones (OMZs) are a common feature, and higher TEX86 values have been found within the OMZs in the water column off Cape Blanc and elsewhere. Thus, contributions from GDGTs produced in OMZs might explain the warmer temperature estimates during the cold season in both regions. We thus conclude that in the eastern Atlantic upwelling system, TEXH86 temperature estimates are influenced by non-thermal factors such as nutrient depth distributions and GDGTs produced in the OMZ. In paleoenvironmental records of TEX86, non-thermal signals have to be considered on regional scales.
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  • 61
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    In:  Supplement to: Pauli, Nora-Charlotte; Paiva, Filipa; Briski, Elizabeta (2018): Are Ponto-Caspian species able to cross salinity barriers? A case study of the gammarid Pontogammarus maeoticus. Ecology and Evolution, 8(19), 9817-9826, https://doi.org/10.1002/ece3.4461
    Publication Date: 2023-03-16
    Description: Recently, Ponto-Caspian species (i.e. area of Azov, Black and Caspian Seas) have invaded brackish and freshwater habitats of the North and Baltic Seas and the Laurentian Great Lakes in much higher numbers than expected based on shipping frequency and environmental conditions among these regions. Therefore, it has been hypothesized that Ponto-Caspian species may have inherent advantages over other species in colonizing new habitats, or that they are of freshwater origin. To test these hypotheses, we conducted artificial selection experiment on Ponto-Caspian amphipod Pontogammarus maeoticus collected from 10 PSU to evaluate adaptation capacity of this species to different salinities. Our results indicated that selection to lower salinity than that of population's ambient salinity is possible. Though, generation time in lower salinity conditions took slightly longer. On the contrary, selection to higher salinity was unsuccessful. Taking into account the results from this and previous studies and the geological history of the Ponto-Caspian region, we suggest that majority of the Ponto-Caspian relict fauna might be of freshwater origin and lack necessary genetic background for adaptation to fully marine conditions. Further selection studies using more species and populations, as well as molecular techniques, should be conducted to confirm this hypothesis on a broader scale. Consequently, if Ponto-Caspian relict species are of freshwater origin, the perception that they are better colonizers than species from other regions might be inclined by the fact that areas with biggest introduction frequency of nonindigenous species (i.e., shipping ports) are environmentally variable habitats which often include freshwater conditions.
    Keywords: AWI_BioOce; Biological Oceanography @ AWI
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  • 62
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    In:  Supplement to: Hörner, Tanja; Stein, Ruediger; Fahl, Kirsten (2018): Paleo-sea ice distribution and polynya variability on the Kara sea shelf during the last 12 ka. arktos - The Journal of Arctic Geosciences, https://doi.org/10.1007/s41063-018-0040-4
    Publication Date: 2023-03-16
    Description: The Kara Sea is an important area for paleo-climatic research since sea ice and brine formation take place on its shelf-two processes inducing supra-regional climatic implications and thereby connecting regional environmental variability with global climatic conditions. To gain information about past sea ice coverage and variations, three sediment cores distributed in the southern and central parts of the marginal Sea were investigated. By applying the sea ice biomarker IP25 and the PIP25 index [phytoplankton biomarker (dinosterol)-IP25 index] post-glacial sea ice variability could be detected in the central Kara Sea (Core BP00-36/4), with most intense sea ice cover between 12.4 and 11.8 ka coinciding with the Younger Dryas (12.9-11.6 ka), and reduced sea ice cover between 10 and 8 ka during the Holocene Thermal Maximum. During the last ~7 ka, increasing sea ice indicators might indicate a Holocene cooling trend, probably induced by declining summer insolation. Furthermore, temporal changes in the fast ice?polynya distribution in the southern Kara Sea were detected: expanding fast ice during the late Holocene and a cyclic short-term Holocene climate variability documented by abrupt changes in the sea ice coverage at the BP00-07/7 core site. Core BP99-04/7 from the Yenisei estuary recorded consistently seasonal sea ice cover since ~9.3 ka, apart from five short phases of fast ice expansion to the core site. The strong influence of river run-off as well as estuary processes might prevent the detection of (short-term) climatic signals at this study site.
    Keywords: AWI_Paleo; Paleoenvironmental Reconstructions from Marine Sediments @ AWI
    Type: Dataset
    Format: application/zip, 3 datasets
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  • 63
    Publication Date: 2023-03-14
    Description: Ocean acidification causes an accumulation of CO2 in marine organisms and leads to shifts in acid-base parameters. Acid-base regulation in gill breathers involves a net increase of internal bicarbonate levels through transmembrane ion exchange with the surrounding water. Successful maintenance of body fluid pH depends on the functional capacity of ion-exchange mechanisms and associated energy budget. For a detailed understanding of the dependence of acid-base regulation on water parameters, we investigated the physiological responses of the shore crab Carcinus maenas to 4 weeks of ocean acidification [OA, P(CO2)w = 1800 µatm], at variable water bicarbonate levels, paralleled by changes in water pH. Cardiovascular performance was determined together with extra-(pHe) and intracellular pH (pHi), oxygen consumption, haemolymph CO2 parameters, and ion composition. High water P(CO2) caused haemolymph P(CO2) to rise, but pHe and pHi remained constant due to increased haemolymph and cellular [HCO3-]. This process was effective even under reduced seawater pH and bicarbonate concentrations. While extracellular cation concentrations increased throughout, anion levels remained constant or decreased. Despite similar levels of haemolymph pH and ion concentrations under OA, metabolic rates, and haemolymph flow were significantly depressed by 40 and 30%, respectively, when OA was combined with reduced seawater [HCO3-] and pH. Our findings suggest an influence of water bicarbonate levels on metabolic rates as well as on correlations between blood flow and pHe. This previously unknown phenomenon should direct attention to pathways of acid-base regulation and their potential feedback on whole-animal energy demand, in relation with changing seawater carbonate parameters.
    Keywords: Bicarbonate; Eggs, hatched; EXP; Experiment; Incubation duration; pH; Pressure, air; Salinity; Spiekeroog_Island; Temperature, water; Treatment
    Type: Dataset
    Format: text/tab-separated-values, 288 data points
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  • 64
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    PANGAEA
    In:  Institut für Meereskunde, Universität Hamburg
    Publication Date: 2023-03-10
    Keywords: cruise 02+03; CTD/Rosette; CTD-RO; DATE/TIME; DEPTH, water; Event label; KJACK0107; KJACK2001_101; KJACK2001_102; KJACK2001_103; KJACK2001_104; KJACK2001_105; KJACK2001_106; KJACK2001_107; KJACK2001_108; KJACK2001_109; KJACK2001_110; KJACK2001_111; KJACK2001_112; KJACK2001_113; KJACK2001_114; KJACK2001_115; KJACK2001_116; KJACK2001_117; KJACK2001_118; KJACK2001_119; KJACK2001_120; KJACK2001_121; KJACK2001_122; KJACK2001_123; KJACK2001_124; KJACK2001_125; KJACK2001_126; KJACK2001_127; KJACK2001_128; KJACK2001_129; KJACK2001_130; KJACK2001_131; KJACK2001_132; KJACK2001_133; KJACK2001_134; KJACK2001_135; KJACK2001_136; KJACK2001_137; KJACK2001_138; KJACK2001_139; KJACK2001_140; KJACK2001_141; KJACK2001_142; KJACK2001_143; KJACK2001_144; KJACK2001_145; KJACK2001_146; KJACK2001_147; KJACK2001_148; KJACK2001_149; KJACK2001_150; KJACK2001_151; KJACK2001_152; KJACK2001_153; KJACK2001_154; KJACK2001_155; KJACK2001_156; KJACK2001_157; KJACK2001_158; KJACK2001_159; KJACK2001_160; KJACK2001_161; KJACK2001_162; KJACK2001_163; KJACK2001_164; KJACK2001_165; KJACK2001_166; KJACK2001_167; KJACK2001_169; KJACK2001_170; KJACK2001_171; KJACK2001_172; KJACK2001_173; KJACK2001_174; KJACK2001_175; KJACK2001_176; KJACK2001_177; KJACK2001_178; KJACK2001_179; KJACK2001_180; KJACK2001_181; KJACK2001_182; KJACK2001_183; KJACK2001_184; KJACK2001_185; KJACK2001_186; KJACK2001_187; KJACK2001_188; KJACK2001_189; KJACK2001_190; KJACK2001_191; KJACK2001_192; KJACK2001_193; KJACK2001_194; KJACK2001_195; KJACK2001_196; KJACK2001_197; KJACK2001_198; KJACK2001_199; KJACK2001_200; KJACK2001_201; KJACK2001_202; KJACK2001_203; KJACK2001_204; KJACK2001_205; KJACK2001_206; KJACK2001_207; KJACK2001_208; KJACK2001_209; KJACK2001_210; KJACK2001_211; KJACK2001_212; KJACK2001_213; KJACK2001_214; KJACK2001_215; KJACK2001_216; KJACK2001_217; KJACK2001_218; KJACK2001_219; KJACK2001_220; KJACK2001_221; KJACK2001_222; KJACK2001_223; KJACK2001_224; KJACK2001_225; KJACK2001_226; KJACK2001_227; KJACK2001_228; KJACK2001_229; KJACK2001_230; KJACK2001_231; KJACK2001_232; KJACK2001_233; KJACK2001_234; KJACK2001_235; KJACK2001_236; KJACK2001_237; KJACK2001_238; KJACK2001_239; KJACK2001_240; KJACK2001_241; KJACK2001_242; KJACK2001_243; KJACK2001_244; KJACK2001_245; KJACK2001_246; KJACK2001_247; KJACK2001_248; KJACK2001_249; KJACK2001_250; KJACK2001_251; KJACK2001_252; KJACK2001_253; KJACK2001_254; KJACK2001_255; KJACK2001_256; KJACK2001_257; KJACK2001_258; KJACK2001_259; KJACK2001_260; KJACK2001_261; KJACK2001_262; KJACK2001_263; KJACK2001_264; KJACK2001_265; KJACK2001_266; KJACK2001_267; KJACK2001_268; KJACK2001_269; KJACK2001_270; KJACK2001_271; Kommandor Jack; LATITUDE; LONGITUDE; Oxygen; Oxygen, dissolved; Pressure, water; Recalculated from ml/l by using (ml/l)*44.66; Salinity; South Atlantic Ocean; Temperature, water; UniHH_CTD
    Type: Dataset
    Format: text/tab-separated-values, 436810 data points
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  • 65
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    PANGAEA
    In:  Institut für Meereskunde, Universität Hamburg
    Publication Date: 2023-03-10
    Keywords: Chlorophyll a; Conductivity; CTD, Seabird; CTD/Rosette; CTD-R; CTD-RO; DATE/TIME; DEPTH, water; Elevation of event; Event label; LATITUDE; LONGITUDE; Pressure, water; Salinity; South Atlantic Ocean; Temperature, water; Transmission of light; UniHH_CTD; VA176; VA176_00-3; VA176_01-2; VA176_01-3; VA176_01-4; VA176_01-5; VA176_02; VA176_02-1; VA176_02-2; VA176_02-3; VA176_02-4; VA176_02-5; VA176_03; VA176_03-1; VA176_03-2; VA176_03-3; VA176_03-4; VA176_03-5; VA176_04; VA176_04-1; VA176_04-2; VA176_04-3; VA176_04-4; VA176_04-5; VA176_05; VA176_05-1; VA176_05-2; VA176_05-3; VA176_05-4; VA176_05-5; VA176_06; VA176_07; VA176_08; VA176_08-1; VA176_08-2; VA176_08-3; VA176_08-4; VA176_08-5; VA176_09; VA176_10; VA176_11; VA176_12; VA176_13; VA176_14; VA176_15; VA176_15-1; VA176_15-2; VA176_15-3; VA176_15-4; VA176_15-5; VA176_16; VA176_17; VA176_18; VA176_19; VA176_20; VA176_21; VA176_22; VA176_23; VA176_24; VA176_25; VA176_26; VA176_26-1; VA176_26-2; VA176_26-3; VA176_26-4; VA176_26-5; VA176_27; VA176_28; VA176_29; VA176_30; VA176_30-1; VA176_30-2; VA176_30-3; VA176_30-4; VA176_30-5; VA176_30-6; VA176_31; VA176_32; VA176_33; VA176_34; VA176_35; VA176_36; VA176_36-1; VA176_37; VA176_38; VA176_39; VA176_40; VA176_41; VA176_42; VA176_43; Valdivia (1961)
    Type: Dataset
    Format: text/tab-separated-values, 371658 data points
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  • 66
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    PANGAEA
    In:  Institut für Meereskunde, Universität Hamburg
    Publication Date: 2023-03-10
    Keywords: Conductivity; CTD/Rosette; CTD-RO; Date/Time of event; DEPTH, water; Event label; Greenland Sea; Latitude of event; Longitude of event; POS290; POS290_336; POS290_337; POS290_338; POS290_339; POS290_341; POS290_342; POS290_343; POS290_344; POS290_345; POS290_346; POS290_347; POS290_355; POS290_356; POS290_358; POS290_359; POS290_360; POS290_361; POS290_362; POS290_363; POS290_364; POS290_365; POS290_366; POS290_367; POS290_368; POS290_369; POS290_370; POS290_371; POS290_376; POS290_378; POS290_379; POS290_380; POS290_381; POS290_385; POS290_386; POS290_387; POS290_388; POS290_389; POS290_390; POS290_392; POS290_394; POS290_395; POS290_396; POS290_397; POS290_398; POS290_399; POS290_400; POS290_401; POS290_402; POS290_403; POS290_404; POS290_405; POS290_406; POS290_407; POS290_408; POS290_409; POS290_410; POS290_411; POS290_412; POS290_413; POS290_414; POS290_415; POS290_416; POS290_417; POS290_418; POS290_419; POS290_420; POS290_421; POS290_422; POS290_423; POS290_424; POS290_425; POS290_426; POS290_427; POS290_428; POS290_429; POS290_430; Poseidon; Pressure, water; Salinity; South Atlantic Ocean; Temperature, water; Transmission of light; UniHH_CTD
    Type: Dataset
    Format: text/tab-separated-values, 688315 data points
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  • 67
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    PANGAEA
    In:  Institut für Meereskunde, Universität Hamburg
    Publication Date: 2023-03-10
    Keywords: Conductivity; CTD/Rosette; CTD-RO; Date/Time of event; DEPTH, water; Event label; KONTROL 85; Latitude of event; Longitude of event; Pressure, water; Salinity; South Atlantic Ocean; Temperature, water; UniHH_CTD; VA35; VA35_01; VA35_02; VA35_03; VA35_04; VA35_05; VA35_06; VA35_07; VA35_08; VA35_09; VA35_10; VA35_11; VA35_12; VA35_13; VA35_14; VA35_15; VA35_16; VA35_17; VA35_18; VA35_19; VA35_20; VA35_21; VA35_22; VA35_23; VA35_24; VA35_25; VA35_26; VA35_27; VA35_28; VA35_29; VA35_30; VA35_31; VA35_32; VA35_33; VA35_34; VA35_35; VA35_36; VA35_37; VA35_38; VA35_39; VA35_40; Valdivia (1961)
    Type: Dataset
    Format: text/tab-separated-values, 13808 data points
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  • 68
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    PANGAEA
    In:  Supplement to: Asmala, Eero; Haraguchi, Lumi; Markager, Stiig; Massicotte, Philippe; Riemann, Bo; Staehr, Peter A; Carstensen, Jacob (2018): Eutrophication leads to accumulation of recalcitrant autochthonous organic matter in coastal environment. Global Biogeochemical Cycles, 32(11), 1673-1687, https://doi.org/10.1029/2017GB005848
    Publication Date: 2023-03-14
    Description: Anthropogenic nutrient enrichment is changing the structure and the function of coastal ecosystems. These coastal zones are transitions between freshwater and marine systems where multiple biogeochemical processes remove, produce and transform organic matter. The extent to which the coastal zone is merely a conduit for terrestrial (allochthonous) organic matter, versus a distinct source of autochthonous organic matter fueled by eutrophication, is unclear. To address this issue, we characterized the freshwater and marine dissolved organic matter (DOM) pools in an eutrophic estuary with a long water residence time (Roskilde Fjord, Denmark) over an annual cycle. We combined elemental, optical (absorbance and fluorescence) and isotopic analyses to obtain insight about the bulk properties of the DOM pool during this period. We also used sediment traps to analyze the changes related to the exchange of organic matter between the particulate (POM) and dissolved (DOM) fractions. The results showed that labile autochthonous DOM from in situ primary production was rapidly transformed to more recalcitrant DOM that accumulated in the estuary despite continuous exchange with the open sea. Also, parts of the POM pool were degraded rapidly (within 24h) and transformed into the DOM pool. Accumulated DOM was characterized by relatively low molecular size and stable carbon isotopic value, and by high protein-like fluorescence. These results indicate that autotrophic material can be a major source of specific recalcitrant DOM in eutrophic coastal waters, contributing significantly to the flux of organic carbon to the ocean.
    Keywords: Absorption coefficient, 230 nm; Absorption coefficient, 254 nm; Absorption coefficient, 275 nm; Absorption coefficient, 295 nm; Absorption coefficient, 300 nm; Absorption coefficient, 350 nm; Absorption coefficient, 355 nm; Absorption coefficient, 375 nm; Absorption coefficient, 400 nm; Absorption coefficient, 440 nm; Ammonium; Biological index; Carbon, organic, dissolved; Carbon, organic, total; Chlorophyll a; Conductivity; DATE/TIME; DEPTH, water; Event label; Fluorescence, peak A; Fluorescence, peak C; Fluorescence, peak M; Fluorescence, peak T; Fluorescence index; Humification index; LATITUDE; LONGITUDE; Molecular mass; MULT; Multiple investigations; Nitrate; Nitrate and Nitrite; Nitrite; Nitrogen, inorganic, dissolved; Nitrogen, organic, dissolved; Nitrogen, total; Nitrogen, total dissolved; PDZ Europa ANCA-GSL elemental analyser; pH; Phosphate; Phosphorus, inorganic, dissolved; Phosphorus, organic, dissolved; Phosphorus, total; Phosphorus, total dissolved; Ratio; Roskilde_fjord_RF01; Roskilde_fjord_RF02; Roskilde_fjord_RF03; Roskilde_fjord_RF04; Roskilde_fjord_RF05; Roskilde_fjord_RF06; Roskilde_fjord_RF07; Roskilde_fjord_RF08; Salinity; Sample ID; SEC analyser; Silicate; Specific ultraviolet absorbance normalized to DOC, 254 nm; Spectral slope, 275-295 nm; Spectral slope, 300-650 nm; Spectral slope, 350-400 nm; Spectrophotometer UV/VIS (Shimadzu 2401PC); Temperature, water; Varian Cary Eclipse fluorometer (Agilent); Wet oxidation total organic carbon analyzer Shimadzu; δ13C, dissolved organic carbon
    Type: Dataset
    Format: text/tab-separated-values, 7907 data points
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  • 69
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    PANGAEA
    In:  Supplement to: Juhlke, Tobias René; van Geldern, Robert; Huneau, Frédéric; Garel, Emilie; Santoni, Sébastien; Hemmerle, Hannes; Barth, Johannes A C (2019): Riverine carbon dioxide evasion along a high-relief watercourse derived from seasonal dynamics of the water-atmosphere gas exchange. Science of the Total Environment, 657, 1311-1322, https://doi.org/10.1016/j.scitotenv.2018.12.158
    Publication Date: 2023-03-14
    Description: The high-relief catchment of the Tavignanu River (Corsica Island, France) with an elevation range from sea level to 2622 m above sea level was investigated from January 2016 to April 2017 for its on-site parameters (T, pH, EC, TA), riverine carbon budget (TCO2) and stable carbon isotopes (d13C). Partial pressure of CO2 (pCO2) and annual carbon flux across the air-water boundary (FCO2) were calculated from analytical results. This data set contains the supplementary analytical data of the related publication.
    Keywords: Alkalinity, total; Carbon, inorganic, total; Carbon dioxide, flux; Carbon dioxide, flux, standard deviation; Carbon dioxide, partial pressure; Carbon dioxide, partial pressure, standard deviation; Conductivity, electrical; DATE/TIME; Distance; Elevation of event; Event label; I_Orta; II_Zincaghju; III_Vechju; IV_Corsigliese; Latitude of event; Longitude of event; pH; Restonica_R1; Restonica_R2; Restonica_R3; Restonica_R4; Restonica_R5; Restonica_R6; Site; Tavignanu_1; Tavignanu_10; Tavignanu_2; Tavignanu_3; Tavignanu_4; Tavignanu_5; Tavignanu_6; Tavignanu_7; Tavignanu_8; Tavignanu_9; Temperature, water; V_Tagnone; Water sample; WS; δ13C, dissolved inorganic carbon
    Type: Dataset
    Format: text/tab-separated-values, 920 data points
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  • 70
    Publication Date: 2023-03-14
    Keywords: Acid titration; Area/locality; Aufsess; Bicarbonate ion; Calcium; Chloride; Conductivity, electrolytic; DATE/TIME; Distance; Ion chromatography; Kainach; LATITUDE; Leinleiter; LONGITUDE; Magnesium; Nitrate; Oxygen; pH; Phosphate; Potassium; Puettlach; Sample ID; Site; Sodium; Southern Germany; Sulfate; Temperature, water; Trubach; Truppach; Water sample; WS
    Type: Dataset
    Format: text/tab-separated-values, 590 data points
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  • 71
    Publication Date: 2023-03-14
    Keywords: Acid titration; Area/locality; Bicarbonate ion; Calcium; Chloride; Conductivity, electrolytic; DATE/TIME; Distance; Ion chromatography; LATITUDE; LONGITUDE; Magnesium; Nitrate; Oxygen; pH; Phosphate; Potassium; Sample ID; Site; Sodium; Southern Germany; Sulfate; Temperature, water; Water sample; Wiesent_River; WS
    Type: Dataset
    Format: text/tab-separated-values, 1063 data points
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  • 72
    Publication Date: 2023-03-14
    Keywords: Ammonium; Bicarbonate ion; Carbon, inorganic, total; Carbon, organic, dissolved; Carbon, organic, particulate; Carbon, organic, total; Carbon, total; Carbon dioxide; Chlorophyll a; Conductivity, electrical; DATE/TIME; DEPTH, water; Flow velocity, water; Laguna_LaConceja; Location; MULT; Multiple investigations; Nitrate; Nitrite; Nitrogen, inorganic, total; Nitrogen, organic, dissolved; Nitrogen, organic, total; Nitrogen, total; Nitrogen, total dissolved; pH; Phosphorus, reactive soluble; Phosphorus, total; River discharge; River level; River width; Spain; Suspended particulate matter; Visibility; Volume
    Type: Dataset
    Format: text/tab-separated-values, 1963 data points
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  • 73
    Publication Date: 2023-03-14
    Keywords: Bicarbonate; Carbon dioxide; Carbon dioxide, flux; Carbon dioxide, gradient at air/water interface; Carbon dioxide, partial pressure; Carbon dioxide (water) partial pressure; DATE/TIME; DEPTH, water; Laguna_LaConceja; MULT; Multiple investigations; pH; Piston velocity; Salinity; Spain; Temperature, water
    Type: Dataset
    Format: text/tab-separated-values, 315 data points
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  • 74
    Publication Date: 2023-03-14
    Keywords: Alkalinity, total; Experiment day; Nitrate; Nitrite; Nitrogen, inorganic, dissolved; Nitrogen in ammonium; Number; pH; Phosphate; Treatment
    Type: Dataset
    Format: text/tab-separated-values, 840 data points
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  • 75
    Publication Date: 2023-03-14
    Keywords: Aluminium; Automatic water sampler (ISCO 3700); AWI_PerDyn; AWS_ISCO; Barium 2+; Bicarbonate ion; Bromide; Calcium; Carbon, organic, dissolved; Chloride; Conductivity, electrical; DATE/TIME; Fluoride; Herschel Island, Yukon Territory, Canada; Ice_Creek_West; Iron; Magnesium; Manganese 2+; Nitrate; Permafrost Research (Periglacial Dynamics) @ AWI; pH; Phosphorus; Potassium; Sample code/label; Silicon; Sodium; Strontium 2+; Sulfate
    Type: Dataset
    Format: text/tab-separated-values, 1260 data points
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  • 76
    Publication Date: 2023-03-14
    Keywords: Aluminium; Automatic water sampler (ISCO 3700); AWI_PerDyn; AWS_ISCO; Barium 2+; Bicarbonate ion; Bromide; Calcium; Carbon, organic, dissolved; Chloride; Conductivity, electrical; DATE/TIME; Fluoride; Herschel Island, Yukon Territory, Canada; Ice_Creek_West; Iron; Magnesium; Manganese 2+; Nitrate; Nitrogen, total dissolved; Oxygen saturation; Permafrost Research (Periglacial Dynamics) @ AWI; pH; Phosphate; Phosphorus; Potassium; Sample code/label; Silicon; Sodium; Strontium 2+; Sulfate; Suspended particulate matter
    Type: Dataset
    Format: text/tab-separated-values, 896 data points
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  • 77
    Publication Date: 2023-03-14
    Keywords: Alkalinity, total; Calculated; Carbon, inorganic, dissolved; Carbon dioxide, partial pressure; CO2 acid liberation; Conductivity, electrical; Czech Republic; DATE/TIME; Element analyser isotope ratio mass spectrometer (EA-IRMS); Elevation of event; Event label; Isotope ratio mass spectrometry; Latitude of event; Longitude of event; Multiparameter instrument; Original value; Oxidation reduction (RedOx) potential; Oxygen; Oxygen saturation; pH; Sample ID; Temperature, water; Uhlirska_DST; Uhlirska_HST; Uhlirska_P84; Water sample; WS; δ13C, dissolved inorganic carbon; δ13C, particulate organic carbon
    Type: Dataset
    Format: text/tab-separated-values, 772 data points
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  • 78
    Publication Date: 2023-03-14
    Keywords: Alkalinity, total; Calculated; Carbon, inorganic, dissolved; Carbon dioxide, partial pressure; CO2 acid liberation; Conductivity, electrical; Czech Republic; DATE/TIME; DEPTH, water; Element analyser isotope ratio mass spectrometer (EA-IRMS); Isotope ratio mass spectrometry; Multiparameter instrument; Original value; Oxidation reduction (RedOx) potential; Oxygen; Oxygen saturation; pH; River discharge; Sample ID; Temperature, water; Uhlirska_UHL; V-notch weir; Water sample; WS; δ13C, dissolved inorganic carbon; δ13C, particulate organic carbon
    Type: Dataset
    Format: text/tab-separated-values, 855 data points
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  • 79
    Publication Date: 2023-03-14
    Keywords: Alkalinity, total; Aragonite saturation state; Bicarbonate ion; Calcite saturation state; Calculated using CO2SYS; Carbonate ion; Carbon dioxide (water) partial pressure; DATE/TIME; Dry air column-averaged mixing ratio of carbon dioxide; Kristineberg_Loven-Centre; Number; Oxygen; pH; Research station; RS; Salinity; Sweden; Temperature, water
    Type: Dataset
    Format: text/tab-separated-values, 404 data points
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  • 80
    Publication Date: 2023-03-14
    Keywords: Classification; Color, a*; Color, b*; Color, L*, lightness; Conductivity; DEPTH, sediment/rock; Elba; Elba_F-I; F-I; Gravel; Gravel classification according to Ad-Hoc-AG Boden 2005 (KA5); Hand-held checker, 1:2.5 sample:ddH2O solution; Hand-held checker, 1:2.5 sample:KCl solution; Loss on ignition; Magnetic susceptibility, frequency dependence; Magnetic susceptibility, frequency dependence, standard deviation; Magnetic susceptibility, low-field; MS2B sensor; pH; Portable spectrophotometer Minolta CM-2500d; VC; Vibro corer
    Type: Dataset
    Format: text/tab-separated-values, 1076 data points
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  • 81
    Publication Date: 2023-03-14
    Keywords: CHN +S analyser; Classification; Color, a*; Color, b*; Color, L*, lightness; Conductivity; DEPTH, sediment/rock; Elba; Elba_S-I; Gravel; Gravel classification according to Ad-Hoc-AG Boden 2005 (KA5); Hand-held checker, 1:2.5 sample:ddH2O solution; Hand-held checker, 1:2.5 sample:KCl solution; Loss on ignition; Magnetic susceptibility, frequency dependence; Magnetic susceptibility, frequency dependence, standard deviation; Magnetic susceptibility, low-field; MS2B sensor; pH; Portable spectrophotometer Minolta CM-2500d; S-I; Sulfur, total; VC; Vibro corer
    Type: Dataset
    Format: text/tab-separated-values, 1351 data points
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  • 82
    Publication Date: 2023-03-14
    Keywords: Africa, Ethiopia; Branched and isoprenoid tetraether index; Calculated; Cyclization ratio of branched tetraethers; DEPTH, soil; Depth, soil, maximum; Depth, soil, minimum; Elevation of event; Event label; I; II; III; IV; Jimma_zone_I; Jimma_zone_II; Jimma_zone_III; Jimma_zone_IV; Jimma_zone_V; Jimma_zone_VI; Land use; Methylation index of dominant branched tetraethers; MULT; Multiple investigations; Optional event label; pH; Temperature, annual mean; V; VI
    Type: Dataset
    Format: text/tab-separated-values, 144 data points
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  • 83
    Publication Date: 2023-03-14
    Keywords: Alkalinity, total; Autotitrator Metrohm 785 and electrode; Barium/Calcium ratio; Barium/Calcium ratio, standard deviation; Comment; Experiment; ICP-MS, Agilent 7500-ce; Number of observations; pH; Strontium-86/Strontium-88, standard deviation; Strontium-86/Strontium-88 ratio; Strontium-87/Strontium-88, standard deviation; Strontium-87/Strontium-88 ratio; Treatment
    Type: Dataset
    Format: text/tab-separated-values, 98 data points
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  • 84
    Publication Date: 2023-03-14
    Keywords: Barium/Calcium ratio; Experiment; ICP-MS, Agilent 7500-ce; LA-ICP-MS, Laser-ablation inductively coupled plasma mass spectrometer; Neogloboquadrina dutertrei, Barium/Calcium ratio; pH; Temperature, water
    Type: Dataset
    Format: text/tab-separated-values, 325 data points
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  • 85
    facet.materialart.
    Unknown
    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-16
    Description: This data set was collected during the R. V. Polarstern cruise PS82. Outside territorial waters, current velocities were measured nearly continuously along the ship's track with a vessel-mounted TRD Instruments 153.6-kHz Ocean Surveyor ADCP. The transducers were located 11 meters below the water line and were protected against ice floes by an acoustically transparent plastic window. The current measurements used a pulse of 2 seconds and vertical bin length of 4 meters. The ship's velocity was calculated from position fixes obtained by the Global Positioning System (GPS). Heading, roll and pitch data from the ship's gyro platforms and the navigation data were used to convert the ADCP velocities into earth coordinates. The accuracy of the ADCP velocities mainly depends on the quality of the position fixes and the ship's heading data. Further errors stem from a misalignment of the transducer with the ship's centerline. The ADCP data were processed using the Ocean Surveyor Sputum Interpreter (OSSI) software developed by GEOMAR Helmholtz-Zentrum für Ozeanforschung Kiel. The reference layer was set to avoid near surface effects. The averaging interval was set to 120 seconds. Sampling interval setting: 2s; Number of bins: 80; Bin length: 4m; Pulse length: 4m; Blank beyond transmit length: 4m. Data processing setting: Upper depth of reference layer: 30m; Lower depth of reference layer: 80m; Time average: 120s; Misalignment angle: 0.9200 (from 2014-01-01T09:22:00 to 2014-02-04T15:34:00 Misalignment angle: 0.8600); amplitude: 1.0225. The precision for single ping and 4m cell size reported by TRDI is 0.30m/s. Resulting from the single ping precision and the number of pings (most of the time 36) during 120seconds the velocity accuracy is nearly 0.05m/s. (Velocity accuracy = single ping precision divided by square root of the number of pings).
    Keywords: Acoustic Doppler Current Profiling (ADCP), TRDI Ocean Surveyor, 153.6 kHz; ANT-XXIX/9; AWI_PhyOce; CT; Current velocity, east-west; Current velocity, north-south; DATE/TIME; DEPTH, water; LATITUDE; LONGITUDE; Physical Oceanography @ AWI; Polarstern; PS82; PS82-track; Quality; Underway cruise track measurements; Weddell Sea
    Type: Dataset
    Format: text/tab-separated-values, 8047893 data points
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  • 86
    Publication Date: 2023-03-16
    Keywords: Arctic Ocean; ARK-XXVI/3; DATE/TIME; DEPTH, water; Elevation of event; Event label; FRAM; FRontiers in Arctic marine Monitoring; Laptev Sea; Latitude of event; Longitude of event; Polarstern; PS78/216-2; PS78/226-2; PS78/227-3; PS78/230-3; PS78/235-3; PS78/242-2; PS78/245-4; PS78/259-2; PS78/262-2; PS78/265-2; PS78/270-3; PS78/272-1; PS78/276-2; PS78/280-2; PS78/300-2; PS78 TransArc; RAMSES; RAMSES-ACC-VIS hyperspectral radiometer and RAMSES-ARC hyperspectral radiometer, TriOS; RAMSES hyperspectral radiometer; Remote sensing reflectance at 350 nm; Remote sensing reflectance at 351 nm; Remote sensing reflectance at 352 nm; Remote sensing reflectance at 353 nm; Remote sensing reflectance at 354 nm; Remote sensing reflectance at 355 nm; Remote sensing reflectance at 356 nm; Remote sensing reflectance at 357 nm; Remote sensing reflectance at 358 nm; Remote sensing reflectance at 359 nm; Remote sensing reflectance at 360 nm; Remote sensing reflectance at 361 nm; Remote sensing reflectance at 362 nm; Remote sensing reflectance at 363 nm; Remote sensing reflectance at 364 nm; Remote sensing reflectance at 365 nm; Remote sensing reflectance at 366 nm; Remote sensing reflectance at 367 nm; Remote sensing reflectance at 368 nm; Remote sensing reflectance at 369 nm; Remote sensing reflectance at 370 nm; Remote sensing reflectance at 371 nm; Remote sensing reflectance at 372 nm; Remote sensing reflectance at 373 nm; Remote sensing reflectance at 374 nm; Remote sensing reflectance at 375 nm; Remote sensing reflectance at 376 nm; Remote sensing reflectance at 377 nm; Remote sensing reflectance at 378 nm; Remote sensing reflectance at 379 nm; Remote sensing reflectance at 380 nm; Remote sensing reflectance at 381 nm; Remote sensing reflectance at 382 nm; Remote sensing reflectance at 383 nm; Remote sensing reflectance at 384 nm; Remote sensing reflectance at 385 nm; Remote sensing reflectance at 386 nm; Remote sensing reflectance at 387 nm; Remote sensing reflectance at 388 nm; Remote sensing reflectance at 389 nm; Remote sensing reflectance at 390 nm; Remote sensing reflectance at 391 nm; Remote sensing reflectance at 392 nm; Remote sensing reflectance at 393 nm; Remote sensing reflectance at 394 nm; Remote sensing reflectance at 395 nm; Remote sensing reflectance at 396 nm; Remote sensing reflectance at 397 nm; Remote sensing reflectance at 398 nm; Remote sensing reflectance at 399 nm; Remote sensing reflectance at 400 nm; Remote sensing reflectance at 401 nm; Remote sensing reflectance at 402 nm; Remote sensing reflectance at 403 nm; Remote sensing reflectance at 404 nm; Remote sensing reflectance at 405 nm; Remote sensing reflectance at 406 nm; Remote sensing reflectance at 407 nm; Remote sensing reflectance at 408 nm; Remote sensing reflectance at 409 nm; Remote sensing reflectance at 410 nm; Remote sensing reflectance at 411 nm; Remote sensing reflectance at 412 nm; Remote sensing reflectance at 413 nm; Remote sensing reflectance at 414 nm; Remote sensing reflectance at 415 nm; Remote sensing reflectance at 416 nm; Remote sensing reflectance at 417 nm; Remote sensing reflectance at 418 nm; Remote sensing reflectance at 419 nm; Remote sensing reflectance at 420 nm; Remote sensing reflectance at 421 nm; Remote sensing reflectance at 422 nm; Remote sensing reflectance at 423 nm; Remote sensing reflectance at 424 nm; Remote sensing reflectance at 425 nm; Remote sensing reflectance at 426 nm; Remote sensing reflectance at 427 nm; Remote sensing reflectance at 428 nm; Remote sensing reflectance at 429 nm; Remote sensing reflectance at 430 nm; Remote sensing reflectance at 431 nm; Remote sensing reflectance at 432 nm; Remote sensing reflectance at 433 nm; Remote sensing reflectance at 434 nm; Remote sensing reflectance at 435 nm; Remote sensing reflectance at 436 nm; Remote sensing reflectance at 437 nm; Remote sensing reflectance at 438 nm; Remote sensing reflectance at 439 nm; Remote sensing reflectance at 440 nm; Remote sensing reflectance at 441 nm; Remote sensing reflectance at 442 nm; Remote sensing reflectance at 443 nm; Remote sensing reflectance at 444 nm; Remote sensing reflectance at 445 nm; Remote sensing reflectance at 446 nm; Remote sensing reflectance at 447 nm; Remote sensing reflectance at 448 nm; Remote sensing reflectance at 449 nm; Remote sensing reflectance at 450 nm; Remote sensing reflectance at 451 nm; Remote sensing reflectance at 452 nm; Remote sensing reflectance at 453 nm; Remote sensing reflectance at 454 nm; Remote sensing reflectance at 455 nm; Remote sensing reflectance at 456 nm; Remote sensing reflectance at 457 nm; Remote sensing reflectance at 458 nm; Remote sensing reflectance at 459 nm; Remote sensing reflectance at 460 nm; Remote sensing reflectance at 461 nm; Remote sensing reflectance at 462 nm; Remote sensing reflectance at 463 nm; Remote sensing reflectance at 464 nm; Remote sensing reflectance at 465 nm; Remote sensing reflectance at 466 nm; Remote sensing reflectance at 467 nm; Remote sensing reflectance at 468 nm; Remote sensing reflectance at 469 nm; Remote sensing reflectance at 470 nm; Remote sensing reflectance at 471 nm; Remote sensing reflectance at 472 nm; Remote sensing reflectance at 473 nm; Remote sensing reflectance at 474 nm; Remote sensing reflectance at 475 nm; Remote sensing reflectance at 476 nm; Remote sensing reflectance at 477 nm; Remote sensing reflectance at 478 nm; Remote sensing reflectance at 479 nm; Remote sensing reflectance at 480 nm; Remote sensing reflectance at 481 nm; Remote sensing reflectance at 482 nm; Remote sensing reflectance at 483 nm; Remote sensing reflectance at 484 nm; Remote sensing reflectance at 485 nm; Remote sensing reflectance at 486 nm; Remote sensing reflectance at 487 nm; Remote sensing reflectance at 488 nm; Remote sensing reflectance at 489 nm; Remote sensing reflectance at 490 nm; Remote sensing reflectance at 491 nm; Remote sensing reflectance at 492 nm; Remote sensing reflectance at 493 nm; Remote sensing reflectance at 494 nm; Remote sensing reflectance at 495 nm; Remote sensing reflectance at 496 nm; Remote sensing reflectance at 497 nm; Remote sensing reflectance at 498 nm; Remote sensing reflectance at 499 nm; Remote sensing reflectance at 500 nm; Remote sensing reflectance at 501 nm; Remote sensing reflectance at 502 nm; Remote sensing reflectance at 503 nm; Remote sensing reflectance at 504 nm; Remote sensing reflectance at 505 nm; Remote sensing reflectance at 506 nm; Remote sensing reflectance at 507 nm; Remote sensing reflectance at 508 nm; Remote sensing reflectance at 509 nm; Remote sensing reflectance at 510 nm; Remote sensing reflectance at 511 nm; Remote sensing reflectance at 512 nm; Remote sensing reflectance at 513 nm; Remote sensing reflectance at 514 nm; Remote sensing reflectance at 515 nm; Remote sensing reflectance at 516 nm; Remote sensing reflectance at 517 nm; Remote sensing reflectance at 518 nm; Remote sensing reflectance at 519 nm; Remote sensing reflectance at 520 nm; Remote sensing reflectance at 521 nm; Remote sensing reflectance at 522 nm; Remote sensing reflectance at 523 nm; Remote sensing reflectance at 524 nm; Remote sensing reflectance at 525 nm; Remote sensing reflectance at 526 nm; Remote sensing reflectance at 527 nm; Remote sensing reflectance at 528 nm; Remote sensing reflectance at 529 nm; Remote sensing reflectance at 530 nm; Remote sensing reflectance at 531 nm; Remote sensing reflectance at 532 nm; Remote sensing reflectance at 533 nm; Remote sensing reflectance at 534 nm; Remote sensing reflectance at 535 nm; Remote sensing reflectance at 536 nm; Remote sensing reflectance at 537 nm; Remote sensing reflectance at 538 nm; Remote sensing reflectance at 539 nm; Remote sensing reflectance at 540 nm; Remote sensing reflectance at 541 nm; Remote sensing reflectance at 542 nm; Remote sensing reflectance at 543 nm; Remote sensing reflectance at 544 nm; Remote sensing reflectance at 545 nm; Remote sensing reflectance at 546
    Type: Dataset
    Format: text/tab-separated-values, 6015 data points
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  • 87
    Publication Date: 2023-03-16
    Keywords: Arctic Ocean; ARK-XXVI/3; DATE/TIME; DEPTH, water; Elevation of event; Event label; FRAM; FRontiers in Arctic marine Monitoring; Laptev Sea; Latitude of event; Longitude of event; Polarstern; PS78/216-2; PS78/226-2; PS78/227-3; PS78/230-3; PS78/235-3; PS78/242-2; PS78/245-4; PS78/259-2; PS78/262-2; PS78/265-2; PS78/270-3; PS78/272-1; PS78/276-2; PS78/280-2; PS78/300-2; PS78 TransArc; RAMSES; RAMSES-ACC-VIS hyperspectral radiometer and RAMSES-ARC hyperspectral radiometer, TriOS; RAMSES hyperspectral radiometer; Remote sensing reflectance at 350 nm; Remote sensing reflectance at 351 nm; Remote sensing reflectance at 352 nm; Remote sensing reflectance at 353 nm; Remote sensing reflectance at 354 nm; Remote sensing reflectance at 355 nm; Remote sensing reflectance at 356 nm; Remote sensing reflectance at 357 nm; Remote sensing reflectance at 358 nm; Remote sensing reflectance at 359 nm; Remote sensing reflectance at 360 nm; Remote sensing reflectance at 361 nm; Remote sensing reflectance at 362 nm; Remote sensing reflectance at 363 nm; Remote sensing reflectance at 364 nm; Remote sensing reflectance at 365 nm; Remote sensing reflectance at 366 nm; Remote sensing reflectance at 367 nm; Remote sensing reflectance at 368 nm; Remote sensing reflectance at 369 nm; Remote sensing reflectance at 370 nm; Remote sensing reflectance at 371 nm; Remote sensing reflectance at 372 nm; Remote sensing reflectance at 373 nm; Remote sensing reflectance at 374 nm; Remote sensing reflectance at 375 nm; Remote sensing reflectance at 376 nm; Remote sensing reflectance at 377 nm; Remote sensing reflectance at 378 nm; Remote sensing reflectance at 379 nm; Remote sensing reflectance at 380 nm; Remote sensing reflectance at 381 nm; Remote sensing reflectance at 382 nm; Remote sensing reflectance at 383 nm; Remote sensing reflectance at 384 nm; Remote sensing reflectance at 385 nm; Remote sensing reflectance at 386 nm; Remote sensing reflectance at 387 nm; Remote sensing reflectance at 388 nm; Remote sensing reflectance at 389 nm; Remote sensing reflectance at 390 nm; Remote sensing reflectance at 391 nm; Remote sensing reflectance at 392 nm; Remote sensing reflectance at 393 nm; Remote sensing reflectance at 394 nm; Remote sensing reflectance at 395 nm; Remote sensing reflectance at 396 nm; Remote sensing reflectance at 397 nm; Remote sensing reflectance at 398 nm; Remote sensing reflectance at 399 nm; Remote sensing reflectance at 400 nm; Remote sensing reflectance at 401 nm; Remote sensing reflectance at 402 nm; Remote sensing reflectance at 403 nm; Remote sensing reflectance at 404 nm; Remote sensing reflectance at 405 nm; Remote sensing reflectance at 406 nm; Remote sensing reflectance at 407 nm; Remote sensing reflectance at 408 nm; Remote sensing reflectance at 409 nm; Remote sensing reflectance at 410 nm; Remote sensing reflectance at 411 nm; Remote sensing reflectance at 412 nm; Remote sensing reflectance at 413 nm; Remote sensing reflectance at 414 nm; Remote sensing reflectance at 415 nm; Remote sensing reflectance at 416 nm; Remote sensing reflectance at 417 nm; Remote sensing reflectance at 418 nm; Remote sensing reflectance at 419 nm; Remote sensing reflectance at 420 nm; Remote sensing reflectance at 421 nm; Remote sensing reflectance at 422 nm; Remote sensing reflectance at 423 nm; Remote sensing reflectance at 424 nm; Remote sensing reflectance at 425 nm; Remote sensing reflectance at 426 nm; Remote sensing reflectance at 427 nm; Remote sensing reflectance at 428 nm; Remote sensing reflectance at 429 nm; Remote sensing reflectance at 430 nm; Remote sensing reflectance at 431 nm; Remote sensing reflectance at 432 nm; Remote sensing reflectance at 433 nm; Remote sensing reflectance at 434 nm; Remote sensing reflectance at 435 nm; Remote sensing reflectance at 436 nm; Remote sensing reflectance at 437 nm; Remote sensing reflectance at 438 nm; Remote sensing reflectance at 439 nm; Remote sensing reflectance at 440 nm; Remote sensing reflectance at 441 nm; Remote sensing reflectance at 442 nm; Remote sensing reflectance at 443 nm; Remote sensing reflectance at 444 nm; Remote sensing reflectance at 445 nm; Remote sensing reflectance at 446 nm; Remote sensing reflectance at 447 nm; Remote sensing reflectance at 448 nm; Remote sensing reflectance at 449 nm; Remote sensing reflectance at 450 nm; Remote sensing reflectance at 451 nm; Remote sensing reflectance at 452 nm; Remote sensing reflectance at 453 nm; Remote sensing reflectance at 454 nm; Remote sensing reflectance at 455 nm; Remote sensing reflectance at 456 nm; Remote sensing reflectance at 457 nm; Remote sensing reflectance at 458 nm; Remote sensing reflectance at 459 nm; Remote sensing reflectance at 460 nm; Remote sensing reflectance at 461 nm; Remote sensing reflectance at 462 nm; Remote sensing reflectance at 463 nm; Remote sensing reflectance at 464 nm; Remote sensing reflectance at 465 nm; Remote sensing reflectance at 466 nm; Remote sensing reflectance at 467 nm; Remote sensing reflectance at 468 nm; Remote sensing reflectance at 469 nm; Remote sensing reflectance at 470 nm; Remote sensing reflectance at 471 nm; Remote sensing reflectance at 472 nm; Remote sensing reflectance at 473 nm; Remote sensing reflectance at 474 nm; Remote sensing reflectance at 475 nm; Remote sensing reflectance at 476 nm; Remote sensing reflectance at 477 nm; Remote sensing reflectance at 478 nm; Remote sensing reflectance at 479 nm; Remote sensing reflectance at 480 nm; Remote sensing reflectance at 481 nm; Remote sensing reflectance at 482 nm; Remote sensing reflectance at 483 nm; Remote sensing reflectance at 484 nm; Remote sensing reflectance at 485 nm; Remote sensing reflectance at 486 nm; Remote sensing reflectance at 487 nm; Remote sensing reflectance at 488 nm; Remote sensing reflectance at 489 nm; Remote sensing reflectance at 490 nm; Remote sensing reflectance at 491 nm; Remote sensing reflectance at 492 nm; Remote sensing reflectance at 493 nm; Remote sensing reflectance at 494 nm; Remote sensing reflectance at 495 nm; Remote sensing reflectance at 496 nm; Remote sensing reflectance at 497 nm; Remote sensing reflectance at 498 nm; Remote sensing reflectance at 499 nm; Remote sensing reflectance at 500 nm; Remote sensing reflectance at 501 nm; Remote sensing reflectance at 502 nm; Remote sensing reflectance at 503 nm; Remote sensing reflectance at 504 nm; Remote sensing reflectance at 505 nm; Remote sensing reflectance at 506 nm; Remote sensing reflectance at 507 nm; Remote sensing reflectance at 508 nm; Remote sensing reflectance at 509 nm; Remote sensing reflectance at 510 nm; Remote sensing reflectance at 511 nm; Remote sensing reflectance at 512 nm; Remote sensing reflectance at 513 nm; Remote sensing reflectance at 514 nm; Remote sensing reflectance at 515 nm; Remote sensing reflectance at 516 nm; Remote sensing reflectance at 517 nm; Remote sensing reflectance at 518 nm; Remote sensing reflectance at 519 nm; Remote sensing reflectance at 520 nm; Remote sensing reflectance at 521 nm; Remote sensing reflectance at 522 nm; Remote sensing reflectance at 523 nm; Remote sensing reflectance at 524 nm; Remote sensing reflectance at 525 nm; Remote sensing reflectance at 526 nm; Remote sensing reflectance at 527 nm; Remote sensing reflectance at 528 nm; Remote sensing reflectance at 529 nm; Remote sensing reflectance at 530 nm; Remote sensing reflectance at 531 nm; Remote sensing reflectance at 532 nm; Remote sensing reflectance at 533 nm; Remote sensing reflectance at 534 nm; Remote sensing reflectance at 535 nm; Remote sensing reflectance at 536 nm; Remote sensing reflectance at 537 nm; Remote sensing reflectance at 538 nm; Remote sensing reflectance at 539 nm; Remote sensing reflectance at 540 nm; Remote sensing reflectance at 541 nm; Remote sensing reflectance at 542 nm; Remote sensing reflectance at 543 nm; Remote sensing reflectance at 544 nm; Remote sensing reflectance at 545 nm; Remote sensing reflectance at 546
    Type: Dataset
    Format: text/tab-separated-values, 6015 data points
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  • 88
    Publication Date: 2023-03-16
    Keywords: AGE; Arctic Ocean; ARK-XXIX/1, TRANSSIZ; AWI_Paleo; Calcium carbonate; Carbon, organic, total; Carbon, total; Carbon/Nitrogen ratio; DEPTH, sediment/rock; KAL; Kasten corer; Nitrogen, total; Paleoenvironmental Reconstructions from Marine Sediments @ AWI; Polarstern; PS92; PS92/039-2; Sulfur, total
    Type: Dataset
    Format: text/tab-separated-values, 1006 data points
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  • 89
    Publication Date: 2023-03-16
    Keywords: AWI_Paleo; File format; File name; File size; Paleoenvironmental Reconstructions from Marine Sediments @ AWI; Uniform resource locator/link to file
    Type: Dataset
    Format: text/tab-separated-values, 12 data points
    Location Call Number Expected Availability
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  • 90
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    Unknown
    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-16
    Keywords: DATE/TIME; DEPTH, sediment/rock; MULT; Multiple investigations; Oxygen; PotterCove_Isla_D_2015; Potter Cove, King George Island, Antarctic Peninsula
    Type: Dataset
    Format: text/tab-separated-values, 902 data points
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  • 91
    Publication Date: 2023-03-16
    Keywords: AWI_Envi; DATE/TIME; LATITUDE; LONGITUDE; MULT; Multiple investigations; ORDINAL NUMBER; Plot; Polar Terrestrial Environmental Systems @ AWI; Reflectance; Replicate; Season; Site; ToolikL_plot; Toolik Lake, Alaska; UTM Easting, Universal Transverse Mercator; UTM Northing, Universal Transverse Mercator; UTM Zone, Universal Transverse Mercator; Vegetation type; Wavelength
    Type: Dataset
    Format: text/tab-separated-values, 3314520 data points
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  • 92
    Publication Date: 2023-03-16
    Keywords: Biological oxygen saturation anomalies; CT; DATE/TIME; Distance; LATITUDE; LONGITUDE; NCP_2016_sep; Net community production of oxygen; Sea surface salinity; Sea surface temperature; Underway cruise track measurements
    Type: Dataset
    Format: text/tab-separated-values, 53400 data points
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  • 93
    Publication Date: 2023-03-16
    Keywords: AWI_Envi; Polar Terrestrial Environmental Systems @ AWI; Taymyr_peninsula
    Type: Dataset
    Format: application/zip, 659.4 MBytes
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  • 94
    Publication Date: 2023-03-16
    Keywords: Date/Time of event; Event label; Indian Ocean; Latitude of event; Longitude of event; Marion Dufresne (1995); MD206; MD206_OISO11; MD206_OISO14; MD206_OISO15; MD206_OISO16; MD206_OISO18; MD206_OISO2; MD206_OISO3; MD206_OISO37; MD206_OISO4; MD206_OISO6; MD206_OISO7; MD206_OISO9; MD206_OISOE; Method comment; MULT; Multiple investigations; Nitrogen; Nitrogen, total; Nitrogen-15, atmospheric; Nitrogen fixation rate; Replicate; Salinity; δ15N
    Type: Dataset
    Format: text/tab-separated-values, 792 data points
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  • 95
    Publication Date: 2023-03-16
    Keywords: AWI_Envi; DATE/TIME; Event label; Imnavait_vegGrid; LATITUDE; LONGITUDE; MULT; Multiple investigations; ORDINAL NUMBER; Plot; Polar Terrestrial Environmental Systems @ AWI; Reflectance; Replicate; Season; ToolikL_plot; Toolik Lake, Alaska; UTM Easting, Universal Transverse Mercator; UTM Northing, Universal Transverse Mercator; UTM Zone, Universal Transverse Mercator; Vegetation type; Wavelength
    Type: Dataset
    Format: text/tab-separated-values, 9265320 data points
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  • 96
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    Unknown
    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Publication Date: 2023-03-16
    Keywords: 19-Butanoyloxyfucoxanthin; 19-Hexanoyloxyfucoxanthin; Alloxanthin; alpha-Carotene; Antheraxanthin; beta-Carotene; Chlorophyll a; Chlorophyll b; Chlorophyll c1+c2; Chlorophyll c3; Chlorophyllide a; Date/Time of event; Diadinoxanthin; Diatoxanthin; Divinyl chlorophyll a; Event label; Fucoxanthin; Indian Ocean; Latitude of event; Longitude of event; Lutein; Marion Dufresne (1995); MD206; MD206_OISO10; MD206_OISO11; MD206_OISO12; MD206_OISO14; MD206_OISO15; MD206_OISO16; MD206_OISO18; MD206_OISO2; MD206_OISO3; MD206_OISO37; MD206_OISO4; MD206_OISO6; MD206_OISO7; MD206_OISO9; MD206_OISOE; MULT; Multiple investigations; Neoxanthin; Peridinin; Prasinoxanthin; Salinity; Timeslice; Violaxanthin; Zeaxanthin
    Type: Dataset
    Format: text/tab-separated-values, 552 data points
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  • 97
    Publication Date: 2023-03-16
    Keywords: Ammonium; Ammonium uptake rate; Carbon fixation rate; Chlorophyll a; Date/Time of event; DEPTH, water; Event label; Fraction; Indian Ocean; Latitude of event; Longitude of event; Marion Dufresne (1995); MD206; MD206_OISO11; MD206_OISO14; MD206_OISO15; MD206_OISO16; MD206_OISO18; MD206_OISO2; MD206_OISO3; MD206_OISO37; MD206_OISO4; MD206_OISO6; MD206_OISO7; MD206_OISO9; MD206_OISOE; Method comment; Mixed layer depth; MULT; Multiple investigations; Nitrate; Nitrate uptake rate; Nitrite; Oxygen; Phosphate; Replicate; Salinity; Silicate; Temperature, water; Timeslice
    Type: Dataset
    Format: text/tab-separated-values, 1253 data points
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  • 98
    Publication Date: 2023-03-16
    Keywords: Aggregates; Center for Marine Environmental Sciences; Equivalent spherical diameter; Equivalent spherical diameter, standard deviation; Event label; Experiment; GeoB19401; GeoB19403; GeoB19406; High deposition; Latitude of event; Longitude of event; Low deposition; MARUM; MULT; Multiple investigations; POS481; Poseidon; ROBEX; Scavenging; SeaPump; Seasonal and regional food web interactions with the biological pump; Sinking velocity; Sinking velocity, standard deviation; Standard deviation; Treatment
    Type: Dataset
    Format: text/tab-separated-values, 57 data points
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  • 99
    Publication Date: 2023-03-16
    Keywords: Aggregates; Aggregates, mean volume; Carbon, organic, particulate mass; Center for Marine Environmental Sciences; Equivalent spherical diameter; Equivalent spherical diameter, standard deviation; Event label; Experiment; GeoB19401; GeoB19403; GeoB19406; High deposition; Latitude of event; Longitude of event; Low deposition; MARUM; MULT; Multiple investigations; POS481; Poseidon; Ratio; ROBEX; Scavenging; SeaPump; Seasonal and regional food web interactions with the biological pump; Treatment
    Type: Dataset
    Format: text/tab-separated-values, 141 data points
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  • 100
    Publication Date: 2023-03-16
    Type: Dataset
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet, 21.1 kBytes
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