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  • 2020-2024  (166,548)
  • 1990-1994  (1,575,054)
  • 1985-1989  (1,263,454)
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  • 1
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    Benthic foraminiferal δ¹⁸O alignments for IODP Site U1541, ODP Site 1090 and ODP Site 980-981 based on different tuning targets for the past ~3.5 Myr (2024)
    PANGAEA
    Details
    Publication Date: 2024-06-01
    Description: This dataset presents benthic foraminiferal δ¹⁸O chronostratigraphies for International Ocean Discovery Program (IODP) Site U1541, Ocean Drilling Program (ODP) Site 1090 and ODP Site 980-981 based on different tuning targets including LR04 (Lisiecki and Raymo, 2005), LR09 (Lisiecki and Raymo, 2009), CENOGRID (Westerhold et al., 2020) and Probstack (Ahn et al., 2017) obtained by Middleton et al. (2024). The benthic foraminiferal δ¹⁸O record for IODP Site U1541 (54°13'S, 125°25'W) recently recovered from the central South Pacific on IODP Expedition 383 (Winckler et al., 2021) is shown for the first time and is published in Middleton et al. (2024). All data records are based on Cibicidoides wuellerstorfi and Cibicides kullenbergi, or combinations thereof. The dataset provides the basis for investigating and discussing the uncertainties of benthic foraminiferal δ¹⁸O stratigraphies for conventional manual and automated tuning techniques and evaluate their impact on sedimentary age models over the past 3.5 Myr (Middleton et al., 2024).
    Keywords: Integrated Ocean Drilling Program / International Ocean Discovery Program; IODP; Ocean Drilling Program; ODP
    Type: Dataset
    Format: application/zip, 7 datasets
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  • 2
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    Presence-absence records for four cold-water coral taxa on the seamounts of Cabo Verde (NW Africa) (2023)
    PANGAEA
    Details
    Publication Date: 2024-06-01
    Description: Presence-absence records for four cold-water coral (CWC) taxa (Enallopsammia rostrata, Acanella arbuscula, Metallogorgia spp. and Paramuricea spp.) were gathered to conduct distribution models on seamounts (Cadamosto, Nola, Senghor and Cabo Verde) of the Cabo Verde archipelago (NW Africa), covering a bathymetric range from 2100 to 750 m water depth. Data were extracted from video footage collected with Remotely Operated Vehicles during the M80/3 Meteor (2010) and the iMirabilis2 (2021) research expeditions. Video data from the iMirabilis2 expedition was analysed, quantitively, using the open-source software BIIGLE (Langenkämper et al. 2017). Observations from five continuous 1 to 2 km-long video transects between 2000 and 1400 m depth at Cadamosto Seamount were converted into presence-absence data points. Similar data were not available for the seamounts explored during M80/3 Meteor. However, all the available images and short video clips from that expedition were analysed to identify presence and absence points for each of the four target CWC taxa. All the available presence/absence data from the two expeditions was transformed into one point per grid cell of a 100 m resolution bathymetry grid, with the prevalence of the presence records over the absence records, in grid cells where both categories overlapped.
    Keywords: Atlantic Ocean; Binary Object; Binary Object (File Size); Binary Object (Media Type); Cabo Verde; Cadamosto Seamount, Cabo Verde; Cape Verde; cold-water coral; Cruise/expedition; DATE/TIME; Deep-sea; distribution modelling; Event label; File content; Genus; Horizontal datum; iAtlantic; iMirabilis2_Leg1; iMirabilis2_Leg1_24; iMirabilis2_Leg1_46; iMirabilis2_Leg1_55; iMirabilis2_Leg1_64; iMirabilis2_Leg1_75; Integrated Assessment of Atlantic Marine Ecosystems in Space and Time; LATITUDE; Latitude, northbound; Latitude, southbound; Location; LONGITUDE; Longitude, eastbound; Longitude, westbound; M80/3; M80/3_10; M80/3_100; M80/3_33; M80/3_35; M80/3_7; M80/3_84; Meteor (1986); Presence/absence; Remote operated vehicle; ROV; ROV Luso; Sarmiento de Gamboa; Species; Taxon/taxa, unique identification (Semantic URI); Taxon/taxa, unique identification (URI); UTM Easting, Universal Transverse Mercator; UTM Northing, Universal Transverse Mercator; UTM Zone, Universal Transverse Mercator; Vertical datum; VIDEO; Video camera
    Type: Dataset
    Format: text/tab-separated-values, 10855 data points
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  • 3
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    Tie points for manual alignment of the benthic foraminiferal δ¹⁸O record at IODP Site U1541 to LR04 (2024)
    PANGAEA
    Details
    Publication Date: 2024-06-01
    Description: This dataset presents user-defined tiepoints of the manual alignment of the benthic foraminiferal δ¹⁸O record at IODP Site U1541 to the benthic foraminiferal LR04 δ¹⁸O stack of Lisiecki and Raymo (2005) obtained by Middleton et al. (2024). The benthic foraminiferal δ¹⁸O record for IODP Site U1541 is based on stable isotope analyses of Cibicidoides wuellerstorfi and Cibicides kullenbergi, and was published in Middleton et al. (2024).
    Keywords: 383-U1541; AGE; COMPCORE; Composite Core; DEPTH, sediment/rock; EXP383; Integrated Ocean Drilling Program / International Ocean Discovery Program; IODP; Joides Resolution
    Type: Dataset
    Format: text/tab-separated-values, 0 data points
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  • 4
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    Tie points for manual alignment of the benthic foraminiferal δ¹⁸O record at ODP Site 1090 to LR04 (2024)
    PANGAEA
    Details
    Publication Date: 2024-06-01
    Description: This dataset presents user-defined tiepoints of the manual alignment of the benthic foraminiferal δ¹⁸O record at ODP Site 1090 to the benthic foraminiferal LR04 δ¹⁸O stack of Lisiecki and Raymo (2005) obtained by Middleton et al. (2024). The benthic foraminiferal δ¹⁸O record is based on Cibicidoides wuellerstorfi and was previously published in Hodell et al. (2000) and Venz and Hodell (2002).
    Keywords: 177-1090; AGE; COMPCORE; Composite Core; DEPTH, sediment/rock; Joides Resolution; Leg177; Ocean Drilling Program; ODP; South Atlantic Ocean
    Type: Dataset
    Format: text/tab-separated-values, 0 data points
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  • 5
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    Tie points between sediment core PS75/059-2 and IODP Site U1541 based on an alignment of high-resolution X-ray fluorescence (XRF) Fe intensity variations (2024)
    PANGAEA
    Details
    Publication Date: 2024-06-01
    Description: This dataset presents tie points between sediment core PS75/059-2 and IODP Site U1541 based on an alignment of high-resolution X-ray fluorescence (XRF) Fe intensity variations in both cores, obtained by Middleton et al. (2024). The splicing of the two cores provides the basis for a combination of the benthic foraminiferal δ¹⁸O records for PS75/059-2 (Ullermann et al., 2016) and IODP Site U1541 (Middleton et al., 2024).
    Keywords: 383-U1541; ANT-XXVI/2; COMPCORE; Composite Core; DEPTH, sediment/rock; EXP383; Integrated Ocean Drilling Program / International Ocean Discovery Program; IODP; Joides Resolution; KL; Piston corer (BGR type); Polarstern; PS75/059-2; PS75 BIPOMAC; South Pacific Ocean
    Type: Dataset
    Format: text/tab-separated-values, 0 data points
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  • 6
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    Benthic foraminiferal δ¹⁸O alignments for IODP Site U1541 based on the tuning targets LR04, L09, CENOGRID and Probstack for the past ~3.5 Myr (2024)
    PANGAEA
    Details
    Publication Date: 2024-06-01
    Description: This dataset presents benthic foraminiferal δ¹⁸O chronostratigraphies and associated uncertainties for International Ocean Discovery Program (IODP) Site U1541, based on different tuning targets including LR04 (Lisiecki and Raymo, 2005), LR09 (Lisiecki and Raymo, 2009), CENOGRID (Westerhold et al., 2020) and Probstack (Ahn et al., 2017) and based on manual versus automated tuning techniques (Middleton et al., 2024). The benthic foraminiferal δ¹⁸O record for IODP Site U1541 (54°13'S, 125°25'W) recently recovered from the central South Pacific on IODP Expedition 383 (Winckler et al., 2021) is presented for the first time in Middleton et al. (2024). It is based on stable isotope analyses of Cibicidoides wuellerstorfi and Cibicides kullenbergi (Middleton et al., 2024), and was combined with the benthic foraminiferal δ¹⁸O record of PS75/059-2 (Ullermann et al., 2016). Automated tuning is based on Hidden Markov Model (HMM)-Match-based alignments (Middleton et al., 2024) generated using the automated probabilistic HMM-Match algorithm of Lin et al. (2014). The manual tuning was generated by visual alignment of characteristic peaks and troughs of the benthic foraminiferal δ¹⁸O record of IODP Site U1541 to the benthic foraminiferal LR04 stack using the publicly available QAnalySeries software (Kotov and Pälike, 2018). The dataset provides the basis for investigating and discussing the uncertainties of benthic foraminiferal δ¹⁸O stratigraphies for conventional manual and automated tuning techniques and evaluate their impact on sedimentary age models over the past 3.5 Myr (Middleton et al., 2024).
    Keywords: 383-U1541; 383-U1541A; 383-U1541B; 383-U1541C; Age, dated; Age model; ANT-XXVI/2; Cibicidoides spp., δ18O; COMPCORE; Composite Core; Core; Data source; DEPTH, sediment/rock; DRILL; Drilling/drill rig; DSDP/ODP/IODP sample designation; Event label; EXP383; Hidden Markov Model (HMM)-Match-based alignment to CENOGRID; Hidden Markov Model (HMM)-Match-based alignment to LR04; Hidden Markov Model (HMM)-Match-based alignment to LR09 Pacific; Hidden Markov Model (HMM)-Match-based alignment to Prob-stack; Hole; Integrated Ocean Drilling Program / International Ocean Discovery Program; IODP; Joides Resolution; KL; Leg Number; Manual Alignment to LR04; Piston corer (BGR type); Polarstern; PS75/059-2; PS75 BIPOMAC; Sample code/label; Section; Section position; Site; South Pacific Ocean; Type
    Type: Dataset
    Format: text/tab-separated-values, 33741 data points
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  • 7
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    Tie points for manual alignment of the benthic foraminiferal δ¹⁸O record at ODP Sites 980/981 to LR04 (2024)
    PANGAEA
    Details
    Publication Date: 2024-06-01
    Description: This dataset presents user-defined tiepoints of the manual alignment of the benthic foraminiferal δ¹⁸O record at ODP Site 980 and 981 to the benthic foraminiferal LR04 δ¹⁸O stack of Lisiecki and Raymo (2005) obtained by Middleton et al. (2024). The benthic foraminiferal δ¹⁸O record at ODP 980 is based on Cibicidoides wuellerstorfi and Cibicides kullenbergi, and was previously published (McManus et al., 1999; Flower et al., 2000; Oppo et al., 1998). The ODP Site 981 data were measured on benthic foraminifera of the genus Cibicidoides (Raymo et al., 2004). The benthic foraminiferal δ¹⁸O records of ODP Site 980 and 981 were spliced together at ~860 ka (Raymo et al., 2004).
    Keywords: 162-980; 162-981; AGE; COMPCORE; Composite Core; DEPTH, sediment/rock; Event label; Joides Resolution; Leg162; Ocean Drilling Program; ODP; South Atlantic Ocean
    Type: Dataset
    Format: text/tab-separated-values, 0 data points
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  • 8
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    Benthic foraminiferal δ¹⁸O alignments for ODP Site 1090 based on the tuning targets LR04, L09, CENOGRID and Probstack for the past ~2.9 Myr (2024)
    PANGAEA
    Details
    Publication Date: 2024-06-01
    Description: This dataset presents benthic foraminiferal δ¹⁸O chronostratigraphies and associated uncertainties for Ocean Drilling Program (ODP) Site 1090, based on different tuning targets including LR04 (Lisiecki and Raymo, 2005), LR09 (Lisiecki and Raymo, 2009), CENOGRID (Westerhold et al., 2020) and Probstack (Ahn et al., 2017) and based on manual versus automated tuning techniques (Middleton et al., 2024). The benthic foraminiferal δ¹⁸O record at ODP Site 1090 is based on Cibicidoides wuellerstorfi and was previously published in Hodell et al. (2000) and Venz and Hodell (2002). Automated tuning is based on Hidden Markov Model (HMM)-Match-based alignments (Middleton et al., 2024) generated using the automated probabilistic HMM-Match algorithm of Lin et al. (2014). The manual alignments of ODP Site 1090 were obtained by realigning the original age model tie points (Venz and Hodell, 2002) to the benthic foraminiferal LR04 δ¹⁸O stack using the QAnalySeries software (Kotov and Pälike, 2018). The dataset provides the basis for investigating and discussing the uncertainties of benthic foraminiferal δ¹⁸O stratigraphies for conventional manual and automated tuning techniques and evaluate their impact on sedimentary age models over the past 2.9 Myr (Middleton et al., 2024).
    Keywords: 177-1090; 177-1090B; 177-1090D; 177-1090E; Age, dated; Age model; Cibicidoides spp., δ18O; COMPCORE; Composite Core; Core; DEPTH, sediment/rock; DRILL; Drilling/drill rig; DSDP/ODP/IODP sample designation; Event label; Hidden Markov Model (HMM)-Match-based alignment B to Probstack; Hidden Markov Model (HMM)-Match-based alignment to CENOGRID; Hidden Markov Model (HMM)-Match-based alignment to LR04; Hidden Markov Model (HMM)-Match-based alignment to LR09 Atlantic; Hidden Markov Model (HMM)-Match-based alignment to Prob-stack; Joides Resolution; Leg177; Leg Number; Manual Alignment to LR04; Ocean Drilling Program; ODP; PC; Piston corer; Sample code/label; Section; Section position; Site; South Atlantic Ocean; TN057-6-PC4
    Type: Dataset
    Format: text/tab-separated-values, 21310 data points
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  • 9
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    Benthic foraminiferal δ¹⁸O alignments for ODP Site 980 and ODP Site 981 based on the tuning targets LR04, L09, CENOGRID and Probstack for the past ~1.8 Myr (2024)
    PANGAEA
    Details
    Publication Date: 2024-06-01
    Description: This dataset presents benthic foraminiferal δ¹⁸O chronostratigraphies and associated uncertainties for Ocean Drilling Program (ODP) Site 980 and 981, based on different tuning targets including LR04 (Lisiecki and Raymo, 2005), LR09 (Lisiecki and Raymo, 2009), CENOGRID (Westerhold et al., 2020) and Probstack (Ahn et al., 2017) and based on manual versus automated tuning techniques (Middleton et al., 2024). The benthic foraminiferal δ¹⁸O record at ODP 980 is based on Cibicidoides wuellerstorfi and Cibicides kullenbergi, and was previously published (McManus et al., 1999; Flower et al., 2000; Oppo et al., 1998). The ODP Site 981 data were measured on benthic foraminifera of the genus Cibicidoides (Raymo et al., 2004). The benthic foraminiferal δ¹⁸O records of ODP Site 980 and 981 were spliced together at ~860 ka (Raymo et al., 2004). Automated tuning is based on Hidden Markov Model (HMM)-Match-based alignments (Middleton et al., 2024) generated using the automated probabilistic HMM-Match algorithm of Lin et al. (2014). The manual alignments of ODP Site 980/981 were obtained by realigning the original age model tie points (e.g., Raymo et al., 2004) to the benthic foraminiferal LR04 δ¹⁸O stack using the QAnalySeries software (Kotov and Pälike, 2018). The dataset provides the basis for investigating and discussing the uncertainties of benthic foraminiferal δ¹⁸O stratigraphies for conventional manual and automated tuning techniques and evaluate their impact on sedimentary age models over the past 1.8 Myr (Middleton et al., 2024).
    Keywords: 162-980; 162-981; Age, dated; Age model; Cibicidoides spp., δ18O; COMPCORE; Composite Core; DEPTH, sediment/rock; Event label; Hidden Markov Model (HMM)-Match-based alignment to CENOGRID; Hidden Markov Model (HMM)-Match-based alignment to LR04; Hidden Markov Model (HMM)-Match-based alignment to LR09 Atlantic; Hidden Markov Model (HMM)-Match-based alignment to Prob-stack; Joides Resolution; Leg162; Manual Alignment to LR04; Ocean Drilling Program; ODP; South Atlantic Ocean
    Type: Dataset
    Format: text/tab-separated-values, 22351 data points
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  • 10
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    The functional diversity of fishes in a Neotropical reservoir based on intraspecific trait variability: trends on community assembly rules and biological invasions. (2024)
    Universidade Estadual de Maringá. Departamento de Biologia. Programa de Pós-Graduação em Ecologia de Ambientes Aquáticos Continentais.
    Details
    Publication Date: 2024-05-31
    Description: An essential question in ecology relies on whether to analyze functional diversity through species traits or to explore the traits' variability at the individual level. Traditionally, several studies have been based on unique values to represent species traits, assuming that intraspecific trait variation (ITV) has minimal impact on overall community trait variability. However, ITV can significantly influence assessments of individual and species adaptation to environmental disturbances, providing insights concerning density patterns, speciation, dispersal, and biological interactions. Thus, the importance of ITV was assessed from two perspectives: (i) community assembly rules and (ii) biological invasions. A dataset comprising ten morphological traits related to habitat use and diet of 5226 fishes belonging to 49 species that occupy the marginal areas of the Itaipu Reservoir (Brazil) was used as a case study. First, the relative contributions of ITV and species turnover (interspecific variability) to overall trait variability and the strength of internal and external filters on fish assemblages using individual traits were investigated. Species turnover accounted for most trait variance within assemblages, but ITV also played an important role for specific traits. Internal filters such as competition highly influence the functional diversity of fish species in an old reservoir. Alternatively, external filters (i.e., regional processes) did not present significant effects on functional traits, which may be related to their greater influence during the reservoir's filling phase. The difference between the functional niche occupied by native species and non-native ones, and the impact of non-native species dominance on the functional diversity patterns of native assemblages (indexed by functional richness, functional evenness, functional divergence, and functional redundancy) was also investigated. It was observed that the functional niche occupied by native species differs from non-native species, suggesting that non-native species have traits that enable them to exploit resources differently. Non-native species presented negative effects on the functional attributes of native fish populations, even in highly impacted environments such as reservoirs, reinforcing the importance of understanding the dynamics between native and non-native species in specific ecosystems. It is expected that the results of this study will assist in the development of public policies in the area of reservoir conservation, offering new insights into critical mechanisms associated with the biodiversity of the marginal regions of reservoirs that are exploited by human activities.
    Description: Uma questão fundamental na ecologia consiste na escolha entre analisar a diversidade funcional por meio de traços a nível de espécie ou explorar a variabilidade dentro de cada espécie, a nível de indivíduo. Tradicionalmente, a maioria dos estudos têm se baseado em valores únicos para representar os traços das espécies, assumindo que a variabilidade intraespecífica dos traços (VIT) tem um impacto mínimo na variabilidade geral dos traços em uma comunidade. No entanto, a VIT pode influenciar significativamente a adaptação das espécies a perturbações ambientais, fornecendo insights sobre padrões de densidade, especiação, dispersão e interações biológicas. Assim, a importância da VIT foi avaliada a partir de duas perspectivas: (i) regras de montagem de comunidades e (ii) invasões biológicas, utilizando como estudo de caso um conjunto de dados composto por 10 traços morfológicos relacionados ao uso de habitat e dieta de 5226 peixes pertencentes a 49 espécies que ocupam as margens do reservatório de Itaipu. Primeiro, investigou-se a contribuição relativa da VIT versus turnover de espécies (variabilidade interespecífica) para a variabilidade geral dos traços, e também quais filtros atuam sobre as assembleias de peixes utilizando dados a nível de indivíduo. O turnover de espécies representou a maior parte da variância dos traços dentro das assembleias, mas a VIT também exerceu um papel significativo, especialmente para alguns traços. Observou-se que os filtros internos, como a competição, parecem atuar sobre a diversidade funcional das espécies de peixes em um reservatório antigo. Filtros externos (ou seja, processos regionais) não apresentaram efeitos significativos, o que pode ser atribuído à sua provável maior influência durante a fase de formação do reservatório, onde mudanças ambientais ocorreram de forma mais frequente. Investigou-se também a diferença entre o nicho funcional ocupado por espécies nativas e não nativas, e o impacto da dominância de espécies não nativas sobre a riqueza, equitabilidade, divergência e redundância funcional das assembleias de peixes nativas. Observou-se que nicho funcional ocupado por espécies nativas difere das espécies não nativas, sugerindo que as espécies não nativas possuem traços que lhes permitem explorar recursos de maneira diferente. Também se demonstrou que espécies não nativas exerceram efeitos negativos nos atributos funcionais das populações de peixes nativos, mesmo em ambientes altamente impactados como os reservatórios, destacando a importância de compreender a dinâmica entre espécies nativas e não nativas dentro de ecossistemas específicos. Espera-se que os resultados deste estudo auxiliem na elaboração de políticas públicas na área da conservação de reservatórios, oferecendo novos insights sobre mecanismos críticos associados à biodiversidade das áreas marginais de reservatórios que são exploradas por atividades humanas.
    Description: PhD
    Keywords: Peixes de água doce ; Comunidades, Ecologia de ; Invasões biológicas ; Diversidade funcional ; Ecomorfologia ; Variabilidade intraespecífica dos traços (VIT) ; Reservatórios ; ASFA_2015::F::Freshwater fish ; ASFA_2015::F::Freshwater ecology ; ASFA_2015::C::Communities (ecological) ; ASFA_2015::D::Dams ; ASFA_2015::B::Biodiversity ; ASFA_2015::D
    Repository Name: AquaDocs
    Type: Thesis/Dissertation
    Format: 77pp.
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  • 11
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    State of the Ocean Report 2024. (2024)
    UNESCO-IOC | Paris, France
    Details
    Publication Date: 2024-05-31
    Description: The State of the Ocean Report (StOR) has the ambition to inform policymakers about the state of the ocean and to stimulate research and policy actions towards ‘the ocean we need for the future we want’, contributing to the 2030 Agenda and in particular SDG 14, which reads ‘Conserve and sustainably use the oceans, seas and marine resources’, as well as other global processes such as the UNFCCC, the Convention on Biological Diversity and the Sendai Framework for Disaster Risk Reduction. Structured around the seven UN Decade of Ocean Science for Sustainable Development Outcomes, the Report provides important information about the achievements of the UN Ocean Decade and, in the longer term, about ocean well-being. The StOR will be used to inform policy and administrative priorities and identify research focus areas that need to be strengthened or developed.
    Description: Published
    Description: Refereed
    Keywords: Plastic pollution ; Ecosystem restoration ; Deoxygenation ; Blue carbon ecosystems ; Marine spatial planning (MSP) ; Sustainable production ; Sustainable food prduction ; Carbon dioxide ; Harmful algal blooms ; Global Ocean Observing System ; Data sharing ; ASFA_2015::P::Plastics ; ASFA_2015::A::Acidification ; ASFA_2015::G::Global warming ; ASFA_2015::C::Carbon
    Repository Name: AquaDocs
    Type: Report
    Format: 92pp.
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  • 12
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    Aerosol Transport from the Asian Summer Monsoon into the Arctic Lower Stratosphere (2024)
    Copernicus Publications
    In:  EPIC3Copernicus Publications
    Details
    Publication Date: 2024-05-31
    Description: The Asian summer monsoon is linked to deep convection over the Indian subcontinent and to an anticyclonic flow that extends from the upper troposphere into the lower stratosphere region. This allows both gas-phase aerosol precursors and aerosol particles from surface sources to reach the stratosphere. The horizontal transport out of the Asian monsoon anticyclone towards the extratropical lower stratosphere of the Northern Hemisphere is the focus of this study. We present an annual record of Lidar observations at AWIPEV in Ny-Ålesund. The data record is free from obvious layers like polar stratospheric clouds, volcanic eruptions or forest fires. Nevertheless, the lower stratosphere reveals an annual cycle with lower backscatter values in winter and spring and higher backscatter values in summer and autumn. The Lidar measurements have been linked to backward trajectory calculations and simulations of artificial surface origin tracers with the three-dimensional Chemical Lagrangian Model of the Stratosphere (CLaMS). The simulations show that air masses observed above Ny-Ålesund have been transported from surface sources in Asia into the Arctic lower stratosphere. Thus, the increased backscatter values during summer and autumn can be explained by transport of aerosol particles from the Asian summer monsoon into the Arctic lower stratosphere.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Other , notRev
    Format: application/pdf
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  • 13
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    Improvement of Star Photometer Validation (2024)
    In:  EPIC3
    Details
    Publication Date: 2024-05-31
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , NonPeerReviewed
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  • 14
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    Improving daily-to-seasonal sea ice forecasts of the AWI coupled prediction system with sea-ice and ocean data assimilation and atmospheric large-scale wind nudging. (2024)
    Copernicus Publications
    In:  EPIC3Copernicus Publications
    Details
    Publication Date: 2024-05-31
    Description: Predictive skills of coupled sea-ice/ocean and atmosphere models are limited by the chaotic nature of the atmosphere. Assimilation of observational information on ocean hydrography and sea ice allows to obtain a coupled-system state that provides a basis for subseasonal-to-seasonal ocean and sea-ice forecast (Mu et al., 2022). However, if the atmosphere is not additionally constrained, the quasi-random atmospheric states within an ensemble forecast lead to a fast divergence of the ocean and sea-ice states, degrading the system’s performance with respect to the sea ice forecasts. As reported previously, imposing an additional constraint by nudging large-scale winds to the ERA5 reanalysis data (Sánchez-Benítez et al., 2021; Athanase et al., 2022) improves predictive skills of the AWI Coupled Prediction System (AWI-CPS, Mu et al. 2022) with regard to sea ice drift (Losa et al., 2023). Here we provide results based on a much more extensive set of ensemble-based data assimilation experiments spanning the time period from 2002 to 2023 and a series of long forecast experiments over 2010 – 2023, initialized in four different seasons. We compare the performance of forecasts initialized from two sets of data assimilation experiments, with and without atmospheric wind nudging. The additional relaxation of the large-scale atmospheric circulation to the ERA5 reanalysis data for the initialization leads to reasonable atmospheric forecast skill on weather timescales: Despite the simple technique, the coarse resolution compared to NWP systems, and the limited optimization efforts, 10-day forecasts of the 500 hPa geopotential height are about as skillful as the best performing NWP forecasts were about 10 –15 years ago. Among other aspects, this leads to significantly improved subseasonal-to-seasonal sea-ice concentration and thickness forecasts. Athanase, M., Schwager, M., Streffing, J., Andrés-Martínez, M., Loza, S., and Goessling, H.: Impact of the atmospheric circulation on the Arctic snow cover and ice thickness variability , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5836, https://doi.org/10.5194/egusphere-egu22-5836, 2022. Losa, S. N., Mu, L., Athanase, M., Streffing, J., Andrés-Martínez, M., Nerger, L., Semmler, T., Sidorenko, D., and Goessling, H. F.: Combining sea-ice and ocean data assimilation with nudging atmospheric circulation in the AWI Coupled Prediction System, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-14227, https://doi.org/10.5194/egusphere-egu23-14227, 2023. Mu, L. , Nerger, L. , Streffing, J. , Tang, Q. , Niraula, B. , Zampieri, L., Loza, S. N. and Goessling, H. F. (2022): Sea‐Ice Forecasts With an Upgraded AWI Coupled Prediction System , Journal of Advances in Modeling Earth Systems, 14 (12) . doi: 10.1029/2022ms003176 Sánchez-Benítez, A. , Goessling, H. , Pithan, F. , Semmler, T. and Jung, T. (2022): The July 2019 European Heat Wave in a Warmer Climate: Storyline Scenarios with a Coupled Model Using Spectral Nudging , Journal of Climate, 35 (8), pp. 2373-2390 . doi: 10.1175/JCLI-D-21-0573.1
    Repository Name: EPIC Alfred Wegener Institut
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    Improvement of Aerosol Coarse-Mode Detection through Additional Use of Infrared Wavelengths in the Inversion of Arctic Lidar Data (2024)
    MDPI
    In:  EPIC3Remote Sensing, MDPI, 16(9), pp. 1576-1576, ISSN: 2072-4292
    Details
    Publication Date: 2024-05-31
    Description: An Nd:YAG-based Raman lidar provides a mature technology to derive profiles of the optical properties of aerosols over a wide altitude range. However, the derivation of micro-physical parameters is an ill-posed problem. Hence, increasing the information content of lidar data is desirable. Recently, ceilometers and wind lidar systems, both operating in the near-infrared region, have been successfully employed in aerosol research. In this study, we demonstrate that the inclusion of additional backscatter coefficients from these two latter instruments clearly improves the inversion of micro-physical parameters such as volume distribution function, effective radius, or single-scattering albedo. We focus on the Arctic aerosol and start with the typical volume distribution functions of Arctic haze and boreal biomass burning. We forward calculate the optical coefficients that the lidar systems should have seen and include or exclude the backscatter coefficients of the ceilometer (910 nm) and wind lidar data (1500 nm) to analyze the value of these wavelengths in their ability to reproduce the volume distribution function, which may be mono- or bimodal. We found that not only the coarse mode but also the properties of the accumulation mode improved when the additional wavelengths were considered. Generally, the 1500 nm wavelength has greater value in correctly reproducing the aerosol properties
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    Yedoma: Late Pleistocene ice-rich syngenetic permafrost of Beringia (2024)
    Elsevier
    In:  EPIC3Elsevier, 16 p., ISBN: 9780124095489
    Details
    Publication Date: 2024-05-31
    Description: Yedoma is a permafrost deposit widely distributed across the Arctic and found exclusively within the unglaciated regions in northern Siberia, Alaska, and the Yukon, which are the core regions of Beringia. Yedoma deposits accumulated during the late Pleistocene Stage and are characterized by their predominantly fine-grained texture and association with syngenetic perma-frost formation. The very high ground ice content is most commonly present as pore ice and wedge ice that formed contemporaneously with sediment deposition. In the last decade, research has transitioned from debates about the origin of the Yedoma deposits towards increasing attention on the large carbon and nitrogen pools in Yedoma, their vulnerability to thaw, and increasing mobilization as the climate has warmed across the Arctic. In addition to classical cryolithological and sedimentological research, new methods such as stable isotope paleoclimate reconstruction and ancient sedimentary DNA studies have been more widely applied to better understand the characteristics of Yedoma deposits and helped emphasize their value as archives of Quaternary climate and paleoecological conditions during Ice Age Beringia.
    Repository Name: EPIC Alfred Wegener Institut
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    Glacial isostatic adjustment reduces past and future Arctic subsea permafrost (2024)
    Springer Nature
    In:  EPIC3Nature Communications, Springer Nature, 15(1), pp. 3232-3232, ISSN: 2041-1723
    Details
    Publication Date: 2024-05-31
    Description: Sea-level rise submerges terrestrial permafrost in the Arctic, turning it into subsea permafrost. Subsea permafrost underlies ~ 1.8 million km2 of Arctic continental shelf, with thicknesses in places exceeding 700 m. Sea-level variations over glacial-interglacial cycles control subsea permafrost distribution and thickness, yet no permafrost model has accounted for glacial isostatic adjustment (GIA), which deviates local sea level from the global mean due to changes in ice and ocean loading. Here we incorporate GIA into a pan-Arctic model of subsea permafrost over the last 400,000 years. Including GIA significantly reduces present-day subsea permafrost thickness, chiefly because of hydro-isostatic effects as well as deformation related to Northern Hemisphere ice sheets. Additionally, we extend the simulation 1000 years into the future for emissions scenarios outlined in the Intergovernmental Panel on Climate Change’s sixth assessment report. We find that subsea permafrost is preserved under a low emissions scenario but mostly disappears under a high emissions scenario.
    Repository Name: EPIC Alfred Wegener Institut
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    Exploring Prokaryotic Communities in the Guts and Mucus of Nudibranchs, and Their Similarity to Sediment and Seawater Microbiomes (2023)
    In:  Current Microbiology vol. 80 no. 294
    Details
    Publication Date: 2024-05-31
    Description: In the present study, we compared mucus and gut-associated prokaryotic communities from seven nudibranch species with sediment and seawater from Thai coral reefs using high-throughput 16S rRNA gene sequencing. The nudibranch species were identified as Doriprismatica atromarginata (family Chromodorididae), Jorunna funebris (family Discodorididae), Phyllidiella nigra, Phyllidiella pustulosa, Phyllidia carlsonhoffi, Phyllidia elegans, and Phyllidia picta (all family Phyllidiidae). The most abundant bacterial phyla in the dataset were Proteobacteria, Tenericutes, Chloroflexi, Thaumarchaeota, and Cyanobacteria. Mucus and gut-associated communities differed from one another and from sediment and seawater communities. Host phylogeny was, furthermore, a significant predictor of differences in mucus and gut-associated prokaryotic community composition. With respect to higher taxon abundance, the order Rhizobiales (Proteobacteria) was more abundant in Phyllidia species (mucus and gut), whereas the order Mycoplasmatales (Tenericutes) was more abundant in D. atromarginata and J. funebris. Mucus samples were, furthermore, associated with greater abundances of certain phyla including Chloroflexi, Poribacteria, and Gemmatimonadetes, taxa considered to be indicators for high microbial abundance (HMA) sponge species. Overall, our results indicated that nudibranch microbiomes consisted of a number of abundant prokaryotic members with high sequence similarities to organisms previously detected in sponges.
    Repository Name: National Museum of Natural History, Netherlands
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    A standardized database of Last Interglacial (MIS 5e) sea-level indicators in Southeast Asia (2021)
    Copernicus GmbH
    In:  Earth System Science Data vol. 13 no. 9, pp. 4313-4329
    Details
    Publication Date: 2024-05-31
    Description: Marine Isotope Stage 5e (MIS 5e; the Last Interglacial, 125 ka) represents a process analog for a warmer world. Analysis of sea-level proxies formed in this period helps in constraining both regional and global drivers of sea-level change. In Southeast Asia, several studies have reported elevation and age information on MIS 5e sea-level proxies, such as fossil coral reef terraces or tidal notches, but a standardized database of such data was hitherto missing. In this paper, we produced such a sea-level database using the framework of the World Atlas of Last Interglacial Shorelines (WALIS; https://warmcoasts.eu/world-atlas.html). Overall, we screened and reviewed 14 studies on Last Interglacial sea-level indicators in Southeast Asia, from which we report 43 proxies (42 coral reef terraces and 1 tidal notch) that were correlated to 134 dated samples. Five data points date to MIS 5a (80 ka), six data points are MIS 5c (100 ka), and the rest are dated to MIS 5e. The database compiled in this study is available at https://doi.org/10.5281/zenodo.5040784 (Maxwell et al., 2021).
    Repository Name: National Museum of Natural History, Netherlands
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    Dynamics of large benthic foraminiferal assemblages: A tool to foreshadow reef degradation? (2022)
    In:  Science of The Total Environment vol. 811 no. 151396
    Details
    Publication Date: 2024-05-31
    Description: Ecological regime shifts in the marine realm have been recorded from a variety of systems and locations around the world. Coral reefs have been especially affected, with their benthic habitat changing from a dominance of stony corals to a dominance of other organisms such as fleshy algae. To detect changes in the benthic habitat of coral reefs, simple tools applicable on a global scale are necessary for future monitoring programs. Hence, the aim of this research is to explore the hypothesis that shifts in assemblages of large benthic foraminifera (LBF) can detect early signs of degradation in the reef benthic habitat. To do so, data on living assemblages of LBF collected between 1997 and 2018 at 12 islands in the Spermonde Archipelago (South Sulawesi, Indonesia) were analyzed. Foraminiferal specimens were morphologically identified to the species level and statistical analyses performed to assess changes in their assemblage composition. A clear temporal shift was observed. Typical foraminiferal assemblages in a coral-dominated (e.g., Amphistegina lobifera, Calcarina spengleri, Heterostegina depressa) and fleshy algaedominated (e.g., Neorotalia gaimardi, C. mayori) reef habitats were identified and significantly linked to the substrate type. Other species (e.g., Elphidium spp., Peneroplis planatus and Sphaerogypsina globulus) seem to reflect a spatial and temporal gradient of anthropogenic pollution from local inhabited islands and ongoing urban development on the mainland. Hence communities of LBF consistently follow gradual shifts in environmental conditions. Additionally to foraminiferal assemblages being an indicator for actual reef condition, closely monitoring LBF may provide early information on reef degradation, in time to take action against identified stressors (e.g., eutrophication or intensive fishing) at local and regional scales. The circumtropical distribution of LBF is such that they can be included worldwide in reef monitoring programs, conditional to calibration to the regional species pool.
    Keywords: Temporal dynamics ; Bioindicator ; Early detection ; Coral reef ; Spermonde Archipelago ; Indonesia
    Repository Name: National Museum of Natural History, Netherlands
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    Marine conservation beyond MPAs: Towards the recognition of other effective area-based conservation measures (OECMs) in Indonesia (2022)
    In:  Marine Policy vol. 137 no. 104939
    Details
    Publication Date: 2024-05-31
    Description: In a marine environment that is rapidly changing due to anthropogenic activities and climate change, area-based management tools are often used to mitigate threats and conserve biodiversity. Marine protected areas (MPAs) are amongst the most widespread and recognized marine conservation tools worldwide, however, MPAs alone are inadequate to address the environmental crisis. The promotion of other effective area-based conservation measures (OECMs) under draft Target 3 of the Post-2020 Global Biodiversity Framework, i.e., conserving 30% of marine areas by 2030, holds promise to acknowledge sites and practices occurring beyond MPAs that contribute to conservation. Here, we evaluate the potential recognition of OECMs into Indonesia's national policy framework on marine resource management and provide the first-ever overview of distribution and types of potential marine OECMs in Indonesia, including a review of the existing evidence on conservation effectiveness. We identified 〉 390 potential marine OECMs, led by government, customary and local communities, or the private sector, towards diverse management objectives, including habitat protection, traditional/customary management, fisheries, tourism, or other purposes. While some evidence exists regarding the conservation effectiveness of these practices, the long-term impacts on biodiversity of all potential marine OECMs in Indonesia are unknown. Many OECM elements have been included in several national policies, yet there are no established mechanisms to identify, recognize and report sites as OECMs in Indonesia. We propose four transformational strategies for future OECM recognition in Indonesia, namely: (i) safeguard customary and traditional communities, (ii) leverage cross-sector and cross-scale collaboration, (iii) focus on delivering outcomes, and (iv) streamline legal frameworks. Our study shows that OECMs have the potential to play a significant role in underpinning marine area-based conservation in Indonesia, including supporting the Government of Indonesia in reaching national and international conservation targets and goals.
    Keywords: Area-based management ; Biodiversity conservation ; Customary management ; Fisheries ; Co-management ; Sustainable marine management
    Repository Name: National Museum of Natural History, Netherlands
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    The annelid community of a natural deep-sea whale fall off eastern Australia (2023)
    Australian Museum
    In:  Records of the Australian Museum vol. 75 no. 3, pp. 167-213
    Details
    Publication Date: 2024-05-31
    Description: n the deep ocean, whale falls (deceased whales that sink to the seafloor) act as a boost of productivity in this otherwise generally food-limited setting, nourishing organisms from sharks to microbes during the various stages of their decomposition. Annelid worms are habitual colonizers of whale falls, with new species regularly reported from these settings and their systematics helping to resolve biogeographic patterns among deep-sea organic fall environments. During a 2017 expedition of the Australian research vessel RV Investigator to sample bathyal to abyssal communities off Australia’s east coast, a natural whale fall was opportunistically trawled at ~1000 m depth. In this study, we provide detailed taxonomic descriptions of the annelids associated with this whale-fall community, using both morphological and molecular techniques. From this material we describe nine new species from five families (Dorvilleidae: Ophryotrocha dahlgreni sp. nov. Ophryotrocha hanneloreae sp. nov., Ophryotrocha ravarae sp. nov.; Hesionidae: Vrijenhoekia timoharai sp. nov.; Nereididae: Neanthes adriangloveri sp. nov., Neanthes visicete sp. nov.; Orbiniidae: Orbiniella jamesi sp. nov.), including two belonging to the bone-eating genus Osedax (Siboglinidae: Osedax waadjum sp. nov., Osedax byronbayensis sp. nov.) that are the first to be described from Australian waters. We further provide systematic accounts for 10 taxa within the Ampharetidae, Amphinomidae, Microphthalmidae, Nereididae, Orbiniidae, Phyllodocidae, Protodrilidae, Sphaerodoridae and Phascolosomatidae. Our investigations uncover unique occurrences and for the first time enable the evaluation of biogeographic links between Australian whale falls and others in the western Pacific as well as worldwide.
    Keywords: polychaete ; chemosynthesis ; organic fall ; bathyal ; Bathymodiolinae ; Pacific Ocean
    Repository Name: National Museum of Natural History, Netherlands
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    Limited Progress in Improving Gender and Geographic Representation in Coral Reef Science (2021)
    Frontiers Media SA
    In:  Frontiers in Marine Science vol. 8 no. 731037
    Details
    Publication Date: 2024-05-31
    Description: Despite increasing recognition of the need for more diverse and equitable representation in the sciences, it is unclear whether measurable progress has been made. Here, we examine trends in authorship in coral reef science from 1,677 articles published over the past 16 years (2003–2018) and find that while representation of authors that are women (from 18 to 33%) and from non-OECD nations (from 4 to 13%) have increased over time, progress is slow in achieving more equitable representation. For example, at the current rate, it would take over two decades for female representation to reach 50%. Given that there are more coral reef non-OECD countries, at the current rate, truly equitable representation of non-OECD countries would take even longer. OECD nations also continue to dominate authorship contributions in coral reef science (89%), in research conducted in both OECD (63%) and non-OECD nations (68%). We identify systemic issues that remain prevalent in coral reef science (i.e., parachute science, gender bias) that likely contribute to observed trends. We provide recommendations to address systemic biases in research to foster a more inclusive global science community. Adoption of these recommendations will lead to more creative, innovative, and impactful scientific approaches urgently needed for coral reefs and contribute to environmental justice efforts.
    Keywords: coral reef science ; gender ; equity ; inclusion ; representation ; diversity
    Repository Name: National Museum of Natural History, Netherlands
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    Simulation of the mid-Pliocene Warm Period using HadGEM3: experimental design and results from model–model and model–data comparison (2021)
    Copernicus GmbH
    In:  Climate of the Past vol. 17 no. 5, pp. 2139-2163
    Details
    Publication Date: 2024-05-31
    Description: Here we present the experimental design and results from a new mid-Pliocene simulation using the latest version of the UK's physical climate model, HadGEM3-GC31-LL, conducted under the auspices of CMIP6/PMIP4/PlioMIP2. Although two other palaeoclimate simulations have been recently run using this model, they both focused on more recent periods within the Quaternary, and therefore this is the first time this version of the UK model has been run this far back in time. The mid-Pliocene Warm Period, ∼3 Ma, is of particular interest because it represents a time period when the Earth was in equilibrium with CO2 concentrations roughly equivalent to those of today, providing a possible analogue for current and future climate change. The implementation of the Pliocene boundary conditions is firstly described in detail, based on the PRISM4 dataset, including CO2, ozone, orography, ice mask, lakes, vegetation fractions and vegetation functional types. These were incrementally added into the model, to change from a pre-industrial setup to a Pliocene setup. The results of the simulation are then presented, which are firstly compared with the model's pre-industrial simulation, secondly with previous versions of the same model and with available proxy data, and thirdly with all other models included in PlioMIP2. Firstly, the comparison with the pre-industrial simulation suggests that the Pliocene simulation is consistent with current understanding and existing work, showing warmer and wetter conditions, and with the greatest warming occurring over high-latitude and polar regions. The global mean surface air temperature anomaly at the end of the Pliocene simulation is 5.1 ∘C, which is the second highest of all models included in PlioMIP2 and is consistent with the fact that HadGEM3-GC31-LL has one of the highest Effective Climate Sensitivities of all CMIP6 models. Secondly, the comparison with previous generation models and with proxy data suggests a clear increase in global sea surface temperatures as the model has undergone development. Up to a certain level of warming, this results in a better agreement with available proxy data, and the “sweet spot” appears to be the previous CMIP5 generation of the model, HadGEM2-AO. The most recent simulation presented here, however, appears to show poorer agreement with the proxy data compared with HadGEM2 and may be overly sensitive to the Pliocene boundary conditions, resulting in a climate that is too warm. Thirdly, the comparison with other models from PlioMIP2 further supports this conclusion, with HadGEM3-GC31-LL being one of the warmest and wettest models in all of PlioMIP2, and if all the models are ordered according to agreement with proxy data, HadGEM3-GC31-LL ranks approximately halfway among them. A caveat to these results is the relatively short run length of the simulation, meaning the model is not in full equilibrium. Given the computational cost of the model it was not possible to run it for a longer period; a Gregory plot analysis indicates that had it been allowed to come to full equilibrium, the final global mean surface temperature could have been approximately 1.5 ∘C higher.
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    In welche Richtung steuert die internationale Klimapolitik? : Eine Bilanz der COP28 in Dubai Bericht (2024)
    Details
    Publication Date: 2024-05-31
    Keywords: ddc:320
    Repository Name: Wuppertal Institut für Klima, Umwelt, Energie
    Language: German
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    A generative toolkit to help raise industrial design students' awareness of low metal recycling rates (2024)
    Cambridge : Cambridge University Press
    Details
    Publication Date: 2024-05-31
    Description: Education for Sustainable Development requires raising individuals' awareness of problems relevant to the environment. We designed a Generative Toolkit that supports industrial design students carrying out a Speculative Design task and through this process initiates greater problem awareness of low metal recycling rates. In this paper we give insights into the Toolkit's theoretical derivation and the design process. Findings from testing suggest that there are several opportunities for improvement, such as considering further content-related competencies in the Toolkit's design.
    Keywords: ddc:600
    Repository Name: Wuppertal Institut für Klima, Umwelt, Energie
    Language: English
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    Humboldtn and the sustainable transformation of universities (2024)
    Cham : Springer
    Details
    Publication Date: 2024-05-31
    Description: The sustainable transformation of society is one of the greatest challenges of our time. Universities are central actors for knowledge generation and transfer in the sustainability field and, at the same time, are facing the question of how they can become sustainable social actors and make their activities and infrastructure sustainable. Against this background, the 16 member universities of the State Rectors' Conference of North Rhine-Westphalia have joined forces in the Humboldtn initiative to pool their efforts in the field of sustainability and to anchor generational responsibility for sustainable action in research, teaching, administration, infrastructure, and transfer. How the joint responsibility for the questions for the future in the aforementioned complex of topics is addressed via Humboldtn and which focal points are set in the process will be presented and discussed using examples from the institutional sustainability transformation and examples from the research area from RWTH Aachen University. In this way, the implementation of transformation processes at universities and their possible blueprint effect can be illuminated.
    Keywords: ddc:300
    Repository Name: Wuppertal Institut für Klima, Umwelt, Energie
    Language: English
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    Comparative analysis of residential building decarbonization policies in major economies : insights from the EU, China, and India (2024)
    Details
    Publication Date: 2024-05-31
    Description: The global building sector, responsible for over 30% of CO2 emissions, necessitates urgent decarbonization efforts. This paper examines residential building decarbonization policies in three major economies - the European Union (EU), China, and India. It provides an overview of diverse policies through policy landscape analysis and delves into the design specifics with a detailed policy intensity analysis of building energy codes, information disclosure, and financial incentives in each region. Our findings reveal a diverse mix of policies targeting residential building decarbonization in all three regions. While the EU and China have long-established diverse policy instruments, India's building energy efficiency policies are relatively recent and limited. Detailed analyses of building energy codes, information disclosure, and financial incentives expose variations in ambition, scope, and implementation, even with shared policy instruments. Significant advancements in building energy codes, particularly in stringency and compliance checks, are evident in the EU and China. Conversely, India faces a notable obstacle with limited adoption of residential building energy codes, impacting its journey towards net-zero. The EU leads in building energy labelling policies, while China and India encounter various challenges hindering widespread implementation. Financial incentives across the three regions predominantly take the form of subsidies, potentially straining public budgets. The study concludes with reflections on the pressing need for future research extending beyond the operational phase of buildings.
    Keywords: ddc:320
    Repository Name: Wuppertal Institut für Klima, Umwelt, Energie
    Language: English
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    CbD (Circular by Design): Ressourcenwende über nachhaltiges Produktdesign von Konsumgütern am Fallbeispiel Kühl-/Gefriergerät : Abschlussbericht (2024)
    Freiberg : Helmholtz-Zentrum Dresden Rossendorf
    Details
    Publication Date: 2024-05-31
    Description: Im Projekt wird ein kreislauffähiges Produktdesign für Kühl-/Gefriergeräte auf Basis von im Labor- und Industriemaßstab ermittelten Daten entwickelt, das gleichermaßen energie- als auch ressourceneffizient ist. Übergreifendes Ziel war die modellhafte Weiterentwicklung eines Konsumgutes, das neben dem bereits bestehenden Fokus auf Energieeffizienz auch das Thema Ressourceneffizienz in den Blick nimmt. In der Konzeptphase wurden dazu verschiedene Ansätze entwickelt und mit einem Bewertungs- und Entscheidungstool ergänzt, das als Standard für weitere Konsumgüter dienen kann. Dabei wurde ein übertragbares Designkonzept zur Kreislaufführung der verwendeten Materialien von Konsumgütern am Beispiel eines Kühl-/Gefriergerät-Prototyps erstellt. Da die dafür erforderlichen Daten in der Literatur sowie über öffentlich zugängliche Datenbanken nicht vorhanden bzw. für Forschungseinrichtungen zugänglich waren, wurden diese über Labor- und Großversuch beim Recycling-Unternehmen Stena (Recular) selbst und damit in jedem Schritt nachvollziehbar erhoben. Auf dieser Grundlage wurden verschiedene Designoptionen, mit dem Fokus auf ein möglichst ressourceneffizientes und reparaturfreundliches Produkt zur Schaffung tatsächlich geschlossener Stoffkreisläufe und von Möglichkeiten für Repair/Reuse sowie neuer Geschäftsmodelle, entwickelt. Die Zusammenführung der Ressourceneffizienzanalyse mit einem multiregional erweiterten Input-Output-Modell wird zukünftig die Abschätzung der Recyclingfähigkeit von Produkten bereits im Designstadium ermöglichen und dadurch ein Design-for-Repair und/oder -Recycling unterstützen.
    Keywords: ddc:600
    Repository Name: Wuppertal Institut für Klima, Umwelt, Energie
    Language: German
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  • 30
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    Global warming will increase earthquake hazards through rising sea levels and cascading effects (2024)
    In:  Seismological Research Letters
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    Publication Date: 2024-05-31
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    Acoustic Emission and Seismic moment tensor catalogs associated with triaxial stick-slip experiments performed on Westerly Granite samples (2024)
    GFZ Data Services
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    Publication Date: 2024-05-31
    Description: The dataset contains source parameters of acoustic emission (AE) events recorded during triaxial friction (stick-slip) experiments performed on the Westerly Granite sample WgN05. In addition we provide raw waveform data of AE events recorded in triggered mode with a network of 16 AE sensors. Basic seismic catalog associated with the stick-slip experiment contains origin time, hypocentral location in local Cartesian coordinate system of the sample (with associated uncertainties), and AE-derived magnitude. In addition, for a subset of AEs we provide full moment tensors. This catalog include information on fault parameters (strike, dip and rake of the two nodal planes), percentage of isotropic, compensated linear vector dipole and double-couple components of the full moment tensor, P, T, B axes orientations in the coordinate system of the sample, uncertainty assessment, as well as the six independent moment tensor components. Finally, we provide a time series of axial stress values as presented in the Kwiatek et al. (2023) as well as the coordinates of the AE sensors. The catalog and parametric data is supplemented with the raw waveform recordings stored in HDF5 format from 16 acoustic emission sensors placed on the surface of the sample.
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    A micromechanical analysis of marble pulverization under quasi-static progressive cyclic loading (2024)
    In:  International Journal of Rock Mechanics and Mining Sciences
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    Publication Date: 2024-05-31
    Description: Highly fragmented rocks (i.e., pulverized rocks) in the fault damage zone presumably develop during co-seismic deformation processes. These pulverized rocks close to the fault core are generally thought to originate from high strain rates, whereas the genesis of pulverized rocks that can be found several hundred meters away from the fault core – where quasi-static conditions prevail – remains unclear. We thus conducted uniaxial cyclic loading experiments with axial strain rate of ∼10−3 s−1 on Leiyang marble in a stress-controlled manner in order to produce crushed rocks for analysis. We found that cyclic loading between 0.8 σc and 1.3 σc can simultaneously compact pre-existing cracks and generated new cracks in marble, which strengthened and stiffened the rock. The stiffened marble developed a higher crack density and energy density before rupture, thereby facilitating rock fragmentation compared with the reference sample, which was fractured monotonically in one cycle. Our results provide a plausible explanation for the genesis of pulverized marble at quasi-static strain rate in the field.
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    Autotrophy to Heterotrophy: Shift in Bacterial Functions During the Melt Season in Antarctic Cryoconite Holes (2024)
    In:  Journal of Microbiology
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    Publication Date: 2024-05-31
    Description: Microbes residing in cryoconite holes (debris, water, and nutrient-rich ecosystems) on the glacier surface actively participate in carbon and nutrient cycling. Not much is known about how these communities and their functions change during the summer melt-season when intense ablation and runoff alter the influx and outflux of nutrients and microbes. Here, we use high-throughput-amplicon sequencing, predictive metabolic tools and Phenotype MicroArray techniques to track changes in bacterial communities and functions in cryoconite holes in a coastal Antarctic site and the surrounding fjord, during the summer season. The bacterial diversity in cryoconite hole meltwater was predominantly composed of heterotrophs (Proteobacteria) throughout the season. The associated functional potentials were related to heterotrophic-assimilatory and -dissimilatory pathways. Autotrophic Cyanobacterial lineages dominated the debris community at the beginning and end of summer, while heterotrophic Bacteroidota- and Proteobacteria-related phyla increased during the peak melt period. Predictive functional analyses based on taxonomy show a shift from predominantly phototrophy-related functions to heterotrophic assimilatory pathways as the melt-season progressed. This shift from autotrophic to heterotrophic communities within cryoconite holes can affect carbon drawdown and nutrient liberation from the glacier surface during the summer. In addition, the flushing out and export of cryoconite hole communities to the fjord could influence the biogeochemical dynamics of the fjord ecosystem.
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    Semi-Airborne Electromagnetic Survey Design and Inversion for Large-Scale Mineral Exploration in the Harz Area, Germany (2024)
    In:  Protokoll über das 30. Schmucker-Weidelt-Kolloquium für Elektromagnetische Tiefenforschung: virtuell, 25. September - 29. September 2023
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    Publication Date: 2024-05-31
    Description: This study investigates the optimization of Semi-Airborne Electromagnetic (SAEM) surveys for enhanced subsurface imaging in mineral exploration. It highlights the utility of multi-transmitter systems and explores real data utilization and the challenges of large-scale surveys. With emphasis on Data obtained from DESMEX project surveys. The use of multiple transmitters is crucial. Single transmitters can distort results and mask subsequent bodies. Employing two transmitters on both sides of the target enhances resolution and depth accuracy. results are based on finite element forward operator custEM and pyGIMLi’s inverse solver [1]. substantial advantages of combining single and multi-patch inversion data. This integration results in improved resolution, reduced artifacts, enhanced continuity of geological structures, superior anomaly detection, minimized edge effects, and improved depth penetration [2]. These findings open promising avenues for further exploration and research in geosciences, offering valuable insights into the Earth's subsurface and its intricate geological features. The next logical step involves expanding our methodology to large-scale inversion using more than three transmitters.
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    Multidimensional inversion of sedimentary sequences in the Atacama Desert, Chile, using transient electromagnetic data (2024)
    In:  Protokoll über das 30. Schmucker-Weidelt-Kolloquium für Elektromagnetische Tiefenforschung: virtuell, 25. September - 29. September 2023
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    Publication Date: 2024-05-31
    Description: The Atacama Desert along the Chilean Coastal Cordillera is a unique landscape to understand the Earth's evolution in hyper-arid and arid environments. The Paranal clay pan has studied by the CRC 1211 project to recover a continuous climate record for paleoclimate research. The goal is to provide the sedimentary architecture and bedrock topography of the Paranal site by interpreting multidimensional inversion of loop source transient electromagnetic (TEM) data. A total of 133 TEM soundings were carried out using a central loop configuration, with a transmitter loop size of 40×40 m2 and a receiver of about 10×10 m2. The TEM data was processed and analyzed, exhibiting high-quality data, with an average of noise level of about ηnoi = 3·10−10V/Am2. The 1D Occam inversion results exhibits a clear three-layered resistivitydepth structure with a second conductive layer of roughly 20 Ωm. The clay pan's resistivity distribution is well-resolved with a global misfit of around 1.1. However, the study site showed 2D effects that were stronlgy visible at the edges of the clay pan, leading to misinterpretations of the TEM data. This was confirmed based on 2D forward modelling. In this manner, to better deal with the observed 2D distortions in the TEM data and to derive a more accurate geometry of the clay pan, the recently developed Julia Package (3DTEMinv) for time-domain 3D inversion and modeling data was performed. The resulting 3D inversion presents a high convergence rate, and acceptable solutions are obtained after ten iterations with a good misfit of about 1.6. The 3D model exhibits a well-resolved geometry of the clay pan, with a high resolution of the derived conductive body. The drill core results confirm the 1D and 3D TEM models at the center of the clay pan, which is in good agreement with the resulting lithology with a maximum thickness of about 171 m depth and a weathered granodioritic bedrock below. These results agree with the local and regional geological context, improving the understanding of sediment deposition and transportation in this hilly and arid environment.
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    3D Inversion of Loop-Source Time-Domain Electromagnetic Data - Application to Synthetic & Field Data (2024)
    In:  Protokoll über das 30. Schmucker-Weidelt-Kolloquium für Elektromagnetische Tiefenforschung: virtuell, 25. September - 29. September 2023
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    Publication Date: 2024-05-31
    Description: Multi-dimensional inversion of Transient electromagnetic data is a computationally expensive task. Only few developments and practical interpretation tools exist. Here, we present a multidimensional inversion framework for loop source time-domain electromagnetic data. The developed algorithm is a robust, efficient, and user-oriented tool for the multi-dimensional inversion of typical loop source time-domain electromagnetic configurations. A time-domain finite volume discretization and the direct solver MUMPS are utilized to solve the 3D TEM forward problem. An iterative Gauss-Newton optimization method is implemented for the inversion kernel. The code is parallelized for calculating multiple sources simultaneously to accelerate the inversion. Based on exploration tasks, different configurations exist for commonly used loop source TEM configurations and typical field scales. Synthetic examples are used to verify the effectiveness and benchmark the developed 3D algorithm. Considering that TEM data is often gathered along profiles, adjusting the model roughness along the different modeling domain directions, sufficiently constrains to allow for 2D imaging. In addition to the vertical signal components, we also included horizontal components for large scale fixed loop applications. Subsequent to synthetic validation, the inversion algorithm is further verified using ~120 dense TEM soundings collected over a clay pan site in the Atacama Desert, Chile, to provide bedrock geometry information and suitable coring sites. The 3D inversion result provided an excellent depth estimate of sedimentary infill as well as the bedrock topography and was later confirmed by deep coring. Another interesting site is the Roter Kamm impact crater in Namibia. Our preliminary results obtained from largescale multicomponent fixed loop TEM data reveal a sedimentary infill down to ~300 m depth. In conclusion, our presented 3D inversion code is capable to handle data from various exploration scenarios and provides a robust tool for advanced EM interpretation.
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    Smart data selection - First insights from using machine learning for controlled-source RMT data processing (2024)
    In:  Protokoll über das 30. Schmucker-Weidelt-Kolloquium für Elektromagnetische Tiefenforschung: virtuell, 25. September - 29. September 2023
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    Publication Date: 2024-05-31
    Language: English
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    Virtual experiments on an IP laboratory measurement (2024)
    In:  Protokoll über das 30. Schmucker-Weidelt-Kolloquium für Elektromagnetische Tiefenforschung: virtuell, 25. September - 29. September 2023
    Details
    Publication Date: 2024-05-31
    Description: Carrying out laboratory experiments is usually a time-consuming process. In addition, the options for varying parameter studies are limited and adjustments to the design of the measuring equipment are often not possible at all. In order to circumvent these limitations, we supplement our laboratory experiments with virtual experiments as best as possible. For this purpose, we have expanded our finite element library FEMALY [1] to include the so-called complete electrode model [2], which allows us to simulate electrodes of any shape for DC and IP applications and also provides us with explicit mathematical expressions for calculating sensitivities [3]. As a first case study, we consider an IP measurement on a measuring cylinder with embedded ring electrodes to virtually reproduce the time-varying change of the apparent resistivity for laboratory tracer experiments (Figure 1). We present the real and imaginary part of the sensitivity distribution of the underlying measurement configuration that confirms our initial assumption that the actual electrode surface shape has a relatively small influence on the observed measurement quantities.
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    Semi-airborne electromagnetic exploration for deep earth resources - large scale multi source 3D imaging of a graphite deposit (2024)
    In:  Protokoll über das 30. Schmucker-Weidelt-Kolloquium für Elektromagnetische Tiefenforschung: virtuell, 25. September - 29. September 2023
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    Publication Date: 2024-05-31
    Description: The transition towards renewable energies demands secure supply with critical raw material and requires efficient non-invasive methods for deep earth resources exploration. The novel DESMEX (Deep electromagnetic sounding for mineral exploration) semi-airborne electromagnetic (semi-AEM) exploration concept aims at efficient exploration of resources down to 1 km depth. Here we present a large-scale semi-AEM exploration study in a graphite mining district in eastern Bavaria, Germany. At the ground, several horizontal electrical dipole transmitters were deployed and helicopter-towed magnetic field sensors measure the EM fields along flight lines within several overlapping flight areas, providing a fast data acquisition and a high spatial coverage. Imaged shallow high conductivity structures can be correlated with graphite-rich zones and match well with existing helicopter-borne EM results. The presence of graphite leads to significant induced polarization (IP) effects with considerably high chargeabilities superposing electromagnetic induction. We include these effects in a realistic 3D inversion using a synthetic data study to analyse, if the IP effect alters the overall conductivity structure and demonstrate that the obtained 3D model is reliable.
    Language: English
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    FEMALY: A Finite Element MAtlab LibrarY for Electromagnetics (2024)
    In:  Protokoll über das 30. Schmucker-Weidelt-Kolloquium für Elektromagnetische Tiefenforschung: virtuell, 25. September - 29. September 2023
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    Publication Date: 2024-05-31
    Description: We present a finite element software library written in Matlab for the numerical simulation and inversion of electromagnetic fields in two and three dimensions. It is designed in a modular way to easily plug together fundamental building blocks for various electromagnetic applications from DC to the inductive range in the frequency and even time domain. External modules comprise the mesh generator and the equation solver library. Through its homogeneous software concept the adoption to any field application is relatively simple and makes the code suitable to open source distribution. We introduce the key features of this library including higher-order Lagrange and Nédélec finite elements formulated on unstructured tetrahedral grids, a Gauss- Newton inversion approach using linear Raviart-Thomas elements for H1 regularization, and the ability to incorporate any geometric feature such as topography, bathymetry and internal voids like caves, tunnels and mine buildings. The library is currently being tested with large real data sets to confirm its usefulness as a tool for practical data interpretation. Therefore, case studies for the magnetotelluric, direct current resistivity, controlled source electromagnetic and induced polarization methods in the field and laboratory are briefly outlined as examples with challenging geometric features.
    Language: English
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    Effect of microvariability on electrical rock properties: investigations based on microstructure simulations (2024)
    In:  Protokoll über das 30. Schmucker-Weidelt-Kolloquium für Elektromagnetische Tiefenforschung: virtuell, 25. September - 29. September 2023
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    Publication Date: 2024-05-31
    Description: In petrophysics, physical rock properties are typically established through laboratory measurements of individual samples. These measurements predominantly relate to the specific sample and can be challenging to associate with the rock as a whole since the physical attributes are heavily reliant on the microstructure, which can vary significantly in different areas. Thus, the obtained values have limited applicability to the entirety of the original rock mass. To examine the dependence of petrophysical measurements based on the variable microstructure, we generate sets of random microstructure representations for a sample, taking into account macroscopic parameters such as porosity and mean grain size. We show that the methodology can adequately mimic the physical behavior of real rocks, showing consistent emulation of the dependence of electrical conductivity on connected porosity according to Archie's law across different types of pore space (micro-fracture, inter-granular, and vuggy, oomoldic pore space). Furthermore, properties such as the internal surface area and its fractal dimension as well as the electrical tortuosity are accessible for the random microstructures and show reasonable behavior. Finally, the possibilities, challenges and meshing strategies for extending the methodology to 3D microstructures are discussed.
    Language: English
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    Hydraulic conductivity imaging by induced polarization and hydraulic tomography (2024)
    In:  Protokoll über das 30. Schmucker-Weidelt-Kolloquium für Elektromagnetische Tiefenforschung: virtuell, 25. September - 29. September 2023
    Details
    Publication Date: 2024-05-31
    Language: English
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    1D modeling of TEM data influenced by IP effects (2024)
    In:  Protokoll über das 30. Schmucker-Weidelt-Kolloquium für Elektromagnetische Tiefenforschung: virtuell, 25. September - 29. September 2023
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    Publication Date: 2024-05-31
    Description: Transient electromagnetic (TEM) data can be significantly distorted by induced polarization (IP) effect, leading to a sign reversal feature and, if overlooked, false geological interpretation. The aim of this paper is to incorporate IP effects in the forward modelling and recover the distorted TEM data using an efficient inversion algorithm. To achieve this aim, we developed a 1D forward solver to incorporate the IP effects using various IP parameterizations including Cole-Cole, maximum phase angle (MPA), maximum imaginary conductivity (MIC) (Fiandaca et al., 2018) and the Jeffrey transform of Cole-Cole parameters (Ghorbani et al., 2007). For 1D inversion of distorted TEM data we used Levenberg-Marquardt and very fast simulated annealing algorithms. The result of 1D forward calculation and inversion of synthetic IPdistorted TEM data revealed that, for incorporation the IP effects into the TEM data, the Cole- Cole parametrization is more robust and reliable than MPA, MIC, and Jeffrey transform. Moreover, the result of inversion using Levenberg-Marquardt algorithm is strongly depends on the starting model. We successfully implemented these algorithms for 1D inversion of synthetic IP-affected TEM data (Fig. 1 ). For synthetic data generation, a 3-layered half space model with the thickness of the first and second layers of 5 m was considered. The resistivities of the layers from top to bottom are 10, 5 and 300 Ωm, respectively. To include the IP effect, second layer considered to be chargeable with Cole-Cole parameters of m = 0.5, τ = 0.01 s and c = 0.5. TEM central-loop configuration with a loop size of 50*50 m2 and step-off current of 1 A with a zero ramp time was used for data simulation. We evaluated the performance of our algorithm using field data, successfully.
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    Ongoing Approaches for utilizing Neural Networks in DC Resistivity Inversion (2024)
    In:  Protokoll über das 30. Schmucker-Weidelt-Kolloquium für Elektromagnetische Tiefenforschung: virtuell, 25. September - 29. September 2023
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    Publication Date: 2024-05-31
    Description: As part of an investigation into applications of Neural Networks for EM problems, different approaches have been tested for DC resistivity modeling and inversion. The first approach consists of using Convolutional Neural Networks (CNN) for DC resistivity inversion. For this purpose, dipole-dipole pseudosections were simulated using the in-house FEMALY toolbox and used as input data for a CNN, which was trained to output underground resistivity. Training results showed qualitatively good match with the ground truth. However, the predictions are characterized by lack of extrapolation to unseen types of data (e.g. homogeneous half-spaces) and coarse grid enforced by the approach. The second approach laid in the use of Physics Informed Neural Networks (PINN). In this approach, the relevant partial differential equation is included as a regularization term in the loss function, leading to a network whose outputs are guided by physics. Derivatives for the PDE termare obtained via automatic differentiation, removing the need for discretization. This also necessitated a move to solving the forward problem. While this approach has the benefits of being mesh-free and incorporating physics into the training process, in practice it failed at even elementary modeling cases, particularly involving resistivity anomalies. A third approach aimed at combining the previous two, by creating a physics-informed Convolutional Neural Network. This was achieved by replacing the previous loss approaches by a convolution with a Laplace-operator Kernel. This approach produces results that look promising qualitatively for homogeneous half-spaces, however full Dirichlet boundary conditions are required and resistivity anomalies can again not be easily incorporated.
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    First results from a new surface-towed controlled source electromagnetic experiment to detect offshore extensions of freshwater aquifers in the Adriatic Sea (2024)
    In:  Protokoll über das 30. Schmucker-Weidelt-Kolloquium für Elektromagnetische Tiefenforschung: virtuell, 25. September - 29. September 2023
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    Publication Date: 2024-05-31
    Description: play significant roles in coastal hydrologic systems. Despite the importance of these offshore groundwater systems and their interactions with onshore systems along global coastlines, a lack of understanding persists due to limitations in geophysical methodologies. Controlled-source electromagnetic (CSEM) techniques are one promising noninvasive avenue for identifying and characterizing OFG and SGD. However, the current availability of CSEM systems in academic research is limited, and applications are still restricted to specific regions. Existing CSEM systems are commonly associated with high deployment costs, logistical complexity, limited modification options and in case of seafloor-towed applications, slow data acquisition rates. To address these limitations, we introduce SWAN - a low-cost, modular, surface-towed hybrid time-frequency domain CSEM system capable of detecting OFG and SGD up to water depths of 100 m. A field test conducted in the central Adriatic Sea showcased the system's capabilities at water depths ranging from several tens to approximately 160 m. SWAN's ability to provide continuous measurements has proven effective in acquiring high-quality data while operating at towing speeds of 2.5 to 3 knots. The system's data coverage allows for the detection of subsurface resistivity variations to depths of approximately 150–200 m below the seafloor. With its user-friendly, modular design, SWAN offers a cost-efficient solution for investigating the hydrogeology of shallow offshore environments. The presentation shows the technological developments of SWAN, including illustrations of measured time series, processed data and first 2D inversion results from the Adriatic Sea.
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    Leveraging multi-variable observations to reduce and quantify the output uncertainty of a global hydrological model: evaluation of three ensemble-based approaches for the Mississippi River basin (2024)
    In:  Hydrology and Earth System Sciences
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    Publication Date: 2024-05-31
    Description: Global hydrological models enhance our understanding of the Earth system and support the sustainable management of water, food and energy in a globalized world. They integrate process knowledge with a multitude of model input data (e.g., precipitation, soil properties, and the location and extent of surface waterbodies) to describe the state of the Earth. However, they do not fully utilize observations of model output variables (e.g., streamflow and water storage) to reduce and quantify model output uncertainty through processes like parameter estimation. For a pilot region, the Mississippi River basin, we assessed the suitability of three ensemble-based multi-variable approaches to amend this: Pareto-optimal calibration (POC); the generalized likelihood uncertainty estimation (GLUE); and the ensemble Kalman filter, here modified for joint calibration and data assimilation (EnCDA). The paper shows how observations of streamflow (Q) and terrestrial water storage anomaly (TWSA) can be utilized to reduce and quantify the uncertainty of model output by identifying optimal and behavioral parameter sets for individual drainage basins. The common first steps in all approaches are (1) the definition of drainage basins for which calibration parameters are uniformly adjusted (CDA units), combined with the selection of observational data; (2) the identification of potential calibration parameters and their a priori probability distributions; and (3) sensitivity analyses to select the most influential model parameters per CDA unit that will be adjusted by calibration. Data assimilation with the ensemble Kalman filter was modified, to our knowledge, for the first time for a global hydrological model to assimilate both TWSA and Q with simultaneous parameter adjustment. In the estimation of model output uncertainty, we considered the uncertainties of the Q and TWSA observations. Applying the global hydrological model WaterGAP, we found that the POC approach is best suited for identifying a single “optimal” parameter set for each CDA unit. This parameter set leads to an improved fit to the monthly time series of both Q and TWSA as compared to the standard WaterGAP variant, which is only calibrated against mean annual Q, and can be used to compute the best estimate of WaterGAP output. The GLUE approach is almost as successful as POC in increasing WaterGAP performance and also allows, with a comparable computational effort, the estimation of model output uncertainties that are due to the equifinality of parameter sets given the observation uncertainties. Our experiment reveals that the EnCDA approach performs similarly to POC and GLUE in most CDA units during the assimilation phase but is not yet competitive for calibrating global hydrological models; its potential advantages remain unrealized, likely due to its high computational burden, which severely limits the ensemble size, and the intrinsic nonlinearity in simulating Q. Partitioning the whole Mississippi River basin into five CDA units (sub-basins) instead of only one improved model performance in terms of the Nash–Sutcliffe efficiency during the calibration and validation periods. Diverse parameter sets achieved comparable fits to observations, narrowing the range for at least three parameters. Low coverage of observation uncertainty bands by GLUE-derived model output bands is attributed to model structure uncertainties, especially regarding artificial reservoir operations, the location and extent of small wetlands, and the lack of representation of rivers that may lose water to the subsurface. These uncertainties are also likely to be responsible for significant trade-offs between optimal fits to Q and TWSA. Calibration performed exclusively against TWSA in regions without Q observations may worsen the Q simulation as compared to the uncalibrated model variant. We recommend that modelers improve the realism of the output of global hydrological models by calibrating them against observations of multiple output variables, including at least Q and TWSA. Further work on improving the numerical efficiency of the EnCDA approach is necessary.
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    The European Union and seabed mining (2024)
    In:  Routledge Handbook of Seabed Mining and the Law of the Sea
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    Publication Date: 2024-05-31
    Description: The destruction suffered across Europe due to centuries of conquests and wars, particularly those that were inflicted during the second world war, eventually gave birth to a strong desire to foster peace and mutual benefit across the borders of the European powers. The single european act of 1986 marked a first transformation of the European economic community towards a cooperation. This aspiration was subsequently manifested through the 1991 Maastricht Treaty on the European Union. The environmental impact assessment directive is one of the oldest EU environmental legislations. Together with the strategic environmental assessment directive, they apply, in a complementary way, to seabed mining activities on the continental shelf of member states. The Barcelona convention is an emblematic instrument which influenced the making of many other regional conventions due to the mechanism set up between the convention and its seven protocols. It comprises 22 contracting parties bordering the Mediterranean sea, including the EU.
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    Modelling seismic ground motion and its uncertainty in different tectonic contexts: challenges and application to the 2020European Seismic Hazard Model (ESHM20) (2024)
    In:  Natural Hazards and Earth System Sciences (NHESS)
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    Publication Date: 2024-05-31
    Description: Current practice in strong ground motion modelling for probabilistic seismic hazard analysis (PSHA) requires the identification and calibration of empirical models appropriate to the tectonic regimes within the region of application, along with quantification of both their aleatory and epistemic uncertainties. For the development of the 2020 European Seismic Hazard Model (ESHM20) a novel approach for ground motion characterisation was adopted based on the concept of a regionalised scaled-backbone model, wherein a single appropriate ground motion model (GMM) is identified for use in PSHA, to which adjustments or scaling factors are then applied to account for epistemic uncertainty in the underlying seismological properties of the region of interest. While the theory and development of the regionalised scaled-backbone GMM concept have been discussed in earlier publications, implementation in the final ESHM20 required further refinements to the shallow-seismicity GMM in three regions, which were undertaken considering new data and insights gained from the feedback provided by experts in several regions of Europe: France, Portugal and Iceland. Exploration of the geophysical characteristics of these regions and analysis of additional ground motion records prompted recalibrations of the GMM logic tree and/or modifications to the proposed regionalisation. These modifications illustrate how the ESHM20 GMM logic tree can still be refined and adapted to different regions based on new ground motion data and/or expert judgement, without diverging from the proposed regionalised scaled-backbone GMM framework. In addition to the regions of crustal seismicity, the scaled-backbone approach needed to be adapted to earthquakes occurring in Europe's subduction zones and to the Vrancea deep seismogenic source region. Using a novel fuzzy methodology to classify earthquakes according to different seismic regimes within the subduction system, we compare ground motion records from non-crustal earthquakes to existing subduction GMMs and identify a suitable-backbone GMM for application to subduction and deep seismic sources in Europe. The observed ground motion records from moderate- and small-magnitude earthquakes allow us to calibrate the anelastic attenuation of the backbone GMM specifically for the eastern Mediterranean region. Epistemic uncertainty is then calibrated based on the global variability in source and attenuation characteristics of subduction GMMs. With the ESHM20 now completed, we reflect on the lessons learned from implementing this new approach in regional-scale PSHA and highlight where we hope to see new developments and improvements to the characterisation of ground motion in future generations of the European Seismic Hazard Model.
    Language: English
    Type: info:eu-repo/semantics/article
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  • 49
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    5000 years of multi-proxy reconstruction based on sediment core GeoB10053-7 (2023)
    PANGAEA
    Details
    Publication Date: 2024-05-31
    Description: About 40 samples are collected from the upper 250 cm of the sediment core GeoB 10053-7 offshore Java, covering the past 5,000 years (Mohtadi et al., 2011; doi:10.1038/ngeo1209). The average sample resolution is around 120 years. Here, we use markers for low intensity fires and soil erosion to reconstruct human activities in East Java (Indonesia) over the last 5,000 years. We use the accumulation rate of branched glycerol dialkyl glycerol tetraethers (brGDGTs), markers for soil-derived organic matter, to indicate levels of soil erosion in the catchment region. We also use the accumulation rate of levoglucosan to indicate past fire use in the catchment. Independent hydroclimate reconstruction that are not influenced by human activities is compared in order to differentiate the impact of human activities vs. hydroclimate on soil erosion in the catchment area. Specifically, the stable hydrogen isotope composition (δD) of leaf wax n-alkanes reflect changes in the monsoonal rainfall intensity in the catchment. In addition, the stable carbon isotope composition (δ13C) of leaf wax n-alkanes derived from our sediment core reflects the relative abundance of regional C3 versus C4 vegetation.
    Keywords: Center for Marine Environmental Sciences; leaf waxes; levoglucosan; Marine Sediment Core; MARUM
    Type: Dataset
    Format: application/zip, 3 datasets
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    DATA PANGAEA
  • 50
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    Permafrost related measurements in the Mackenzie Delta, Northwest Territories, Canada, from the MOSES field campaign in September 2021 (2022)
    PANGAEA
    Details
    Publication Date: 2024-05-31
    Description: This collection contains permafrost related measurements in the Mackenzie Delta, NWT, Canada from the MOSES (Modular Observation Solutions for Earth Systems) field campaign in September 2021. The field campaign was focused on three subaquatic sites: a small thermokarst lake along the ITH just south of Trail Valley Creek, "Lake 3", an elongated lake with known methane occurence in the outer Mackenzie Delta, "Swiss Cheese Lake", and north and south of Tuktoyaktuk Island. At "Swiss Cheese Lake", we measured methane and CO2 concentrations in surface water and in the air above the lake, lake bed temperatures and detailed bathymetry. At "Lake 3" we measured active layer thickness on the lake banks, lake bed temperatures, and detailed bathymetry, as well as an ERT survey to estimate the talik depth below the lake. North and south of Tuktoyaktuk Island, we measured active layer thickness and sea bed temperatures and did an extensive ERT survey to obtain the depth of the subsea permafrost table. An additional passive seismic survey was carried out and the data is available at https://doi.org/10.5880/GIPP.202199.1.
    Keywords: active layer depth; AWI_PerDyn; AWI_Perma; Beaufort Sea; Modular Observation Solutions for Earth Systems; MOSES; Permafrost; Permafrost Research; Permafrost Research (Periglacial Dynamics) @ AWI; thermokarst lake; Tuktoyaktuk Island
    Type: Dataset
    Format: application/zip, 15 datasets
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    DATA PANGAEA
  • 51
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    Diatom concentrations and fluxes from marine sediment core AMD14-204_CASQ (2021)
    PANGAEA
    Details
    Publication Date: 2024-05-31
    Description: Relative contribution of the “marginal ice zone”, “drift-ice/pack-ice” and “summer subsurface” diatom indicator groups, diatom valve and Chaetoceros resting spore concentrations (valves or spores/g), diatom valve and Chaetoceros resting spore fluxes (valves or spores/unit surface area/yr), and total diatom fluxes (valves and spores/unit surface area/yr) from the marine sediment core AMD14-204 that was retrieved from the West Greenland shelf, offshore Upernavik, and which spans the last ca. 9,000 years.
    Keywords: AGE; Age, error; AMD14_1b; AMD14-204_CASQ; ArcticNet; Baffin Bay; Calculated; Calypso square corer; CASQ; CCGS Amundsen; Chaetoceros, spores, flux; Chaetoceros spp. resting spores per unit sediment mass; DEPTH, sediment/rock; diatoms; Diatoms; Diatoms, pelagic; Diatoms, sea ice; Diatoms, total, flux; Diatoms, valves, flux; Diatom valves, per unit sediment mass; Geochemistry; Highly branched isoprenoid (HBI) biomarkers
    Type: Dataset
    Format: text/tab-separated-values, 749 data points
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  • 52
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    Great Barrier Reef Atmospheric Composition Measurements during the Reef To Rainforest campaign (2024)
    PANGAEA
    Details
    Publication Date: 2024-05-31
    Description: This dataset describes a series of aerosol and meteorological measurements collected in the Great Barrier Reef (GBR) Marine Park collected during the "GBR as a significant source of climatically relevant aerosol particles" campaign, known as "Reef to Rainforest" (R2R). The data covers a broad area of the GBR marine park (-27.3091 to -16.95169 latitudinally, 145.9705 to 154.1146 longitudinally) over approximately one month, from 28th September, 2016 to 24th October, 2016. The data was collected at two sites – one aboard the Australian Government Research Vessel Investigator (RVI), and an onshore site at Garner's Beach, QLD, Australia (-17.8222S, 146.1023E). Parameters measured include particle size distribution, number concentration, composition cloud condensation nuclei (CCN) properties, concentrations of gases and markers including black carbon, radon, carbon monoxide, carbon dioxide, volatile organic compounds (VOCs), dimethylsulfide (DMS), upper air particle concentration/composition, cloud or low lying fog presence, cloud top height, depolarisation ratio, aerosol scattering and optical thickness. The observations were collected in the hope of improving our understanding of the local climate and aerosol properties, which in turn will improve local models and better inform regulatory bodies protecting the GBR.
    Keywords: aerosol; Air Chemistry; atmospheric composition; ccn; climate; clouds; Great Barrier Reef
    Type: Dataset
    Format: application/zip, 16 datasets
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    DATA PANGAEA
  • 53
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    Oxygen and carbon isotopes rom the shells of Globorotaloides hexagonus from sediment core TR163-23 (2024)
    PANGAEA
    Details
    Publication Date: 2024-05-31
    Description: Here we document the stable isotope (δ18O and δ13C) from the shells of planktic foraminifer Globorotaloides hexagonus from Eastern Equatorial Pacific core site TR163-23 (0° 24.6' N, 92° 9.6' W; 2,730 m depth). Morphometric measurements include the length of the shell along the longest dimension from the final chamber, the number of chambers in the final whorl, and porosity. Porosity was assessed by the percentage of surface area on the final chamber consisting of pores. Stable isotope analyses were carried out on pooled samples of 3-10 shells, while morphometrics were measured in individuals.
    Keywords: Carbon isotopes; Depth, bottom/max; DEPTH, sediment/rock; Depth, top/min; Eastern Equatorial Pacific; East Pacific; Foraminifera; Globorotaloides hexagonus; Globorotaloides hexagonus, δ13C; Globorotaloides hexagonus, δ18O; Oxygen isotopes; Sample code/label; TR163-23
    Type: Dataset
    Format: text/tab-separated-values, 140 data points
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    DATA PANGAEA
  • 54
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    Levoglucosan concentrations and accumulation rates of sediment core GeoB10053-7 (2023)
    PANGAEA
    Details
    Publication Date: 2024-05-31
    Keywords: Accumulation rate, levoglucosan; AGE; Calculated; Center for Marine Environmental Sciences; Comment; DEPTH, sediment/rock; GeoB10053-7; Gravity corer (Kiel type); leaf waxes; levoglucosan; Levoglucosan; Levoglucosan according to Schreuder et al. 2018; Marine Sediment Core; MARUM; PABESIA; SL; SO184/2; Sonne
    Type: Dataset
    Format: text/tab-separated-values, 95 data points
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    DATA PANGAEA
  • 55
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    Hydrobiid mudsnail image dataset: Raw stereomicroscope, processed, and segmented images of abundant brackish snails from a mesocosm experiment with multiple temperature treatments (2024)
    PANGAEA
    Details
    Publication Date: 2024-05-31
    Description: We examined the growth response of a brackish snail (Hydrobiidae) against multiple temperature treatments in a mesocosm located beside the Alfred Wegener Institute Wadden Sea Station on Sylt (55°01′19.2″N, 8°26′17.7″E). Bulk sediments were collected south of Pellworm (54° 31' 55.83"N, 8° 42' 40.36"E) at low tide on March 22, 2022, transferred to mesh-lined crates and introduced to mesocosm tanks (170 cm × 85 cm × 1800 L). Experimental warming treatments were conducted using three heaters per tank (Titanium heater 500 W, Aqua Medic, Bissendorf, Germany). The full specifications for the mesocosms are already published (Pansch et al., 2016). Throughout the experimental warming period, four sampling events (March 30, April 25, May 24, June 20) were conducted to core sediments. Sediment cores were washed and sieved (1mm mesh size) to disaggregate infauna. Individuals were separated for the common hydrobiid mudsnail, which were subsequently imaged in groups on a typical petri plate under stereomicroscopy. A semi-automatic object segmentation and size measurement approach was developed to rapidly differentiate and measure individuals from images. Segmentation was highly accurate and precise against manual length measurements (end-to-end; mm) collected in ImageJ for 4595 snails. Scaling the segmentation method across the full dataset estimated 〉40,000 snails and presented a complex species-specific response to warming. The enclosed dataset represents all raw, processed, and segmented images (n= 3201) produced by this study.
    Keywords: Computer vision; DAM sustainMare - iSeal: Trans- and interdisciplinary Social-ecological network analysis based on long-term monitoring, experimental data and stakeholders' assessment; File type; Gastropods; Identification; Image, specimens; Image, specimens (File Size); Image, specimens (MD5 Hash); Image, specimens (Media Type); Image number/name; Image segmentation; iSeal; Magnification; MESO; mesocosm experiment; Mesocosm experiment; Method comment; Object Based Image Analysis; Research Mission of the German Marine Research Alliance (DAM): Protection and sustainable use of marine areas; Resolution; Sample code/label; Sampling date/time, experiment; Stereo microscope, Nikon, SMZ18; coupled with Microscope camera, Nikon, DS-Fi3 [5.39 megapixels, LED base light with oblique coherent contrast]; sustainMare; Sylt_Mesocosm_2022; Tank number; Taxon/taxa, unique identification; Taxon/taxa, unique identification (Semantic URI); Taxon/taxa, unique identification (URI); Treatment: temperature description; Type; Type of study; Wadden Sea
    Type: Dataset
    Format: text/tab-separated-values, 44814 data points
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    DATA PANGAEA
  • 56
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    RootPainter models and outputs for Mycale lingua within image data from the Lofoten Vesterålen Ocean Observatory (2017-19) and an ROV survey of the Tisler Reef (2021) (2024)
    PANGAEA
    Details
    Publication Date: 2024-05-31
    Description: Five models were developed using RootPainter; four to detect and predict the surface area of the deep-sea sponge Mycale lingua and one to identify laser scales. Three of the sponge models were trained and applied to time-lapse images collected by the Lofoten Vesterålen Ocean Observatory. The fourth sponge model and laser model were developed and used on extracted video frames from an ROV survey of the Tisler reef. The total observatory dataset contained 18,346 images, consisting of 9,173 images each of the Mycale lingua sponges 'Magnus' and 'Mini' from 2017-2019. The total ROV video frame dataset contained 1,420 images from the East of the reef, captured in 2021.
    Keywords: automated species detection; Binary Object; Binary Object (File Size); Binary Object (Media Type); File content; iAtlantic; Integrated Assessment of Atlantic Marine Ecosystems in Space and Time; interactive machine learning; Lofoten_Vesterålen_Ocean_Observatory; Lofoten/Vesterålen; marine image analysis; Model, Rootpainter; Mycale lingua; Remote operated vehicle; RootPainter; ROV; sponge surface area; Tisler_Reef_Video_Survey; Tisler Reef, Skagerrak
    Type: Dataset
    Format: text/tab-separated-values, 8 data points
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    DATA PANGAEA
  • 57
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    Alkyl lipid distribution, elemental composition and compound-specific 14C isotope composition in marine and terrestrial sedimentary archives from sub-Antarctic South Georgia (2024)
    PANGAEA
    Details
    Publication Date: 2024-05-31
    Description: The dataset comprises elemental data, alkyl lipid data and radiocarbon (14C) data that was obtained on sediment samples from sub-Antarctic South Georgia. The sediments were collected from a range of different sites, including lakes, peat deposits, a marine inlet and a fjord during RV Polarstern expedition PS81 in 2013. Prior to the geochemical analyses reported here, the sediments were freeze-dried and ground. More details on the study sites, sampling and data evaluation can be found in Berg et al. (submitted manuscript). Total organic carbon (TOC) was analyzed with a DIMATOC 200 (DIMATEC Corp., Canada) analyser. The TOC concentration is derived from the difference between total carbon (TC) and total inorganic carbon (TIC) Total carbon (C), total nitrogen (N) and sulfur (S) were analyzed using a Vario Micro Cube combustion elemental analyser (Elementar, Germany). Alkyl lipid biomarkers were extracted by accelerated solvent extraction (ASE 300, Thermo, USA) with dichloromethane and methanol (DCM, MeOH; 9:1, v/v at 120°C, 75 bar) (cores Co1305, PS81/283, and Co1308) or via consecutive ultrasonication in DCM:Hexan (1:1), MeOH:DCM (1:1) and MeOH (core Co1306 and the peat and soil samples). The total lipid extract (TLE) was saponified with 0.5 M KOH in MeOH and water (9:1, v/v) at 80°C for 2 h. Neutral lipids (NL) were extracted from the TLE with dichloromethane by liquid-liquid phase separation. Alkanes were purified from NL by silica gel column chromatography (SiO2, deactivated, mesh-size 60) by elution with hexane and alkanols by elution with chloroform. To purify alkanoic acids, the remaining TLE was acidified to pH 1 and acids were extracted from the TLE with dichloromethane by liquid-liquid phase separation. Prior to analysis by gas chromatography (GC, Agilent 7890B, Agilent Technologies, USA) equipped with a flame ionization detector (FID), alkanols were acetylated and alkanoic acids were converted to methyl ester derivatives. Alkanes, alkanols and alkanoic acids were identified and quantified against authentic external standards. Concentrations of all reported lipid biomarkers were normalized to the TOC content of the respective sediment samples (µg/g TOC) and are given as fractional abundances for each compound class. Sediment and plant samples for Radiocarbon (14C) analysis were pre-treated and analyzed as described by Rethemeyer et al. (2019). For the analysis of 14C in bulk organic carbon (bulk OC) and plant fossils were washed with 1% HCl (1 hr, 60°C followed by ca. 10 hr at room temperature) to remove carbonates. The acid insoluble fraction was then graphitized and analyzed for 14C at the CologneAMS facility (Cologne, Germany). For compound-specific 14C analysis individual alkanoic acids, alkanes and alkanols were isolated by preparative capillary GC using a gas chromatograph (7680 Agilent Technologies, USA) equipped with a CIS 4 injection system (Gerstel, Germany), coupled with a preparative fraction collector (PFC; Gerstel, Germany). The purity and quantity of individual compounds was monitored by GC-FID (Agilent 7890B equipped with an on-column injector, Agilent Technologies, USA). Samples with a purity of 〉98% were processed further. For samples from core Co1305 compound-specific 14C analysis was performed on a MICADAS AMS system equipped with a gas ionization source (ETH Zurich, Switzerland, Wacker et al., 2010) on purified CO2 produced by combustion in vacuum-sealed quartz tubes. Compound ages were corrected for processing blanks and carbon added during derivatization using mass balance (Berg et al., 2020). For core Co1308 compound-specific 14C analysis was conducted on the original isolated compounds with a High Voltage 6 MV Tandetron coupled to an EA-GIS periphery at the CologneAMS facility (Stolz et al., 2019). Compound-specific F14C values were corrected for processing blanks and the addition of one carbon atom during derivatization using mass balance (Berg et al. 2020 and Scheidt et al., 2021). AMS results are reported as fraction modern (F14C) and conventional radiocarbon ages (yrs BP) as outlined in Stuiver & Polach (1977)
    Keywords: alkanes; alkanoic acids; alkanols; alkyl lipids; compound-specific radiocarbon analysis; Priority Programme 1158 Antarctic Research with Comparable Investigations in Arctic Sea Ice Areas; sediments; South Georgia; SPP1158
    Type: Dataset
    Format: application/zip, 5 datasets
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    DATA PANGAEA
  • 58
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    Oceanographic variability and copepod traits in two coastal ecosystems in the Southeast Pacific (2023)
    PANGAEA
    Details
    Publication Date: 2024-05-31
    Description: Temperature, salinity, and pH, along with copepod traits were measured inter-daily (i.e., on average each 4 days) in an upwelling and temperate estuary in the coastal Southeast Pacific. The purpose of the study was to evaluate the phenotypic plasticity of local copepod populations to natural extreme low pH conditions. Temperature and salinity were measured with CTD (Ocean Seven 305 Plus in the estuary system, and SeaBird SBE19 Plus in the upwelling location). Samples for pH measurements were collected with an oceanographic bottle. pH was measured potentiometrically, and calibrated with Tris buffer at 25 °C. Adult females of the copepod species Acartia tonsa (Copepoda, Calanoidea) were sampled with a WP2 plankton net. Cephalothorax length was measured under a stereomicroscope. Egg production was estimated individually over 24 h incubation.
    Keywords: Acartia tonsa, cephalotorax length; Acartia tonsa, egg production rate per female; Antofagasta_upw; Calculated; Calculated according to Vargas and González (2004); Calculated using the CO2sys_v3.0 software (Pierrot et al. 2021); Carbon, organic, particulate; Carbon chemistry; Coastal variability; copepods; CTD; CTD/Rosette; CTD-RO; DATE/TIME; Depth, bathymetric; DEPTH, water; Event label; extreme events; gene flow; Group; Habitat; Latitude of event; Longitude of event; pH; phenotypic plasticity; Salinity; Southeast Pacific; Species, unique identification; Species, unique identification (Semantic URI); Species, unique identification (URI); Stereo microscope, Leica Microsystems, EZ4 HD; Temperate and subtropical systems; Temperature, water; Valdivia_est; Year of sampling
    Type: Dataset
    Format: text/tab-separated-values, 1914 data points
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    DATA PANGAEA
  • 59
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    GDGT concentrations in ELSA stack samples of the Eifel volcanic field, Germany (2024)
    PANGAEA
    Details
    Publication Date: 2024-05-31
    Description: Isoprenoid and branched GDGTs were measured in soils and lake sediment samples from the Eifel Volcanic field. The modern samples were used to understand sources of GDGTs in sediments, while sediment core samples from Schalkenmehrener Maar, Holzmaar, and Auel Maar were used to reconstruct temperatures during the past 60,000 years. Age model information and additional proxy data from the ELSA-20 stack are found in Sirocko et al., 2021 and Sirocko et al., 2022
    Keywords: Age; AU3; AU4; Aueler Maar, Eifel, Germany; BayMBT - Bayesian calibration for the branched GDGT MBT5Me proxy; Branched glycerol dialkyl glycerol tetraether, Ia; Branched glycerol dialkyl glycerol tetraether, Ib; Branched glycerol dialkyl glycerol tetraether, Ic; Branched glycerol dialkyl glycerol tetraether, IIa; Branched glycerol dialkyl glycerol tetraether, IIa'; Branched glycerol dialkyl glycerol tetraether, IIb; Branched glycerol dialkyl glycerol tetraether, IIb'; Branched glycerol dialkyl glycerol tetraether, IIc; Branched glycerol dialkyl glycerol tetraether, IIc'; Branched glycerol dialkyl glycerol tetraether, IIIa; Branched glycerol dialkyl glycerol tetraether, IIIa'; Branched glycerol dialkyl glycerol tetraether, IIIa''; Branched glycerol dialkyl glycerol tetraether, IIIb; Branched glycerol dialkyl glycerol tetraether, IIIb'; Branched glycerol dialkyl glycerol tetraether, IIIc; Branched glycerol dialkyl glycerol tetraether, IIIc'; Cable Core Drilling; Calculated according to Raberg et al. (2021); CCD; Comment; Crenarchaeol; Crenarchaeol isomer; DEPTH, sediment/rock; Elevation of event; ELSA_AU3; ELSA_AU4; ELSA_HM3; ELSA_HM4; ELSA_SMf1; ELSA_SMf2; Europe; Event label; FRC; Freeze corer; GDGTs; High Performance Liquid Chromatography (HPLC); HM3; HM4; Isoprenoid acyclic glycerol dialkyl glycerol tetraether; Isoprenoid dicyclic glycerol dialkyl glycerol tetraether; Isoprenoid monocyclic glycerol dialkyl glycerol tetraether; Isoprenoid tricyclic glycerol dialkyl glycerol tetraether; Lacustrine-palustrine sediment; Lake Holzmaar, Eifel, Germany; Latitude of event; Longitude of event; Paleoclimate; PCUWI; Piston corer, UWITEC; Sample ID; Sample mass; Schalkenmehrener Maar, Eifel, Germany; SMf1; SMf2; Temperature, air, mean of months, above freezing
    Type: Dataset
    Format: text/tab-separated-values, 9508 data points
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    DATA PANGAEA
  • 60
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    Benthic foraminiferal abundances from eastern Baffin Bay, sediment core AMD14-204C (2020)
    PANGAEA
    Details
    Publication Date: 2024-05-31
    Description: Baffin Bay is a semi-enclosed basin connecting the Arctic Ocean and the western North Atlantic, thus making out a significant pathway for heat exchange. Here we reconstruct the alternating advection of relatively warmer and saline Atlantic waters versus the incursion of colder Arctic water masses entering Baffin Bay through the multiple gateways in the Canadian Arctic Archipelago and the Nares Strait during the Holocene. We carried out benthic foraminiferal assemblage analyses, X-ray fluorescence scanning, and radiocarbon dating of a 738 cm long marine sediment core retrieved from eastern Baffin Bay near Upernavik, Greenland (Core AMD14-204C; 987m water depth). Results reveal that eastern Baffin Bay was subjected to several oceanographic changes during the last 9.2 kyrCE1. Waning deglacial conditions with enhanced meltwater influxes and an extensive sea-ice cover prevailed in eastern Baffin Bay from 9.2 to 7.9 ka. A transition towards bottom water amelioration is recorded at 7.9 ka by increased advection of Atlantic water masses, encompassing the Holocene Thermal Maximum. A cold period with growing sea-ice cover at 6.7 ka interrupts the overall warm subsurface water conditions, promoted by a weaker northward flow of Atlantic waters. The onset of the neoglaciation at ca. 2.9 ka is marked by an abrupt transition towards a benthic fauna dominated by agglutinated species, likely in part explained by a reduction of the influx of Atlantic Water, allowing an increased influx of the cold, corrosive Baffin Bay Deep Water originating from the Arctic Ocean to enter Baffin Bay through the Nares Strait. These cold subsurface water conditions persisted throughout the Late Holocene, only interrupted by short-lived warmings superimposed on this cooling trend.
    Keywords: AGE; AMD14_1b; AMD14-204_CASQ; AMD14-204C; ArcticNet; Astrononion gallowayi; Baffin Bay; Benthic foraminifera; Bolivina pseudopunctata; Buliminella elegantissima; Calypso square corer; CASQ; Cassidulina neoteretis; Cassidulina reniforme; CCGS Amundsen; DEPTH, sediment/rock; Elphidium clavatum; Epistominella arctica; Epistominella vitrea; Foraminifera, benthic; Foraminifera, benthic agglutinated; Foraminifera, benthic atlantic species; Foraminifera, benthic calcareous; Foraminifera, planktic; Foraminifera, sea ice species; Holocene; Islandiella norcrossi; Nonionellina labradorica; Portatrochammina bipolaris; Psammosphaera fusca; Ratio; Recurvoides trochamminiformis; Reophax subfusiformis; Stainforthia feylingi; Textularia earlandi; Textularia kattegatensis; Textularia torquata
    Type: Dataset
    Format: text/tab-separated-values, 2106 data points
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    DATA PANGAEA
  • 61
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    Absorption, attenuation, scattering and backscattering inline data from the Gulf of Alaska in September 2020 (2023)
    PANGAEA
    Details
    Publication Date: 2024-05-31
    Description: The following data set contains particulate absorption, particulate attenuation, and particulate backscatter data from an optical inline system. Auxiliary data from the R/V Sikuliaq's existing underway system has also been attached, this includes standard shipboard physical oceanographic and meteorological data. The data was collected continuously during the cruises following previous work by the authors and IOCCG protocols (Burt et al., 2018 and IOCCG, 2019). The data has been binned to one-minute intervals to match with the existing underway data. The data was collected in the Northern Gulf of Alaska (NGA), as part of the expansion of the Long-Term Ecological Research (LTER) program in the Gulf. The data was collected using an ACS and BB3-eco triplet, on cruise SKQ202012s in the NGA.
    Keywords: Absorption coefficient, 402 nm; Absorption coefficient, 404 nm; Absorption coefficient, 406 nm; Absorption coefficient, 408 nm; Absorption coefficient, 410 nm; Absorption coefficient, 412 nm; Absorption coefficient, 414 nm; Absorption coefficient, 416 nm; Absorption coefficient, 418 nm; Absorption coefficient, 420 nm; Absorption coefficient, 422 nm; Absorption coefficient, 424 nm; Absorption coefficient, 426 nm; Absorption coefficient, 428 nm; Absorption coefficient, 430 nm; Absorption coefficient, 432 nm; Absorption coefficient, 434 nm; Absorption coefficient, 436 nm; Absorption coefficient, 438 nm; Absorption coefficient, 440 nm; Absorption coefficient, 442 nm; Absorption coefficient, 444 nm; Absorption coefficient, 446 nm; Absorption coefficient, 448 nm; Absorption coefficient, 450 nm; Absorption coefficient, 452 nm; Absorption coefficient, 454 nm; Absorption coefficient, 456 nm; Absorption coefficient, 458 nm; Absorption coefficient, 460 nm; Absorption coefficient, 462 nm; Absorption coefficient, 464 nm; Absorption coefficient, 466 nm; Absorption coefficient, 468 nm; Absorption coefficient, 470 nm; Absorption coefficient, 472 nm; Absorption coefficient, 474 nm; Absorption coefficient, 476 nm; Absorption coefficient, 478 nm; Absorption coefficient, 480 nm; Absorption coefficient, 482 nm; Absorption coefficient, 484 nm; Absorption coefficient, 486 nm; Absorption coefficient, 488 nm; Absorption coefficient, 490 nm; Absorption coefficient, 492 nm; Absorption coefficient, 494 nm; Absorption coefficient, 496 nm; Absorption coefficient, 498 nm; Absorption coefficient, 500 nm; Absorption coefficient, 502 nm; Absorption coefficient, 504 nm; Absorption coefficient, 506 nm; Absorption coefficient, 508 nm; Absorption coefficient, 510 nm; Absorption coefficient, 512 nm; Absorption coefficient, 514 nm; Absorption coefficient, 516 nm; Absorption coefficient, 518 nm; Absorption coefficient, 520 nm; Absorption coefficient, 522 nm; Absorption coefficient, 524 nm; Absorption coefficient, 526 nm; Absorption coefficient, 528 nm; Absorption coefficient, 530 nm; Absorption coefficient, 532 nm; Absorption coefficient, 534 nm; Absorption coefficient, 536 nm; Absorption coefficient, 538 nm; Absorption coefficient, 540 nm; Absorption coefficient, 542 nm; Absorption coefficient, 544 nm; Absorption coefficient, 546 nm; Absorption coefficient, 548 nm; Absorption coefficient, 550 nm; Absorption coefficient, 552 nm; Absorption coefficient, 554 nm; Absorption coefficient, 556 nm; Absorption coefficient, 558 nm; Absorption coefficient, 560 nm; Absorption coefficient, 562 nm; Absorption coefficient, 564 nm; Absorption coefficient, 566 nm; Absorption coefficient, 568 nm; Absorption coefficient, 570 nm; Absorption coefficient, 572 nm; Absorption coefficient, 574 nm; Absorption coefficient, 576 nm; Absorption coefficient, 578 nm; Absorption coefficient, 580 nm; Absorption coefficient, 582 nm; Absorption coefficient, 584 nm; Absorption coefficient, 586 nm; Absorption coefficient, 588 nm; Absorption coefficient, 590 nm; Absorption coefficient, 592 nm; Absorption coefficient, 594 nm; Absorption coefficient, 596 nm; Absorption coefficient, 598 nm; Absorption coefficient, 600 nm; Absorption coefficient, 602 nm; Absorption coefficient, 604 nm; Absorption coefficient, 606 nm; Absorption coefficient, 608 nm; Absorption coefficient, 610 nm; Absorption coefficient, 612 nm; Absorption coefficient, 614 nm; Absorption coefficient, 616 nm; Absorption coefficient, 618 nm; Absorption coefficient, 620 nm; Absorption coefficient, 622 nm; Absorption coefficient, 624 nm; Absorption coefficient, 626 nm; Absorption coefficient, 628 nm; Absorption coefficient, 630 nm; Absorption coefficient, 632 nm; Absorption coefficient, 634 nm; Absorption coefficient, 636 nm; Absorption coefficient, 638 nm; Absorption coefficient, 640 nm; Absorption coefficient, 642 nm; Absorption coefficient, 644 nm; Absorption coefficient, 646 nm; Absorption coefficient, 648 nm; Absorption coefficient, 650 nm; Absorption coefficient, 652 nm; Absorption coefficient, 654 nm; Absorption coefficient, 656 nm; Absorption coefficient, 658 nm; Absorption coefficient, 660 nm; Absorption coefficient, 662 nm; Absorption coefficient, 664 nm; Absorption coefficient, 666 nm; Absorption coefficient, 668 nm; Absorption coefficient, 670 nm; Absorption coefficient, 672 nm; Absorption coefficient, 674 nm; Absorption coefficient, 676 nm; Absorption coefficient, 678 nm; Absorption coefficient, 680 nm; Absorption coefficient, 682 nm; Absorption coefficient, 684 nm; Absorption coefficient, 686 nm; Absorption coefficient, 688 nm; Absorption coefficient, 690 nm; Absorption coefficient, 692 nm; Absorption coefficient, 694 nm; Absorption coefficient, 696 nm; Absorption coefficient, 698 nm; Absorption coefficient, 700 nm; Absorption coefficient, 702 nm; Absorption coefficient, 704 nm; Absorption coefficient, 706 nm; Absorption coefficient, 708 nm; Absorption coefficient, 710 nm; Absorption coefficient, 712 nm; Absorption coefficient, 714 nm; Absorption coefficient, 716 nm; Absorption coefficient, 718 nm; Absorption coefficient, 720 nm; Absorption coefficient, 722 nm; Absorption coefficient, 724 nm; Absorption coefficient, 726 nm; Absorption coefficient, 728 nm; Absorption coefficient, 730 nm; Absorption coefficient, 732 nm; Absorption coefficient, 734 nm; Absorption coefficient, 736 nm; Absorption coefficient, 738 nm; According to Graff et al. (2015); ACS; Attenuation coefficient, 402 nm; Attenuation coefficient, 404 nm; Attenuation coefficient, 406 nm; Attenuation coefficient, 408 nm; Attenuation coefficient, 410 nm; Attenuation coefficient, 412 nm; Attenuation coefficient, 414 nm; Attenuation coefficient, 416 nm; Attenuation coefficient, 418 nm; Attenuation coefficient, 420 nm; Attenuation coefficient, 422 nm; Attenuation coefficient, 424 nm; Attenuation coefficient, 426 nm; Attenuation coefficient, 428 nm; Attenuation coefficient, 430 nm; Attenuation coefficient, 432 nm; Attenuation coefficient, 434 nm; Attenuation coefficient, 436 nm; Attenuation coefficient, 438 nm; Attenuation coefficient, 440 nm; Attenuation coefficient, 442 nm; Attenuation coefficient, 444 nm; Attenuation coefficient, 446 nm; Attenuation coefficient, 448 nm; Attenuation coefficient, 450 nm; Attenuation coefficient, 452 nm; Attenuation coefficient, 454 nm; Attenuation coefficient, 456 nm; Attenuation coefficient, 458 nm; Attenuation coefficient, 460 nm; Attenuation coefficient, 462 nm; Attenuation coefficient, 464 nm; Attenuation coefficient, 466 nm; Attenuation coefficient, 468 nm; Attenuation coefficient, 470 nm; Attenuation coefficient, 472 nm; Attenuation coefficient, 474 nm; Attenuation coefficient, 476 nm; Attenuation coefficient, 478 nm; Attenuation coefficient, 480 nm; Attenuation coefficient, 482 nm; Attenuation coefficient, 484 nm; Attenuation coefficient, 486 nm; Attenuation coefficient, 488 nm; Attenuation coefficient, 490 nm; Attenuation coefficient, 492 nm; Attenuation coefficient, 494 nm; Attenuation coefficient, 496 nm; Attenuation coefficient, 498 nm; Attenuation coefficient, 500 nm; Attenuation coefficient, 502 nm; Attenuation coefficient, 504 nm; Attenuation coefficient, 506 nm; Attenuation coefficient, 508 nm; Attenuation coefficient, 510 nm; Attenuation coefficient, 512 nm; Attenuation coefficient, 514 nm; Attenuation coefficient, 516 nm; Attenuation coefficient, 518 nm; Attenuation coefficient, 520 nm; Attenuation coefficient, 522 nm; Attenuation coefficient, 524 nm; Attenuation coefficient, 526 nm; Attenuation coefficient, 528 nm; Attenuation coefficient, 530 nm; Attenuation coefficient, 532 nm; Attenuation coefficient, 534 nm; Attenuation coefficient, 536 nm; Attenuation coefficient, 538 nm; Attenuation coefficient, 540 nm; Attenuation coefficient, 542 nm; Attenuation coefficient, 544 nm; Attenuation coefficient, 546 nm; Attenuation coefficient, 548 nm; Attenuation coefficient, 550 nm; Attenuation coefficient, 552 nm; Attenuation coefficient, 554 nm; Attenuation
    Type: Dataset
    Format: text/tab-separated-values, 3646149 data points
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  • 62
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    Absorption, attenuation, scattering and backscattering inline data from the Gulf of Alaska in June/July 2021 (2023)
    PANGAEA
    Details
    Publication Date: 2024-05-31
    Description: The following data set contains particulate absorption, particulate attenuation, and particulate backscatter data from an optical inline system. Auxiliary data from the R/V Sikuliaq's existing underway system has also been attached, this includes standard shipboard physical oceanographic and meteorological data. The data was collected continuously during the cruises following previous work by the authors and IOCCG protocols (Burt et al., 2018 and IOCCG, 2019). The data has been binned to one-minute intervals to match with the existing underway data. The data was collected in the Northern Gulf of Alaska (NGA), as part of the expansion of the Long-Term Ecological Research (LTER) program in the Gulf. The data was collected using an ACS and BB3-eco triplet, on cruise SKQ202110s in the NGA.
    Keywords: Absorption coefficient, 402 nm; Absorption coefficient, 404 nm; Absorption coefficient, 406 nm; Absorption coefficient, 408 nm; Absorption coefficient, 410 nm; Absorption coefficient, 412 nm; Absorption coefficient, 414 nm; Absorption coefficient, 416 nm; Absorption coefficient, 418 nm; Absorption coefficient, 420 nm; Absorption coefficient, 422 nm; Absorption coefficient, 424 nm; Absorption coefficient, 426 nm; Absorption coefficient, 428 nm; Absorption coefficient, 430 nm; Absorption coefficient, 432 nm; Absorption coefficient, 434 nm; Absorption coefficient, 436 nm; Absorption coefficient, 438 nm; Absorption coefficient, 440 nm; Absorption coefficient, 442 nm; Absorption coefficient, 444 nm; Absorption coefficient, 446 nm; Absorption coefficient, 448 nm; Absorption coefficient, 450 nm; Absorption coefficient, 452 nm; Absorption coefficient, 454 nm; Absorption coefficient, 456 nm; Absorption coefficient, 458 nm; Absorption coefficient, 460 nm; Absorption coefficient, 462 nm; Absorption coefficient, 464 nm; Absorption coefficient, 466 nm; Absorption coefficient, 468 nm; Absorption coefficient, 470 nm; Absorption coefficient, 472 nm; Absorption coefficient, 474 nm; Absorption coefficient, 476 nm; Absorption coefficient, 478 nm; Absorption coefficient, 480 nm; Absorption coefficient, 482 nm; Absorption coefficient, 484 nm; Absorption coefficient, 486 nm; Absorption coefficient, 488 nm; Absorption coefficient, 490 nm; Absorption coefficient, 492 nm; Absorption coefficient, 494 nm; Absorption coefficient, 496 nm; Absorption coefficient, 498 nm; Absorption coefficient, 500 nm; Absorption coefficient, 502 nm; Absorption coefficient, 504 nm; Absorption coefficient, 506 nm; Absorption coefficient, 508 nm; Absorption coefficient, 510 nm; Absorption coefficient, 512 nm; Absorption coefficient, 514 nm; Absorption coefficient, 516 nm; Absorption coefficient, 518 nm; Absorption coefficient, 520 nm; Absorption coefficient, 522 nm; Absorption coefficient, 524 nm; Absorption coefficient, 526 nm; Absorption coefficient, 528 nm; Absorption coefficient, 530 nm; Absorption coefficient, 532 nm; Absorption coefficient, 534 nm; Absorption coefficient, 536 nm; Absorption coefficient, 538 nm; Absorption coefficient, 540 nm; Absorption coefficient, 542 nm; Absorption coefficient, 544 nm; Absorption coefficient, 546 nm; Absorption coefficient, 548 nm; Absorption coefficient, 550 nm; Absorption coefficient, 552 nm; Absorption coefficient, 554 nm; Absorption coefficient, 556 nm; Absorption coefficient, 558 nm; Absorption coefficient, 560 nm; Absorption coefficient, 562 nm; Absorption coefficient, 564 nm; Absorption coefficient, 566 nm; Absorption coefficient, 568 nm; Absorption coefficient, 570 nm; Absorption coefficient, 572 nm; Absorption coefficient, 574 nm; Absorption coefficient, 576 nm; Absorption coefficient, 578 nm; Absorption coefficient, 580 nm; Absorption coefficient, 582 nm; Absorption coefficient, 584 nm; Absorption coefficient, 586 nm; Absorption coefficient, 588 nm; Absorption coefficient, 590 nm; Absorption coefficient, 592 nm; Absorption coefficient, 594 nm; Absorption coefficient, 596 nm; Absorption coefficient, 598 nm; Absorption coefficient, 600 nm; Absorption coefficient, 602 nm; Absorption coefficient, 604 nm; Absorption coefficient, 606 nm; Absorption coefficient, 608 nm; Absorption coefficient, 610 nm; Absorption coefficient, 612 nm; Absorption coefficient, 614 nm; Absorption coefficient, 616 nm; Absorption coefficient, 618 nm; Absorption coefficient, 620 nm; Absorption coefficient, 622 nm; Absorption coefficient, 624 nm; Absorption coefficient, 626 nm; Absorption coefficient, 628 nm; Absorption coefficient, 630 nm; Absorption coefficient, 632 nm; Absorption coefficient, 634 nm; Absorption coefficient, 636 nm; Absorption coefficient, 638 nm; Absorption coefficient, 640 nm; Absorption coefficient, 642 nm; Absorption coefficient, 644 nm; Absorption coefficient, 646 nm; Absorption coefficient, 648 nm; Absorption coefficient, 650 nm; Absorption coefficient, 652 nm; Absorption coefficient, 654 nm; Absorption coefficient, 656 nm; Absorption coefficient, 658 nm; Absorption coefficient, 660 nm; Absorption coefficient, 662 nm; Absorption coefficient, 664 nm; Absorption coefficient, 666 nm; Absorption coefficient, 668 nm; Absorption coefficient, 670 nm; Absorption coefficient, 672 nm; Absorption coefficient, 674 nm; Absorption coefficient, 676 nm; Absorption coefficient, 678 nm; Absorption coefficient, 680 nm; Absorption coefficient, 682 nm; Absorption coefficient, 684 nm; Absorption coefficient, 686 nm; Absorption coefficient, 688 nm; Absorption coefficient, 690 nm; Absorption coefficient, 692 nm; Absorption coefficient, 694 nm; Absorption coefficient, 696 nm; Absorption coefficient, 698 nm; Absorption coefficient, 700 nm; Absorption coefficient, 702 nm; Absorption coefficient, 704 nm; Absorption coefficient, 706 nm; Absorption coefficient, 708 nm; Absorption coefficient, 710 nm; Absorption coefficient, 712 nm; Absorption coefficient, 714 nm; Absorption coefficient, 716 nm; Absorption coefficient, 718 nm; Absorption coefficient, 720 nm; Absorption coefficient, 722 nm; Absorption coefficient, 724 nm; Absorption coefficient, 726 nm; Absorption coefficient, 728 nm; Absorption coefficient, 730 nm; Absorption coefficient, 732 nm; Absorption coefficient, 734 nm; Absorption coefficient, 736 nm; Absorption coefficient, 738 nm; According to Graff et al. (2015); ACS; Attenuation coefficient, 402 nm; Attenuation coefficient, 404 nm; Attenuation coefficient, 406 nm; Attenuation coefficient, 408 nm; Attenuation coefficient, 410 nm; Attenuation coefficient, 412 nm; Attenuation coefficient, 414 nm; Attenuation coefficient, 416 nm; Attenuation coefficient, 418 nm; Attenuation coefficient, 420 nm; Attenuation coefficient, 422 nm; Attenuation coefficient, 424 nm; Attenuation coefficient, 426 nm; Attenuation coefficient, 428 nm; Attenuation coefficient, 430 nm; Attenuation coefficient, 432 nm; Attenuation coefficient, 434 nm; Attenuation coefficient, 436 nm; Attenuation coefficient, 438 nm; Attenuation coefficient, 440 nm; Attenuation coefficient, 442 nm; Attenuation coefficient, 444 nm; Attenuation coefficient, 446 nm; Attenuation coefficient, 448 nm; Attenuation coefficient, 450 nm; Attenuation coefficient, 452 nm; Attenuation coefficient, 454 nm; Attenuation coefficient, 456 nm; Attenuation coefficient, 458 nm; Attenuation coefficient, 460 nm; Attenuation coefficient, 462 nm; Attenuation coefficient, 464 nm; Attenuation coefficient, 466 nm; Attenuation coefficient, 468 nm; Attenuation coefficient, 470 nm; Attenuation coefficient, 472 nm; Attenuation coefficient, 474 nm; Attenuation coefficient, 476 nm; Attenuation coefficient, 478 nm; Attenuation coefficient, 480 nm; Attenuation coefficient, 482 nm; Attenuation coefficient, 484 nm; Attenuation coefficient, 486 nm; Attenuation coefficient, 488 nm; Attenuation coefficient, 490 nm; Attenuation coefficient, 492 nm; Attenuation coefficient, 494 nm; Attenuation coefficient, 496 nm; Attenuation coefficient, 498 nm; Attenuation coefficient, 500 nm; Attenuation coefficient, 502 nm; Attenuation coefficient, 504 nm; Attenuation coefficient, 506 nm; Attenuation coefficient, 508 nm; Attenuation coefficient, 510 nm; Attenuation coefficient, 512 nm; Attenuation coefficient, 514 nm; Attenuation coefficient, 516 nm; Attenuation coefficient, 518 nm; Attenuation coefficient, 520 nm; Attenuation coefficient, 522 nm; Attenuation coefficient, 524 nm; Attenuation coefficient, 526 nm; Attenuation coefficient, 528 nm; Attenuation coefficient, 530 nm; Attenuation coefficient, 532 nm; Attenuation coefficient, 534 nm; Attenuation coefficient, 536 nm; Attenuation coefficient, 538 nm; Attenuation coefficient, 540 nm; Attenuation coefficient, 542 nm; Attenuation coefficient, 544 nm; Attenuation coefficient, 546 nm; Attenuation coefficient, 548 nm; Attenuation coefficient, 550 nm; Attenuation coefficient, 552 nm; Attenuation coefficient, 554 nm; Attenuation
    Type: Dataset
    Format: text/tab-separated-values, 5313583 data points
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  • 63
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    Master track of HEINCKE cruise HE635 in 1 sec resolution (zipped, 50 MB) (2024)
    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Details
    Publication Date: 2024-05-31
    Description: Raw data acquired by position sensors on board RV Heincke during expedition HE635 were processed to receive a validated master track which can be used as reference of further expedition data. During HE635 the inertial navigation system IXSEA PHINS III and the GPS receivers Trimble Marine SPS461 and SAAB R5 SUPREME NAV were used as navigation sensors. Data were downloaded from DAVIS SHIP data base (https://dship.awi.de) with a resolution of 1 sec. Processed data are provided as a master track with 1 sec resolution derived from the position sensors' data selected by priority and a generalized track with a reduced set of the most significant positions of the master track.
    Keywords: 1 sec resolution; CT; HE635; HE635-track; Heincke; MecoMM-NS II; North Sea; Underway cruise track measurements
    Type: Dataset
    Format: application/zip, 50.1 MBytes
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  • 64
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    Nickel toxicity to the dinoflagellate Amphidinium carterae, the coccolithophore Emiliania huxleyi, the diatom Thalassiosira weissflogii during laboratory experiments in 2021 (2023)
    PANGAEA
    Details
    Publication Date: 2024-05-31
    Description: In laboratory culture experiments, phytoplankton species were exposed to a range of nickel concentrations at GEOMAR Helmholtz Centre for Ocean Research Kiel. The experiments were perfomed between Feburary and August 2021. Overall, three experiments were conducted, each with a different taxonomical species (the dinoflagellate Amphidinium carterae, the coccolithophore Emiliania huxleyi and the diatom Thalassiosira weissflogii). Cells were acclimated to experiment conditions for at least 1 week (under salinity 33, 18˚C, 12:12 light and dark cycle). Throughout the experiment cell density was recorded with BD Accuri C6 Flow Cytometer. After the experiment, nickel concentration was measured with ThermoFisher Scientific ElementXR. The study was supported by the OCEAN-ALK-ALIGN project funded by the Carbon to Sea and the Thistledown Foundation.
    Keywords: Amphidinium carterae; CDRmare; Cell density; Comment; DAM CDRmare - RETAKE: CO2 removal by alkalinity enhancement: potential, benefits and risks; Day; Dilution factor; Emiliania huxleyi; Flow cytometer, BD Biosciences, BD Accuri C6; Inductively coupled plasma mass spectrometer (ICP-MS), ThermoFisher Scientific, Element XR; Laboratory experiment; nickel; Nickel; ocean alkalinity enhancement; Phytoplankton; Phytoplankton, forward scatter; Phytoplankton, red fluorescence; Replicate; Research Mission of the German Marine Research Alliance (DAM): Marine carbon sinks in decarbonisation pathways; RETAKE; Sample volume; Sampling date/time, experiment; Species, unique identification; Species, unique identification (Semantic URI); Species, unique identification (URI); Thalassiosira weissflogii; toxicity; Treatment: nickel; Type of study
    Type: Dataset
    Format: text/tab-separated-values, 6613 data points
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  • 65
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    GDGTs in modern soils and lake sediments, Eifel volcanic field, Germany (2024)
    PANGAEA
    Details
    Publication Date: 2024-05-31
    Description: Isoprenoid and branched GDGTs were measured in soils and lake sediment samples from the Eifel Volcanic field. The modern samples were used to understand sources of GDGTs in sediments, while sediment core samples from Schalkenmehrener Maar, Holzmaar, and Auel Maar were used to reconstruct temperatures during the past 60,000 years. Age model information and additional proxy data from the ELSA-20 stack are found in Sirocko et al., 2021 and Sirocko et al., 2022
    Keywords: BayMBT - Bayesian calibration for the branched GDGT MBT5Me proxy; Branched glycerol dialkyl glycerol tetraether, Ia; Branched glycerol dialkyl glycerol tetraether, Ib; Branched glycerol dialkyl glycerol tetraether, Ic; Branched glycerol dialkyl glycerol tetraether, IIa; Branched glycerol dialkyl glycerol tetraether, IIa'; Branched glycerol dialkyl glycerol tetraether, IIb; Branched glycerol dialkyl glycerol tetraether, IIb'; Branched glycerol dialkyl glycerol tetraether, IIc; Branched glycerol dialkyl glycerol tetraether, IIc'; Branched glycerol dialkyl glycerol tetraether, IIIa; Branched glycerol dialkyl glycerol tetraether, IIIa'; Branched glycerol dialkyl glycerol tetraether, IIIa''; Branched glycerol dialkyl glycerol tetraether, IIIb; Branched glycerol dialkyl glycerol tetraether, IIIb'; Branched glycerol dialkyl glycerol tetraether, IIIc; Branched glycerol dialkyl glycerol tetraether, IIIc'; Calculated according to Raberg et al. (2021); Crenarchaeol; Crenarchaeol isomer; DEPTH, sediment/rock; Elevation of event; ELSA_GMF; ELSA_HM3; ELSA_SMf1; ELSA_SMf2; Europe; Event label; FRC; Freeze corer; GDGTs; Gemündener Maar, Eifel, Germany; GM_soil; High Performance Liquid Chromatography (HPLC); HM_soil; HM_surface; HM3; Isoprenoid acyclic glycerol dialkyl glycerol tetraether; Isoprenoid dicyclic glycerol dialkyl glycerol tetraether; Isoprenoid monocyclic glycerol dialkyl glycerol tetraether; Isoprenoid tricyclic glycerol dialkyl glycerol tetraether; Lacustrine-palustrine sediment; Lake, water depth; Lake Holzmaar, Eifel, Germany; Latitude of event; Longitude of event; Paleoclimate; PCUWI; Piston corer, UWITEC; Sample ID; Sample mass; Sample type; Schalkenmehrener Maar, Eifel, Germany; Sediment Grabber; SGRAB; Site; SM_soil; SM_surface; SMf1; SMf2; SOILS; Soil sample; Temperature, air, mean of months, above freezing; Weinfelder Maar, Eifel, Germany; WM_soil
    Type: Dataset
    Format: text/tab-separated-values, 1424 data points
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  • 66
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    A global database of dissolved organic matter (DOM) concentration measurements in coastal waters (CoastDOM v.1) (2023)
    PANGAEA
    Details
    Publication Date: 2024-05-31
    Description: This global database (CoastDOM v.1) contains both previously published and unpublished measurements of Dissolved organic carbon (DOC), nitrogen (DON) and phosphorus (DOP) in coastal waters. The dataset also contains hydrographic data such as temperature and salinity and, to the extent possible, other biogeochemical variables (e.g., Chlorophyll-a, inorganic nutrients) and the inorganic carbon system (e.g., dissolved inorganic carbon and total alkalinity). The data included were collected from 1978 to 2022 and consist of 62339 data points for DOC, 20360 for DON and 13440 for DOP.
    Keywords: Alkalinity, total; Ammonium; Analytical method; Carbon, inorganic, dissolved; Carbon, organic, dissolved; Carbon, organic, particulate; Chlorophyll a; Coastal waters; Comment; DATE/TIME; DEPTH, water; Dissolved Organic Carbon; Dissolved Organic Matter; dissolved organic nitrogen; dissolved organic phosphorus; ELEVATION; global database;; Hydrogen phosphate; Institution; LATITUDE; Location; LONGITUDE; Nitrate and Nitrite; Nitrogen, organic, dissolved; Nitrogen, particulate; Nitrogen, total dissolved; Phosphorus, organic, dissolved; Phosphorus, particulate; Phosphorus, total dissolved; Principal investigator; Quality flag, alkalinity, total; Quality flag, ammonium; Quality flag, carbon, inorganic, dissolved; Quality flag, carbon, organic, dissolved; Quality flag, carbon, organic, particulate; Quality flag, chlorophyll a; Quality flag, hydrogen phosphate; Quality flag, nitrate and nitrite; Quality flag, nitrogen, particulate; Quality flag, nitrogen, total dissolved; Quality flag, phosphorus, particulate; Quality flag, phosphorus, total dissolved; Reference/source; Salinity; Sample ID; Suspended solids, total; Temperature, water; World Oceans Circulation Experiment (WOCE) quality flags according to Jiang et al. (2022)
    Type: Dataset
    Format: text/tab-separated-values, 1286555 data points
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  • 67
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    Porosity profiles of sediments in Atacama Trench and adjacent abyssal plains (2024)
    PANGAEA
    Details
    Publication Date: 2024-05-31
    Description: Sediment cores were recovered by multiple corers. Upon recovery, sediment cores were brought to a thermoregulated room kept at in situ temperature, here sediment cores were sectioned in predefinded sediment horizons and frozen for later analysis. On land, the frozen sediment was thawn and homogenized. Water contents of the respective samples were determined as the weight loss after 24 h at 105°C and wet density from the weight of a given sample volume. Porosity was calculated from the two measured parameters.
    Keywords: Atacama Trench; B_LANDER; Bottom lander; Calculated from weight loss after drying; Date/Time of event; Deep sea; Depth, bottom/max; DEPTH, sediment/rock; Depth, top/min; Elevation of event; Event label; Hadal trench; Latitude of event; Longitude of event; porosity; Porosity; sediment; Site; SO261; SO261_101-1; SO261_111-1; SO261_16-1; SO261_29-1; SO261_4-1; SO261_43-1; SO261_58-1; SO261_69-1; SO261_84-1; Sonne_2
    Type: Dataset
    Format: text/tab-separated-values, 536 data points
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  • 68
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    Oxygen microprofiles measured in situ in sediments of Atacama Trench and adjacent abyssal plains (2024)
    PANGAEA
    Details
    Publication Date: 2024-05-31
    Description: Oxygen microprofiles were measured using an autonomous benthic lander system. Once the lander had stabilized at the seabed, an array of O2 microelectrodes was vertically moved across the sediment-water interface at a predefined resolution - measurements were recorded at each depth after a delay of a few seconds. When the array had reached the maximum measuring depth, sensors were retracted to the start position, and the array was moved horizontally before the measuring routine was repeated (Glud et al. 2021). Sensor signals were converted into O2 concentrations using a linear calibration curve that was based on measurements in the bottom water of known O2 concentration and measurements in the anoxic sediment layers.
    Keywords: B_LANDER; Bottom lander; Clark type electrochemical Oxygen microsensor; Date/Time of event; Deep sea; DEPTH, sediment/rock; Elevation of event; Event label; Hadal trench; Latitude of event; Longitude of event; microsensor; Microsensor concentration profiles; Oxygen; Profile; sediment; Site; SO261; SO261_101-1; SO261_111-1; SO261_16-1; SO261_29-1; SO261_4-1; SO261_43-1; SO261_58-1; SO261_69-1; SO261_84-1; Sonne_2
    Type: Dataset
    Format: text/tab-separated-values, 322278 data points
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  • 69
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    Porosity profiles of sediments in Kermadec Trench and adjacent abyssal plains (2024)
    PANGAEA
    Details
    Publication Date: 2024-05-31
    Description: Sediment cores were recovered by multiple corer or boxcorer. Upon recovery, sediment cores were brought to a thermoregulated room kept at in situ temperature, here sediment cores were sectioned in predefinded sediment horizons and frozen for later analysis. On land, the frozen sediment was thawn and homogenized. Water contents of the respective samples were determined as the weight loss after 24 h at 105°C and wet density from the weight of a given sample volume. Porosity was calculated from the two measured parameters.
    Keywords: BC; Box corer; Calculated from weight loss after drying; Date/Time of event; Deep sea; Depth, bottom/max; DEPTH, sediment/rock; Depth, top/min; Elevation of event; Event label; Hadal trench; Kermadec trench; Kermadec Trench; Latitude of event; Longitude of event; MUC; MultiCorer; porosity; Porosity; sediment; Site; Site K3; Site K4; Site K5; TAN1711; TAN1711_K3; TAN1711_K4-1; TAN1711_K5-1; TAN1711_K6; TAN1711_K7; Tangaroa
    Type: Dataset
    Format: text/tab-separated-values, 208 data points
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  • 70
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    Oxygen microprofiles measured in situ in sediments of Kermadec Trench and adjacent abyssal plains (2024)
    PANGAEA
    Details
    Publication Date: 2024-05-31
    Description: Oxygen microprofiles were measured using an autonomous benthic lander system. Once the lander had stabilized at the seabed, an array of O2 microelectrodes was vertically moved across the sediment-water interface at a predefined resolution - measurements were recorded at each depth after a delay of a few seconds. When the array had reached the maximum measuring depth, sensors were retracted to the start position, and the array was moved horizontally before the measuring routine was repeated (Glud et al. 2021). Sensor signals were converted into O2 concentrations using a linear calibration curve that was based on measurements in the bottom water of known O2 concentration and measurements in the anoxic sediment layers.
    Keywords: B_LANDER; Bottom lander; Clark type electrochemical Oxygen microsensor; Date/Time of event; Deep sea; DEPTH, sediment/rock; Elevation of event; Event label; HADAL; Hadal lander; Hadal trench; Kermadec trench; Kermadec Trench; Latitude of event; Longitude of event; microsensor; Microsensor concentration profiles; Oxygen; Profile; sediment; Site; Site K2; Site K3; Site K5; Site K6; Site K7; TAN1711; TAN1711_K2-1; TAN1711_K3-1; TAN1711_K4; TAN1711_K5-3; TAN1711_K6-1; TAN1711_K7-1; Tangaroa
    Type: Dataset
    Format: text/tab-separated-values, 77559 data points
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  • 71
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    Magnetic susceptibility and calcium carbonate content at the IODP site 320-U1334 (2024)
    PANGAEA
    Details
    Publication Date: 2024-05-31
    Description: These dataset contains data from Integrated Ocean Drilling Program Site U1334, which is correlated in the depth domain to Site 1218 before ages were assigned. Site U1334 Depth (adjusted revised CCSF-A) (armcd), Site 1218 Depth (armcd), Age (ka) (CaCO3 tuned age model), Magnetic Susceptibility (sensor values), and Estimated CaCO3 content (wt%). These data are based on Westerhold et al. (2012), and on Beddow et al. (2018).
    Keywords: 320-U1334; Age, dated; Calcium carbonate; COMPCORE; Composite Core; Depth, composite revised, adjusted; Event label; Exp320; Expedition 320; Integrated Ocean Drilling Program / International Ocean Discovery Program; IODP; IODP 320; Joides Resolution; Magnetic susceptibility; Pacific Equatorial Age Transect I; Pacific Ocean; PFAR; Planktonic foraminifera; Site U1334
    Type: Dataset
    Format: text/tab-separated-values, 6275 data points
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  • 72
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    Planktonic foraminifera counts and their oxygen and carbon isotopes at the IODP site 320-U1334 (2024)
    PANGAEA
    Details
    Publication Date: 2024-05-31
    Description: This dataset contains data from Integrated Ocean Drilling Program Site U1334, which is correlated in the depth domain to Site 1218 before ages were assigned. The dataset contains sample information (Expedition, Site, Hole, etc.), depth (for both Sites U1334 and 1218) and age information (i.e., Site U1334 Depth (CSF-A) (mbsf), Site U1334 Depth (revised CCSF-A) (rmcd), Site U1334 Depth (adjusted revised CCSF-A) (armcd), Site 1218 Depth (armcd) Age (ka) (CaCO3 tuned age model)), planktonic foraminiferal oxygen and carbon isotopes, and the necessary information to compute planktonic foraminiferal accumulation rates.
    Keywords: 320-U1334; Age, dated; Cibicidoides mundulus, δ13C; Cibicidoides mundulus, δ18O; COMPCORE; Composite Core; Core; Cruise/expedition; Density, dry bulk; Dentoglobigerina venezuelana; Dentoglobigerina venezuelana, δ13C; Dentoglobigerina venezuelana, δ18O; Depth, composite revised; Depth, composite revised, adjusted; Depth, section; DEPTH, sediment/rock; DSDP/ODP/IODP sample designation; Event label; Exp320; Expedition 320; Globigerinoides altiapertura; Globigerinoides altiapertura, δ13C; Globigerinoides altiapertura, δ18O; Globigerinoides primordius; Globigerinoides primordius, δ13C; Globigerinoides primordius, δ18O; Hole; Integrated Ocean Drilling Program / International Ocean Discovery Program; IODP; IODP 320; Joides Resolution; Oridorsalis umbonatus, δ13C; Oridorsalis umbonatus, δ18O; Pacific Equatorial Age Transect I; Pacific Ocean; Paragloborotalia siakensis; Paragloborotalia siakensis, δ13C; Paragloborotalia siakensis, δ18O; PFAR; Planktonic foraminifera; Sample code/label; Sample mass; Section; Site; Site U1334; Type
    Type: Dataset
    Format: text/tab-separated-values, 15551 data points
    Location Call Number Expected Availability
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  • 73
    facet.materialart.
    Unknown
    Seawater analysis from cruise KH-14-6 in the western South Pacific Ocean along the GEOTRACES transect GP19 (2023)
    PANGAEA
    Details
    Publication Date: 2024-05-31
    Description: This data contains the basic hydrological parameters, including temperature, salinity, potential density anomaly, potential temperature, dissolved oxygen, silicate, nitrate, phosphate, and chlorophyll-a concentrations, dissolved (d) Cd, dNi, dZn, dCu, dFe and labile particulate (lp) Fe concentrations in the western South Pacific Ocean along the GEOTRACES transect GP19 (~170°W, 64°S - equator). Seawater samples were collected using a clean CTD (Conductivity, Temperature, and Depth) sampling system with Niskin-X bottles during the Japanese GEOTRACES cruise KH-14-6 onboard the research vessel Hakuho Maru from December 2, 2014 to February 26, 2015. Filtered samples for the determination of dissolved trace metals (dMs) were passed through an AcroPak cartridge filter with a 0.8/0.2 µm pore size (Pall Life Sciences) and were transferred to 250-mL low-density polyethylene (LDPE) bottles (Nalgene). Samples for the determination of total dissolvable trace metals (tdMs) were not filtered. The seawater samples were acidified to pH ~2 with ultrapure HCl (Tamapure AA-10, Tama Chemicals) immediately after collection and were stored at room temperature in the laboratory for several years until analysis. An offline automated solid-phase extraction system (SPE-100, Hiranuma Sangyo) equipped with a column of Nobias Chelate-PA1 resin (Hitachi High-Technologies) was used to preconcentrate the trace metals (Al, Mn, Fe, Co, Ni, Cu, Zn, Cd, and Pb) in seawater (Minami et al., 2015; doi:10.1016/j.aca.2014.11.016). Unfiltered samples were first passed through a 0.45-µm pore size Millex syringe filter (Merck Millipore) and then introduced into the SPE-100 system. The labile particulate metal (lpMs) concentrations were calculated as the difference between tdMs and dMs. Trace metal concentrations were determined using a high-resolution inductively coupled plasma mass spectrometer (HR-ICP-MS, Element 2, Thermo Fisher Scientific) using the calibration curve method. Temperature was measured using a CTD sensor. Salinity was determined using a bench salinometer that was standardized based on the IAPSO standard seawater, and the oxygen content was measured using the Winkler method. Nutrient concentrations were determined by spectrophotometry using an automated analyzer onboard the vessel. Chlorophyll a (Chl. a) was collected on a 25-mm Whatman GF/F glass fiber filter and measured by fluorometry. Samples were collected using a clean CTD (Conductivity, Temperature, and Depth) sampling system with Niskin-X bottles (Sohrin and Bruland, 2011). Filtered samples for dMs determination were passed through an AcroPak cartridge filter with a 0.8/0.2-µm pore size (Pall Life Sciences) by the pressure of compressed air and were transferred to 250-mL low-density polyethylene (LDPE) bottles (Nalgene). Samples for tdMs determination were not filtered and were transferred from Niskin-X bottles to 250-mL LDPE bottles using a silicon tube. Filtered and unfiltered samples were placed in a cleanroom (Class 100) and acidified with 20% HCl (Tamapure AA-10, Tama Chemicals, Japan) to a pH of 1.9–2.0 within 24 h of sample collection.
    Keywords: Alkalinity, total; Cadmium, dissolved; Cadmium, dissolved, total; Cadmium, labile particulate; Chlorophyll a; Copper, dissolved; Copper, dissolved, total; Copper, labile particulate; Cruise/expedition; CTD; Date/Time of event; dCd concentration; dCu concentration; Density, potential anomaly; DEPTH, water; dFe concentration; dNi concentration; dZn concentration; Elevation of event; Event label; GEOTRACES; GF/F WHA1825047, Whatman, UK; Global marine biogeochemical cycles of trace elements and their isotopes; HR-ICP-MS, Thermo Finnigan Element 2; Iron, dissolved; Iron, dissolved, total; Iron, labile particulate; JSPS KAKENHI; KAKENHI; KH-14-6_GR04_B; KH-14-6_GR05_B; KH-14-6_GR06_B; KH-14-6_GR07_B; KH-14-6_GR08_B; KH-14-6_GR09_B; KH-14-6_GR10_B; KH-14-6_GR11_B; KH-14-6_GR12_B; KH-14-6_GR13_B; KH-14-6_GR14_B; KH-14-6_GR15_B; KH-14-6_GR16_B; KH-14-6_GR17_B; KH-14-6_GR18_B; KH-14-6_GR19_B; KH-14-6_GR20_B; KH-14-6_GR21_B; labile particulate Fe concentration; Latitude of event; Longitude of event; Nickel, dissolved; Nickel, dissolved, total; Nitrate; Nitrite; Oxygen; pH; Phosphate; Salinity; SALINO; Salinometer; scavenging; Silicon; South Pacific Ocean; SPEC; Spectrophotometer; Station label; supply from the Fiji basins; Temperature, water; Temperature, water, potential; the western South Pacific Ocean; Titration, Winkler; Type; Zinc, dissolved; Zinc, dissolved, total; Zinc, labile particulate
    Type: Dataset
    Format: text/tab-separated-values, 9572 data points
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  • 74
    facet.materialart.
    Unknown
    Absorption, attenuation, scattering and backscattering inline data from the Gulf of Alaska in April/May 2021 (2023)
    PANGAEA
    Details
    Publication Date: 2024-05-31
    Description: The following data set contains particulate absorption, particulate attenuation, and particulate backscatter data from an optical inline system. Auxiliary data from the R/V Sikuliaq's existing underway system has also been attached, this includes standard shipboard physical oceanographic and meteorological data. The data was collected continuously during the cruises following previous work by the authors and IOCCG protocols (Burt et al., 2018 and IOCCG, 2019). The data has been binned to one-minute intervals to match with the existing underway data. The data was collected in the Northern Gulf of Alaska (NGA), as part of the expansion of the Long-Term Ecological Research (LTER) program in the Gulf. The data was collected using an ACS and BB3-eco triplet, on cruise SKQ202106s in the NGA.
    Keywords: Absorption coefficient, 402 nm; Absorption coefficient, 404 nm; Absorption coefficient, 406 nm; Absorption coefficient, 408 nm; Absorption coefficient, 410 nm; Absorption coefficient, 412 nm; Absorption coefficient, 414 nm; Absorption coefficient, 416 nm; Absorption coefficient, 418 nm; Absorption coefficient, 420 nm; Absorption coefficient, 422 nm; Absorption coefficient, 424 nm; Absorption coefficient, 426 nm; Absorption coefficient, 428 nm; Absorption coefficient, 430 nm; Absorption coefficient, 432 nm; Absorption coefficient, 434 nm; Absorption coefficient, 436 nm; Absorption coefficient, 438 nm; Absorption coefficient, 440 nm; Absorption coefficient, 442 nm; Absorption coefficient, 444 nm; Absorption coefficient, 446 nm; Absorption coefficient, 448 nm; Absorption coefficient, 450 nm; Absorption coefficient, 452 nm; Absorption coefficient, 454 nm; Absorption coefficient, 456 nm; Absorption coefficient, 458 nm; Absorption coefficient, 460 nm; Absorption coefficient, 462 nm; Absorption coefficient, 464 nm; Absorption coefficient, 466 nm; Absorption coefficient, 468 nm; Absorption coefficient, 470 nm; Absorption coefficient, 472 nm; Absorption coefficient, 474 nm; Absorption coefficient, 476 nm; Absorption coefficient, 478 nm; Absorption coefficient, 480 nm; Absorption coefficient, 482 nm; Absorption coefficient, 484 nm; Absorption coefficient, 486 nm; Absorption coefficient, 488 nm; Absorption coefficient, 490 nm; Absorption coefficient, 492 nm; Absorption coefficient, 494 nm; Absorption coefficient, 496 nm; Absorption coefficient, 498 nm; Absorption coefficient, 500 nm; Absorption coefficient, 502 nm; Absorption coefficient, 504 nm; Absorption coefficient, 506 nm; Absorption coefficient, 508 nm; Absorption coefficient, 510 nm; Absorption coefficient, 512 nm; Absorption coefficient, 514 nm; Absorption coefficient, 516 nm; Absorption coefficient, 518 nm; Absorption coefficient, 520 nm; Absorption coefficient, 522 nm; Absorption coefficient, 524 nm; Absorption coefficient, 526 nm; Absorption coefficient, 528 nm; Absorption coefficient, 530 nm; Absorption coefficient, 532 nm; Absorption coefficient, 534 nm; Absorption coefficient, 536 nm; Absorption coefficient, 538 nm; Absorption coefficient, 540 nm; Absorption coefficient, 542 nm; Absorption coefficient, 544 nm; Absorption coefficient, 546 nm; Absorption coefficient, 548 nm; Absorption coefficient, 550 nm; Absorption coefficient, 552 nm; Absorption coefficient, 554 nm; Absorption coefficient, 556 nm; Absorption coefficient, 558 nm; Absorption coefficient, 560 nm; Absorption coefficient, 562 nm; Absorption coefficient, 564 nm; Absorption coefficient, 566 nm; Absorption coefficient, 568 nm; Absorption coefficient, 570 nm; Absorption coefficient, 572 nm; Absorption coefficient, 574 nm; Absorption coefficient, 576 nm; Absorption coefficient, 578 nm; Absorption coefficient, 580 nm; Absorption coefficient, 582 nm; Absorption coefficient, 584 nm; Absorption coefficient, 586 nm; Absorption coefficient, 588 nm; Absorption coefficient, 590 nm; Absorption coefficient, 592 nm; Absorption coefficient, 594 nm; Absorption coefficient, 596 nm; Absorption coefficient, 598 nm; Absorption coefficient, 600 nm; Absorption coefficient, 602 nm; Absorption coefficient, 604 nm; Absorption coefficient, 606 nm; Absorption coefficient, 608 nm; Absorption coefficient, 610 nm; Absorption coefficient, 612 nm; Absorption coefficient, 614 nm; Absorption coefficient, 616 nm; Absorption coefficient, 618 nm; Absorption coefficient, 620 nm; Absorption coefficient, 622 nm; Absorption coefficient, 624 nm; Absorption coefficient, 626 nm; Absorption coefficient, 628 nm; Absorption coefficient, 630 nm; Absorption coefficient, 632 nm; Absorption coefficient, 634 nm; Absorption coefficient, 636 nm; Absorption coefficient, 638 nm; Absorption coefficient, 640 nm; Absorption coefficient, 642 nm; Absorption coefficient, 644 nm; Absorption coefficient, 646 nm; Absorption coefficient, 648 nm; Absorption coefficient, 650 nm; Absorption coefficient, 652 nm; Absorption coefficient, 654 nm; Absorption coefficient, 656 nm; Absorption coefficient, 658 nm; Absorption coefficient, 660 nm; Absorption coefficient, 662 nm; Absorption coefficient, 664 nm; Absorption coefficient, 666 nm; Absorption coefficient, 668 nm; Absorption coefficient, 670 nm; Absorption coefficient, 672 nm; Absorption coefficient, 674 nm; Absorption coefficient, 676 nm; Absorption coefficient, 678 nm; Absorption coefficient, 680 nm; Absorption coefficient, 682 nm; Absorption coefficient, 684 nm; Absorption coefficient, 686 nm; Absorption coefficient, 688 nm; Absorption coefficient, 690 nm; Absorption coefficient, 692 nm; Absorption coefficient, 694 nm; Absorption coefficient, 696 nm; Absorption coefficient, 698 nm; Absorption coefficient, 700 nm; Absorption coefficient, 702 nm; Absorption coefficient, 704 nm; Absorption coefficient, 706 nm; Absorption coefficient, 708 nm; Absorption coefficient, 710 nm; Absorption coefficient, 712 nm; Absorption coefficient, 714 nm; Absorption coefficient, 716 nm; Absorption coefficient, 718 nm; Absorption coefficient, 720 nm; Absorption coefficient, 722 nm; Absorption coefficient, 724 nm; Absorption coefficient, 726 nm; Absorption coefficient, 728 nm; Absorption coefficient, 730 nm; Absorption coefficient, 732 nm; Absorption coefficient, 734 nm; Absorption coefficient, 736 nm; Absorption coefficient, 738 nm; According to Graff et al. (2015); ACS; Attenuation coefficient, 402 nm; Attenuation coefficient, 404 nm; Attenuation coefficient, 406 nm; Attenuation coefficient, 408 nm; Attenuation coefficient, 410 nm; Attenuation coefficient, 412 nm; Attenuation coefficient, 414 nm; Attenuation coefficient, 416 nm; Attenuation coefficient, 418 nm; Attenuation coefficient, 420 nm; Attenuation coefficient, 422 nm; Attenuation coefficient, 424 nm; Attenuation coefficient, 426 nm; Attenuation coefficient, 428 nm; Attenuation coefficient, 430 nm; Attenuation coefficient, 432 nm; Attenuation coefficient, 434 nm; Attenuation coefficient, 436 nm; Attenuation coefficient, 438 nm; Attenuation coefficient, 440 nm; Attenuation coefficient, 442 nm; Attenuation coefficient, 444 nm; Attenuation coefficient, 446 nm; Attenuation coefficient, 448 nm; Attenuation coefficient, 450 nm; Attenuation coefficient, 452 nm; Attenuation coefficient, 454 nm; Attenuation coefficient, 456 nm; Attenuation coefficient, 458 nm; Attenuation coefficient, 460 nm; Attenuation coefficient, 462 nm; Attenuation coefficient, 464 nm; Attenuation coefficient, 466 nm; Attenuation coefficient, 468 nm; Attenuation coefficient, 470 nm; Attenuation coefficient, 472 nm; Attenuation coefficient, 474 nm; Attenuation coefficient, 476 nm; Attenuation coefficient, 478 nm; Attenuation coefficient, 480 nm; Attenuation coefficient, 482 nm; Attenuation coefficient, 484 nm; Attenuation coefficient, 486 nm; Attenuation coefficient, 488 nm; Attenuation coefficient, 490 nm; Attenuation coefficient, 492 nm; Attenuation coefficient, 494 nm; Attenuation coefficient, 496 nm; Attenuation coefficient, 498 nm; Attenuation coefficient, 500 nm; Attenuation coefficient, 502 nm; Attenuation coefficient, 504 nm; Attenuation coefficient, 506 nm; Attenuation coefficient, 508 nm; Attenuation coefficient, 510 nm; Attenuation coefficient, 512 nm; Attenuation coefficient, 514 nm; Attenuation coefficient, 516 nm; Attenuation coefficient, 518 nm; Attenuation coefficient, 520 nm; Attenuation coefficient, 522 nm; Attenuation coefficient, 524 nm; Attenuation coefficient, 526 nm; Attenuation coefficient, 528 nm; Attenuation coefficient, 530 nm; Attenuation coefficient, 532 nm; Attenuation coefficient, 534 nm; Attenuation coefficient, 536 nm; Attenuation coefficient, 538 nm; Attenuation coefficient, 540 nm; Attenuation coefficient, 542 nm; Attenuation coefficient, 544 nm; Attenuation coefficient, 546 nm; Attenuation coefficient, 548 nm; Attenuation coefficient, 550 nm; Attenuation coefficient, 552 nm; Attenuation coefficient, 554 nm; Attenuation
    Type: Dataset
    Format: text/tab-separated-values, 6012074 data points
    Location Call Number Expected Availability
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  • 75
    facet.materialart.
    Unknown
    Absorption, attenuation, scattering and backscattering inline data from the Gulf of Alaska in July 2020 (2023)
    PANGAEA
    Details
    Publication Date: 2024-05-31
    Description: The following data set contains particulate absorption, particulate attenuation, and particulate backscatter data from an optical inline system. Auxiliary data from the R/V Sikuliaq's existing underway system has also been attached, this includes standard shipboard physical oceanographic and meteorological data. The data was collected continuously during the cruises following previous work by the authors and IOCCG protocols (Burt et al., 2018 and IOCCG, 2019). The data has been binned to one-minute intervals to match with the existing underway data. The data was collected in the Northern Gulf of Alaska (NGA), as part of the expansion of the Long-Term Ecological Research (LTER) program in the Gulf. The data was collected using an ACS and BB3-eco triplet, on cruise SKQ202010s in the NGA.
    Keywords: Absorption coefficient, 402 nm; Absorption coefficient, 404 nm; Absorption coefficient, 406 nm; Absorption coefficient, 408 nm; Absorption coefficient, 410 nm; Absorption coefficient, 412 nm; Absorption coefficient, 414 nm; Absorption coefficient, 416 nm; Absorption coefficient, 418 nm; Absorption coefficient, 420 nm; Absorption coefficient, 422 nm; Absorption coefficient, 424 nm; Absorption coefficient, 426 nm; Absorption coefficient, 428 nm; Absorption coefficient, 430 nm; Absorption coefficient, 432 nm; Absorption coefficient, 434 nm; Absorption coefficient, 436 nm; Absorption coefficient, 438 nm; Absorption coefficient, 440 nm; Absorption coefficient, 442 nm; Absorption coefficient, 444 nm; Absorption coefficient, 446 nm; Absorption coefficient, 448 nm; Absorption coefficient, 450 nm; Absorption coefficient, 452 nm; Absorption coefficient, 454 nm; Absorption coefficient, 456 nm; Absorption coefficient, 458 nm; Absorption coefficient, 460 nm; Absorption coefficient, 462 nm; Absorption coefficient, 464 nm; Absorption coefficient, 466 nm; Absorption coefficient, 468 nm; Absorption coefficient, 470 nm; Absorption coefficient, 472 nm; Absorption coefficient, 474 nm; Absorption coefficient, 476 nm; Absorption coefficient, 478 nm; Absorption coefficient, 480 nm; Absorption coefficient, 482 nm; Absorption coefficient, 484 nm; Absorption coefficient, 486 nm; Absorption coefficient, 488 nm; Absorption coefficient, 490 nm; Absorption coefficient, 492 nm; Absorption coefficient, 494 nm; Absorption coefficient, 496 nm; Absorption coefficient, 498 nm; Absorption coefficient, 500 nm; Absorption coefficient, 502 nm; Absorption coefficient, 504 nm; Absorption coefficient, 506 nm; Absorption coefficient, 508 nm; Absorption coefficient, 510 nm; Absorption coefficient, 512 nm; Absorption coefficient, 514 nm; Absorption coefficient, 516 nm; Absorption coefficient, 518 nm; Absorption coefficient, 520 nm; Absorption coefficient, 522 nm; Absorption coefficient, 524 nm; Absorption coefficient, 526 nm; Absorption coefficient, 528 nm; Absorption coefficient, 530 nm; Absorption coefficient, 532 nm; Absorption coefficient, 534 nm; Absorption coefficient, 536 nm; Absorption coefficient, 538 nm; Absorption coefficient, 540 nm; Absorption coefficient, 542 nm; Absorption coefficient, 544 nm; Absorption coefficient, 546 nm; Absorption coefficient, 548 nm; Absorption coefficient, 550 nm; Absorption coefficient, 552 nm; Absorption coefficient, 554 nm; Absorption coefficient, 556 nm; Absorption coefficient, 558 nm; Absorption coefficient, 560 nm; Absorption coefficient, 562 nm; Absorption coefficient, 564 nm; Absorption coefficient, 566 nm; Absorption coefficient, 568 nm; Absorption coefficient, 570 nm; Absorption coefficient, 572 nm; Absorption coefficient, 574 nm; Absorption coefficient, 576 nm; Absorption coefficient, 578 nm; Absorption coefficient, 580 nm; Absorption coefficient, 582 nm; Absorption coefficient, 584 nm; Absorption coefficient, 586 nm; Absorption coefficient, 588 nm; Absorption coefficient, 590 nm; Absorption coefficient, 592 nm; Absorption coefficient, 594 nm; Absorption coefficient, 596 nm; Absorption coefficient, 598 nm; Absorption coefficient, 600 nm; Absorption coefficient, 602 nm; Absorption coefficient, 604 nm; Absorption coefficient, 606 nm; Absorption coefficient, 608 nm; Absorption coefficient, 610 nm; Absorption coefficient, 612 nm; Absorption coefficient, 614 nm; Absorption coefficient, 616 nm; Absorption coefficient, 618 nm; Absorption coefficient, 620 nm; Absorption coefficient, 622 nm; Absorption coefficient, 624 nm; Absorption coefficient, 626 nm; Absorption coefficient, 628 nm; Absorption coefficient, 630 nm; Absorption coefficient, 632 nm; Absorption coefficient, 634 nm; Absorption coefficient, 636 nm; Absorption coefficient, 638 nm; Absorption coefficient, 640 nm; Absorption coefficient, 642 nm; Absorption coefficient, 644 nm; Absorption coefficient, 646 nm; Absorption coefficient, 648 nm; Absorption coefficient, 650 nm; Absorption coefficient, 652 nm; Absorption coefficient, 654 nm; Absorption coefficient, 656 nm; Absorption coefficient, 658 nm; Absorption coefficient, 660 nm; Absorption coefficient, 662 nm; Absorption coefficient, 664 nm; Absorption coefficient, 666 nm; Absorption coefficient, 668 nm; Absorption coefficient, 670 nm; Absorption coefficient, 672 nm; Absorption coefficient, 674 nm; Absorption coefficient, 676 nm; Absorption coefficient, 678 nm; Absorption coefficient, 680 nm; Absorption coefficient, 682 nm; Absorption coefficient, 684 nm; Absorption coefficient, 686 nm; Absorption coefficient, 688 nm; Absorption coefficient, 690 nm; Absorption coefficient, 692 nm; Absorption coefficient, 694 nm; Absorption coefficient, 696 nm; Absorption coefficient, 698 nm; Absorption coefficient, 700 nm; Absorption coefficient, 702 nm; Absorption coefficient, 704 nm; Absorption coefficient, 706 nm; Absorption coefficient, 708 nm; Absorption coefficient, 710 nm; Absorption coefficient, 712 nm; Absorption coefficient, 714 nm; Absorption coefficient, 716 nm; Absorption coefficient, 718 nm; Absorption coefficient, 720 nm; Absorption coefficient, 722 nm; Absorption coefficient, 724 nm; Absorption coefficient, 726 nm; Absorption coefficient, 728 nm; Absorption coefficient, 730 nm; Absorption coefficient, 732 nm; Absorption coefficient, 734 nm; Absorption coefficient, 736 nm; Absorption coefficient, 738 nm; According to Graff et al. (2015); ACS; Attenuation coefficient, 402 nm; Attenuation coefficient, 404 nm; Attenuation coefficient, 406 nm; Attenuation coefficient, 408 nm; Attenuation coefficient, 410 nm; Attenuation coefficient, 412 nm; Attenuation coefficient, 414 nm; Attenuation coefficient, 416 nm; Attenuation coefficient, 418 nm; Attenuation coefficient, 420 nm; Attenuation coefficient, 422 nm; Attenuation coefficient, 424 nm; Attenuation coefficient, 426 nm; Attenuation coefficient, 428 nm; Attenuation coefficient, 430 nm; Attenuation coefficient, 432 nm; Attenuation coefficient, 434 nm; Attenuation coefficient, 436 nm; Attenuation coefficient, 438 nm; Attenuation coefficient, 440 nm; Attenuation coefficient, 442 nm; Attenuation coefficient, 444 nm; Attenuation coefficient, 446 nm; Attenuation coefficient, 448 nm; Attenuation coefficient, 450 nm; Attenuation coefficient, 452 nm; Attenuation coefficient, 454 nm; Attenuation coefficient, 456 nm; Attenuation coefficient, 458 nm; Attenuation coefficient, 460 nm; Attenuation coefficient, 462 nm; Attenuation coefficient, 464 nm; Attenuation coefficient, 466 nm; Attenuation coefficient, 468 nm; Attenuation coefficient, 470 nm; Attenuation coefficient, 472 nm; Attenuation coefficient, 474 nm; Attenuation coefficient, 476 nm; Attenuation coefficient, 478 nm; Attenuation coefficient, 480 nm; Attenuation coefficient, 482 nm; Attenuation coefficient, 484 nm; Attenuation coefficient, 486 nm; Attenuation coefficient, 488 nm; Attenuation coefficient, 490 nm; Attenuation coefficient, 492 nm; Attenuation coefficient, 494 nm; Attenuation coefficient, 496 nm; Attenuation coefficient, 498 nm; Attenuation coefficient, 500 nm; Attenuation coefficient, 502 nm; Attenuation coefficient, 504 nm; Attenuation coefficient, 506 nm; Attenuation coefficient, 508 nm; Attenuation coefficient, 510 nm; Attenuation coefficient, 512 nm; Attenuation coefficient, 514 nm; Attenuation coefficient, 516 nm; Attenuation coefficient, 518 nm; Attenuation coefficient, 520 nm; Attenuation coefficient, 522 nm; Attenuation coefficient, 524 nm; Attenuation coefficient, 526 nm; Attenuation coefficient, 528 nm; Attenuation coefficient, 530 nm; Attenuation coefficient, 532 nm; Attenuation coefficient, 534 nm; Attenuation coefficient, 536 nm; Attenuation coefficient, 538 nm; Attenuation coefficient, 540 nm; Attenuation coefficient, 542 nm; Attenuation coefficient, 544 nm; Attenuation coefficient, 546 nm; Attenuation coefficient, 548 nm; Attenuation coefficient, 550 nm; Attenuation coefficient, 552 nm; Attenuation coefficient, 554 nm; Attenuation
    Type: Dataset
    Format: text/tab-separated-values, 5697133 data points
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  • 76
    facet.materialart.
    Unknown
    Master tracks in different resolutions of HEINCKE cruise HE635, Bremerhaven - Bremerhaven, 2024-03-08 - 2024-03-22 (2024)
    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Details
    Publication Date: 2024-05-31
    Description: Raw data acquired by position sensors on board RV Heincke during expedition HE635 were processed to receive a validated master track which can be used as reference of further expedition data. During HE635 the inertial navigation system IXSEA PHINS III and the GPS receivers Trimble Marine SPS461 and SAAB R5 SUPREME NAV were used as navigation sensors. Data were downloaded from DAVIS SHIP data base (https://dship.awi.de) with a resolution of 1 sec. Processed data are provided as a master track with 1 sec resolution derived from the position sensors' data selected by priority and a generalized track with a reduced set of the most significant positions of the master track.
    Keywords: Calculated; Course; CT; DATE/TIME; HE635; HE635-track; Heincke; LATITUDE; LONGITUDE; MecoMM-NS II; North Sea; Speed; Underway cruise track measurements
    Type: Dataset
    Format: text/tab-separated-values, 3866 data points
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  • 77
    facet.materialart.
    Unknown
    Basic and other measurements of radiation at station Tateno (2020-05) (2020)
    PANGAEA
    In:  Aerological Observatory, Japan Meteorological Agency
    Details
    Publication Date: 2024-05-31
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, maximum; Diffuse radiation, minimum; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, maximum; Direct radiation, minimum; Direct radiation, standard deviation; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; Japan; Long-wave downward radiation; Long-wave downward radiation, maximum; Long-wave downward radiation, minimum; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Long-wave upward radiation, maximum; Long-wave upward radiation, minimum; Long-wave upward radiation, standard deviation; Monitoring station; MONS; Pyranometer, Kipp & Zonen, CMP21, SN 090229, WRMC No. 16035; Pyranometer, Kipp & Zonen, CMP21, SN 100363, WRMC No. 16036; Pyranometer, Kipp & Zonen, CMP22, SN 090099, WRMC No. 16037; Pyrgeometer, Kipp & Zonen, CGR4, SN 090133, WRMC No. 16038; Pyrgeometer, Kipp & Zonen, CGR4, SN 090166, WRMC No. 16039; Pyrheliometer, Kipp & Zonen, CHP 1, SN 090140, WRMC No. 16034; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, maximum; Short-wave downward (GLOBAL) radiation, minimum; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Short-wave upward (REFLEX) radiation, maximum; Short-wave upward (REFLEX) radiation, minimum; Short-wave upward (REFLEX) radiation, standard deviation; Station pressure; TAT; Tateno; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 1073592 data points
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  • 78
    facet.materialart.
    Unknown
    Distance between ROV and sea ice at the ROV station ODEN_AO2018_819-1 (2020)
    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Details
    Publication Date: 2024-05-31
    Description: Along with the radiation measurements, ROV positions were obtained from acoustic LBL (Long BaseLine)-positioning and all parameters of vehicle depth, distance to the ice and attitude recorded. All times are given in UTC.
    Keywords: Arctic Ocean; Arctic Ocean 2018, MOCCHA; DATE/TIME; Distance, relative, X; Distance, relative, Y; Distance to sea ice bottom; Oden; Oden_AO2018; Oden_AO2018_819-1; Remote operated vehicle; ROV
    Type: Dataset
    Format: text/tab-separated-values, 13740 data points
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  • 79
    facet.materialart.
    Unknown
    Distance between ROV and sea ice at the ROV station ODEN_AO2018_828-1 (2020)
    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Details
    Publication Date: 2024-05-31
    Description: Along with the radiation measurements, ROV positions were obtained from acoustic LBL (Long BaseLine)-positioning and all parameters of vehicle depth, distance to the ice and attitude recorded. All times are given in UTC.
    Keywords: Arctic Ocean; Arctic Ocean 2018, MOCCHA; DATE/TIME; Distance, relative, X; Distance, relative, Y; Distance to sea ice bottom; Oden; Oden_AO2018; Oden_AO2018_828-1; Remote operated vehicle; ROV
    Type: Dataset
    Format: text/tab-separated-values, 16491 data points
    Location Call Number Expected Availability
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  • 80
    facet.materialart.
    Unknown
    Basic and other measurements of radiation at station Tateno (2019-10) (2020)
    PANGAEA
    In:  Aerological Observatory, Japan Meteorological Agency
    Details
    Publication Date: 2024-05-31
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, maximum; Diffuse radiation, minimum; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, maximum; Direct radiation, minimum; Direct radiation, standard deviation; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; Japan; Long-wave downward radiation; Long-wave downward radiation, maximum; Long-wave downward radiation, minimum; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Long-wave upward radiation, maximum; Long-wave upward radiation, minimum; Long-wave upward radiation, standard deviation; Monitoring station; MONS; Pyranometer, Kipp & Zonen, CMP21, SN 090229, WRMC No. 16035; Pyranometer, Kipp & Zonen, CMP21, SN 100363, WRMC No. 16036; Pyranometer, Kipp & Zonen, CMP22, SN 090099, WRMC No. 16037; Pyrgeometer, Kipp & Zonen, CGR4, SN 090133, WRMC No. 16038; Pyrgeometer, Kipp & Zonen, CGR4, SN 090166, WRMC No. 16039; Pyrheliometer, Kipp & Zonen, CHP 1, SN 090140, WRMC No. 16034; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, maximum; Short-wave downward (GLOBAL) radiation, minimum; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Short-wave upward (REFLEX) radiation, maximum; Short-wave upward (REFLEX) radiation, minimum; Short-wave upward (REFLEX) radiation, standard deviation; Station pressure; TAT; Tateno; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 1073592 data points
    Location Call Number Expected Availability
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  • 81
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    Diatom analyses of IODP Site 341-U1421 (2020)
    PANGAEA
    Details
    Publication Date: 2024-05-31
    Keywords: -; 341-U1421A; 341-U1421C; Accumulation rate, diatoms; Actinocyclus curvatulus; Actinocyclus ochotensis; Actinoptychus spp.; AGE; Area; Asteromphalus spp.; Azpeitia neocrenulata; Azpeitia tabularis; Bacterosira constricta, resting spores; Bathyomphalus contortus; Chaetoceros morphogenera: Dispinodiscus; Chaetoceros morphogenera: Gemellodiscus; Chaetoceros morphogenera: hyaline variety; Chaetoceros morphogenera: Liradiscus; Chaetoceros morphogenera: Peripteropsis; Chaetoceros morphogenera: Syndendrium; Chaetoceros morphogenera: Vallodiscus; Chaetoceros morphogenera: Xanthodiscus; Chaetoceros spp.; Cocconeis costata; Cocconeis spp.; Cordilleran Ice Sheet; Coscinodiscus marginatus; Coscinodiscus oculus-iridis; Coscinodiscus radiatus; deglacial; Density, dry bulk; Depth, bottom/max; Depth, composite; Depth, composite bottom; Depth, composite top; Depth, top/min; Detonula confervacea; Diatoms; Diatoms, centrales; Diatoms, centrales indeterminata; Diatoms, naviculoid pennales; Diatoms, pennales; Diatoms, pennales indeterminata; Diatoms, sea ice; Diploneis spp.; DRILL; Drilling/drill rig; Ehrenbergina spp.; Event label; Exp341; Fossula arctica; Fragilariopsis atlantica; Fragilariopsis cylindrus; Fragilariopsis doliolus; Fragilariopsis nana; Fragilariopsis oceanica; Fragilariopsis pseudonana; Fragilariopsis reginae-jahniae; Gulf of Alaska; Integrated Ocean Drilling Program / International Ocean Discovery Program; IODP; Joides Resolution; Length; LGM; Lindavia spp.; Lioloma pacificum; Melosira sol; Neodenticula seminae; Nitzschia spp.; Odontella aurita; Paralia sulcata; Porosira glacialis; Proboscia eumorpha; Proboscia subarctica; Rhaphoneis spp.; Rhizosolenia borealis; Rhizosolenia hebetata; Rhizosolenia hebetata forma semispina; Rhizosolenia setigera; Rhizosolenia styliformis; Sample code/label; Sample code/label 2; Sample resolution; Sedimentation rate; Shionodiscus oestrupii; Shionodiscus trifultus; Slide; Southern Alaska Margin: Tectonics, Climate and Sedimentation; Stellarima stellaris; Stephanopyxis turris; Synedropsis spp.; Thalassionema nitzschioides; Thalassiosira aestivalis; Thalassiosira angulata; Thalassiosira anguste-lineata; Thalassiosira antarctica; Thalassiosira antarctica, resting spores; Thalassiosira baltica; Thalassiosira binata; Thalassiosira bulbosa; Thalassiosira decipiens; Thalassiosira eccentrica; Thalassiosira gravida; Thalassiosira hispida; Thalassiosira hyalina; Thalassiosira jouseae; Thalassiosira kushirensis; Thalassiosira kushirensis, resting spores; Thalassiosira leptopus; Thalassiosira lineata; Thalassiosira nordenskioeldii; Thalassiosira pacifica; Thalassiosira sp.; Thalassiosira spp.; Thalassiosira symmetrica; Thalassiosira tenera; Thalassiothrix longissima; Transect length; Transect width
    Type: Dataset
    Format: text/tab-separated-values, 3933 data points
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  • 82
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    Basic and other measurements of radiation at station Tateno (2020-07) (2020)
    PANGAEA
    In:  Aerological Observatory, Japan Meteorological Agency
    Details
    Publication Date: 2024-05-31
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, maximum; Diffuse radiation, minimum; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, maximum; Direct radiation, minimum; Direct radiation, standard deviation; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; Japan; Long-wave downward radiation; Long-wave downward radiation, maximum; Long-wave downward radiation, minimum; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Long-wave upward radiation, maximum; Long-wave upward radiation, minimum; Long-wave upward radiation, standard deviation; Monitoring station; MONS; Pyranometer, Kipp & Zonen, CMP21, SN 090229, WRMC No. 16035; Pyranometer, Kipp & Zonen, CMP21, SN 191191, WRMC No. 16044; Pyranometer, Kipp & Zonen, CMP22, SN 090099, WRMC No. 16037; Pyrgeometer, Kipp & Zonen, CGR4, SN 090133, WRMC No. 16038; Pyrgeometer, Kipp & Zonen, CGR4, SN 090166, WRMC No. 16039; Pyrheliometer, Kipp & Zonen, CHP 1, SN 090140, WRMC No. 16034; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, maximum; Short-wave downward (GLOBAL) radiation, minimum; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Short-wave upward (REFLEX) radiation, maximum; Short-wave upward (REFLEX) radiation, minimum; Short-wave upward (REFLEX) radiation, standard deviation; Station pressure; TAT; Tateno; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 1073592 data points
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  • 83
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    Unknown
    Distance between ROV and sea ice at the ROV station ODEN_AO2018_822-1 (2020)
    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Details
    Publication Date: 2024-05-31
    Description: Along with the radiation measurements, ROV positions were obtained from acoustic LBL (Long BaseLine)-positioning and all parameters of vehicle depth, distance to the ice and attitude recorded. All times are given in UTC.
    Keywords: Arctic Ocean; Arctic Ocean 2018, MOCCHA; DATE/TIME; Distance, relative, X; Distance, relative, Y; Distance to sea ice bottom; Oden; Oden_AO2018; Oden_AO2018_822-1; Remote operated vehicle; ROV
    Type: Dataset
    Format: text/tab-separated-values, 5811 data points
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  • 84
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    Unknown
    Basic and other measurements of radiation at station Tateno (2019-12) (2020)
    PANGAEA
    In:  Aerological Observatory, Japan Meteorological Agency
    Details
    Publication Date: 2024-05-31
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, maximum; Diffuse radiation, minimum; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, maximum; Direct radiation, minimum; Direct radiation, standard deviation; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; Japan; Long-wave downward radiation; Long-wave downward radiation, maximum; Long-wave downward radiation, minimum; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Long-wave upward radiation, maximum; Long-wave upward radiation, minimum; Long-wave upward radiation, standard deviation; Monitoring station; MONS; Pyranometer, Kipp & Zonen, CMP21, SN 090229, WRMC No. 16035; Pyranometer, Kipp & Zonen, CMP21, SN 100363, WRMC No. 16036; Pyranometer, Kipp & Zonen, CMP22, SN 090099, WRMC No. 16037; Pyrgeometer, Kipp & Zonen, CGR4, SN 090133, WRMC No. 16038; Pyrgeometer, Kipp & Zonen, CGR4, SN 090166, WRMC No. 16039; Pyrheliometer, Kipp & Zonen, CHP 1, SN 090140, WRMC No. 16034; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, maximum; Short-wave downward (GLOBAL) radiation, minimum; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Short-wave upward (REFLEX) radiation, maximum; Short-wave upward (REFLEX) radiation, minimum; Short-wave upward (REFLEX) radiation, standard deviation; Station pressure; TAT; Tateno; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 1073592 data points
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  • 85
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    Unknown
    Basic and other measurements of radiation at station Tateno (2019-11) (2020)
    PANGAEA
    In:  Aerological Observatory, Japan Meteorological Agency
    Details
    Publication Date: 2024-05-31
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, maximum; Diffuse radiation, minimum; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, maximum; Direct radiation, minimum; Direct radiation, standard deviation; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; Japan; Long-wave downward radiation; Long-wave downward radiation, maximum; Long-wave downward radiation, minimum; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Long-wave upward radiation, maximum; Long-wave upward radiation, minimum; Long-wave upward radiation, standard deviation; Monitoring station; MONS; Pyranometer, Kipp & Zonen, CMP21, SN 090229, WRMC No. 16035; Pyranometer, Kipp & Zonen, CMP21, SN 100363, WRMC No. 16036; Pyranometer, Kipp & Zonen, CMP22, SN 090099, WRMC No. 16037; Pyrgeometer, Kipp & Zonen, CGR4, SN 090133, WRMC No. 16038; Pyrgeometer, Kipp & Zonen, CGR4, SN 090166, WRMC No. 16039; Pyrheliometer, Kipp & Zonen, CHP 1, SN 090140, WRMC No. 16034; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, maximum; Short-wave downward (GLOBAL) radiation, minimum; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Short-wave upward (REFLEX) radiation, maximum; Short-wave upward (REFLEX) radiation, minimum; Short-wave upward (REFLEX) radiation, standard deviation; Station pressure; TAT; Tateno; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 1038956 data points
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  • 86
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    Unknown
    Basic and other measurements of radiation at station Tateno (2020-03) (2020)
    PANGAEA
    In:  Aerological Observatory, Japan Meteorological Agency
    Details
    Publication Date: 2024-05-31
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, maximum; Diffuse radiation, minimum; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, maximum; Direct radiation, minimum; Direct radiation, standard deviation; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; Japan; Long-wave downward radiation; Long-wave downward radiation, maximum; Long-wave downward radiation, minimum; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Long-wave upward radiation, maximum; Long-wave upward radiation, minimum; Long-wave upward radiation, standard deviation; Monitoring station; MONS; Pyranometer, Kipp & Zonen, CMP21, SN 090229, WRMC No. 16035; Pyranometer, Kipp & Zonen, CMP21, SN 100363, WRMC No. 16036; Pyranometer, Kipp & Zonen, CMP22, SN 090099, WRMC No. 16037; Pyrgeometer, Kipp & Zonen, CGR4, SN 090133, WRMC No. 16038; Pyrgeometer, Kipp & Zonen, CGR4, SN 090166, WRMC No. 16039; Pyrheliometer, Kipp & Zonen, CHP 1, SN 090140, WRMC No. 16034; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, maximum; Short-wave downward (GLOBAL) radiation, minimum; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Short-wave upward (REFLEX) radiation, maximum; Short-wave upward (REFLEX) radiation, minimum; Short-wave upward (REFLEX) radiation, standard deviation; Station pressure; TAT; Tateno; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 1073592 data points
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  • 87
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    Geochemistry of sediment core PS97/072-1TC (2020)
    PANGAEA
    Details
    Publication Date: 2024-05-31
    Keywords: Age; AGE; Antarctic sea ice; ANT-XXXI/3; AWI_Envi; AWI_Paleo; Bransfield Strait; Carbon, organic, total; Depth, bottom/max; DEPTH, sediment/rock; Depth, top/min; Diatoms, sea ice; highly branched isoprenoids; IPSO25; Modern analog technique (MAT), D274/28/4an; Paleoclimate; Paleoenvironmental Reconstructions from Marine Sediments @ AWI; Polarstern; Polar Terrestrial Environmental Systems @ AWI; PS97; PS97/072-1TC; sea ice proxy; Sea surface temperature, summer; TC; Transfer function, IKM – D336/29/3q; Trigger corer
    Type: Dataset
    Format: text/tab-separated-values, 238 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 88
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    Unknown
    Distance between ROV and sea ice from ROV survey PS122/4_46-177 on 2020-07-11, survey 3 (2022)
    PANGAEA
    Details
    Publication Date: 2024-05-31
    Description: The distance between a remotely operated vehicle (ROV) and the sea-ice underside was measured by a single-beam upward-looking acoustic sonar altimeter (Tritech PA500) attached to the ROV during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition between November 2019 and September 2020. Sea-ice draft was derived by subtracting the distance to the sea-ice underside from the ROV depth, uncorrected for ROV attitude (pitch, roll). An offset between the depth reference (ROV bumper bars) and the altimeter of 0.105 m is accounted for in the presented data.
    Keywords: Arctic Ocean; AWI_SeaIce; BEAST; Calculated; DATE/TIME; DEPTH, water; Digital precision altimeter, Tritech, PA500; Distance, relative, X; Distance, relative, Y; Distance to sea ice bottom; FRAM; FRontiers in Arctic marine Monitoring; MOSAiC; MOSAiC20192020; MOSAiC expedition; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Polarstern; PS122/4; PS122/4_46-177; Quality flag, position; Remotely operated sensor platform BEAST; Remotely operated vehicle (ROV); Sea ice; Sea ice draft; Sea-ice draft; Sea Ice Physics @ AWI; Survey ID
    Type: Dataset
    Format: text/tab-separated-values, 20910 data points
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  • 89
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    Distance between ROV and sea ice from ROV survey PS122/4_48-213 on 2020-07-26, survey 1 (2022)
    PANGAEA
    Details
    Publication Date: 2024-05-31
    Description: The distance between a remotely operated vehicle (ROV) and the sea-ice underside was measured by a single-beam upward-looking acoustic sonar altimeter (Tritech PA500) attached to the ROV during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition between November 2019 and September 2020. Sea-ice draft was derived by subtracting the distance to the sea-ice underside from the ROV depth, uncorrected for ROV attitude (pitch, roll). An offset between the depth reference (ROV bumper bars) and the altimeter of 0.105 m is accounted for in the presented data.
    Keywords: Arctic Ocean; AWI_SeaIce; BEAST; Calculated; DATE/TIME; DEPTH, water; Digital precision altimeter, Tritech, PA500; Distance, relative, X; Distance, relative, Y; Distance to sea ice bottom; FRAM; FRontiers in Arctic marine Monitoring; MOSAiC; MOSAiC20192020; MOSAiC expedition; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Polarstern; PS122/4; PS122/4_48-213; Quality flag, position; Remotely operated sensor platform BEAST; Remotely operated vehicle (ROV); Sea ice; Sea ice draft; Sea-ice draft; Sea Ice Physics @ AWI; Survey ID
    Type: Dataset
    Format: text/tab-separated-values, 33804 data points
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  • 90
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    Unknown
    Distance between ROV and sea ice from ROV survey PS122/5_59-269 on 2020-08-25, survey 1 (2022)
    PANGAEA
    Details
    Publication Date: 2024-05-31
    Description: The distance between a remotely operated vehicle (ROV) and the sea-ice underside was measured by a single-beam upward-looking acoustic sonar altimeter (Tritech PA500) attached to the ROV during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition between November 2019 and September 2020. Sea-ice draft was derived by subtracting the distance to the sea-ice underside from the ROV depth, uncorrected for ROV attitude (pitch, roll). An offset between the depth reference (ROV bumper bars) and the altimeter of 0.105 m is accounted for in the presented data.
    Keywords: Arctic Ocean; AWI_SeaIce; BEAST; Calculated; DATE/TIME; DEPTH, water; Digital precision altimeter, Tritech, PA500; Distance, relative, X; Distance, relative, Y; Distance to sea ice bottom; FRAM; FRontiers in Arctic marine Monitoring; MOSAiC; MOSAiC20192020; MOSAiC expedition; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Polarstern; PS122/5; PS122/5_59-269; Quality flag, position; Remotely operated sensor platform BEAST; Remotely operated vehicle (ROV); Sea ice; Sea ice draft; Sea-ice draft; Sea Ice Physics @ AWI; Survey ID
    Type: Dataset
    Format: text/tab-separated-values, 38250 data points
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  • 91
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    Distance between ROV and sea ice from ROV survey PS122/5_61-156 on 2020-09-10, survey 1 (2022)
    PANGAEA
    Details
    Publication Date: 2024-05-31
    Description: The distance between a remotely operated vehicle (ROV) and the sea-ice underside was measured by a single-beam upward-looking acoustic sonar altimeter (Tritech PA500) attached to the ROV during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition between November 2019 and September 2020. Sea-ice draft was derived by subtracting the distance to the sea-ice underside from the ROV depth, uncorrected for ROV attitude (pitch, roll). An offset between the depth reference (ROV bumper bars) and the altimeter of 0.105 m is accounted for in the presented data.
    Keywords: Arctic Ocean; AWI_SeaIce; BEAST; Calculated; DATE/TIME; DEPTH, water; Digital precision altimeter, Tritech, PA500; Distance, relative, X; Distance, relative, Y; Distance to sea ice bottom; FRAM; FRontiers in Arctic marine Monitoring; MOSAiC; MOSAiC20192020; MOSAiC expedition; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Polarstern; PS122/5; PS122/5_61-156; Quality flag, position; Remotely operated sensor platform BEAST; Remotely operated vehicle (ROV); Sea ice; Sea ice draft; Sea-ice draft; Sea Ice Physics @ AWI; Survey ID
    Type: Dataset
    Format: text/tab-separated-values, 79488 data points
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  • 92
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    Unknown
    Distance between ROV and sea ice from ROV survey PS122/5_62-103 on 2020-09-17, survey 1 (2022)
    PANGAEA
    Details
    Publication Date: 2024-05-31
    Description: The distance between a remotely operated vehicle (ROV) and the sea-ice underside was measured by a single-beam upward-looking acoustic sonar altimeter (Tritech PA500) attached to the ROV during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition between November 2019 and September 2020. Sea-ice draft was derived by subtracting the distance to the sea-ice underside from the ROV depth, uncorrected for ROV attitude (pitch, roll). An offset between the depth reference (ROV bumper bars) and the altimeter of 0.105 m is accounted for in the presented data.
    Keywords: Arctic Ocean; AWI_SeaIce; BEAST; Calculated; DATE/TIME; DEPTH, water; Digital precision altimeter, Tritech, PA500; Distance, relative, X; Distance, relative, Y; Distance to sea ice bottom; FRAM; FRontiers in Arctic marine Monitoring; MOSAiC; MOSAiC20192020; MOSAiC expedition; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Polarstern; PS122/5; PS122/5_62-103; Quality flag, position; Remotely operated sensor platform BEAST; Remotely operated vehicle (ROV); Sea ice; Sea ice draft; Sea-ice draft; Sea Ice Physics @ AWI; Survey ID
    Type: Dataset
    Format: text/tab-separated-values, 48552 data points
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  • 93
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    Distance between ROV and sea ice from ROV survey PS122/5_61-200 on 2020-09-12, survey 1 (2022)
    PANGAEA
    Details
    Publication Date: 2024-05-31
    Description: The distance between a remotely operated vehicle (ROV) and the sea-ice underside was measured by a single-beam upward-looking acoustic sonar altimeter (Tritech PA500) attached to the ROV during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition between November 2019 and September 2020. Sea-ice draft was derived by subtracting the distance to the sea-ice underside from the ROV depth, uncorrected for ROV attitude (pitch, roll). An offset between the depth reference (ROV bumper bars) and the altimeter of 0.105 m is accounted for in the presented data.
    Keywords: Arctic Ocean; AWI_SeaIce; BEAST; Calculated; DATE/TIME; DEPTH, water; Digital precision altimeter, Tritech, PA500; Distance, relative, X; Distance, relative, Y; Distance to sea ice bottom; FRAM; FRontiers in Arctic marine Monitoring; MOSAiC; MOSAiC20192020; MOSAiC expedition; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Polarstern; PS122/5; PS122/5_61-200; Quality flag, position; Remotely operated sensor platform BEAST; Remotely operated vehicle (ROV); Sea ice; Sea ice draft; Sea-ice draft; Sea Ice Physics @ AWI; Survey ID
    Type: Dataset
    Format: text/tab-separated-values, 72912 data points
    Location Call Number Expected Availability
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  • 94
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    Basic and other measurements of radiation at station Tateno (2022-11) (2023)
    PANGAEA
    In:  Aerological Observatory, Japan Meteorological Agency
    Details
    Publication Date: 2024-05-31
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, maximum; Diffuse radiation, minimum; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, maximum; Direct radiation, minimum; Direct radiation, standard deviation; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; Japan; Long-wave downward radiation; Long-wave downward radiation, maximum; Long-wave downward radiation, minimum; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Long-wave upward radiation, maximum; Long-wave upward radiation, minimum; Long-wave upward radiation, standard deviation; Monitoring station; MONS; Pyranometer, Kipp & Zonen, CMP21, SN 090229, WRMC No. 16035; Pyranometer, Kipp & Zonen, CMP21, SN 191191, WRMC No. 16044; Pyranometer, Kipp & Zonen, CMP22, SN 090099, WRMC No. 16037; Pyrgeometer, Kipp & Zonen, CGR4, SN 090133, WRMC No. 16038; Pyrgeometer, Kipp & Zonen, CGR4, SN 120502, WRMC No. 16042; Pyrheliometer, Kipp & Zonen, CHP 1, SN 090140, WRMC No. 16034; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, maximum; Short-wave downward (GLOBAL) radiation, minimum; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Short-wave upward (REFLEX) radiation, maximum; Short-wave upward (REFLEX) radiation, minimum; Short-wave upward (REFLEX) radiation, standard deviation; Station pressure; TAT; Tateno; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 1166242 data points
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  • 95
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    Basic and other measurements of radiation at station Tateno (2023-02) (2023)
    PANGAEA
    In:  Aerological Observatory, Japan Meteorological Agency
    Details
    Publication Date: 2024-05-31
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, maximum; Diffuse radiation, minimum; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, maximum; Direct radiation, minimum; Direct radiation, standard deviation; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; Japan; Long-wave downward radiation; Long-wave downward radiation, maximum; Long-wave downward radiation, minimum; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Long-wave upward radiation, maximum; Long-wave upward radiation, minimum; Long-wave upward radiation, standard deviation; Monitoring station; MONS; Pyranometer, Kipp & Zonen, CMP21, SN 090229, WRMC No. 16035; Pyranometer, Kipp & Zonen, CMP21, SN 191191, WRMC No. 16044; Pyranometer, Kipp & Zonen, CMP22, SN 090099, WRMC No. 16037; Pyrgeometer, Kipp & Zonen, CGR4, SN 090133, WRMC No. 16038; Pyrgeometer, Kipp & Zonen, CGR4, SN 120502, WRMC No. 16042; Pyrheliometer, Kipp & Zonen, CHP 1, SN 090140, WRMC No. 16034; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, maximum; Short-wave downward (GLOBAL) radiation, minimum; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Short-wave upward (REFLEX) radiation, maximum; Short-wave upward (REFLEX) radiation, minimum; Short-wave upward (REFLEX) radiation, standard deviation; Station pressure; TAT; Tateno; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 1088640 data points
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  • 96
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    Basic and other measurements of radiation at station Tateno (2023-04) (2023)
    PANGAEA
    In:  Aerological Observatory, Japan Meteorological Agency
    Details
    Publication Date: 2024-05-31
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, maximum; Diffuse radiation, minimum; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, maximum; Direct radiation, minimum; Direct radiation, standard deviation; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; Japan; Long-wave downward radiation; Long-wave downward radiation, maximum; Long-wave downward radiation, minimum; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Long-wave upward radiation, maximum; Long-wave upward radiation, minimum; Long-wave upward radiation, standard deviation; Monitoring station; MONS; Pyranometer, Kipp & Zonen, CMP21, SN 090229, WRMC No. 16035; Pyranometer, Kipp & Zonen, CMP21, SN 191191, WRMC No. 16044; Pyranometer, Kipp & Zonen, CMP22, SN 090099, WRMC No. 16037; Pyrgeometer, Kipp & Zonen, CGR4, SN 090133, WRMC No. 16038; Pyrgeometer, Kipp & Zonen, CGR4, SN 120502, WRMC No. 16042; Pyrheliometer, Kipp & Zonen, CHP 1, SN 090140, WRMC No. 16034; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, maximum; Short-wave downward (GLOBAL) radiation, minimum; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Short-wave upward (REFLEX) radiation, maximum; Short-wave upward (REFLEX) radiation, minimum; Short-wave upward (REFLEX) radiation, standard deviation; Station pressure; TAT; Tateno; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 1166392 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 97
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    Unknown
    Basic and other measurements of radiation at station Tateno (2023-01) (2023)
    PANGAEA
    In:  Aerological Observatory, Japan Meteorological Agency
    Details
    Publication Date: 2024-05-31
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, maximum; Diffuse radiation, minimum; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, maximum; Direct radiation, minimum; Direct radiation, standard deviation; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; Japan; Long-wave downward radiation; Long-wave downward radiation, maximum; Long-wave downward radiation, minimum; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Long-wave upward radiation, maximum; Long-wave upward radiation, minimum; Long-wave upward radiation, standard deviation; Monitoring station; MONS; Pyranometer, Kipp & Zonen, CMP21, SN 090229, WRMC No. 16035; Pyranometer, Kipp & Zonen, CMP21, SN 191191, WRMC No. 16044; Pyranometer, Kipp & Zonen, CMP22, SN 090099, WRMC No. 16037; Pyrgeometer, Kipp & Zonen, CGR4, SN 090133, WRMC No. 16038; Pyrgeometer, Kipp & Zonen, CGR4, SN 120502, WRMC No. 16042; Pyrheliometer, Kipp & Zonen, CHP 1, SN 090140, WRMC No. 16034; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, maximum; Short-wave downward (GLOBAL) radiation, minimum; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Short-wave upward (REFLEX) radiation, maximum; Short-wave upward (REFLEX) radiation, minimum; Short-wave upward (REFLEX) radiation, standard deviation; Station pressure; TAT; Tateno; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 1205114 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 98
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    Unknown
    Basic and other measurements of radiation at station Tateno (2023-03) (2023)
    PANGAEA
    In:  Aerological Observatory, Japan Meteorological Agency
    Details
    Publication Date: 2024-05-31
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, maximum; Diffuse radiation, minimum; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, maximum; Direct radiation, minimum; Direct radiation, standard deviation; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; Japan; Long-wave downward radiation; Long-wave downward radiation, maximum; Long-wave downward radiation, minimum; Long-wave downward radiation, standard deviation; Long-wave upward radiation; Long-wave upward radiation, maximum; Long-wave upward radiation, minimum; Long-wave upward radiation, standard deviation; Monitoring station; MONS; Pyranometer, Kipp & Zonen, CMP21, SN 090229, WRMC No. 16035; Pyranometer, Kipp & Zonen, CMP21, SN 191191, WRMC No. 16044; Pyranometer, Kipp & Zonen, CMP22, SN 090099, WRMC No. 16037; Pyrgeometer, Kipp & Zonen, CGR4, SN 090133, WRMC No. 16038; Pyrgeometer, Kipp & Zonen, CGR4, SN 120502, WRMC No. 16042; Pyrheliometer, Kipp & Zonen, CHP 1, SN 090140, WRMC No. 16034; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, maximum; Short-wave downward (GLOBAL) radiation, minimum; Short-wave downward (GLOBAL) radiation, standard deviation; Short-wave upward (REFLEX) radiation; Short-wave upward (REFLEX) radiation, maximum; Short-wave upward (REFLEX) radiation, minimum; Short-wave upward (REFLEX) radiation, standard deviation; Station pressure; TAT; Tateno; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 1205280 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 99
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    Unknown
    Proton Transfer Reaction Mass Spectrometer measurements during the Reef To Rainforest campaign (2024)
    PANGAEA
    Details
    Publication Date: 2024-05-31
    Keywords: aerosol; Air Chemistry; atmospheric composition; ccn; climate; clouds; CT; CTD/Rosette; CTD-RO; DATE/TIME; Dimethyl sulfide; Event label; Great Barrier Reef; IN2016_R2R, Reef to Rainforest; IN2016_V05; IN2016-V05-S1; IN2016-V05-S2; IN2016-V05-S3-1; IN2016-V05-S3-2; IN2016-V05-S4; IN2016-V05-S6; IN2016-V05-UW; Investigator (2014); Isoprene; LATITUDE; LONGITUDE; Methacrolein + methyl vinyl ketone; MULT; Multiple investigations; Proton Transfer - Quadrupole mass spectrometry, Ionicon Analytics; Quality flag; Underway cruise track measurements
    Type: Dataset
    Format: text/tab-separated-values, 11775 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 100
    facet.materialart.
    Unknown
    Lufft Weatherstation measurements at Garner's Beach during the Reef To Rainforest campaign (2024)
    PANGAEA
    Details
    Publication Date: 2024-05-31
    Description: 2 minute resolution data file with measurements from the Luuft Weather Station and the Spectronus Fourier Transform Infrared (FTIR) Spectrometer. This data file contains meteorology parameter such as humidity, wind speed, pressure, temperature, as well as the concentraiton of chemical species such as CH4, CO2, N2O, O3 and NOx.
    Keywords: aerosol; Air Chemistry; atmospheric composition; Australia; Carbon dioxide; Carbon monoxide; ccn; climate; clouds; DATE/TIME; Density, air; Dew/frost point; Enthalpy; Event label; Fourier Transform Infrared (FTIR) spectrometer, Echotech, Spectronus Trace Greenhouse Gas and Isotope Analyser; Garners Beach, QLD; Great Barrier Reef; HEIGHT above ground; Humidity, absolute; Humidity, relative; IN2016-V05-AB1; LATITUDE; LONGITUDE; Lufft Weatherstation, WS800; Methane; MULT; Multiple investigations; Nitric oxide; Nitrogen dioxide; Nitrogen oxide; Nitrous oxide; Ozone; Precipitation; Precipitation/Rain; Pressure, atmospheric; Serinus NOx Analyzer, Ecotech; Short-wave downward (GLOBAL) radiation; Temperature, air; Temperature, air, wet bulb; Water vapour mixing ratio; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 442948 data points
    Location Call Number Expected Availability
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