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  • 1
    Publication Date: 2024-06-27
    Description: Upwelling of nutrient-rich deep waters make eastern boundary upwelling systems (EBUSs), such as the Humboldt Current system, hot spots of marine productivity. Associated settling of organic matter to depth and consecutive aerobic decomposition results in large subsurface water volumes being oxygen depleted. Under these circumstances, organic matter remineralisation can continue via denitrification, which represents a major loss pathway for bioavailable nitrogen. Additionally, anaerobic ammonium oxidation can remove significant amounts of nitrogen in these areas. Here we assess the interplay of suboxic water upwelling and nitrogen cycling in a manipulative offshore mesocosm experiment. Measured denitrification rates in incubations with water from the oxygen-depleted bottom layer of the mesocosms (via 15N label incubations) mostly ranged between 5.5 and 20 nmol N2 L−1 h−1 (interquartile range), reaching up to 80 nmol N2 L−1 h−1. However, actual in situ rates in the mesocosms, estimated via Michaelis–Menten kinetic scaling, did most likely not exceed 0.2–4.2 nmol N2 L−1 h−1 (interquartile range) due to substrate limitation. In the surrounding Pacific, measured denitrification rates were similar, although indications of substrate limitation were detected only once. In contrast, anammox (anaerobic ammonium oxidation) made only a minor contribution to the overall nitrogen loss when encountered in both the mesocosms and the Pacific Ocean. This was potentially related to organic matter C / N stoichiometry and/or process-specific oxygen and hydrogen sulfide sensitivities. Over the first 38 d of the experiment, total nitrogen loss calculated from in situ rates of denitrification and anammox was comparable to estimates from a full nitrogen budget in the mesocosms and ranged between ∼ 1 and 5.5 µmol N L−1. This represents up to ∼  20 % of the initially bioavailable inorganic and organic nitrogen standing stocks. Interestingly, this loss is comparable to the total amount of particulate organic nitrogen that was exported into the sediment traps at the bottom of the mesocosms at about 20 m depth. Altogether, this suggests that a significant portion, if not the majority of nitrogen that could be exported to depth, is already lost, i.e. converted to N2 in a relatively shallow layer of the surface ocean, provided that there are oxygen-deficient conditions like those during coastal upwelling in our study. Published data for primary productivity and nitrogen loss in all EBUSs reinforce such conclusion.
    Type: Article , PeerReviewed
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  • 2
    Publication Date: 2024-06-27
    Description: The dataset contains carbon (C) and nitrogen (N) stable isotope compositions analysed in the muscle tissue of 15 meso- to bathypelagic species sampled in the twilight zone (deep pelagic area) of the Bay of Biscay, North-East Atlantic. The species included 4 crustacean species (Pasiphaea sivado, Sergia robusta, Systellaspis debilis, Ephyrina figueirai) and 11 fish species (Xenodermichthys copei, Searsia koefoedi, Myctophum punctatum, Notoscopelus kroeyeri, Lampanyctus crocodilus, Argyropelecus olfersii, Arctozenus risso, Stomias boa, Serrivomer beanii, Chauliodus sloani, Aphanopus carbo). Specimens were collected during a single fishery in a canyon of the slope of the Bay of Biscay in October 2017, during the EVHOE fishery survey (“Evaluation Halieutique de l'Ouest de l'Europe”; https://doi.org/10.17600/17002300) conducted each autumn by the “Institut Français de Recherche pour l'Exploitation de la Mer” (Ifremer) on R/V Thalassa. A total of 266 individuals belonging to the 15 species were collected at night using a 25 m vertical opening pelagic trawl in the deep scattering layer (ca. 800 m depth in the water column; 1330 m bottom depth). All organisms were collected during one haul of 60 min, at a speed of approximately 4 knots (geographical coordinates at the beginning of the turn/end of the fishing: 45.103°N, -3.543° W). For small fish and crustaceans, organisms belonging to the same species were pooled by individuals of similar sizes. The size of each individual (total length for fish, cephalothorax length for crustaceans, in mm) as well as the total fresh weight of individuals or pools (to the nearest 0.5 g wet mass) were determined on board, and the individuals were rinsed with ultrapure water before storage. Mean individual sizes and fresh wet weights are here reported for each sample constituted by a pool of individuals. Samples (individuals or pools of individuals, N=39 in total) were finally stored at -20°C until further treatment in the laboratory. In clean and contamination-free conditions of the laboratory, whole organisms were briefly thawed and a small piece of white muscle (typically 〈3% of individual total weight) was collected from each individual. The muscle tissue is indeed generally recommended in the literature for food web studies inferred from stable isotope analyses (Pinnegar and Polunin, 1999). After collection, muscle subsamples were frozen again at -20°C, freeze-dried and homogenised manually into a fine powder. An aliquot of this powder (0.40 ± 0.05 mg dry mass) was weighed in tin cups. Analyses were finally performed with an isotope ratio mass spectrometer (Delta V Advantage with a Conflo IV interface, Thermo Scientific) coupled to an elemental analyser (Flash EA 2000, Thermo Scientific). The results are presented in the usual δ notation relative to the deviation from international standards (Vienna Pee Dee Belemnite for δ13C values, and atmospheric nitrogen for δ15N values), in parts per thousand (‰). Based on replicate measurements of USGS-61 and USGS-62 used as laboratory internal standards, experimental analytical precision was 〈0.10‰ and 〈0.15‰ for δ13C and δ15N, respectively. With the elemental analyser, bulk C:N ratios in muscle could be also determined as a proxy of the lipid content or body condition of organisms (Hoffman et al., 2015; Post et al., 2007). Samples were thus untreated (not lipid-extracted) before analyses in order to have access to bulk (untreated) C:N ratios. However, lipids are highly depleted in 13C relative to other tissue components (DeNiro and Epstein, 1977) and significant variations in lipids (especially between species) can affect δ13C signatures even if trophic sources are similar. Before using data as trophic markers, we thus recommend to mathematically correct δ13C values for the potential effect of lipids according to the formula proposed by Post et al. (2007) using bulk C:N ratios (δ13C (corrected) = δ13C (bulk) – 3.32 + 0.99 x C:N ratio). Alternatively, δ15N values do not need to be corrected.
    Keywords: bathypelagic; Bay of Biscay; Calculated; Carbon, total; Carbon/Nitrogen ratio; Class; crustacea; Delta V Advantage IRMS coupled to a Flash 2000 EA (EA-IRMS) by a 199 Conflo IV (Thermo Fisher Scientific Inc.); DEPTH, water; Device type; EVHOE-2017; EVHOE-2017_CHP21-V0494; Family; Field observation; fish; GOVT; Grande Ouverture Verticale trawl; Identification; isotope ratios; Length; mesopelagic; Nitrogen, total; Number of individuals; Order; Phylum; Sample ID; Sample type; Size; Species; Station label; SUMMER; Sustainable Management of Mesopelagic Resources; temperate marine system; Thalassa; Tissue Descriptor; trophic markers; Uniform resource locator/link to reference; Wet mass; δ13C; δ15N
    Type: Dataset
    Format: text/tab-separated-values, 841 data points
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  • 3
    Publication Date: 2024-06-27
    Description: The dataset contains energy density values and concentrations in 19 elements analysed in whole bodies of 15 meso- to bathypelagic species sampled in the twilight zone (deep pelagic area) of the Bay of Biscay, North-East Atlantic. The species included 4 crustacean species (Pasiphaea sivado, Sergia robusta, Systellaspis debilis, Ephyrina figueirai) and 11 fish species (Xenodermichthys copei, Searsia koefoedi, Myctophum punctatum, Notoscopelus kroeyeri, Lampanyctus crocodilus, Argyropelecus olfersii, Arctozenus risso, Stomias boa, Serrivomer beanii, Chauliodus sloani, Aphanopus carbo). The elements included 6 major constitutive elements (macro-minerals) and 13 trace elements among which 9 essential (micro-nutrients) and 4 non-essential elements (undesirables, with no know biological function). Specimens were collected during a single fishery in a canyon of the slope of the Bay of Biscay in October 2017, during the EVHOE fishery survey (“Evaluation Halieutique de l'Ouest de l'Europe”; https://doi.org/10.17600/17002300) conducted each autumn by the “Institut Français de Recherche pour l'Exploitation de la Mer” (Ifremer) on R/V Thalassa. A total of 266 individuals belonging to the 15 species were collected at night using a 25 m vertical opening pelagic trawl in the deep scattering layer (ca. 800 m depth in the water column; 1330 m bottom depth). All organisms were collected during one haul of 60 min, at a speed of approximately 4 knots (geographical coordinates at the beginning of the turn/end of the fishing: 45.103°N, -3.543° W). For small fish and crustaceans, organisms belonging to the same species were pooled by individuals of similar sizes. The size of each individual (total length for fish, cephalothorax length for crustaceans, in mm) as well as the total fresh weight of individuals or pools (to the nearest 0.5 g wet mass) were determined on board, and the individuals were rinsed with ultrapure water before storage. Mean individual sizes and fresh wet weights are here reported for each sample constituted by a pool of individuals. Samples (individuals or pools of individuals, N=39 in total) were finally stored at -20°C until further treatment in the laboratory. In clean and contamination-free conditions of the laboratory, whole organisms were briefly thawed and the digestive tracts of fish (i.e. stomachs and intestines) were emptied and put back in individuals. Whole individuals were then cut into small pieces and a first fresh grinding of individuals (or pools of individuals for small fish and crustaceans) was carried out using an Ultra Turrax® type grinder with stainless steel arms. Samples were finally refrozen at -20° C in acid pre-cleaned and calcined (450°C) glass jars, lyophilized during 72 h, and ground again into a fine and homogeneous powder using a stainless-steel knife mill. If necessary, this was completed by ball milling (MM400 Retsch®) using bowls and marbles with zirconium oxide coating. Each material was conscientiously rinsed with a succession of ultrapure water/ethanol/ultrapure water between each sample. Energy density was estimated on dried homogenised samples following Spitz et al. (2010), using a Parr® 1266 semi-micro-oxygen bomb calorimeter and an adiabatic bomb-calorimetry in which gross energy is determined by measuring heat of combustion. Values are presented in kJ/g dry weight and are means of duplicate determination (deviation between two assays 〈2%). Total concentrations of calcium (Ca), potassium (K), magnesium (Mg), sodium (Na), phosphorus (P) and strontium (Sr), as major constitutive chemical elements (macro-minerals) in biological organisms, were determined by inductively coupled plasma atomic emission spectrometry (ICP-OES, Vista-Pro Varian) according to an in-laboratory approved method. Briefly with this method, aliquots of samples (~250 mg dry mass of homogenised powder) were digested using a 6:2 (v/v) mixture with nitric acid (HNO3 69%, Trace Metal Grade®, FisherScientific) and hydrochloric acid (HCl, 34%, Trace Metal Grade®, FisherScientific). Acidic digestion of the samples was performed overnight at room temperature and then in a microwave oven (START-D, Milestone). The digests were finally diluted to 50 mL with ultrapure water before analyses with ICP-OES. Total concentrations of 9 essential – arsenic (As), cobalt (Co), copper (Cu), iron (Fe), manganese (Mn), molybdenum (Mo), selenium (Se), vanadium (V), zinc (Zn) – and 4 non-essential – silver (Ag), cadmium (Cd), lead (Pb) – trace elements were determined by inductively coupled plasma mass spectrometry (ICP-MS, ICAP-Qc ThermoFisher) according to an in-laboratory approved method. Briefly with this method, aliquots of samples (~200 mg of homogenised powder) were placed in Teflon bombs and mineralized with a mixture of ultrapure HNO3 acid (PlasmaPure Plus grade, SCP Science®) and ultrapure water using a microwave (ETHOS-UP, Milestone). The digests were then diluted to 50 ml with ultrapure water before analyses with ICP-MS. Finally, total mercury (Hg) concentrations (a non-essential-element) were determined by atomic absorption spectrophotometry using an Advanced Mercury Analyser (ALTEC AMA-254, Altec Ltd), on aliquots of homogenised powder (50 ± 5 mg), according to the standard operating procedure described in the US-EPA method N°7473 (U.S. Environmental Protection Agency, 1998). The quality assurance of all metal analyses relied on blank and internal standard controls, and on the accuracy and reproducibility of data relative to the certified reference materials (CRMs) used in each analytical run. Blank values were systematically below the detection limits and CRM values concurred with certified concentrations. All elemental concentrations given on a dry weight basis can be converted on a wet weight basis according to the percentage of moisture measured for each sample.
    Keywords: Arsenic; Atomic absorption spectrophotometry (Altec, AMA 254); bathypelagic; Bay of Biscay; Cadmium; Calcium; Calorimetry (Parr 6725 semimicro calorimeter and Parr 6772 precision thermometer); Class; Cobalt; Copper; crustacea; DEPTH, water; Device type; energy density; Energy density, per dry mass; EVHOE-2017; EVHOE-2017_CHP21-V0494; Family; Field observation; fish; GOVT; Grande Ouverture Verticale trawl; ICP-OES, Varian Vista Pro; Identification; inorganic elements; Iron; Lead; Length; macro-minerals; Magnesium; Manganese; Mercury; mesopelagic; Micro-nutrients; Moisture; Molybdenum; Number of individuals; Order; Phosphorus; Phylum; Potassium; S-(Q)-ICP-MS measurements, Thermo Scientific iCAP-Qc ICP-MS; Sample ID; Sample type; Selenium; Silver; Size; Sodium; Species; Station label; Strontium; SUMMER; Sustainable Management of Mesopelagic Resources; temperate marine system; Thalassa; Tissue Descriptor; trace metals; Uniform resource locator/link to reference; Vanadium; Wet mass; Zinc
    Type: Dataset
    Format: text/tab-separated-values, 1465 data points
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  • 4
    Publication Date: 2024-06-27
    Description: The dataset contains carbon (C) and nitrogen (N) stable isotope compositions analysed in the muscle tissue and energy density values and concentrations of 19 elements analysed in whole bodies of 15 meso- to bathypelagic species sampled in the twilight zone (deep pelagic area) of the Bay of Biscay, North-East Atlantic. The species included 4 crustacean species (Pasiphaea sivado, Sergia robusta, Systellaspis debilis, Ephyrina figueirai) and 11 fish species (Xenodermichthys copei, Searsia koefoedi, Myctophum punctatum, Notoscopelus kroeyeri, Lampanyctus crocodilus, Argyropelecus olfersii, Arctozenus risso, Stomias boa, Serrivomer beanii, Chauliodus sloani, Aphanopus carbo). The elements included 6 major constitutive elements (macro-minerals) and 13 trace elements among which 9 essential (micro-nutrients) and 4 non-essential elements (undesirables, with no know biological function). Specimens were collected during a single fishery in a canyon of the slope of the Bay of Biscay in October 2017, during the EVHOE fishery survey (“Evaluation Halieutique de l'Ouest de l'Europe”; https://doi.org/10.17600/17002300) conducted each autumn by the “Institut Français de Recherche pour l'Exploitation de la Mer” (Ifremer) on R/V Thalassa. A total of 266 individuals belonging to the 15 species were collected at night using a 25 m vertical opening pelagic trawl in the deep scattering layer (ca. 800 m depth in the water column; 1330 m bottom depth). All organisms were collected during one haul of 60 min, at a speed of approximately 4 knots (geographical coordinates at the beginning of the turn/end of the fishing: 45.103°N, -3.543° W).
    Keywords: bathypelagic; crustacea; energy density; Field observation; fish; inorganic elements; isotope ratios; macro-minerals; mesopelagic; Micro-nutrients; SUMMER; Sustainable Management of Mesopelagic Resources; temperate marine system; trace metals; trophic markers
    Type: Dataset
    Format: application/zip, 2 datasets
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  • 5
    Publication Date: 2024-06-27
    Description: Two Teledyne RDI Ocean Surveyor systems with 38 and 75 kHz transmission frequency were used. Data was processed with a software package developed at GEOMAR following the GO-SHIP standards (Firing and Hummon, 2010). The data was subsequently averaged over one minute intervals, converted to a NetCDF based format.
    Keywords: Acoustic Doppler Current Profiler; Acoustic Doppler Current Profiling, vessel-mounted (VM-ADCP); ADCP; AtlantOS; Binary Object; Binary Object (File Size); Binary Object (Media Type); Description; Maria S. Merian; MSM74; MSM74_0_underway-3; Optimizing and Enhancing the Integrated Atlantic Ocean Observing System; RACE-II; Regional Atlantic Circulation and global Change II
    Type: Dataset
    Format: text/tab-separated-values, 4 data points
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  • 6
    Publication Date: 2024-06-27
    Description: Seabird 911plus systems equipped with dual temperature-conductivity-oxygen sensors were employed. All systems had a 24-bottle water sampling rosette with 10 l Niskin bottles. Water sampling, processing, and calibration followed GO-SHIP recommendations (Swift, 2010; McTaggart et al., 2010; Uchida et al., 2010) and included the recommended steps Data Conversion, Sensor Time-Alignment, Creation of Bottle Files, Outlier Removal, Pressure Sensor Filtering, Conductivity Cell Thermal Mass Correction, Ship Roll Correction and Deck Offset Correction by Loop Editing, as well as Derivation of Calculated Properties. After these steps, conductivity and oxygen readings were calibrated against values determined with salinometry and Winkler titration , respectively. Finally, the downcast data was averaged over 1 dbar wide intervals. An independent upcast calibration was used to obtain calibrated CTDO values coincident with the discrete water samples.
    Keywords: AtlantOS; Attenuation, optical beam transmission; CTD/Rosette; CTD-RO; DATE/TIME; Density, sigma, in situ; DEPTH, water; Event label; Fluorescence; Maria S. Merian; MSM74; MSM74_100-1; MSM74_101-1; MSM74_102-1; MSM74_103-1; MSM74_104-1; MSM74_105-1; MSM74_106-1; MSM74_107-1; MSM74_108-1; MSM74_109-1; MSM74_1-1; MSM74_110-1; MSM74_11-1; MSM74_111-1; MSM74_11-2; MSM74_112-1; MSM74_113-1; MSM74_117-2; MSM74_118-1; MSM74_119-1; MSM74_120-1; MSM74_12-1; MSM74_121-1; MSM74_123-2; MSM74_124-1; MSM74_124-2; MSM74_125-1; MSM74_126-1; MSM74_127-1; MSM74_130-1; MSM74_131-1; MSM74_132-1; MSM74_14-1; MSM74_17-1; MSM74_18-1; MSM74_19-1; MSM74_20-1; MSM74_21-1; MSM74_23-1; MSM74_23-2; MSM74_24-1; MSM74_25-1; MSM74_26-1; MSM74_26-2; MSM74_27-1; MSM74_3-1; MSM74_31-1; MSM74_32-1; MSM74_33-1; MSM74_36-1; MSM74_37-1; MSM74_38-1; MSM74_38-2; MSM74_39-1; MSM74_40-1; MSM74_4-1; MSM74_41-2; MSM74_44-1; MSM74_45-1; MSM74_45-2; MSM74_45-3; MSM74_47-1; MSM74_48-1; MSM74_49-1; MSM74_50-1; MSM74_5-1; MSM74_51-1; MSM74_52-1; MSM74_52-2; MSM74_53-1; MSM74_54-1; MSM74_55-1; MSM74_56-1; MSM74_57-1; MSM74_58-1; MSM74_59-1; MSM74_60-1; MSM74_6-1; MSM74_61-3; MSM74_62-1; MSM74_63-1; MSM74_64-1; MSM74_65-1; MSM74_66-1; MSM74_67-1; MSM74_68-1; MSM74_69-1; MSM74_70-1; MSM74_71-1; MSM74_76-1; MSM74_77-1; MSM74_78-1; MSM74_79-1; MSM74_79-2; MSM74_80-1; MSM74_81-1; MSM74_83-1; MSM74_84-1; MSM74_85-1; MSM74_86-1; MSM74_87-1; MSM74_88-1; MSM74_89-1; MSM74_90-1; MSM74_91-1; MSM74_91-2; MSM74_92-1; MSM74_92-2; MSM74_93-1; MSM74_94-1; MSM74_95-1; MSM74_96-1; MSM74_97-1; MSM74_98-1; MSM74_99-1; Optimizing and Enhancing the Integrated Atlantic Ocean Observing System; Oxygen; Pressure, water; RACE-II; Regional Atlantic Circulation and global Change II; Salinity; Sound velocity in water; Temperature, water; Turbidity (Nephelometric turbidity unit)
    Type: Dataset
    Format: text/tab-separated-values, 2311020 data points
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  • 7
    Publication Date: 2024-06-26
    Description: Observed oxygen minimum zones (OMZs) in the tropical Pacific Ocean are located above intermediate-depth waters (IDWs), defined here as the 500–1500 m water layer. Typical climate models do not represent IDW properties well and are characterized by OMZs that are too deep-reaching. We analyze the role of the IDW in the misrepresentation of oxygen levels in a heterogeneous subset of ocean models characterized by a horizontal resolution ranging from 0.1 to 2.8∘. First, we show that forcing the extratropical boundaries (30∘ S and N) to observed oxygen values results in a significant increase in oxygen levels in the intermediate eastern tropical region. Second, we highlight the fact that the Equatorial Intermediate Current System (EICS) is a key feature connecting the western and eastern part of the basin. Typical climate models lack in representing crucial aspects of this supply at intermediate depth, as the EICS is basically absent in models characterized by a resolution lower than 0.25∘. These two aspects add up to a “cascade of biases” that hampers the correct representation of oxygen levels at intermediate depth in the eastern tropical Pacific Ocean and potentially future OMZ projections.
    Type: Article , PeerReviewed
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  • 8
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    Naturalis Biodiversity Center
    In:  Blumea: Biodiversity, Evolution and Biogeography of Plants vol. 66 no. 1, pp. 101-105
    Publication Date: 2024-06-26
    Description: Two new Hanguana species from Kalimantan, Indonesian Borneo, are described here. Hanguana karimatae from Karimata Island, West Kalimantan province, is characterised by a stout habit, prominently oblique yellow fruits with raised stigma and 1- or 2-seeded fruits. Hanguana nana from Central Kalimantan province is the smallest species in the genus with the stem entirely covered by leaves, deflexed barely branched infructescences with only a few fruits, each with a single bowl-shaped seed with a large and incurved appendage. These are the first descriptions of new Hanguana species from Kalimantan (Indonesian Borneo). Colour plates as well as notes on distribution, ecology, habitat and conservation status are provided.
    Keywords: Plant Science ; Ecology ; Evolution ; Behavior and Systematics ; Borneo ; Hanguana karimatae ; Hanguana nana ; Kalimantan ; Karimata Island ; taxonomy
    Repository Name: National Museum of Natural History, Netherlands
    Type: info:eu-repo/semantics/article
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  • 9
    Publication Date: 2024-06-26
    Description: A set of eight ice-tethered buoy systems (2019O1 to 2019O8) were deployed by the Akademik Fedorov in the Northern Laptev Sea in early October 2019 as part of the MOSAiC Distributed Network. Each buoy consisted of 5 Seabird SBE37IMP Microcat CTDs mounted along an inductive modem tether at depths of 10, 20, 50, 75 and 100m. The buoys were installed on stable sea ice floes (designated as “M-sites”) at a distance of 15-35 km around the main MOSAiC ice camp, and co-located with Snow Buoys, Ice Mass Balance Buoys and D-TOP ocean profilers. The individual instruments were programmed to record oceanographic data internally at 2-minute intervals. The surface unit of the buoy prompted the instruments for an additional measurement every 10 minutes, which was then transmitted to a base station via iridium along with GPS position and time, as well as surface temperature. After a several months long drift through the Central Arctic Ocean, 4 out of 8 buoys were recovered in August 2020, and the internally recorded data from the CTDs were secured. The attached zip archive comprises the unprocessed 10-minute data transmitted by the buoy (.txt file), as well as the 2-minute data downloaded and converted from the 5 individual CTDs after their recovery (either .cap or .cnv). A processed and quality controlled version of this dataset will be supplemented and linked to upon completion. A link to a data paper describing the processing will be given below.
    Keywords: 2019O1; 2019O3; 2019O4; 2019O6; AF-MOSAiC-1; AF-MOSAiC-1_106; AF-MOSAiC-1_110; AF-MOSAiC-1_114; AF-MOSAiC-1_117; AF-MOSAiC-1_121; AF-MOSAiC-1_124; AF-MOSAiC-1_127; AF-MOSAiC-1_131; Akademik Fedorov; Akademik Tryoshnikov; Arctic Ocean; AT-MOSAiC-1; AT-MOSAiC-1_1; AT-MOSAiC-1_4; buoy; eddy; FRAM; FRontiers in Arctic marine Monitoring; mesoscale; MIDO; MOSAiC; MOSAIC_PO; MOSAiC20192020; MOSAiC20192020, AF122/1; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Multidisciplinary Ice-based Distributed Observatory; North Greenland Sea; Ocean CTD buoy; oceanography; OCTDB; Polarstern; PS122/1_1-148, 2019O1; PS122/1_1-149, 2019O2; PS122/1_1-150, 2019O3; PS122/1_1-151, 2019O4; PS122/1_1-152, 2019O5; PS122/1_1-153, 2019O6; PS122/1_1-154, 2019O7; PS122/1_1-155, 2019O8; PS122/4; PS122/4_43-149; PS122/4_43-165; Transpolar Drift
    Type: Dataset
    Format: application/zip, 8 datasets
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  • 10
    Publication Date: 2024-06-26
    Description: This dataset captures the yearlong evolution of physical properties of the snow cover over Arctic sea ice during the MOSAiC expedition (October 2019-September 2020). It also includes the surface scattering layer that is typical of the melting summer sea ice surface. This dataset is specifically for measurements that were logged as “snowpit events” during MOSAiC. The snowpit events were either detailed point-measurements of vertical snow profiles or horizontally repeated transects, measured at selected locations in designated undisturbed areas. One snowpit event corresponds to one site visit. The snowpits are often co-located with measurements from other MOSAiC teams to improve our understanding of how snow cover affects and interacts with the atmosphere-sea ice-ocean-ecology system. Most snowpits were measured at least bi-weekly to capture the temporal evolution of physical properties of snow. Some snowpits were one-off events to capture interesting and unplanned-for surface conditions. This dataset includes 576 snowpit events, and describes the snow conditions during the entire expedition. Please direct inquiries to; David Wagner (PS122/1), Martin Schneebeli (PS122/2), Amy Macfarlane (PS122/3 and PS122/4), Ruzica Dadic (PS122/5).
    Keywords: Arctic Ocean; Arctic Research Icebreaker Consortium: A strategy for meeting the needs for marine-based research in the Arctic; ARICE; MOSAiC; MOSAiC20192020; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Polarstern; PS122/1; PS122/1_10-11; PS122/1_10-18; PS122/1_10-5; PS122/1_10-50; PS122/1_10-58; PS122/1_10-70; PS122/1_10-71; PS122/1_10-72; PS122/1_11-23; PS122/1_4-10; PS122/1_5-28; PS122/1_5-35; PS122/1_5-5; PS122/1_6-146; PS122/1_6-147; PS122/1_6-29; PS122/1_6-30; PS122/1_6-41; PS122/1_6-42; PS122/1_6-43; PS122/1_6-44; PS122/1_6-45; PS122/1_6-46; PS122/1_6-47; PS122/1_6-5; PS122/1_6-6; PS122/1_6-65; PS122/1_6-66; PS122/1_6-67; PS122/1_6-68; PS122/1_6-69; PS122/1_6-70; PS122/1_6-75; PS122/1_7-12; PS122/1_7-129; PS122/1_7-32; PS122/1_7-33; PS122/1_7-34; PS122/1_7-35; PS122/1_7-36; PS122/1_7-37; PS122/1_7-38; PS122/1_7-5; PS122/1_7-68; PS122/1_7-69; PS122/1_7-70; PS122/1_7-71; PS122/1_7-72; PS122/1_7-73; PS122/1_7-8; PS122/1_7-87; PS122/1_7-88; PS122/1_8-1; PS122/1_8-27; PS122/1_8-28; PS122/1_8-29; PS122/1_8-30; PS122/1_8-31; PS122/1_8-32; PS122/1_8-68; PS122/1_8-69; PS122/1_8-70; PS122/1_8-78; PS122/1_8-79; PS122/1_9-111; PS122/1_9-117; PS122/1_9-23; PS122/1_9-25; PS122/1_9-3; PS122/1_9-71; PS122/1_9-72; PS122/1_9-73; PS122/1_9-74; PS122/2; PS122/2_16-24; PS122/2_16-44; PS122/2_16-45; PS122/2_16-46; PS122/2_16-62; PS122/2_16-73; PS122/2_16-9; PS122/2_16-90; PS122/2_17-109; PS122/2_17-16; PS122/2_17-43; PS122/2_17-44; PS122/2_17-45; PS122/2_17-46; PS122/2_17-47; PS122/2_17-49; PS122/2_17-89; PS122/2_17-90; PS122/2_17-91; PS122/2_18-107; PS122/2_18-108; PS122/2_18-17; PS122/2_18-47; PS122/2_18-52; PS122/2_18-53; PS122/2_18-54; PS122/2_18-55; PS122/2_18-56; PS122/2_18-66; PS122/2_18-76; PS122/2_18-8; PS122/2_18-9; PS122/2_19-128; PS122/2_19-129; PS122/2_19-131; PS122/2_19-132; PS122/2_19-133; PS122/2_19-134; PS122/2_19-135; PS122/2_19-137; PS122/2_19-141; PS122/2_19-142; PS122/2_19-144; PS122/2_19-145; PS122/2_19-146; PS122/2_19-160; PS122/2_19-161; PS122/2_19-181; PS122/2_19-28; PS122/2_19-35; PS122/2_19-41; PS122/2_19-75; PS122/2_19-9; PS122/2_19-92; PS122/2_20-107; PS122/2_20-108; PS122/2_20-123; PS122/2_20-136; PS122/2_20-137; PS122/2_20-138; PS122/2_20-139; PS122/2_20-140; PS122/2_20-141; PS122/2_20-142; PS122/2_20-143; PS122/2_20-144; PS122/2_20-145; PS122/2_20-164; PS122/2_20-35; PS122/2_20-36; PS122/2_20-4; PS122/2_20-70; PS122/2_20-80; PS122/2_20-83; PS122/2_21-14; PS122/2_21-15; PS122/2_21-158; PS122/2_21-159; PS122/2_21-16; PS122/2_21-170; PS122/2_21-52; PS122/2_21-53; PS122/2_21-72; PS122/2_21-84; PS122/2_21-96; PS122/2_22-43; PS122/2_22-46; PS122/2_22-5; PS122/2_22-6; PS122/2_22-61; PS122/2_22-66; PS122/2_22-67; PS122/2_22-68; PS122/2_22-69; PS122/2_22-73; PS122/2_22-74; PS122/2_23-105; PS122/2_23-2; PS122/2_23-34; PS122/2_23-53; PS122/2_23-73; PS122/2_23-74; PS122/2_23-75; PS122/2_23-76; PS122/2_23-77; PS122/2_23-78; PS122/2_23-79; PS122/2_23-85; PS122/2_23-9; PS122/2_24-112; PS122/2_24-113; PS122/2_24-14; PS122/2_24-15; PS122/2_24-16; PS122/2_24-35; PS122/2_24-56; PS122/2_24-81; PS122/2_24-86; PS122/2_25-105; PS122/2_25-128; PS122/2_25-22; PS122/2_25-23; PS122/2_25-59; PS122/2_25-60; PS122/2_25-61; PS122/2_25-62; PS122/2_25-63; PS122/2_25-80; PS122/2_25-81; PS122/3; PS122/3_29-28; PS122/3_29-29; PS122/3_29-38; PS122/3_29-43; PS122/3_29-50; PS122/3_29-9; PS122/3_30-17; PS122/3_30-25; PS122/3_30-42; PS122/3_30-61; PS122/3_31-55; PS122/3_31-79; PS122/3_32-22; PS122/3_32-41; PS122/3_32-59; PS122/3_32-61; PS122/3_32-88; PS122/3_32-92; PS122/3_32-93; PS122/3_33-102; PS122/3_33-103; PS122/3_33-112; PS122/3_33-113; PS122/3_33-40; PS122/3_33-41; PS122/3_33-42; PS122/3_33-65; PS122/3_33-66; PS122/3_34-2; PS122/3_34-34; PS122/3_34-45; PS122/3_34-46; PS122/3_34-60; PS122/3_34-91; PS122/3_35-111; PS122/3_35-120; PS122/3_35-121; PS122/3_35-23; PS122/3_35-24; PS122/3_35-53; PS122/3_35-56; PS122/3_36-102; PS122/3_36-103; PS122/3_36-104; PS122/3_36-105; PS122/3_36-106; PS122/3_36-107; PS122/3_36-137; PS122/3_36-138; PS122/3_36-14; PS122/3_36-15; PS122/3_36-35; PS122/3_36-99; PS122/3_37-129; PS122/3_37-130; PS122/3_37-131; PS122/3_37-132; PS122/3_37-133; PS122/3_37-156; PS122/3_37-21; PS122/3_37-22; PS122/3_37-39; PS122/3_37-40; PS122/3_37-41; PS122/3_37-56; PS122/3_37-57; PS122/3_37-58; PS122/3_37-68; PS122/3_38-1; PS122/3_38-141; PS122/3_38-142; PS122/3_38-152; PS122/3_38-4; PS122/3_38-51; PS122/3_38-52; PS122/3_38-93; PS122/3_38-94; PS122/3_38-95; PS122/3_38-96; PS122/3_38-97; PS122/3_38-98; PS122/3_39-45; PS122/3_39-46; PS122/3_39-47; PS122/3_39-48; PS122/3_39-87; PS122/3_39-88; PS122/3_39-89; PS122/3_39-90; PS122/3_39-91; PS122/3_39-92; PS122/3_40-14; PS122/3_40-15; PS122/4; PS122/4_44-121; PS122/4_44-122; PS122/4_44-155; PS122/4_44-156; PS122/4_44-157; PS122/4_44-193; PS122/4_44-215; PS122/4_44-216; PS122/4_44-218; PS122/4_44-220; PS122/4_44-249; PS122/4_44-44; PS122/4_44-45; PS122/4_44-46; PS122/4_44-47; PS122/4_45-107; PS122/4_45-108; PS122/4_45-132; PS122/4_45-16; PS122/4_45-17; PS122/4_45-176; PS122/4_45-177; PS122/4_45-179; PS122/4_45-18; PS122/4_45-180; PS122/4_45-181; PS122/4_45-182; PS122/4_45-46; PS122/4_45-62; PS122/4_45-63; PS122/4_45-8; PS122/4_45-86; PS122/4_45-87; PS122/4_45-89; PS122/4_46-104; PS122/4_46-105; PS122/4_46-106; PS122/4_46-107; PS122/4_46-108; PS122/4_46-109; PS122/4_46-110; PS122/4_46-111; PS122/4_46-112; PS122/4_46-135; PS122/4_46-138; PS122/4_46-139; PS122/4_46-140; PS122/4_46-146; PS122/4_46-181; PS122/4_46-187; PS122/4_46-188; PS122/4_46-190; PS122/4_46-191; PS122/4_46-192; PS122/4_46-288; PS122/4_46-29; PS122/4_46-30; PS122/4_46-31; PS122/4_46-32; PS122/4_46-48; PS122/4_46-50; PS122/4_47-156; PS122/4_47-175; PS122/4_47-176; PS122/4_47-177; PS122/4_47-178; PS122/4_47-179; PS122/4_47-22; PS122/4_47-23; PS122/4_47-61; PS122/4_47-66; PS122/4_47-76; PS122/4_47-77; PS122/4_47-97; PS122/4_48-100; PS122/4_48-142; PS122/4_48-143; PS122/4_48-144; PS122/4_48-145; PS122/4_48-146; PS122/4_48-147; PS122/4_48-148; PS122/4_48-177; PS122/4_48-186; PS122/4_48-187; PS122/4_48-188; PS122/4_48-189; PS122/4_48-190; PS122/4_48-191; PS122/4_48-196; PS122/4_48-40; PS122/4_48-41; PS122/4_48-42; PS122/4_48-43; PS122/4_48-44; PS122/4_48-45; PS122/4_48-47; PS122/4_48-58; PS122/4_48-83; PS122/4_48-85; PS122/4_48-86; PS122/4_49-15; PS122/4_49-19; PS122/4_49-20; PS122/4_49-46; PS122/4_49-47; PS122/4_49-48; PS122/4_49-7; PS122/4_49-8; PS122/4_99-56; PS122/4_99-57; PS122/4_99-58; PS122/4_99-59; PS122/4_99-60; PS122/4_99-61; PS122/4_99-62; PS122/4_99-63; PS122/4_99-65; PS122/4_99-66; PS122/4_99-67; PS122/4_99-68; PS122/4_99-69; PS122/4_99-70; PS122/4_99-71; PS122/4_99-72; PS122/4_99-73; PS122/5; PS122/5_59-193; PS122/5_59-204; PS122/5_59-206; PS122/5_59-222; PS122/5_59-235; PS122/5_59-250; PS122/5_59-267; PS122/5_59-268; PS122/5_59-292; PS122/5_59-302; PS122/5_59-303; PS122/5_59-304; PS122/5_59-313; PS122/5_59-314; PS122/5_59-315; PS122/5_59-350; PS122/5_59-351; PS122/5_59-352; PS122/5_59-353; PS122/5_59-354; PS122/5_59-368; PS122/5_60-10; PS122/5_60-117; PS122/5_60-118; PS122/5_60-119; PS122/5_60-120; PS122/5_60-128; PS122/5_60-142; PS122/5_60-143; PS122/5_60-144; PS122/5_60-145; PS122/5_60-168; PS122/5_60-170; PS122/5_60-2; PS122/5_60-24; PS122/5_60-25; PS122/5_60-26; PS122/5_60-43; PS122/5_60-74; PS122/5_60-75; PS122/5_60-76; PS122/5_60-77; PS122/5_60-78; PS122/5_60-91; PS122/5_61-10; PS122/5_61-102; PS122/5_61-103; PS122/5_61-104; PS122/5_61-105; PS122/5_61-132; PS122/5_61-138; PS122/5_61-139; PS122/5_61-140; PS122/5_61-162; PS122/5_61-166; PS122/5_61-167; PS122/5_61-168; PS122/5_61-170; PS122/5_61-198; PS122/5_61-2; PS122/5_61-230; PS122/5_61-231; PS122/5_61-232; PS122/5_61-233; PS122/5_61-234; PS122/5_61-235; PS122/5_61-236; PS122/5_61-237; PS122/5_61-25; PS122/5_61-27; PS122/5_61-28; PS122/5_61-29; PS122/5_61-4; PS122/5_61-5; PS122/5_61-8; PS122/5_61-9; PS122/5_61-97; PS122/5_62-10; PS122/5_62-100; PS122/5_62-101; PS122/5_62-102; PS122/5_62-119; PS122/5_62-123; PS122/5_62-124; PS122/5_62-125; PS122/5_62-126; PS122/
    Type: Dataset
    Format: application/zip, 15 datasets
    Location Call Number Expected Availability
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