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  • 2020-2024  (166,790)
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  • 1
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    Ocean Decade Vision 2030 White Papers – Challenge 2: Protect and Restore Ecosystems and Biodiversity. (2024)
    UNESCO-IOC | Paris, France
    Details
    Publication Date: 2024-06-10
    Description: This draft White Paper has been prepared as part of the Vision 2030 process being undertaken in the framework of the UN Decade of Ocean Science for Sustainable Development. The Vision 2030 process aims to achieve a common and tangible measure of success for each of the ten Ocean Decade Challenges by 2030. From a starting point of existing initiatives underway in the Ocean Decade and beyond, and through a lens of priority user needs, the process determines priority datasets, critical gaps in science and knowledge, and needs in capacity development, infrastructure and technology required for each Challenge to ensure that it can be fulfilled by the end of the Ocean Decade in 2030. The results of the process will contribute to the scoping of future Decade Actions, identification of resource mobilization priorities, and ensuring the ongoing relevance of the Challenges over time. The process identifies achievable recommendations that can be implemented in the context of the Decade, or more broadly before 2030 to achieve the identified strategic ambition and indicators that will be used to measure progress. This draft White Paper is one of a series of ten White Papers all of which have been authored by an expert Working Group. Accompanied by a synthesis report authored by the Decade Coordination Unit, this white paper was discussed at the 2024 Ocean Decade Conference (Barcelona. Spain). Input received from diverse groups through public consultation and at the Conference was reviewed and incorporated as relevant.
    Description: Published
    Description: Refereed
    Keywords: Forward look ; Vision paper ; Marine biodiversity ; Ecosystem restoration ; Marine ecosystems ; Climate change effects
    Repository Name: AquaDocs
    Type: Report
    Format: 28pp.
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  • 2
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    Ocean Decade Vision 2030 White Papers – Challenge 3: Ocean Contributions to Nourishing the World’s Population. (2024)
    UNESCO-IOC | Paris, France
    Details
    Publication Date: 2024-06-10
    Description: This draft White Paper has been prepared as part of the Vision 2030 process of the United Nations (UN) Decade of Ocean Science for Sustainable Development (hereafter, Ocean Decade). The Vision 2030 process aims to identify tangible measures of success for each of the ten Ocean Decade Challenges by 2030. From a starting point of existing initiatives underway in the Ocean Decade and beyond, and through a lens of priority user needs, the process determines critical gaps in science and knowledge, needs for capacity development, priority datasets, infrastructure, and technology for each Challenge. Focusing investments in science and knowledge to address these needs will help ensure progress towards meeting each critical Challenge by the end of the Ocean Decade in 2030. The results of the process will contribute to the scoping of future Decade Actions, identification of resource mobilisation priorities, and ensure relevance of the Challenges over time. This draft White Paper is one of a series of ten White Papers, all of which have been authored by an expert Working Group and discussed at the 2024 Ocean Decade Conference. A synthesis report, authored by the Intergovernmental Oceanographic Commission of the United Nations Educational, Scientific, and Cultural Organization (UNESCO/IOC), will accompany the White Papers. With a substantial portion of people depending on the ocean as a primary source of nutrition and livelihood, a significant challenge comes into focus: How can we ensure that the ocean's resources continue to effectively nourish an expanding global population? The Ocean Decade responds to this critical concern through its Challenge 3: “Sustainably nourish the global population”.
    Description: Published
    Description: Refereed
    Keywords: Food ; Agriculture ; Sustainable economy ; Fisheries ; World population ; Ocean economy ; Nutrition ; Aquatic foods ; Aquaculture ; Sustainable production ; Forward look ; Vision paper
    Repository Name: AquaDocs
    Type: Report
    Format: 33pp.
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  • 3
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    Ocean Decade Vision 2030 White Papers – Challenge 1: Understand And Beat Marine Pollution. (2024)
    UNESCO-IOC | Paris, France
    Details
    Publication Date: 2024-06-10
    Description: By 2030, the success of Ocean Decade Challenge No.1 ‘Understand and Beat Marine Pollution’ will be demonstrated by the generation of scientifically sound data enabling a holistic understanding of the extent and impact of pollution across the land-ocean continuum, thereby supporting the achievement of a cleaner and healthier ocean where all ecosystems and their inhabitants thrive free from the impacts of marine pollution, allowing for their full functioning and service provision. This success will be based on completion of a comprehensive review of all available evidence about marine pollution, including an analysis of data gaps and the development and implementation of strategies for filling those gaps, as well as a comprehensive analysis of solutions for addressing and preventing the negative effects of marine pollution. Achieving this success will require knitting together existing and new data sets using AI and other technologies, identifying priority pollutants and areas for action, and providing globally consistent monitoring, data collection, storage and sharing protocols. Success will further be demonstrated through the establishment of new connections and partnerships among users across the public - private spectrum that lead to the funding, development and implementation of new technologies and projects aimed at monitoring, controlling, reducing, and/or mitigating marine pollution from any source, including the creation and sustainability of a global network of strategically positioned sentinel stations and regional laboratory hubs for sustained, long-term monitoring of marine pollution. Success will include fulfilment of the following critical knowledge gaps: • a comprehensive and holistic understanding of the impacts of priority pollutants (e.g., pollutants found or expected to emerge in high concentrations, or with high toxicity, or with significant adverse effects on biota or human health) across the land to ocean continuum; • a better understanding of the sources, sinks, fate and impacts of all pollutants, including the pollutants of emerging concern; • improved knowledge on the distribution and impacts of marine pollution, particularly in the Global South and deep ocean waters, which currently represent the largest geographical gaps. and the following priority datasets gaps: • long-term time series of marine pollutants; • baseline and toxicity data of pollutants across the land-ocean continuum; • data on the impacts of the co-occurrence of multiple pollutants; • data on the effects of climate change on the toxicity, bioavailability and impacts of multiple co-existent pollutants. • It will include development of: • a global network of strategically positioned sentinel stations for continuous, long-term monitoring; • cost-effective, real-time monitoring systems and technologies for tracking pollutant sources, distribution, and transfers across the land-ocean continuum; • a global network of regional laboratory hubs focused on generating high-quality data, promoting capacity building and facilitating technology transfer; • training programs on harmonized protocols for the acquisition, reporting and recording of quality-controlled data on marine pollution; • environmentally robust new technologies and processes for the control and mitigation of marine pollution.
    Description: Published
    Description: Refereed
    Keywords: Marine pollution ; Pollutants ; Ocean health
    Repository Name: AquaDocs
    Type: Report
    Format: 27pp.
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  • 4
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    Ocean Decade Vision 2030 White Papers - Challenge 10: Restoring Society's Relationship with the Ocean. (2024)
    UNESCO-IOC | Paris, France
    Details
    Publication Date: 2024-06-10
    Description: By 2030, success for Ocean Decade Challenge No. 10 will be evidenced through a culture shift in the ocean community leading to implicit understanding that ocean threats are an outcome of human behaviour. This will require a shift in the way that ocean science, in the broad sense as defined in the Decade, is formulated, practiced, and communicated to ensure that all sectors of society have strengthened emotional connections with the ocean, and understand the vital role that the ocean plays in human and planetary well-being, including climate stability. All members of society across regions, sectors, and scales will have increased motivation, capability, and opportunity to make decisions and behave in ways that ensure a healthy ocean. By 2030, success for Ocean Decade Challenge No. 10 will include fulfilment of critical science and knowledge gaps: Increased priority and practice of science that embraces multiple knowledge systems and transdisciplinary collaboration Increased priority of Indigenous-led research, consistent with the supporting articles of the United Nations Declaration on the Rights of Indigenous Peoples (UNDRIP), inherent rights, and signed treaty obligations with Indigenous Nations Increased priority of marine social sciences, particularly: public perceptions ocean research marine citizenship and identity research behavioural science research linked to ocean-climate education and communications research on how ocean literacy can be measured and monitored over time, and the impacts of an ocean literate society on ocean health research on ocean literacy as a policy tool science communication through multiple approaches including immersive technology, storytelling, and the arts Success will also depend on the generation, sharing, and use of the following priority datasets: human-ocean connection/human-ocean values dataset(s) pro-ocean behaviour change methodologies, case studies, and effective practices impact mapping of regional and key global ocean literacy initiatives ocean culture mapping that includes a global body of evidence (contextual, local knowledge) that demonstrates and supports cultural engagement as an enabler of ocean-human health. It will include the development of: a co-designed theory of change to action key drivers of Challenge 10, in which regional expertise helps guide the initial and ongoing strategic direction of the newly launched Decade Coordinating Office (DCO), Connecting People and Ocean a guiding portfolio of best practices on research co-design, co-production, co-implementation, and co-evaluation, respectfully bridging different forms of knowledge, ensuring mutual recognition and benefits, and nurturing long-term relationships with each other and nature a collaborative global, multi-dimensional ocean literacy survey tool (i.e., Ocean & Society Survey) to measure ocean connection and values, as well as motivators, enablers, barriers to action and behaviour change a global network of ocean communications experts and regional ocean communications communities of practice to support training, accreditation, upskilling, knowledge exchange, and impact measurement a global network of ocean-climate education experts (formal, informal, and non-formal) to support teacher training, certification programmes, and knowledge exchange a Global Blue Schools Network, building off the All-Atlantic and European Blue Schools Networks, to bridge practitioner best practices with research and training a global framework for sharing successful community projects that demonstrate practices and solutions specific to cultural connections, heritage, language, and place-based innovations for ocean-human health.
    Description: Published
    Description: Refereed
    Keywords: Human activities ; Ocean health ; Indigenous knowledge ; Marine social sciences ; Ocean literacy ; Societal impact ; Science communication
    Repository Name: AquaDocs
    Type: Report
    Format: 38pp.
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  • 5
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    Ocean Decade Vision 2030 White Papers – Challenge 7: Sustainably Expand the Global Ocean Observing System. (2024)
    UNESCO-IOC | Paris, France
    Details
    Publication Date: 2024-06-10
    Description: The strategic ambition is to develop an operational, comprehensive, and resourced system that delivers priority observations and information to guide mitigation and adaptation responses to climate change, sustains ocean health within a sustainable blue economy, and facilitates informed decision-making for science, business and society. Such a system is envisioned to be co-designed, fit-for-purpose, multidisciplinary, geographically expanded, responsive, and sustainable in time, delivering ocean observations to all nations and users, prioritising societal needs. Transforming ocean observations into accessible information will require integration across disciplines, across national observing systems, along the value chain, and across stakeholders. Innovative technology approaches and a diversified set of actors and approaches will be required for success. The Global Ocean Observing System (GOOS) of IOC UNESCO can provide the implementation framework for Challenge 7 and the UN Ocean Decade provides the opportunity and vehicle for transformation. Five recommendations have been identified to fulfil the strategic ambition of Ocean Decade Challenge 7. Act now on known observational needs. Upgrade and expand ocean observing capacity in poorly-observed areas such as polar regions, island nations and territories, coastal areas of developing nations, coastal systems that are rapidly changing, and the under-observed deep ocean. Thematic priorities for ocean observing by 2030 should focus on key climate risk and adaptation needs, extreme events, coastal services for ocean management, ocean carbon, marine pollution, biogeochemistry, and biodiversity. Adopt new economic thinking. Establish new and sustained financing mechanisms for global ocean observing, including resourcing for Small Island Developing States (SIDS) and Least Developed Countries (LDCs). Use economic models for ocean investment to diversify and accelerate investment in ocean observing and infrastructure from new actors. Partnerships are key. Increase national, regional and global coordination, focusing on co-design and partnerships. Improved coordination that uses the GOOS framework to ensure standards, best practices for a sustainably expanded GOOS. Diversify partnerships across sectors (economic, public, private, and philanthropic) and embrace the abilities and needs of the different stakeholders to co-design, co-develop, and co-deliver observations that translate into the information required by these sectors. Technology and innovation will be a pillar. Integrate and harmonise observations across observing platforms (in situ, satellite, emerging networks). Develop innovative in situ, autonomous and cost-effective technologies to maximise reach, ensuring standardisation and best practices. Technology barriers still need to be lowered to ensure everyone has equitable access to observing technology and has the ability to use these assets. Artificial Intelligence (AI) and Machine Learning (ML) tools will provide user-ready information from integrated observations to democratise information for users. Expanded, capable, and diversified workforce. Expand and diversify the workforce of skilled and trained ocean professionals. Training and capacity development will be critical across the observing ‘ecosystem’ outlined in the Framework for Ocean Observing (FOO), from data collection to data analysis and modelling, and for data use and application.
    Description: Published
    Description: Refereed
    Keywords: Ocean observation ; GOOS ; Global Ocean Observing System ; Ocean observing
    Repository Name: AquaDocs
    Type: Report
    Format: 22pp.
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  • 6
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    Ocean Decade Vision 2030 White Papers – Challenge 5: Unlock Ocean-Based Solutions to Climate Change. (2024)
    UNESCO-IOC | Paris, France
    Details
    Publication Date: 2024-06-10
    Description: By 2030, success for Ocean Decade Challenge number 5 will be marked by a move toward a more sustainable and climate-resilient ocean that aligns with the United Nations’ sustainable development goals. Crucially, the success of Challenge 5 is intricately linked to the outcomes of Challenges 1 to 4, which focus on understanding climate-ocean interactions, controlling marine pollution, conserving biodiversity, and ensuring sustainable food production. Success will include fulfillment of critical science and knowledge gaps with respect to climate adaptation and mitigation. Both approaches need to be addressed in parallel. Key mitigation approaches include the development of marine renewable energies, reduction in marine pollution, the development of blue carbon ecosystems, and marine carbon dioxide removal (mCDR). Adaptation approaches include increased ocean literacy/awareness; co-designed governance and co-operation; improved risk reduction policies; and improved predictive capability of ocean, climate, and weather forecasts. Challenge 5 was reported as one of the most commonly cited Challenges for knowledge uptake in the Decade. However, important gaps still remain in terms of the geographical scope of the actions under this and other challenges.
    Description: Published
    Description: Refereed
    Keywords: Climate change effects ; Ocean prediction ; Ocean forecasting ; Weather forecasting
    Repository Name: AquaDocs
    Type: Report
    Format: 25pp.
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  • 7
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    Ocean Decade Vision 2030 White Papers – Challenge 8: Create a digital representation of the ocean. (2024)
    UNESCO-IOC | Paris, France
    Details
    Publication Date: 2024-06-10
    Description: Ocean Decade Challenge 8 of the United Nations Decade of Ocean Science for Sustainable Development 2021-2030 (the ‘Ocean Decade’) seeks to create an adaptive and dynamic digital representation of the ocean to make the ocean accessible to a broader community, to enhance decision-making and to support sustainable ocean management. While creating a comprehensive digital representation of the Ocean is the ultimate objective of Decade Challenge 8, the focus in this White Paper is on delivering concrete outcomes and the transformational change needed to create the enabling environment and initial digital content, by 2030, that will allow us to fully deliver on the ambitions of Challenge 8 on the longer term. An Implementation Plan (IP) for the Ocean Decade’s Data and Information Strategy is currently under development by the Data Strategy Implementation Group (DSIG). This IP will outline how data systems participating in the Ocean Decade can co-create a distributed, robust, and collaborative ‘digital ecosystem’ that leverages open, scalable, easily implementable, and responsive technologies and management solutions. An interoperable, distributed data and information sharing system must be both deployed and maintained to allow the realization of Challenge 8, addressing specific challenges such as data interoperability, accessibility, and inclusivity. Additionally, potential issues related to data privacy, cybersecurity, and equitable access to technological infrastructure should be addressed to ensure the comprehensive development of the strategic ambition. In developing the Strategic Ambition for Challenge 8, we consider the data and information needs and priorities identified by the other Decade Challenges and their working groups, as our primary users (and contributors), representing as they do the key sustainability challenges for the Decade, and encompassing all relevant stakeholders. Guided by the Decade’s ambition to ‘leave no one behind’ we recognize that this challenge must deliver outputs that are relevant and useful for the global ocean science community, and in fact by extension the widest possible range of users and stakeholders, including the eight billion people on this planet, who should be able to access and use what is delivered by the Decade in ways adapted to their needs and capacities, if so desired. By 2030, the Strategic Ambition for Ocean Decade Challenge 8 is to have in place the enabling environment for the creation of and access to an increasing number of digital representations and twin applications of the Ocean as well as the underpinning data and information needed to develop them, delivering at minimum 10 societally relevant 0global base-layers accessible via a global online Digital Atlas, complemented by a minimum of 10 local use cases (prioritizing SIDS and LDCs) to address challenges in using and contributing to the Decade’s distributed digital ecosystem and to demonstrate and stress test its relevance, effectiveness and inclusiveness.
    Description: Published
    Description: Refereed
    Keywords: Digital Twin of the Ocean ; Data visualisation ; Digital representations ; Digital atlas ; Federated Ocean Data Discovery Service ; Data products ; Ocean forecasting
    Repository Name: AquaDocs
    Type: Report , Report , Report
    Format: 54pp.
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  • 8
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    Ocean Decade Vision 2030 White Papers – Challenge 6: Increase Community Resilience to Ocean Hazards. (2024)
    UNESCO-IOC | Paris, France
    Details
    Publication Date: 2024-06-10
    Description: By 2030, successful achievement of Ocean Decade Challenge No. 6 will require demonstrating substantial advancements within the global community towards enhancing their resilience to coastal and ocean hazards. This includes implementing two crucial elements: (1) establishing comprehensive 'people-centered' early warning systems capable of addressing multiple hazards, and (2) devising adaptation strategies that specifically target risks associated with the ocean, including those linked to climate change. These endeavours will play a pivotal role in guiding sustainable practices in ocean planning. Success will also hinge on addressing critical gaps in scientific understanding and knowledge across important components such as risk assessment and risk reduction, in addition to putting in place robust institutional mechanisms for implanting novel solutions that contribute to coastal resilience. Some key elements to be addressed in this context include: (i) gathering and generating observational and modelling datasets relevant to risk assessment, including downscaled climate scenarios for coastal regions, within robust data-sharing frameworks; (ii) promoting interdisciplinary and international research and innovation to tackle challenges comprehensively, with a focus on methodologies like Digital Twin approaches; (iii) improving standards for risk communication at both national and international levels; (iv) fostering partnerships at various scales involving local communities, public and private disaster risk reduction entities, governmental bodies, and academic institutions; (v) building capacity in research and communication to cultivate a shared understanding of coastal resilience strategies; and (vi) enhancing resilient infrastructure and promoting sustainable resource management along coastlines. It is imperative to establish partnerships with existing international UN programs dedicated to disaster risk reduction and coastal resilience. Strengthening connections with UN Decade Actions through Decade Coordination Offices and Decade Collaboration Centers is of utmost importance for effective coordination and collaboration. Based on the above strategic ambition it is also suggested that the formulation of the Ocean Decade Challenge could be modified as follows: Increase community resilience to ocean and coastal risks
    Description: Published
    Description: Refereed
    Keywords: Coastal resilience ; Coastal zone management ; Hazard warning system ; Risk assessement ; Ocean hazards
    Repository Name: AquaDocs
    Type: Report
    Format: 37pp.
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  • 9
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    Ocean Decade Vision 2030 White Papers – Challenge 9: Skills, Knowledge, Technology, and Participatory Decision-Making for All. (2024)
    UNESCO-IOC | Paris, France
    Details
    Publication Date: 2024-06-10
    Description: Challenge 9 aims to ensure comprehensive capacity development and equitable access to data, information, knowledge, technology, and participatory decision-making across all aspects of ocean science and for all stakeholders. It is based on the understanding that everyone has something to contribute through shared knowledge, resources, ideas, or partnerships. Challenge 9 therefore is focused on equity and justice in access to capacity, resources, and decision making. By 2030, success for Ocean Decade Challenge 9 will be reached when: Technical, transdisciplinary, and transversal skills required by scientists, resource users, educators, communicators, managers, and policymakers, to deliver the Decade’s challenges, are strengthened and evenly distributed with an emphasis on least developed countries (LDCs) and Small Island Developing States (SIDS) and other under-represented groups. Funding mechanisms, multi-directional partnerships, multi-directional partnerships, infrastructure, and technology required to deliver the Decade’s challenges across regions and communities are enhanced and evenly distributed with emphasis on promoting access to LDCs and SIDS and on promoting greater cooperation between regions. Users and stakeholders from currently under-represented groups (i.e., women; ECOPs; Indigenous communities; LDCs and SIDS; people with disabilities; and others) are well-represented and participatory in ocean science, communication, management, decision making, and policy within the Decade framework. Wider promotion of ethically-driven actions and access to open-source software, ocean data, knowledge, and information among different users of the ocean has been achieved, and language barriers/restrictions have been mediated, including sharing knowledge in forms that are well articulated by non-scientific audiences. Recognition for Indigenous and local knowledge and traditional beliefs that promote conservation receives backing by the Decade and is integrated into all the Decade challenges. Success will include fulfilment of the following critical capacity development needs: skills enhancement; representation and meaningful participation; equitable funding; infrastructure; technology; access to data and information; publishing of research findings; better representation of scientists and knowledge from LDCs, SIDS and other under-represented groups in international publications and decision-making bodies and procedures; and promotion of the use of multiple languages in ocean science communication.
    Description: Published
    Description: Refereed
    Keywords: Capacity development ; Under-represented groups ; Least Developed Countries (LDC) ; Equitable access ; Open access ; Small Island Developing States (SIDS)
    Repository Name: AquaDocs
    Type: Report
    Format: 28pp.
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  • 10
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    Ocean Decade Vision 2030 White Papers – Challenge 4: Develop a Sustainable and Equitable Ocean Economy. (2024)
    UNESCO-IOC | Paris, France
    Details
    Publication Date: 2024-06-10
    Description: This draft White Paper is one of a series of ten White Papers all of which have been authored by an expert Working Group. Accompanied by a synthesis report authored by the Decade Coordination Unit, it will be discussed at the 2024 Ocean Decade Conference before being finalised and published. 1.2 Strategic Ambition of Ocean Decade Challenge No. 4 By 2030, success for Ocean Decade Challenge No. 4: Develop a sustainable and equitable ocean economy, will be marked by significant advancements in establishing a knowledge-driven framework for informed decision-making and policy formulation. There will be enhanced collaboration among stakeholders, ensuring diverse community engagement and equitable benefit sharing while acknowledging and prioritising the culture, identity, and rights of IPLC that have historically depended on and thrived alongside ocean resources. Strategic mobilisation of blue finance will support investments in sustainable coastal and marine infrastructure, innovative technologies, and conservation efforts, reinforcing the economic foundation. Key policies and governance frameworks promoting sustainability and equity will be in place, alongside a balanced and reflective approach, laying the groundwork for a resilient and inclusive ocean economy. This success will be underpinned by improved data accessibility and capacity-sharing efforts, fostering a shared understanding and commitment to sustainable ocean use. Success will include fulfilment of the following critical science and knowledge gaps: addressing the interface between knowledge systems, policy implementation, and public-private partnerships to enable informed decision-making, focusing on biodiversity restoration, protection, and sustainable management as foundational elements of a sustainable and equitable ocean economy, and ensuring the inclusion of local and indigenous knowledge alongside environmental sustainability and social equity. The following priority datasets gaps will be targeted: comprehensive and up-to-date data on both human activities and state of the environment supporting informed and equitable decision-making and ensuring stakeholder and rights holder engagement in data capture and knowledge co-production. It will include robust capacity development and sharing as well as knowledge exchange to deepen understanding of ocean-human activity interconnections, emphasising investment in context-specific education, training, and research programs, and the integration of appropriate technology and innovation to support a sustainable, equitable, and resilient ocean economy and ensuring that future generations can benefit from the ocean's diverse resources and opportunities.
    Description: Published
    Description: Refereed
    Keywords: Sustainable economy ; Ocean economy ; Ocean governance ; Science policy interface
    Repository Name: AquaDocs
    Type: Report
    Format: 26pp.
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  • 11
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    Aurantoside L, a New Tetramic Acid Glycoside with Anti-Leishmanial Activity Isolated from the Marine Sponge Siliquariaspongia japonica (2024)
    In:  Marine Drugs vol. 22 no. 4
    Details
    Publication Date: 2024-06-10
    Description: A new tetramic acid glycoside, aurantoside L (1), was isolated from the sponge Siliquariaspongia japonica collected at Tsushima Is., Nagasaki Prefecture, Japan. The structure of aurantoside L (1) composed of a tetramic acid bearing a chlorinated polyene system and a trisaccharide part was elucidated using spectral analysis. Aurantoside L (1) showed anti-parasitic activity against L. amazonensis with an IC50 value of 0.74 μM.
    Keywords: aurantosides ; Siliquariaspongia japonica ; marine sponge ; nuclear magnetic resonance ; mass ; spectrometry ; anti-leishmanial activity ; marine natural products
    Repository Name: National Museum of Natural History, Netherlands
    Type: info:eu-repo/semantics/article
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  • 12
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    Macroevolutionary Dynamics in Micro-organisms: Generalists Give Rise to Specialists Across Biomes in the Ubiquitous Bacterial Phylum Myxococcota (2024)
    In:  Molecular Biology and Evolution vol. 41 no. 5
    Details
    Publication Date: 2024-06-10
    Keywords: macroevolution ; microbes ; prokaryotes ; habitat transitions ; specialization ; diversification ; myxobacteria ; comparative phylogenetics
    Repository Name: National Museum of Natural History, Netherlands
    Type: info:eu-repo/semantics/article
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  • 13
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    The puzzle of an allanite-like epidote mineral from Malmkärra, Sweden: Toward the new (OH)-analogue of dollaseite-(Ce). (2024)
    In:  Abstracts
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    Publication Date: 2024-06-10
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  • 14
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    The diversity of geochemical types of Erzgebirge granites and their potential of hosting uranium deposits: Comparison to the French Variscan district. (2023)
    In:  Proceedings
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    Publication Date: 2024-06-10
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  • 15
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    An unusual epidote supergroup mineral: A solid solution containing the new (OH)-analogue of dollaseite-(Ce). (2024)
    In:  Abstracts
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    Publication Date: 2024-06-10
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  • 16
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    Holocene hydroclimate variability of the Baltic region inferred from stable isotopes, d-excess and multi-proxy data at lake Nuudsaku, Estonia (NE Europe) (2024)
    In:  Quaternary Science Reviews
    Details
    Publication Date: 2024-06-10
    Description: Long-term hydroclimate records provide an opportunity to understand potential drivers of the past, and give context to modern and future climate warming. A wide variety of proxy data now allow for reconstruction of climate variables that were not previously possible. Here we present a multi-proxy dataset including n-alkane δ2H (δ2Hn-alk) values from an open-basin lake in Estonia to reconstruct past hydroclimate conditions for the eastern Baltic region. We complement our sedimentary δ2Hn-alk data with existing carbonate-based oxygen stable isotope (δ18O) data to derive deuterium (d-) excess. We present multiple isotopic records and reconstructed relative humidity (ΔRH) values over the Holocene, and link these with modern precipitation δ2H and δ18O values to guide the interpretation of the paleo-proxies. Fossil pollen and chironomid-based temperature reconstructions, as well as biogeochemical data provide additional information for inferring past environmental changes. Our results indicate that the middle Holocene in Estonia had on average 6 ± 3% higher RH values than the late Holocene. The δ18O and δ2H values were also higher during the middle Holocene, which we interpret as increased warm season precipitation. Our reconstructed d-excess values were relatively higher during the middle Holocene, indicating a more northerly or cold source water origin, in comparison to the late Holocene. In addition to the paleoclimatic significance, our results show how multiple quantitative proxies can be combined to characterize hydroclimate sensitivity to changes in relative humidity, temperature and moisture source.
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  • 17
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    Multi-disciplinary monitoring of the Ketzin CO 2 pilot site as successful concept for storage integrity assessment (2024)
    In:  Extended Abstracts
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    Publication Date: 2024-06-10
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  • 18
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    Probing the stability of SrIrO3during active water electrolysisvia operandoatomic force microscopy (2023)
    In:  Energy and Environmental Science
    Details
    Publication Date: 2024-06-10
    Description: Mechanistic studies of oxide electrocatalysts for heterogeneous water oxidation have been primarily focused on understanding the origins of activity, with fewer studies addressing fundamental properties that influence stability. The main challenge is directly observing and quantifying local structural instability under operating conditions. In this work, we provide a dynamic view of the perovskite stability as a function of time and operational voltage using operando electrochemical atomic force microscopy (EC-AFM). Specifically, we study the degradation pathways of SrIrO3, a highly active electrocatalyst, during the oxygen evolution reaction (OER) by tracking the potential-dependent Sr leaching and perovskite dissolution at the nanometer scale. This material serves as a model system for degradation studies of perovskite AMO3 oxides, exhibiting both A-cation leaching and transition metal (M) dissolution. We show that Sr leaching precedes perovskite dissolution by up to 0.8 V, leading to a wide voltage window of stability where water oxidation occurs on a Sr-depleted surface without significant corrosion. Moreover, we reveal that the stability of the perovskite surface is strongly influenced by the electrolytic environment and that corrosion rates differ dramatically as a function of dissolved Sr concentration. Ultimately, our study demonstrates that the overall stability of perovskite oxides during electrocatalysis can be substantially improved by suppressing A-site leaching.
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    Compressibility and thermal expansion of magnesium phosphates (2024)
    In:  European Journal of Mineralogy
    Details
    Publication Date: 2024-06-10
    Description: The ambient-temperature compressibility and room-pressure thermal expansion of two Mg3(PO4)2 polymorphs (farringtonite=Mg3(PO4)2-I, with 5- and 6-fold coordinated Mg, and chopinite=“Mgsarcopside”=[6]Mg3(PO4)2-II), three Mg2PO4OH polymorphs (althausite, hydroxylwagnerite and ɛ- Mg2PO4OH, all with [5]Mg and [6]Mg) and phosphoellenbergerite ([6]Mg) were measured on synthetic powders using a synchrotron-based multi-anvil apparatus to 5.5 GPa and a laboratory high-temperature diffractometer, with whole-pattern fitting procedures. Bulk moduli range from 64.5 GPa for althausite to 88.4 GPa for hydroxylwagnerite, the high-pressure Mg2PO4OH polymorph. Chopinite, based on an olivine structure with ordered octahedral vacancies (K0=81.6 GPa), and phosphoellenbergerite, composed of chains of face-sharing octahedra (K0=86.4 GPa), are distinctly more compressible than their homeotypical silicate (127 and 133 GPa, respectively). The compressibility anisotropy is the highest for chopinite and the lowest for phosphoellenbergerite. First-order parameters of quadratic thermal expansions range from v1=2.19x10-5K-1 for ɛ-Mg2PO4OH to v1=3.58x10-5K-1 for althausite. Phosphates have higher thermal-expansion coefficients than the homeotypical silicates. Thermal anisotropy is the highest for farringtonite and the lowest for hydroxylwagnerite and chopinite. These results set the stage for a thermodynamic handling of phase-equilibrium data obtained up to 3 GPa and 1000°C in the MgO–P2O5–H2O and MgO–Al2O3–P2O5–H2O systems.
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    Transition from a mixotrophic/heterotrophic protist community during the dark winter to a photoautotrophic spring community in surface waters of Disko Bay, Greenland (2024)
    In:  Frontiers in Microbiology
    Details
    Publication Date: 2024-06-10
    Description: Unicellular eukaryotic plankton communities (protists) are the major basis of the marine food web. The spring bloom is especially important, because of its high biomass. However, it is poorly described how the protist community composition in Arctic surface waters develops from winter to spring. We show that mixotrophic and parasitic organisms are prominent in the dark winter period. The transition period toward the spring bloom event was characterized by a high relative abundance of mixotrophic dinoflagellates, while centric diatoms and the haptophyte Phaeocystis pouchetii dominated the successive phototrophic spring bloom event during the study. The data shows a continuous community shift from winter to spring, and not just a dormant spring community waiting for the right environmental conditions. The spring bloom initiation commenced while sea ice was still scattering and absorbing the sunlight, inhibiting its penetration into the water column. The initial increase in fluorescence was detected relatively deep in the water column at ~55 m depth at the halocline, at which the photosynthetic cells accumulated, while a thick layer of snow and sea ice was still obstructing sunlight penetration of the surface water. This suggests that water column stratification and a complex interplay of abiotic factors eventually promote the spring bloom initiation.
    Language: English
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    3D shear wave velocity imaging of the subsurface structure of granite rocks in the arid climate of Pan de Azúcar, Chile, revealed by Bayesian inversion of HVSR curves (2024)
    In:  Earth Surface Dynamics
    Details
    Publication Date: 2024-06-10
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    An Estimate of the Effect of 3D Heterogeneous Density Distribution on Coseismic Deformation Using a Spectral Finite-Element Approach (2024)
    In:  X Hotine-Marussi Symposium on Mathematical Geodesy: Proceedings of the Symposium in Milan, Italy, June 13-17, 2022 | International Association of Geodesy Symposia
    Details
    Publication Date: 2024-06-10
    Description: The advancement of the Global Geodetic Observing System (GGOS) has enabled monitoring of mass transport and solid-Earth deformation processes with unprecedented accuracy. Coseismic deformation is modelled as an elastic response of the solid Earth to an internal dislocation. Self-gravitating spherical Earth models can be employed in modelling regional to global scale deformations. Recent seismic tomography and high-pressure/high-temperature experiments have revealed finer-scale lateral heterogeneities in the elasticity and density structures within the Earth, which motivates us to quantify the effects of such finer structures on coseismic deformation. To achieve this, fully numerical approaches including the Finite Element Method (FEM) have often been used. In our previous study, we presented a spectral FEM, combined with an iterative perturbation method, to consider lateral heterogeneities in the bulk and shear moduli for surface loading. The distinct feature of this approach is that the deformation of the entire sphere is modelled in the spectral domain with finite elements dependent only on the radial coordinate. By this, self-gravitation can be treated without special treatments employed when using an ordinary FEM. In this study, we extend the formulation so that it can deal with lateral heterogeneities in density in the case of coseismic deformation. We apply this approach to a longer-wavelength vertical deformation due to a large earthquake. The result shows that the deformation for a laterally heterogeneous density distribution is suppressed mainly where the density is larger, which is consistent with the fact that self-gravitation reduces longer-wavelength deformations for 1-D models. The effect on the vertical displacement is relatively small, but the effect on the gravity change could amount to the same order of magnitude of a given heterogeneity if the horizontal scale of the heterogeneity is large enough.
    Language: English
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    Variation of Fault Creep Along the Overdue Istanbul-Marmara Seismic Gap in NW Turkey (2023)
    In:  Geophysical Research Letters
    Details
    Publication Date: 2024-06-10
    Description: Strain energy from tectonic loading can be partly released through aseismic creep. Earthquake repeaters, repeatedly activated brittle fault patches surrounded by creep, indicate steady-state creep that affects the amount of seismic energy available for the next large earthquake along a plate contact. The offshore Main Marmara Fault (MMF) of the North Anatolian Fault Zone represents a seismic gap capable of generating a M 〉 7 earthquake in direct vicinity to the mega-city Istanbul. Based on a newly compiled seismicity catalog, we identify repeating earthquakes to resolve the spatial creep variability along the MMF during a 15-year period. We observe a maximum of seismic repeaters indicating creep along the central and western MMF segments tapering off toward the locked onshore Ganos fault in the west, and the locked offshore Princes Islands segment immediately south of Istanbul in the east. This indicates a high degree of spatial creep variability along the Istanbul-Marmara seismic gap.
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    Das Norddeutsche Becken als Teil des Zentraleuropäischen Beckensystems (CEBS): strukturelle Entwicklung und thermisches Feld (2024)
    In:  Brandenburgische Geowissenschaftliche Beiträge
    Details
    Publication Date: 2024-06-10
    Description: Das Zentraleuropäische Beckensystem (Central Euro- pean Basin System CEBS; Abb. 1) erstreckt sich von der südlichen Nordsee bis Polen und ist ein Gebiet mit ei- ner außergewöhnlich guten Abdeckung an geologischen und geophysikalischen Daten, die sowohl aus der Koh- lenwasserstoffexploration als auch von wissenschaftli- chen Forschungsprogrammen stammen. Der öffentlich zugängliche Teil dieser Daten wurde genutzt, um ein re- gionales, lithosphärenskaliges 3D-Strukturmodell zu erstellen (Maystrenko & Scheck-Wenderoth 2013; Scheck-Wenderoth & Maystrenko 2013; Maystrenko, Bayer & Scheck-Wenderoth 2013). Dafür wurden iterati- ve Workflows entwickelt, um geologische Beobachtungen, wie z. B. Bohrlochmessungen, seismologische, seismische und Schwerefelddaten, in ein konsistentes dreidimensi- onales geologisches Strukturmodell zu integrieren. Eine Schlüsselmethode in diesem Datenintegrationsprozess ist die 3D-Schweremodellierung (Anikiev et al. 2023). Da- bei werden Dichten von seismischen Geschwindigkeiten in Tiefenprofilen oder seismischen Tomographiestudien abgeleitet und die aus der Dichteverteilung resultierende Schwerewirkung berechnet. In einem iterativen Prozess wird die berechnete Schwere an die Beobachtungsdaten angepasst. Das ermöglicht uns, selbst die tiefsten Krusten- und Manteltiefen zu erforschen. Das so erstellte 3D-Modell ist in zweierlei Hinsicht nützlich: Erstens bildet die Mäch- tigkeitsverteilung der erhaltenen geologischen Einheiten die mehr als 300 Millionen Jahre währende Absenkungs- geschichte und die damit verbundenen Deformationspha- sen ab. Zweitens kann das Modell als Grundlage für die Simulation von Wärme- und Fluidtransportprozessen im Untergrund verwendet werden, um z. B. das heutige tiefe Temperaturfeld zu berechnen. Die hier dargestellte Zusam- menfassung mehrerer Arbeiten der letzten Jahre setzt die tiefe Struktur in Beziehung zur Entwicklung und zum heu- tigen tiefen Temperaturfeld.
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    Fifteen Years of Integrated Terrestrial Environmental Observatories (TERENO) in Germany: Functions, Services, and Lessons Learned (2024)
    In:  Earth's Future
    Details
    Publication Date: 2024-06-10
    Description: The need to develop and provide integrated observation systems to better understand and manage global and regional environmental change is one of the major challenges facing Earth system science today. In 2008, the German Helmholtz Association took up this challenge and launched the German research infrastructure TERrestrial ENvironmental Observatories (TERENO). The aim of TERENO is the establishment and maintenance of a network of observatories as a basis for an interdisciplinary and long-term research program to investigate the effects of global environmental change on terrestrial ecosystems and their socio-economic consequences. State-of-the-art methods from the field of environmental monitoring, geophysics, remote sensing, and modeling are used to record and analyze states and fluxes in different environmental disciplines from groundwater through the vadose zone, surface water, and biosphere, up to the lower atmosphere. Over the past 15 years we have collectively gained experience in operating a long-term observing network, thereby overcoming unexpected operational and institutional challenges, exceeding expectations, and facilitating new research. Today, the TERENO network is a key pillar for environmental modeling and forecasting in Germany, an information hub for practitioners and policy stakeholders in agriculture, forestry, and water management at regional to national levels, a nucleus for international collaboration, academic training and scientific outreach, an important anchor for large-scale experiments, and a trigger for methodological innovation and technological progress. This article describes TERENO's key services and functions, presents the main lessons learned from this 15-year effort, and emphasizes the need to continue long-term integrated environmental monitoring programmes in the future.
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    Magnetotelluric images of the medium enthalpy Bakreswar geothermal province within a granitic gneissic complex, Eastern Indian Peninsula (2024)
    In:  Geophysical Prospecting
    Details
    Publication Date: 2024-06-10
    Description: The Bakreswar geothermal province represents a medium enthalpy geothermal system with its Bakreswar and Tantloie hot springs. It lies within the Chotanagpur Granite Gneissic Complex in the eastern part of the Indian Peninsula. The province has a high heat flow and a high geothermal gradient of 90°C/km. Magnetotelluric data from 95 sites in a frequency range of 10 kHz–10 Hz were acquired over the Bakreswar geothermal province to obtain an electrical conductivity model and map the geothermal reservoir with its fluid pathways and related geological structures. Subsurface conductivity models obtained from three-dimensional inversions of the Magnetotelluric data exhibit several prominent anomalies, which are supplemented by gravity results. The conductivity model maps three features which act as a conduit (a) a northwest–southeast trending feature, (b) an east–west trending feature to the south of the northwest–southeast trending feature (which lies 1 km north of the Oil and Natural Gas Corporation fault marked by previous studies) and (c) shallow conducting features close to Bakreswar hot spring. The northwest–southeast trending feature coincides with the boundary of the high-density intrusive block. This northwest–southeast trending feature provides the pathway for the meteoric water to reach a maximum depth of 2.7 km, where it gets heated by interacting with deep-seated structures and then it rises towards the surface. The radiogenic process occurring within the granites of Chotanagpur Granite Gneissic Complex provides the heat responsible for heating the meteoric water. The northwest–southeast and east–west trending features are responsible for the transport of meteoric water to deeper depths and then towards the shallow regions of the Earth. The near surface features close to the Bakreswar hot spring are responsible for carrying the water further towards the hot spring. The resistivity of these structures plotted as a function of salinity and temperatures for saline crustal fluids suggests the involvement of meteoric water. Further, applying Archie's law to this resistivity suggests that the conduit path has a porosity greater than 10%. This study successfully maps the anomalous structures which might foster the migration of geothermal fluid in Bakreswar geothermal province.
    Language: English
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    Deep ocean hydrographic variability estimated from distributed geodetic sensor arrays off northern Chile (2024)
    Nature Research
    Details
    Publication Date: 2024-06-10
    Description: Observations of spatio-temporal variability of the deep ocean are rare and little is known about occurrence of deep ocean mesoscale dynamics. Here, we make use of 2.5 years of time series data from three distributed sensor arrays, which acquired high-resolution temperature, pressure and sound speed data of the bottom layer offshore northern Chile. Estimating salinity and density from the direct observations enable access to the full spectrum of hydrographic variability from a multi-hourly to annual time scale and with average inter-station distances of less than 1 km. Analyses revealed interannual warming over the continental slope of 0.002 °C yr−1–0.003 °C yr−1, and could trace periodic hydrographic anomalies, likely related to coastal-trapped waves, as far as to the lower continental slope. A concurrent change in the shape of the warm anomalies and the rate of deep-sea warming that occurs with the crossing of the deep-sea trench suggests that the abyssal part of the eastern boundary current system off Chile does not extend past the deep sea trench. Furthermore, the comparison of anomaly timing and shape in between stations implies southwards flow over the mid to lower continental slope, centred closer to the trench.
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    A climatology of weather-driven anomalies in European photovoltaic and wind power production (2024)
    Nature Research | Springer
    Details
    Publication Date: 2024-06-10
    Description: Weather causes extremes in photovoltaic and wind power production. Here we present a comprehensive climatology of anomalies in photovoltaic and wind power production associated with weather patterns in Europe considering the 2019 and potential 2050 installations, and hourly to ten-day events. To that end, we performed kilometer-scale numerical simulations of hourly power production for 23 years and paired the output with a weather classification which allows a detailed assessment of weather-driven spatio-temporal production anomalies. Our results highlight the dependency of low-power production events on the installed capacities and the event duration. South-shifted Westerlies (Anticyclonic South-Easterlies) are associated with the lowest hourly (ten-day) extremes for the 2050 (both) installations. Regional power production anomalies can differ from the ones in the European mean. Our findings suggest that weather patterns can serve as indicators for expected photovoltaic and wind power production anomalies and may be useful for early warnings in the energy sector.
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    Mixed layer depth dominates over upwelling in regulating the seasonality of ecosystem functioning in the Peruvian Upwelling System (2022)
    Copernicus Publications (EGU)
    Details
    Publication Date: 2024-06-10
    Description: The Peruvian Upwelling System hosts an extremely high productive marine ecosystem. Observations show that the Peruvian Upwelling System is the only Eastern Boundary Upwelling Systems (EBUS) with an out-of-phase relationship of seasonal surface chlorophyll concentrations and upwelling intensity. This "seasonal paradox" triggers the questions: (1) what is the uniqueness of the Peruvian Upwelling System compared with other EBUS that leads to the out of phase relationship; (2) how does this uniqueness lead to low phytoplankton biomass in austral winter despite strong upwelling and ample nutrients? Using observational climatologies for four EBUS we diagnose that the Peruvian Upwelling System is unique in that intense upwelling coincides with deep mixed layers. We then apply a coupled regional ocean circulation-biogeochemical model (CROCO-BioEBUS) to assess how the interplay between mixed layer and upwelling is regulating the seasonality of surface chlorophyll in the Peruvian Upwelling System. The model recreates the "seasonal paradox" within 200 km off the Peruvian coast. We confirm previous findings that deep mixed layers, which cause vertical dilution and stronger light limitation, mostly drive the diametrical seasonality of chlorophyll relative to upwelling. In contrast to previous studies, reduced phytoplankton growth due to enhanced upwelling of cold waters and lateral advection are second-order drivers of low surface chlorophyll concentrations. This impact of deep mixed layers and upwelling propagates up the ecosystem, from primary production to export efficiency. Our findings emphasize the crucial role of the interplay of the mixed layer and upwelling and suggest that surface chlorophyll may increase along with a weakened seasonal paradox in response to shoaling mixed layers under climate change.
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    Effects of Mixed Layer Depth on Productive Marine Ecosystems: From seasonality to climate change (2022)
    Details
    Publication Date: 2024-06-10
    Description: Marine ecosystems, particularly productive marine ecosystems, substantially impact global fisheries and are considerably influenced by climate change as an integral component of the earth system. Modelling is an essential tool to understand marine ecosystems and project their possible response to climate change. However, current ecosystem modelling projections have significant uncertainties, which are partially caused by a lack of overall understanding of the underlying physical-biological interactions. This thesis seeks to identify the driving mechanisms of the trophodynamics in productive marine ecosystems in the contemporary climate, which is key to improve future ecosystem projections under climate change.
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    Comparing Urban Anthropogenic NMVOC Measurements With Representation in Emission Inventories—A Global Perspective (2023)
    In:  Journal of Geophysical Research: Atmospheres
    Details
    Publication Date: 2024-06-10
    Description: Emission inventories are a critical basis for air quality and climate modeling, as well as policy decisions. Non-methane volatile organic compounds (NMVOCs) are key precursor compounds in ozone and secondary organic aerosol formation. Accurately representing NMVOCs in emission inventories is crucial for understanding atmospheric chemistry, the impact of policy measures, and climate projections. Improving NMVOC representation in emission inventories is fraught with challenges, ranging from the lack of (long-term) NMVOC measurements, limited efforts in updating emission factors, to the diversity of NMVOC species reactivity. Here we take an initial step to evaluate the representation of urban NMVOC speciation in an emission inventory (EDGARv4.3.2 and EDGARv6.1) at the global level. To compare the urban measurements of NMVOCs to the emission inventory estimates, ratios of individual NMVOCs to acetylene are used. Owing to limitations in measurement data and grouping of NMVOCs in emission inventories, the comparison includes only a limited number of alkanes, alkenes, and aromatics. Results show little to no agreement between the ratios in the observations and those in the global emission inventory for the species compared (r2 0.01–0.20). This could be related to incorrect speciation profiles and/or spatial allocation of NMVOCs to urban areas. Regional emission inventories show better agreement among the ratios (r2 0.43–0.70). The inclusion of oxygenated species in NMVOC measurements, as well as greater global coverage of measurements could improve representation of NMVOC species in emission inventories, and a mosaic of regional inventories may be a better approach.
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    Learning and community building in support of collective action: Toward a new climate of communication at the COP (2023)
    In:  Wiley Interdisciplinary Reviews - Climate Change
    Details
    Publication Date: 2024-06-10
    Description: The international UN Climate Change conferences known as “Conferences of the Parties (COPs)” have an enormous convening power and are attended annually by tens of thousands of actors working on climate change topics from a wide range of perspectives. In the COP spaces outside of the formal negotiations, the communication culture is dominated by “side events,” a format that relies heavily on conventional presentations and panels that can be informative, but is generally not conducive to mutual engagement, reflection, or dialogue. There is an urgent need for new dialogue formats that can better foster learning and community-building and thereby harness the enormous latent potential for climate action represented by the diverse stakeholders that gather at the COP. Against this backdrop, and drawing on our experience with the development and implementation of the Co-Creative Reflection and Dialogue Spaces at COP25, COP26, and COP27, we make recommendations for further developing the communication culture of the COPs. At the level of individual sessions, we provide recommendations for designing participatory dialogues that can better support reflection, interconnection, and action orientation. In addition, we offer guidance for scaling up these practices, for instance through networks and communities of practice to support a shift of the overall communication culture of the COPs. Our recommendations focus on interactions and exchanges that unfold outside of the formal negotiation sessions, with a view toward enabling and accelerating transformative action by non-state actors.
    Language: English
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    Global distribution and composition of Neogene-Quaternary intraplate volcanic rocks (2022)
    GFZ Data Services
    Details
    Publication Date: 2024-06-10
    Description: Abstract
    Description: Global database of  〉20, 000 geochemical analyses of Neogene-Quaternary intraplate volcanic rocks. The database collates major, trace element and Sr-Nd-Pb isotopic data for whole-rock samples 〈20 Ma old that were published between 1990 and 2020. Database as published in Ball et al. (2021). Key publication: Ball, P. W., White, N. J., Maclennan, J., & Stephenson, S. N. (2021). Global influence of mantle temperature and plate thickness on intraplate volcanism. Nature Communications, 12(1), 2045. https://doi.org/10.1038/s41467-021-22323-9
    Description: Other
    Description: The DIGIS geochemical data repository is a research data repository in the Earth Sciences domain with a specific focus on geochemical data. It is hosted at GFZ Data Services through a collaboration between the Digital Geochemical Data Infrastructure (DIGIS) for GEOROC 2.0 (https://digis.geo.uni-goettingen.de) and the GFZ German Research Centre for Geosciences. The repository archives, publishes and makes accessible user-contributed, peer-reviewed research data that fall within the scope of the GEOROC database. Compilations of previously published data are also made available on the GEOROC website (https://georoc.eu) as Expert Datasets.
    Keywords: intraplate ; volcanic ; major elements ; trace elements ; Sr87_Sr86 ; Nd143_Nd144 ; Pb206_Pb204 ; Pb207_Pb206 ; Pb208_Pb204 ; andesite ; basalt ; basaltic andesite ; basaltic trachyandesite ; basanite ; dacite ; foidite ; phonolite ; phonotephrite ; picrobasalt ; rhyolite ; tephriphonolite ; trachyandesite ; trachybasalt ; trachyte ; Sr-Nd-Pb isotopes ; GEOROC Expert Dataset ; EARTH SCIENCE 〉 SOLID EARTH 〉 GEOCHEMISTRY ; Phanerozoic 〉 Cenozoic 〉 Neogene ; Phanerozoic 〉 Cenozoic 〉 Quaternary
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    Physical oceanography and CFC-12 measured on water bottle samples during Maria S. Merian cruise MSM05/1 (2020)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: Temperature, salinity, oxygen data and CFC-12 measured on RV Maria S. Merian Cruise MSM05/1 Las Palmas - St. John's 04/14 - 05/03/2007 Chief Scientist: Monika Rhein Region: Subpolar North Atlantic
    Keywords: 1; 10; 11; 12; 13; 15; 16; 17; 18; 19; 2; 20; 21; 22; 23; 24; 25; 26; 28; 29; 3; 30; 31; 32; 33; 34; 35; 36; 37; 38; 39; 4; 40; 5; 6; 7; 8; 9; anthropogenic tracers; Bottle number; Calculated; Capillary-chromatographic system with electron capture detector; CTD, SEA-BIRD SBE 9 plus, SBE 11 plus deck unit; CTD/Rosette; CTD-RO; Date/Time of event; Density, sigma-theta (0); DEPTH, water; Der Nordatlantik als Teil des Erdsystems; Elevation of event; Event label; Freon-12 (dichlorodifluoromethane); Latitude of event; Longitude of event; Maria S. Merian; MSM05/1; MSM05/1_394; MSM05/1_395; MSM05/1_396; MSM05/1_397; MSM05/1_398; MSM05/1_399; MSM05/1_400; MSM05/1_401; MSM05/1_402; MSM05/1_403; MSM05/1_404; MSM05/1_405; MSM05/1_406; MSM05/1_408; MSM05/1_409; MSM05/1_410; MSM05/1_411; MSM05/1_412; MSM05/1_413; MSM05/1_414; MSM05/1_415; MSM05/1_416; MSM05/1_417; MSM05/1_418; MSM05/1_419; MSM05/1_424; MSM05/1_425; MSM05/1_426; MSM05/1_427; MSM05/1_428; MSM05/1_429; MSM05/1_430; MSM05/1_431; MSM05/1_432; MSM05/1_433; MSM05/1_434; MSM05/1_435; MSM05/1_436; Nordatlantik; Oxygen; Oxygen, Winkler (Culberson, 1991, WOCE Report 68/91); Oxygen sensor, SBE 43; Pressure, water; Profile ID; Salinity; Station label; subpolar North Atlantic; Temperature, water; Temperature, water, potential; Time in days
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    Physical oceanography, CFC-11 and CFC-12 measured on water bottle samples during Maria S. Merian cruise MSM21/2 (2020)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: Temperature, salinity and CFCs measured on the RV Maria S. Merian Cruise MSM21/2 Reykjavik - Nuuk 25th June - 24th July 2012 Chief Scientist: Dagmar Kieke Region: Subpolar North Atlantic
    Keywords: anthropogenic tracers; Bottle number; Calculated; Capillary-chromatographic system with electron capture detector; CTD, SEA-BIRD SBE 9 plus, SBE 11 plus deck unit; CTD/Rosette; CTD-RO; Date/Time of event; Density, sigma-theta (0); DEPTH, water; Elevation of event; Event label; Freon-11 (trichorofluoromethane); Freon-12 (dichlorodifluoromethane); Latitude of event; Longitude of event; Maria S. Merian; MSM21/2; MSM21/2_383-1; MSM21/2_387-1; MSM21/2_388-1; MSM21/2_389-1; MSM21/2_390-1; MSM21/2_394-1; MSM21/2_395-1; MSM21/2_396-1; MSM21/2_397-1; MSM21/2_400-1; MSM21/2_403-1; MSM21/2_407-1; MSM21/2_408-1; MSM21/2_410-1; MSM21/2_412-1; MSM21/2_415-1; MSM21/2_416-1; MSM21/2_421-1; MSM21/2_427-1; MSM21/2_428-1; MSM21/2_429-1; MSM21/2_430-1; MSM21/2_431-1; MSM21/2_432-1; MSM21/2_433-1; MSM21/2_434-1; MSM21/2_435-1; MSM21/2_436-1; MSM21/2_440-1; MSM21/2_444-1; MSM21/2_445-1; MSM21/2_446-1; MSM21/2_447-1; MSM21/2_448-1; MSM21/2_449-1; MSM21/2_450-1; MSM21/2_454-1; MSM21/2_455-1; MSM21/2_456-1; MSM21/2_457-1; MSM21/2_458-1; MSM21/2_460-1; MSM21/2_461-1; MSM21/2_463-1; MSM21/2_464-1; MSM21/2_465-1; MSM21/2_467-1; MSM21/2_468-1; MSM21/2_469-1; MSM21/2_470-1; MSM21/2_471-1; MSM21/2_475-1; MSM21/2_476-1; MSM21/2_477-1; MSM21/2_478-1; MSM21/2_480-1; MSM21/2_481-1; MSM21/2_482-1; MSM21/2_484-1; MSM21/2_485-1; MSM21/2_486-1; MSM21/2_488-1; MSM21/2_489-1; MSM21/2_491-1; MSM21/2_492-1; MSM21/2_494-1; MSM21/2_495-1; MSM21/2_496-1; MSM21/2_497-1; MSM21/2_498-1; MSM21/2_499-1; msm212_000; msm212_001; msm212_002; msm212_003; msm212_004; msm212_005; msm212_006; msm212_007; msm212_008; msm212_009; msm212_010; msm212_011; msm212_012; msm212_013; msm212_014; msm212_015; msm212_016; msm212_017; msm212_018; msm212_019; msm212_020; msm212_021; msm212_022; msm212_023; msm212_024; msm212_025; msm212_026; msm212_027; msm212_037; msm212_038; msm212_039; msm212_040; msm212_041; msm212_042; msm212_043; msm212_044; msm212_045; msm212_046; msm212_047; msm212_048; msm212_049; msm212_050; msm212_051; msm212_052; msm212_053; msm212_054; msm212_055; msm212_056; msm212_057; msm212_058; msm212_059; msm212_060; msm212_061; msm212_062; msm212_063; msm212_064; msm212_065; msm212_066; msm212_067; msm212_068; msm212_069; msm212_070; msm212_071; msm212_072; msm212_073; msm212_074; msm212_075; msm212_076; msm212_078; msm212_079; Pressure, water; Profile ID; Salinity; South Atlantic Ocean; Station label; subpolar North Atlantic; Temperature, water; Temperature, water, potential; Time in days
    Type: Dataset
    Format: text/tab-separated-values, 14657 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 36
    facet.materialart.
    Unknown
    Physical oceanography, CFC-11 and CFC-12 measured on water bottle samples during Maria S. Merian cruise MSM27 (2020)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: Temperature, salinity, oxygen data and anthropogenic tracers measured on the Maria S. Merian Cruise MSM27 St. John's - St. John's 04/19 - 05/06/2013 Chief Scientist: Dagmar Kieke Region: Flemish Pass, Orphan Basin, DWBC east of Flemish Cap
    Keywords: anthropogenic tracers; Bottle number; Calculated; CTD, SEA-BIRD SBE 9 plus, SBE 11 plus deck unit; CTD/Rosette; CTD-RO; Date/Time of event; Density, sigma-theta (0); DEPTH, water; Elevation of event; Event label; Flemish Pass Variability; FLEPVAR; Freon-11 (trichorofluoromethane); Freon-12 (dichlorodifluoromethane); Latitude of event; Longitude of event; Maria S. Merian; MSM27; MSM27_138-1; MSM27_139-1; MSM27_140-1; MSM27_141-1; MSM27_142-1; MSM27_143-1; MSM27_144-1; MSM27_145-1; MSM27_146-1; MSM27_147-1; MSM27_148-1; MSM27_149-1; MSM27_150-1; MSM27_152-1; MSM27_153-1; MSM27_154-1; MSM27_155-1; MSM27_156-1; MSM27_157-2; MSM27_162-1; MSM27_163-1; MSM27_164-1; MSM27_165-1; MSM27_166-1; MSM27_167-1; MSM27_168-1; MSM27_169-1; MSM27_170-1; MSM27_171-1; MSM27_172-1; MSM27_173-1; MSM27_174-1; MSM27_175-1; MSM27_176-1; MSM27_177-1; MSM27_178-1; MSM27_179-1; MSM27_180-1; MSM27_181-1; MSM27_182-1; MSM27_183-1; MSM27_184-1; MSM27_185-1; MSM27_186-1; MSM27_187-1; MSM27_188-1; MSM27_189-1; MSM27_190-1; MSM27_191-1; MSM27_192-1; MSM27_193-1; MSM27_194-1; MSM27_195-1; MSM27_196-1; MSM27_197-1; MSM27_198-1; MSM27_199-1; MSM27_200-1; MSM27_201-1; MSM27_202-1; MSM27_203-1; MSM27_204-1; MSM27_205-1; MSM27_206-1; MSM27_207-1; MSM27_208-1; MSM27_209-1; MSM27_210-1; MSM27_211-1; MSM27_212-1; MSM27_213-1; MSM27_214-1; MSM27_215-1; MSM27_216-1; MSM27_217-1; MSM27_218-1; MSM27_219-1; MSM27_220-1; MSM27_221-1; MSM27_223-1; MSM27_224-1; MSM27_225-1; MSM27_226-1; MSM27_227-1; MSM27_228-1; MSM27_229-1; MSM27_230-1; MSM27_231-1; MSM27_232-1; MSM27_233-1; MSM27_234-1; MSM27_235-1; MSM27_236-1; MSM27_237-1; MSM27_239-1; MSM27_240-1; MSM27_241-1; MSM27_242-1; MSM27_243-1; MSM27_244-1; MSM27_245-1; MSM27_246-1; MSM27_247-1; MSM27_248-1; MSM27_249-1; MSM27_250-1; MSM27_251-1; MSM27_252-1; MSM27_253-1; MSM27_254-1; MSM27_255-1; MSM27_256-1; MSM27_257-1; MSM27_258-1; MSM27_259-1; MSM27_260-1; MSM27_261-1; MSM27_262-1; MSM27_263-1; MSM27_264-1; MSM27_265-1; MSM27_266-1; MSM27_267-1; MSM27_268-1; MSM27_269-1; Oxygen; Oxygen sensor, SBE 43; Pressure, water; Profile ID; Salinity; South Atlantic Ocean; Station label; subpolar North Atlantic; Temperature, water; Temperature, water, potential; Time in days
    Type: Dataset
    Format: text/tab-separated-values, 20758 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 37
    facet.materialart.
    Unknown
    Physical oceanography and CFC-12 measured on water bottle samples during Meteor cruise M82/2 (2020)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: Temperature, salinity and CFCs measured on the RV Meteor Cruise M82/2 St. John's - Pta. Delgada 08/04 - 09/01/2010 Chief Scientist: Monika Rhein Region: Subpolar North Atlantic
    Keywords: 513; 514; 515; 516; 517; 518; 519; 523; 524; 525; 526; 527; 528; 529; 530; 532; 533; 535; 545; 547; 548; 550; 551; 556; 560; 566; 571; 575; 579; 584; 587; 589; 591; 592; 601; 603; 604; 609; 610; 611; 612; 613; 617; 619; 620; 622; 623; 625; 626; 627; 628; 629; 631; 632; 633; 634; 636; 637; 638; 639; 640; 643; 646; 649; 652; 655; 658; 662; 665; 668; 671; 673; 674; 675; 676; anthropogenic tracers; Bottle number; Calculated; Capillary-chromatographic system with electron capture detector; CTD, SEA-BIRD SBE 9 plus, SBE 11 plus deck unit; Date/Time of event; Density, sigma-theta (0); DEPTH, water; Der Nordatlantik als Teil des Erdsystems; Elevation of event; Event label; Freon-12 (dichlorodifluoromethane); Latitude of event; Longitude of event; M82/2; M82/2_513-1; M82/2_514-1; M82/2_515-1; M82/2_516-1; M82/2_517-1; M82/2_518-1; M82/2_519-1; M82/2_523-1; M82/2_524-1; M82/2_525-1; M82/2_526-1; M82/2_527-1; M82/2_528-1; M82/2_529-1; M82/2_530-1; M82/2_532-1; M82/2_533-1; M82/2_535-1; M82/2_545-1; M82/2_547-1; M82/2_548-1; M82/2_550-1; M82/2_551-1; M82/2_556-1; M82/2_560-1; M82/2_566-1; M82/2_571-1; M82/2_575-1; M82/2_579-1; M82/2_584-1; M82/2_587-1; M82/2_589-1; M82/2_591-1; M82/2_592-1; M82/2_601-1; M82/2_603-1; M82/2_604-1; M82/2_609-1; M82/2_610-1; M82/2_611-1; M82/2_612-1; M82/2_613-1; M82/2_617-1; M82/2_619-1; M82/2_620-1; M82/2_622-1; M82/2_623-1; M82/2_625-1; M82/2_626-1; M82/2_627-1; M82/2_628-1; M82/2_629-1; M82/2_631-1; M82/2_632-1; M82/2_633-1; M82/2_634-1; M82/2_636-1; M82/2_637-1; M82/2_638-1; M82/2_639-1; M82/2_640-1; M82/2_643-1; M82/2_646-1; M82/2_649-1; M82/2_652-1; M82/2_655-1; M82/2_658-1; M82/2_662-1; M82/2_665-1; M82/2_668-1; M82/2_671-1; M82/2_673-1; M82/2_674-1; M82/2_675-1; M82/2_676-1; Meteor (1986); MULT; Multiple investigations; Nordatlantik; Northeast Atlantic; Oxygen; Oxygen, Winkler (Culberson, 1991, WOCE Report 68/91); Oxygen sensor, SBE 43; Pressure, water; Profile ID; Salinity; Station label; subpolar North Atlantic; Temperature, water; Temperature, water, potential; Time in days
    Type: Dataset
    Format: text/tab-separated-values, 16104 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 38
    facet.materialart.
    Unknown
    Physical oceanography and anthropogenic tracers measured on water bottle samples during Maria S. Merian cruise MSM42 (2020)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: Temperature, salinity and anthropogenic tracers measured on the RV Maria S. Merian Cruise MSM42 Bermuda - St. John's 05/02 - 05/22/2015 Chief Scientist: Dagmar Kieke Region: around Flemish Cap, Orphan Basin
    Keywords: anthropogenic tracers; Bottle number; Calculated; Capillary-chromatographic system with electron capture detector; CTD, SEA-BIRD SBE 9 plus, SBE 11 plus deck unit; CTD-Acoustic Doppler Current Profiler; CTD-ADCP; Date/Time of event; Density, sigma-theta (0); DEPTH, water; Elevation of event; Event label; Flemish Pass Variability; FLEPVAR; FLEPVAR2015; Freon-11 (trichorofluoromethane); Freon-12 (dichlorodifluoromethane); Latitude of event; Longitude of event; Maria S. Merian; MSM42; MSM42_100; MSM42_101; MSM42_102; MSM42_103; MSM42_104; MSM42_105; MSM42_106; MSM42_107; MSM42_108; MSM42_109; MSM42_110; MSM42_111; MSM42_112; MSM42_114; MSM42_115; MSM42_116; MSM42_117; MSM42_118; MSM42_119; MSM42_120; MSM42_121; MSM42_122; MSM42_123; MSM42_124; MSM42_125; MSM42_135; MSM42_136; MSM42_137; MSM42_138; MSM42_139; MSM42_140; MSM42_141; MSM42_142; MSM42_143; MSM42_144; MSM42_145; MSM42_146; MSM42_147; MSM42_148; MSM42_149; MSM42_150; MSM42_151; MSM42_152; MSM42_153; MSM42_154; MSM42_155; MSM42_156; MSM42_157; MSM42_158; MSM42_159; MSM42_160; MSM42_161; MSM42_162; MSM42_163; MSM42_164; MSM42_165; MSM42_166; MSM42_167; MSM42_168; MSM42_169; MSM42_170; MSM42_171; MSM42_172; MSM42_173; MSM42_174; MSM42_175; MSM42_176; MSM42_177; MSM42_178; MSM42_179; MSM42_180; MSM42_181; MSM42_182; MSM42_183; MSM42_184; MSM42_185; MSM42_186; MSM42_187; MSM42_188; MSM42_189; MSM42_190; MSM42_191; MSM42_192; MSM42_193; MSM42_194; MSM42_195; MSM42_196; MSM42_197; MSM42_198; MSM42_199; MSM42_200; MSM42_201; MSM42_202; MSM42_203; MSM42_204; MSM42_210; MSM42_50; MSM42_51; MSM42_52; MSM42_53; MSM42_54; MSM42_55; MSM42_56; MSM42_57; MSM42_58; MSM42_59; MSM42_60; MSM42_61; MSM42_62; MSM42_63; MSM42_64; MSM42_65; MSM42_66; MSM42_67; MSM42_68; MSM42_69; MSM42_70; MSM42_71; MSM42_72; MSM42_73; MSM42_74; MSM42_75; MSM42_76; MSM42_77; MSM42_78; MSM42_79; MSM42_80; MSM42_81; MSM42_82; MSM42_83; MSM42_84; MSM42_85; MSM42_86; MSM42_87; MSM42_88; MSM42_89; MSM42_90; MSM42_91; MSM42_92; MSM42_93; MSM42_94; MSM42_95; MSM42_96; MSM42_97; MSM42_98; MSM42_99; Oxygen; Oxygen sensor, SBE 43; Pressure, water; Profile_001; Profile_002; Profile_003; Profile_004; Profile_005; Profile_006; Profile_007; Profile_008; Profile_009; Profile_010; Profile_011; Profile_012; Profile_013; Profile_014; Profile_015; Profile_016; Profile_017; Profile_018; Profile_019; Profile_020; Profile_021; Profile_022; Profile_023; Profile_024; Profile_025; Profile_026; Profile_027; Profile_028; Profile_029; Profile_030; Profile_031; Profile_032; Profile_033; Profile_034; Profile_035; Profile_036; Profile_037; Profile_038; Profile_039; Profile_040; Profile_041; Profile_042; Profile_043; Profile_044; Profile_045; Profile_046; Profile_047; Profile_048; Profile_049; Profile_050; Profile_051; Profile_052; Profile_053; Profile_054; Profile_055; Profile_056; Profile_057; Profile_058; Profile_059; Profile_060; Profile_061; Profile_062; Profile_063; Profile_064; Profile_065; Profile_066; Profile_067; Profile_068; Profile_069; Profile_070; Profile_071; Profile_072; Profile_073; Profile_074; Profile_075; Profile_085; Profile_086; Profile_087; Profile_088; Profile_089; Profile_090; Profile_091; Profile_092; Profile_093; Profile_094; Profile_095; Profile_096; Profile_097; Profile_098; Profile_099; Profile_100; Profile_101; Profile_102; Profile_103; Profile_104; Profile_105; Profile_106; Profile_107; Profile_108; Profile_109; Profile_110; Profile_111; Profile_112; Profile_113; Profile_114; Profile_115; Profile_116; Profile_117; Profile_118; Profile_119; Profile_120; Profile_121; Profile_122; Profile_123; Profile_124; Profile_125; Profile_126; Profile_127; Profile_128; Profile_129; Profile_130; Profile_131; Profile_132; Profile_133; Profile_134; Profile_135; Profile_136; Profile_137; Profile_138; Profile_139; Profile_140; Profile_141; Profile_142; Profile_143; Profile_144; Profile_145; Profile_146; Profile_147; Profile_148; Profile_149; Profile_150; Profile_151; Profile_152; Profile_153; Profile_154; Profile_160; Profile ID; Salinity; South Atlantic Ocean; Station label; subpolar North Atlantic; Sulfur hexafluoride, SF6; Temperature, water; Temperature, water, potential; Time in days
    Type: Dataset
    Format: text/tab-separated-values, 33355 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 39
    facet.materialart.
    Unknown
    Hydrochemistry of water samples during METEOR cruise M119 (2021)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: Water sample data from M119. The data are a combination of CTD values at the time of the bottle closing, salinity measurements with an Autosal salinometer, dissolved oxygen measurements by Winkler titration and nutrient measurements. Nutrient samples were collected for analysis of inorganic nutrients - nitrate+nitrite, soluble reactive phosphorus, and silicate from several depths in the upper 200m. About 15mL of seawater was frozen and transported back to Georgia Institute of Technology for analysis using a Lachat QuikChem 8000 flow-injection analysis system (Lachat Instruments, Loveland CO, USA) and following JGOFS methods described by (Knap 1996).
    Keywords: Bottle number; Climate - Biogeochemistry Interactions in the Tropical Ocean; CTD; CTD/Rosette; CTD001; CTD002; CTD003; CTD004; CTD005; CTD006; CTD007; CTD008; CTD009; CTD010; CTD011; CTD012; CTD013; CTD014; CTD015; CTD016; CTD017; CTD018; CTD019; CTD020; CTD022; CTD024; CTD026; CTD027; CTD028; CTD029; CTD030; CTD031; CTD032; CTD033; CTD034; CTD035; CTD036; CTD037; CTD038; CTD039; CTD040; CTD041; CTD042; CTD043; CTD044; CTD045; CTD046; CTD047; CTD048; CTD049; CTD050; CTD051; CTD052; CTD053; CTD054; CTD056; CTD057; CTD058; CTD059; CTD060; CTD061; CTD062; CTD063; CTD064; CTD065; CTD066; CTD067; CTD068; CTD069; CTD070; CTD071; CTD072; CTD073; CTD074; CTD075; CTD076; CTD077; CTD078; CTD079; CTD080; CTD081; CTD082; CTD083; CTD084; CTD085; CTD086; CTD087; CTD088; CTD089; CTD090; CTD091; CTD-Acoustic Doppler Current Profiler; CTD-ADCP; CTD-RO; Date/Time of event; DEPTH, water; Event label; Guildline autosal salinometer; LATITUDE; LONGITUDE; M119; M119_684-1; M119_686-1; M119_692-1; M119_697-1; M119_698-1; M119_700-1; M119_703-1; M119_704-1; M119_706-1; M119_708-1; M119_714-1; M119_718-1; M119_722-1; M119_723-1; M119_724-1; M119_725-1; M119_729-1; M119_731-1; M119_733-1; M119_734-1; M119_737-1; M119_740-1; M119_745-1; M119_747-1; M119_750-1; M119_753-1; M119_754-1; M119_755-1; M119_756-1; M119_758-1; M119_759-1; M119_761-1; M119_762-1; M119_764-1; M119_765-1; M119_766-1; M119_770-1; M119_774-1; M119_780-1; M119_781-1; M119_782-1; M119_783-1; M119_784-1; M119_785-1; M119_787-1; M119_788-1; M119_789-1; M119_791-1; M119_792-1; M119_793-1; M119_795-1; M119_799-1; M119_801-1; M119_802-1; M119_803-1; M119_804-1; M119_805-1; M119_812-1; M119_814-1; M119_816-1; M119_818-1; M119_825-1; M119_827-1; M119_829-1; M119_833-1; M119_835-1; M119_837-1; M119_840-1; M119_842-1; M119_846-1; M119_848-1; M119_850-1; M119_852-1; M119_855-1; M119_857-1; M119_859-1; M119_861-1; M119_863-1; M119_865-1; M119_867-1; M119_869-1; M119_871-1; M119_873-1; M119_874-1; M119_875-1; M119_876-1; M119_877-1; Meteor (1986); Nitrate; Nitrite; Oxygen; Phosphate; Pressure, water; Profile ID; Quality flag; Run; Salinity; Sample code/label; SFB754; Silicate; Temperature, water; Titration, Winkler
    Type: Dataset
    Format: text/tab-separated-values, 12840 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 40
    facet.materialart.
    Unknown
    2D multichannel seismic reflection raw data (GI Gun & GGun array entire dataset) of RV SONNE during cruise SO294 (2024)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: The raw 2D multichannel seismic reflection data in this project were acquired during expedition SO294 offshore Vancouver Island, Canada, using two different sources, i.e. a single GI gun and a G-gun array. The data were recorded with an 184-channel streamer. The objectives of expedition SO294 were twofold: provision of geophysical images to constrain the hazard potential of the Cascadia subduction zone and to constrain the geophysical properties of the oceanic crust to assess its storage potential for carbon capture and storage (CCS). The data comprise 1660 line kilometers and are provided in raw format (SEG-D) according to standard metadata descriptions. Detailed information on the acquisition can be found in the SO294 cruise report (https://doi.org/10.48433/cr_so294). In addition, a technical report is provided with this data set.
    Keywords: 2D seismic data; Binary Object; Binary Object (File Size); Binary Object (MD5 Hash); Binary Object (Media Type); BSR; Cable depth; Carbon capture and storage; CLOCKS; Comment; Compass birds; Data source; DATE/TIME; deformation front; Device type; Distance near channel dx; Distance near channel dy; Distance to antenna dx; Distance to antenna dy; earthquake; Event label; Extracted from file; File format; File name; gas hydrates; GGun array; GI gun; Group spacing constant; Group spacing nominell; Identification; LATITUDE; LONGITUDE; multi-channel seismic reflection; NMEA string; Number of auxillary channels; Number of guns; Number of sections; Number of total channels; P1000; P2000/P3000; P4000/P5000; P6000; P7000; Profile ID; raw data; Receiver array; Recording delay; Reel format; Samples per trace; Sampling interval; SEIS; Seismic; Seismic pressure; seismic reflection; Seismic source; Seismic time delay; SO294; SO294_135-1; SO294_136-1; SO294_208-1; SO294_209-1; SO294_69-1; Sonne_2; Total active cable length; Total seismic source volume; tsunami; Water depth of gun
    Type: Dataset
    Format: text/tab-separated-values, 1937989 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 41
    facet.materialart.
    Unknown
    French Airborne Measurement Platform (PMA) cloud particle size distribution and volumic cloud particle scattering properties dataset near Svalbard for the HALO-AC3 measurement campaign in 2022 (2024)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: This data set is composed of in-situ measurement of arctic cloud microphysical properties (particle size distribution and volumic cloud particle scattering properties) observed during the HALO-AC3 campaign, which occurred between March 20th and April 10th 2022. These measurements were made using the 2D stereoscopic (2D-S, SPEC Inc.) and Polar Nephelometer (Gayet et al., 1997) probes from the airborne measurement platform of the Laboratoire de Météorologie Physique (CNRS/UCA, Aubière, France). There is one file per flight. All files are in NetCDF format, with a complete description of the parameters inside. A detailed list of the parameters present in the data set is added in a separate document (see "Further details" link).
    Keywords: 2D-S Stereo Probe, SPEC Inc., and Polar Nephelometer according to Gayet et al. (1997); AC; AC3; Aircraft; Arctic; Arctic Amplification; Atmospheric and Earth System Research with HALO – High Altitude and Long Range Research Aircraft; Cloud Microphysics; Date/Time of event; Event label; HALO - (AC)3; HALO-(AC)³; HALO-AC3_20220320_P6_RF01; HALO-AC3_20220322_P6_RF02; HALO-AC3_20220326_P6_RF04; HALO-AC3_20220328_P6_RF05; HALO-AC3_20220329_P6_RF06; HALO-AC3_20220330_P6_RF07; HALO-AC3_20220401_P6_RF08; HALO-AC3_20220404_P6_RF09; HALO-AC3_20220405_P6_RF10; HALO-AC3_20220408_P6_RF11; HALO-AC3_20220409_P6_RF12; HALO-AC3_20220410_P6_RF13; In-Situ Measurements; netCDF file; netCDF file (File Size); P6_231_HALO_2022_2203200401; P6_231_HALO_2022_2203220501; P6_231_HALO_2022_2203260702; P6_231_HALO_2022_2203280801; P6_231_HALO_2022_2203290901; P6_231_HALO_2022_2203301001; P6_231_HALO_2022_2204011101; P6_231_HALO_2022_2204041201; P6_231_HALO_2022_2204051301; P6_231_HALO_2022_2204081401; P6_231_HALO_2022_2204091501; P6_231_HALO_2022_2204101601; P6-231_HALO_2022; Polar 6; POLAR 6; SPP1294; Svalbard
    Type: Dataset
    Format: text/tab-separated-values, 12 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 42
    facet.materialart.
    Unknown
    Quasi-Lagrangian air mass matches during HALO-(AC)3: Matches occuring on the same day (2024)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: One of the main goals of the HALO-(AC)3 Arctic airborne campaign conducted in spring 2022 was a quasi-Lagrangian sampling of air masses. This means that the same air masses were to be sampled twice. Such a measurement strategy allows for concrete observations of air mass transformations, which can for example be used to benchmark weather models. After finishing the campaign, trajectory calculations were conducted for all flights of the HALO aircraft to check whether the flight strategy was a success. For this, the trajectory calculation tool Lagranto was used in conjunction with wind fields from the ERA5 reanalysis. Latter has an output resolution of around 30 km and one hour. The hourly data was bi-linearly interpolated to one minute resolution. Air masses were initialized temporally every one minute along the flight track of HALO, and vertically every 5 hPa between 250 hPa and 10 hPa above the ground level. Horizontally, air masses were started within a 30 km radius circle centered around the location of HALO. In each circle, 30 air masses were initialized evenly spaced approximately every 10 km, allowing for a better statistical analysis. Trajectories were then calculated in one-minute steps up to 10 hours forward in time. At typical HALO flight times of up to 10 hours, around 2.7 million trajectories were calculated per research flight. A quasi-Lagrangian match is registered if the same air mass is seen again below HALO at a later time of the same day and within the same 30 km radius. In order to allow air masses to evolve, a minimum temporal threshold of one hour was applied between matches.
    Keywords: AC; AC3; Aircraft; Arctic; Arctic Amplification; Date/Time of event; Event label; HALO; HALO_220312a; HALO_220313a; HALO_220314a; HALO_220315a; HALO_220316a; HALO_220320a; HALO_220321a; HALO_220328a; HALO_220329a; HALO_220330a; HALO_220401a; HALO_220404a; HALO_220407a; HALO_220408a; HALO_220410a; HALO_220411a; HALO_220412a; HALO_AC3; HALO-(AC)³; Image; Lagrangian data; Optional event label; RF02; RF03; RF04; RF05; RF06; RF07; RF08; RF09; RF10; RF11; RF12; RF13; RF14; RF15; RF16; RF17; RF18; Text file; trajectories
    Type: Dataset
    Format: text/tab-separated-values, 34 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 43
    facet.materialart.
    Unknown
    Radiance fields of clouds and the Arctic surface measured by a digital camera during HALO-(AC)3 (2024)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: During the HALO-(AC)3 campaign performed in March/April 2022 a downward-looking commercial digital camera equipped with a 180° - fisheye lens was installed on the aircraft Polar 5. Images of the Arctic surface and clouds were taken every 4 - 6 seconds. The data set provides rectified fields of calibrated radiances along the flight track for the three spectral bands (red, green, and blue).
    Keywords: AC; AC3; Aircraft; Arctic; Arctic Amplification; Arctic surface; clouds; DATE/TIME; Digital camera; Event label; HALO-(AC)³; HALO-AC3_20220320_P5_RF01; HALO-AC3_20220322_P5_RF03; HALO-AC3_20220325_P5_RF04; HALO-AC3_20220328_P5_RF05; HALO-AC3_20220329_P5_RF06; HALO-AC3_20220329_P5_RF07; HALO-AC3_20220330_P5_RF08; HALO-AC3_20220401_P5_RF09; HALO-AC3_20220404_P5_RF10; HALO-AC3_20220405_P5_RF11; HALO-AC3_20220407_P5_RF12; HALO-AC3_20220410_P5_RF13; images; netCDF file; netCDF file (File Size); Optional event label; P5_232_HALO_2022_2203200401; P5_232_HALO_2022_2203220602; P5_232_HALO_2022_2203250701; P5_232_HALO_2022_2203280801; P5_232_HALO_2022_2203290901; P5_232_HALO_2022_2203291002; P5_232_HALO_2022_2203301101; P5_232_HALO_2022_2204011201; P5_232_HALO_2022_2204041301; P5_232_HALO_2022_2204051401; P5_232_HALO_2022_2204071501; P5_232_HALO_2022_2204101601; P5-232_HALO_2022; POLAR 5; radiances
    Type: Dataset
    Format: text/tab-separated-values, 55 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 44
    facet.materialart.
    Unknown
    Yedoma domain Mineral Concentrations Assessment (YMCA) (2020)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: Mineral elements play a crucial role for organic carbon stabilization, which is key for organic carbon mineralization rates in soils. With thawing permafrost, especially in ice-rich regions such as the Yedoma domain, vast amounts of organic carbon previously stored in deep frozen deposits are unlocked and therefore available to undergo microbial mineralization leading to potential carbon dioxide and methane emissions. Mineral elements interfere with organic carbon degradation through various processes: i) mineral protection (aggregation, adsorption, and complexation) stabilizes organic carbon and mitigates its mineralization, and ii) change in mineral nutrients availability affects microorganisms growth and metabolic activity. Despite huge efforts to assess organic carbon stocks and lability in permafrost regions, there is a lack of studies on the mineral component assessment, which we aim to close with this dataset. Here, we provide a large-scale Yedoma domain Mineral Concentrations Assessment (YMCA) dataset of never thawed (since deposition) ice-rich Yedoma permafrost and previously thawed and partly refrozen Alas deposits. We used a portable X-ray fluorescence device (pXRF) for Si, Al, Fe, Ca, K, Ti, Mn, Zn, Sr and Zr concentration measurements on 1,292 sediment samples. Portable XRF measured concentrations trueness was calibrated using standard alkaline fusion and ICP-OES measurement from a subset of 144 samples (R² from 0.725 to 0.996). This methodology lead to the creation of the Yedoma domain Mineral Concentration Assessment (YMCA) dataset, a necessary step to estimate mineral element stocks in never thawed Yedoma and previously thawed Alas deposits. Practically, the YMCA dataset is organized as follow: (i) all site and sample properties: sample ID, type of deposit, site location, profile ID, GPS coordinates, country, lithology, unconsolidated sediment type, geological epoch, samples depth below surface level (b.s.l) or height above sea/river level (a.s.l), sediment characteristics, bulk density, gravimetric and absolute ice content, total organic carbon content; (ii) the Si, Al, Fe, Ca, K, Ti, Mn, Zn, Sr and Zr concentrations (corrected based on linear regressions) in Yedoma and Alas deposits (n=1292).
    Keywords: Alas; Aluminium; Calcium; Carbon, organic, total; Country; Density, bulk, permafrost; Deposit type; DEPTH, sediment/rock; Description; Epoch; Height above sea level; Ice content; Ice content, gravimetric; Iron; LATITUDE; Lithology/composition/facies; LONGITUDE; Manganese; Mineral element; Number; organic carbon; Permafrost; Portable X-ray fluorescence device; Potassium; Profile ID; pXRF; Sample code/label; Sample ID; Sediment type; Silicon; Site; Strontium; Titanium; Yedoma; Zinc; Zirconium
    Type: Dataset
    Format: text/tab-separated-values, 32624 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 45
    facet.materialart.
    Unknown
    Dissolved Organic Matter in the Upwelling System off Peru from METEOR cruises M136 and M138 (2020)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Keywords: Alanine; Amino acids, dissolved; Amino acids, dissolved, Carbon; Amino acids, dissolved, Nitrogen; Amino acids, free; Amino acids, free, Carbon; Amino acids, free, Nitrogen; Arabinose; Arginine; Aspartic acid and Asparagine; Carbohydrates, dissolved combined; Carbohydrates, dissolved combined, Carbon; Carbohydrates, dissolved combined, Nitrogen; Carbon, organic, dissolved; Chlorophyll a; Climate - Biogeochemistry Interactions in the Tropical Ocean; CTD/Rosette; CTD 002; CTD 004; CTD 006; CTD 010; CTD 012; CTD 013; CTD 017; CTD 019; CTD 023; CTD 028; CTD 032; CTD 036; CTD 039; CTD 043; CTD 044; CTD 046; CTD 047; CTD 050; CTD 053; CTD 055; CTD 058; CTD 059; CTD 061; CTD 063; CTD 065; CTD 066; CTD 071; CTD 073; CTD 074; CTD 076; CTD 080; CTD 082; CTD 087; CTD 088; CTD 091; CTD 092; CTD 095; CTD 101; CTD-RO; Date/Time of event; Degradation; Degradation index; DEPTH, water; Event label; Fucose; Galactosamine; Galactose; Galacturonic acid; gamma-Aminobutyric acid; Gluconic acid; Glucosamine; Glucose; Glucuronic acid; Glutamine and Glutamic acid; Glycine; Isoleucine; LATITUDE; Leucine; LONGITUDE; M136; M136_339-1; M136_358-1; M136_368-1; M136_393-1; M136_402-1; M136_422-1; M136_432-1; M136_435-1; M136_445-1; M136_456-1; M136_467-1; M136_472-1; M136_480-1; M136_491-1; M136_508-1; M136_516-1; M136_532-1; M136_547-1; M136_559-1; M136_567-1; M138; M138_880-1; M138_880-4; M138_882-10; M138_883-12; M138_884-1; M138_886-3; M138_888-7; M138_892-3; M138_894-4; M138_897-12; M138_898-1; M138_902-1; M138_904-16; M138_906-18; M138_907-7; M138_908-3; M138_912-11; M138_915-3; M138_919-1; Mannose/Xylose; Meteor (1986); Muramic acid; Nitrogen, inorganic, dissolved; Nitrogen, total dissolved; Oxygen; Phenylalanine; Profile ID; Rhamnose; Salinity; Sample code/label; Score on PC1; Serine; SFB754; Station label; Temperature, water; Threonine; Turnover rate, carbon; Tyrosine; Valine
    Type: Dataset
    Format: text/tab-separated-values, 19069 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 46
    facet.materialart.
    Unknown
    Metadata and NCBI-Accession numbers of the global Deep-sea Sponge Microbiome Project (2022)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: The Deep-sea Sponge Microbiome Project is a large-scale study, integrating 16S amplicon sequencing data of seawater, sediment, and sponges, with a large set of ecological and physical metadata. The present dataset includes NCBI-accession numbers, sample collection details, and diverse measurements, adding up to 50 entries for each of the 1546 covered samples.
    Keywords: Accession number, genetics; Ada Rebikoff; Agassiz Trawl; AGT; Alkalinity, total; Anchor dredge; Angeles Alvarino; ANT-XXXI/2 FROSN; Arctic Ocean; Area/locality; ARK-XXVII/2; ARK-XXX/3; ARK-XXXI/2; Azores2018; Bay of Biscay; BC; BEAM; Beam trawl; Bleiksdjupet; Bottle, Niskin; Bottom trawl; Box corer; BT; Campaign; Carbon, inorganic, particulate; Carbon, organic, dissolved; Carbon, organic, particulate; Carbon dioxide, total; Celtic Voyager; Class; Conductivity; CTD; CTD/Rosette; CTD1; CTD10; CTD11; CTD12; CTD13; CTD14; CTD15; CTD2; CTD3; CTD4; CTD5; CTD6; CTD7; CTD8; CTD9; CTD-RO; CV13012; CV13012_A; DATE/TIME; Deep-sea; Deep-sea Sponge Grounds Ecosystems of the North Atlantic; Density, sigma, in situ; DEPTH, water; derived from MODIS remote sensing data; Distance; Dive_041; Dive_042; Dive_043; Dive_044; Dive_045; Dive_046; DIVER; DR10; DR15; DR4; DR7; DR9; Dredge, chain bag; Dredge, rock; Dredge, triangle; DRG_A; DRG_C; DRG_R; Duse Bay; Event label; extracted from GLODAPv2.2020; extracted from the World Ocean Atlas 2018 (WOA18); Family; G. O. Sars (2003); Gear; Genus; Geological feature; Grab; GRAB; GS16A-202; GS2016109A; GS2016109A-01-CTD-01; GS2016109A-06-ROV-01; GS2016109A-09-BC-01; GS2016109A-10-BC-02; GS2016109A-14-CTD-02; GS2016109A-16-CTD-04; GS2016109A-18-CTD-06; GS2016109A-21-BC-05; GS2016109A-24-CTD-07; GS2016109A-26-CTD-09; GS2016109A-27-CTD-10; GS2016109A-28-CTD-11; GS2016109A-32-ROV-05; GS2016109A-33-AGT-01; GS2017110; GS2017110-02-ROV-02; GS2017110-03-CTD-01; GS2017110-04-CTD-02; GS2017110-05-ROV-03; GS2017110-06-ROV-04; GS2017110-08-ROV-05; GS2017110-09-ROV-6; GS2017110-15-CTD-05; GS2017110-16-ROV8; GS2017110-19-ROV10; GS2017110-22-BC-02; GS2017110-23-ROV12; GS2017110-26-CTD-08; GS2017110-28-CTD-10; GS2017110-30-CTD-12; GS2017110-34-ROV-15; GS2017110-40-ROV-18; GS2017110-41-ROV-19; GS2017110-42-CTD-16; GS2017110-44-BC-1; GS2017110-45-BC-2; GS2017110-46-BC-3; GS2017110-47-BC-4; GS2017110-50-CTD-19; GS2017110-54-CTD-20; GS2017110-57-AGT-01; GS2017110-59-CTD-21; GS2017110-60-BC-5; GS2017110-61-BC-6; GS2017110-62-BC-7; GS2017110-63-ROV-24; GS2017110-67-CTD-23; GS2017110-68-ROV-25; GS2017110-71-BC-8; GS2017110-72-BC-9; GS2017110-73-BC-10; GS2017110-74-ROV-26; GS2018108; GS2018108-01-ROV-01; GS2018108-02-CTD-01; GS2018108-03-ROV-02; GS2018108-04-ROV-03; GS2018108-05-CTD-02; GS2018108-07-ROV-05; GS2018108-08-ROV-06; GS2018108-12-CTD-03; GS2018108-13-CTD-04; GS2018108-14-CTD-05; GS2018108-17-AGT-01; GS2018108-19-ROV-12; GS2018108-22-CTD-07; GS2018108-23-ROV-15; GS2018108-25-ROV-17; GS2018108-29-CTD-09; GS2018108-30-CTD-10; GS2018108-31-CTD-11; GS2018108-34-ROV-22; GS2018108-37-CTD-12; GS2018108-39-ROV-26; GS2018108-43-ROV-30; GS2018108-44-ROV-31; GS2018108-46-ROV-33; GS2018108-48-CTD-13; GS2018108-55-CTD-14; GS2018108-58-ROV-43; GS2018108-62-CTD-15; GS2018108-63-ROV-47; GS2018108-64-ROV-48; GS2018108-66-CTD-16; GS2018108-70-ROV-50; GS2018108-77-CTD-24; GS2018108-78-ROV-52; GS2018108-79-ROV-53; Gulf of Bothnia, Baltic sea; H045_A; Hans Brattström; HB2016952; HB2016952_2; HB2016952_5; HB2016952_6; HB2016952_7; HB2016952_8; HB27102017_A; HB27102017_B; HB27102017_C; HB27102017a; HB27102017b; HUD16/19_010; HUD16/19_012; HUD16/19_013; HUD16/19_018; HUD16/19_020; HUD16/19_383; HUD16/19_387; HUD16/19_391; HUD16/19_392; HUD16/19_395; HUD2016019; Hudson; Identification; James Clark Ross; JR17003A; JR17003A_12; JR17003A_19; JR17003A_42; JR17003A_44; JR17003A_46-1; KB2017610; KB2017610_CTD7; KB2017610_KB-28; KB2017610_KB-32; KB2017610_KB-60; KB2017610_KB-61; KB2017610_ROV9; Korsfjord; Kristine Bonnevie; LATITUDE; LONGITUDE; LULA0718_Dive1; LULA0718_Dive2; LULA0718_Dive3; Malangsgrunnen; Maria S. Merian; Martha L. Black; meta-analysis; microbes; MLB2017001; MLB2017001_004; MLB2017001_005; MLB2017001_006; MLB2017001_015; MLB2017001_017; MLB2017001_020; MOOR; Mooring; MSM86; MSM86_006; MSM86_008; MSM86_009; MSM86_010; MSM86_012; MSM86_013; MSM86_015; MSM86_016; MSM86_019; MSM86_021; MSM86_022; MSM86_027; MSM86_028; MSM86_031; MSM86_032; MSM86_034; MSM86_035; MSM86_036; MSM86_038; MSM86_040; MSM86_041; MSM86_052; MSM86_054; MSM86_061; MSM86_062; MSM86_063; MSM86_067; MSM86_080; MSM86_081; MSM86_083; MSM86_086; MSM86_088; MSM86_090; MSM86_091; MSM86_094; MSM86_101; MSM86_106; Multicorer with television; NIS; Nitrate; Nitrogen, total dissolved; Nitrogen/Phosphorus ratio; North Greenland Sea; ocean; Ocean; Order; OT; OTNMoor_275; Otter trawl; Oxygen, apparent utilization; Oxygen, dissolved; Oxygen saturation; PAA2014007; PAA2014007_003; PAA2014007_056; PAA2014007_068; PAA2014007_070; PAA2014007_078; PAA2014007_079; PAA2014007_088; PAA2014007_110; PAA2014007_120; PAA2014007_123; PAA2014007_124; PAA2014007_125; PAA2014007_131; PAA2014007_133; PAA2014007_136; Paamiut; pH; Phosphate; Phylum; Polarstern; Pori Bac NewZ; Pressure, water; Prince Gustav Channel; Profile ID; Project; PS101; PS101/088-1; PS101/092-1; PS101/093-1; PS101/094-1; PS101/123-1; PS101/154-1; PS101/155-1; PS101/170-1; PS101/172-1; PS101/193-1; PS101/194-1; PS101/196-1; PS101/197-1; PS101/198-1; PS101/200-1; PS101/208-1; PS101/216-1; PS107; PS107_2-1; PS107_33-1; PS107_47-1; PS107_6-3; PS80; PS80/176-9; PS80/192-1; PS96; PS96/006-1; PS96/009-3; PS96/009-4; Realm; Remote operated platform for oceanography; Remote operated vehicle; ROPOS; ROPOS 2028; ROPOS 2029; ROPOS 2030; ROPOS 2034; ROV; Salinity; Sample type; Sampling by diver; Schultz Bank; Scotia; Scotia_0915S; Scotia_0915S_A; Scotia_0915S_B; Scotia_0915S_C; Scotia_0915S_D; Sea surface chlorophyll a; seawater; sediment; Silicate; Silicon/Phosphorus ratio; SO254; SO254_10-1; SO254_1-1; SO254_14-1; SO254_18-1; SO254_2-1; SO254_22-1; SO254_23-1; SO254_33-1; SO254_34-1; SO254_36-1; SO254_69-1; SO254_76-1; SO254_77-1; SO254_78-1; SO254_79-1; SO254_8-1; SO254_81-1; SO254_84-1; SO254_85-1; SO254_diver; Sognefjord; Sonne_2; South Atlantic Ocean; South Pacific Ocean; Species; sponge; SponGES; SponGES_0617; SPONGES_0617_04-DR4; SPONGES_0617_06-BT2; SPONGES_0617_07-CTD1; SPONGES_0617_09-DR5; SPONGES_0617_10-DR6; SPONGES_0617_12-CTD2; SPONGES_0617_13-CTD3; SPONGES_0617_15-DR7; SPONGES_0617_18-CTD4; SPONGES_0617_19-CTD5; SPONGES_0617_20-BT3; SPONGES_0617_23-DR9; SPONGES_0617_24-CTD6; SPONGES_0617_26-BT4; SPONGES_0617_27-CTD7; SPONGES_0617_28-DR10; SPONGES_0617_29-CTD8; SPONGES_0617_37-DR11; SPONGES_0617_38-DR12; SPONGES_0617_40-CTD9; SPONGES_0617_41-BT5; SPONGES_0617_42-CTD10; SPONGES_0617_43-BC1; SPONGES_0617_45-BC2; SPONGES_0617_46-CTD11; SPONGES_0617_47-BT6; SPONGES_0617_48-DR14; SPONGES_0617_49-CTD12; SPONGES_0617_50-BT7; SPONGES_0617_52-BT9; SPONGES_0617_53-BC3M1; SPONGES_0617_54-BT10; SPONGES_0617_55-CTD13; SPONGES_0617_56-BT11; SPONGES_0617_57-BT12; SPONGES_0617_58-CTD14; SPONGES_0617_59-BC4M1; SPONGES_0617_60-DR15; SPONGES_0617_61-CTD15; SPONGES_0617_63-DR16; Station label; Stjernsund; SUB; Submersible; Sula reef; TAD; Television-Grab; Temperature, water; Tromsoflaket East; Tromsøflaket; TVG; TVMUC; Uniform resource locator/link to reference; Vesteris; Water bodies; Weddell Sea; Zone
    Type: Dataset
    Format: text/tab-separated-values, 54242 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 47
    facet.materialart.
    Unknown
    Dissolved gas and dissolved inorganic nitrogen concentrations and isotopes during METEOR cruise M91 (2021)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: Seawater samples for stable isotopes measurements of nitrate (δ15NO3-) and nitrite (δ15NO2-) were taken from the CTD/rosette. δ15NO3- and δ15NO2- samples were either preserved frozen or an azide treatment was applied depending on the nitrite concentration (Altabet et al., 2012; Bourbonnais et al., 2015; Hu et al., 2016). The isotopic composition of both N-species was measured using the Cd reduction/azide method (McIlvin and Altabet, 2005).
    Keywords: Bottle number; Climate - Biogeochemistry Interactions in the Tropical Ocean; CTD/Rosette; CTD-002; CTD-003; CTD-005; CTD-006; CTD-008; CTD-010; CTD-012; CTD-013; CTD-016; CTD-017; CTD-018; CTD-019; CTD-021; CTD-022; CTD-024; CTD-026; CTD-028; CTD-033; CTD-034; CTD-035; CTD-036; CTD-038; CTD-039; CTD-041; CTD-044; CTD-046; CTD-048; CTD-049; CTD-050; CTD-051; CTD-052; CTD-053; CTD-054; CTD-058; CTD-059; CTD-060; CTD-061; CTD-062; CTD-063; CTD-064; CTD-065; CTD-066; CTD-067; CTD-068; CTD-069; CTD-070; CTD-073; CTD-074; CTD-075; CTD-076; CTD-078; CTD-079; CTD-080; CTD-081; CTD-082; CTD-083; CTD-084; CTD-085; CTD-086; CTD-087; CTD-088; CTD-089; CTD-090; CTD-091; CTD-092; CTD-093; CTD-094; CTD-097; CTD-RO; DATE/TIME; DEPTH, water; Event label; LATITUDE; LONGITUDE; M91; M91_1713-1; M91_1713-3; M91_1715-1; M91_1715-3; M91_1717-1; M91_1719-1; M91_1721-1; M91_1721-3; M91_1724-1; M91_1724-3; M91_1725-1; M91_1725-3; M91_1727-1; M91_1727-3; M91_1729-1; M91_1731-1; M91_1733-1; M91_1736-1; M91_1736-3; M91_1737-1; M91_1737-3; M91_1739-1; M91_1739-3; M91_1741-1; M91_1744-1; M91_1746-1; M91_1748-1; M91_1749-1; M91_1750-1; M91_1751-1; M91_1751-3; M91_1752-1; M91_1752-4; M91_1754-1; M91_1755-2; M91_1755-4; M91_1756-1; M91_1757-1; M91_1758-1; M91_1759-1; M91_1760-1; M91_1761-1; M91_1762-2; M91_1763-1; M91_1764-1; M91_1764-3; M91_1765-1; M91_1766-1; M91_1766-3; M91_1767-1; M91_1768-1; M91_1768-3; M91_1769-1; M91_1770-2; M91_1770-4; M91_1771-1; M91_1772-1; M91_1773-2; M91_1773-3; M91_1774-1; M91_1774-3; M91_1775-1; M91_1775-3; M91_1776-1; M91_1776-3; M91_1777-1; M91_1777-4; M91_1778-1; Meteor (1986); Nitrogen excess; Profile ID; SFB754; South Pacific Ocean; δ15N, nitrate; δ15N, nitrite; δ18O, nitrate; δ18O, nitrite
    Type: Dataset
    Format: text/tab-separated-values, 3789 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 48
    facet.materialart.
    Unknown
    Dissolved gas and dissolved inorganic nitrogen concentrations isotopes during METEOR cruise M90 (2021)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: Seawater samples for stable isotopes measurements of nitrate (δ15NO3-) and nitrite (δ15NO2-) were taken from the CTD/rosette. δ15NO3- and δ15NO2- samples were either preserved frozen or an azide treatment was applied depending on the nitrite concentration (Altabet et al., 2012; Bourbonnais et al., 2015; Hu et al., 2016). The isotopic composition of both N-species was measured using the Cd reduction/azide method (McIlvin and Altabet, 2005).
    Keywords: Bottle number; Climate - Biogeochemistry Interactions in the Tropical Ocean; CTD/Rosette; CTD 1; CTD 10; CTD 100; CTD 101; CTD 102; CTD 103; CTD 105; CTD 106; CTD 107; CTD 108; CTD 109; CTD 110; CTD 111; CTD 112; CTD 113; CTD 114; CTD 115; CTD 116; CTD 117; CTD 119; CTD 120; CTD 121; CTD 122; CTD 123; CTD 124; CTD 125; CTD 126; CTD 127; CTD 128; CTD 129; CTD 13; CTD 130; CTD 131; CTD 132; CTD 133; CTD 135; CTD 136; CTD 138; CTD 139; CTD 14; CTD 141; CTD 143; CTD 144; CTD 145; CTD 147; CTD 149; CTD 15; CTD 150; CTD 151; CTD 152; CTD 153; CTD 154; CTD 156; CTD 158; CTD 16; CTD 160; CTD 162; CTD 165; CTD 168; CTD 171; CTD 173; CTD 183; CTD 2; CTD 20; CTD 22; CTD 23; CTD 24; CTD 25; CTD 26; CTD 27; CTD 28; CTD 29; CTD 3; CTD 30; CTD 31; CTD 32; CTD 33; CTD 34; CTD 35; CTD 36; CTD 37; CTD 38; CTD 39; CTD 4; CTD 41; CTD 42; CTD 43; CTD 44; CTD 45; CTD 48; CTD 49; CTD 5; CTD 50; CTD 51; CTD 52; CTD 54; CTD 55; CTD 56; CTD 57; CTD 58; CTD 59; CTD 61; CTD 62; CTD 63; CTD 64; CTD 65; CTD 66; CTD 67; CTD 69; CTD 70; CTD 71; CTD 72; CTD 73; CTD 74; CTD 77; CTD 78; CTD 79; CTD 81; CTD 82; CTD 83; CTD 84; CTD 85; CTD 86; CTD 89; CTD 9; CTD 90; CTD 91; CTD 92; CTD 93; CTD 94; CTD 95; CTD 96; CTD 97; CTD 98; CTD 99; CTD-RO; DATE/TIME; DEPTH, water; Event label; LATITUDE; LONGITUDE; M90; M90_1552-1; M90_1553-1; M90_1554-1; M90_1555-1; M90_1555-2; M90_1559-1; M90_1560-1; M90_1563-1; M90_1563-2; M90_1564-1; M90_1565-1; M90_1569-1; M90_1571-1; M90_1572-1; M90_1572-2; M90_1573-1; M90_1574-1; M90_1575-1; M90_1576-1; M90_1577-1; M90_1577-2; M90_1578-1; M90_1579-1; M90_1580-1; M90_1581-1; M90_1581-2; M90_1582-1; M90_1583-1; M90_1583-2; M90_1584; M90_1586-1; M90_1587-1; M90_1588-1; M90_1589-1; M90_1590-1; M90_1593-1; M90_1594-1; M90_1595-1; M90_1596-1; M90_1596-2; M90_1598-1; M90_1599-1; M90_1600-1; M90_1600-2; M90_1601-1; M90_1602-1; M90_1604-1; M90_1604-2; M90_1605-1; M90_1606-1; M90_1607-1; M90_1608-1; M90_1608-2; M90_1610-1; M90_1611-1; M90_1612-1; M90_1612-2; M90_1613-1; M90_1614-1; M90_1617-1; M90_1618-1; M90_1619-1; M90_1621-1; M90_1621-2; M90_1622-1; M90_1623-1; M90_1624-1; M90_1625-1; M90_1628-1; M90_1628-2; M90_1629-1; M90_1630-1; M90_1631-1; M90_1632-1; M90_1633-1; M90_1634-1; M90_1635-1; M90_1636-1; M90_1637-1; M90_1638-1; M90_1639-1; M90_1639-2; M90_1640-1; M90_1642-1; M90_1643-1; M90_1644-1; M90_1645-1; M90_1646-1; M90_1646-2; M90_1647-1; M90_1648-1; M90_1649-1; M90_1650-1; M90_1651-1; M90_1652-1; M90_1652-2; M90_1654-1; M90_1655-1; M90_1656-1; M90_1656-2; M90_1657-1; M90_1658-1; M90_1659-1; M90_1659-2; M90_1660-1; M90_1661-1; M90_1661-2; M90_1662-1; M90_1663-1; M90_1664-1; M90_1664-2; M90_1666-1; M90_1666-2; M90_1668-1; M90_1668-2; M90_1670-1; M90_1672-1; M90_1673-1; M90_1673-1b; M90_1675-1; M90_1677-1; M90_1678-1; M90_1679-1; M90_1679-2; M90_1680-1; M90_1681-1; M90_1683-1; M90_1685-1; M90_1687-1; M90_1689-1; M90_1692-1; M90_1695-1; M90_1698-1; M90_1700-1; M90_1710-1; Meteor (1986); Nitrogen, biogenic; Nitrogen, biogenic, standard deviation; Nitrogen deficit; Nitrogen excess; Profile ID; SFB754; Standard deviation; δ15N, gas; δ15N, nitrate; δ15N, nitrite; δ15N, standard error; δ18O, nitrate; δ18O, nitrite
    Type: Dataset
    Format: text/tab-separated-values, 14903 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 49
    facet.materialart.
    Unknown
    Dissolved gas and dissolved inorganic nitrogen concentrations and isotopes during METEOR cruise M92 (2021)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: Seawater samples for stable isotopes measurements of nitrate (δ15NO3-) and nitrite (δ15NO2-) were taken from the CTD/rosette. δ15NO3- and δ15NO2- samples were either preserved frozen or an azide treatment was applied depending on the nitrite concentration (Altabet et al., 2012; Bourbonnais et al., 2015; Hu et al., 2016). The isotopic composition of both N-species was measured using the Cd reduction/azide method (McIlvin and Altabet, 2005).
    Keywords: Bottle number; Climate - Biogeochemistry Interactions in the Tropical Ocean; CTD/Rosette; CTD-006; CTD-007; CTD-008; CTD-009; CTD-010; CTD-011; CTD-012; CTD-013; CTD-014; CTD-015; CTD-016; CTD-017; CTD-018; CTD-019; CTD-020; CTD-021; CTD-022; CTD-023; CTD-024; CTD-025; CTD-026; CTD-027; CTD-028; CTD-030; CTD-031; CTD-032; CTD-033; CTD-034; CTD-035; CTD-036; CTD-037; CTD-038; CTD-039; CTD-040; CTD-041; CTD-042; CTD-043; CTD-044; CTD-045; CTD-046; CTD-047; CTD-048; CTD-049; CTD-050; CTD-051; CTD-052; CTD-053; CTD-054; CTD-055; CTD-056; CTD-057; CTD-058; CTD-059; CTD-060; CTD-061; CTD-062; CTD-063; CTD-064; CTD-065; CTD-066; CTD-067; CTD-068; CTD-069; CTD-070; CTD-071; CTD-072; CTD-073; CTD-074; CTD-075; CTD-076; CTD-077; CTD-078; CTD-079; CTD-080; CTD-081; CTD-082; CTD-083; CTD-084; CTD-RO; DATE/TIME; DEPTH, water; Event label; LATITUDE; LONGITUDE; M92; M92_0025-1; M92_0032-1; M92_0038-1; M92_0041-1; M92_0045-1; M92_0049-1; M92_0052-1; M92_0053-1; M92_0061-1; M92_0063-1; M92_0066-1; M92_0068-1; M92_0071-1; M92_0076-1; M92_0079-1; M92_0082-1; M92_0084-1; M92_0091-1; M92_0092-1; M92_0095-1; M92_0098-1; M92_0103-1; M92_0105-1; M92_0114-1; M92_0115-1; M92_0118-1; M92_0119-1; M92_0127-1; M92_0129-1; M92_0132-1; M92_0138-1; M92_0140-1; M92_0142-1; M92_0148-1; M92_0150-1; M92_0152-1; M92_0154-1; M92_0158-1; M92_0162-1; M92_0167-1; M92_0170-1; M92_0172-1; M92_0174-1; M92_0179-1; M92_0181-1; M92_0184-1; M92_0186-1; M92_0192-1; M92_0195-1; M92_0197-1; M92_0200-1; M92_0205-1; M92_0210-1; M92_0214-1; M92_0216-1; M92_0225-1; M92_0227-1; M92_0229-1; M92_0231-1; M92_0237-1; M92_0240-1; M92_0241-1; M92_0243-1; M92_0245-1; M92_0256-1; M92_0257-1; M92_0258-1; M92_0259-1; M92_0260-1; M92_0261-1; M92_0264-1; M92_0266-1; M92_0269-1; M92_0276-1; M92_0279-1; M92_0281-1; M92_0283-1; M92_0288-1; Meteor (1986); Nitrogen, biogenic; Nitrogen, biogenic, standard deviation; Nitrogen excess; Nitrogen excess, standard deviation; Profile ID; SFB754; δ15N, gas; δ15N, standard deviation
    Type: Dataset
    Format: text/tab-separated-values, 7894 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 50
    facet.materialart.
    Unknown
    Stable nitrate, nitrite and oxygen isotopes in seawater and particulate samples during METEOR cruise M93 (2021)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: Seawater samples for dual isotopes measurements of nitrate (δ15N_NO3 and δ18_NO3) and nitrite (δ15_NO2) were taken from the CTD-rosette. The isotopic composition was measured using the denitrifier method (Casciotti et al., 2002; Sigman et al., 2001).
    Keywords: Ammonium; Climate - Biogeochemistry Interactions in the Tropical Ocean; CTD/Rosette; CTD008; CTD013; CTD036; CTD045; CTD049; CTD053; CTD065; CTD069; CTD071; CTD076; CTD077; CTD080; CTD081; CTD082; CTD083; CTD120; CTD122; CTD130; CTD134; CTD138; CTD142; CTD143; CTD151; CTD157; CTD-RO; Date/Time of event; DEPTH, water; Event label; LATITUDE; LONGITUDE; M93; M93_295-2; M93_298-1; M93_303-2; M93_318-3; M93_324-1; M93_334-1; M93_338-1; M93_342-1; M93_354-1; M93_359-2; M93_361-2; M93_367-1; M93_368-1; M93_369-4; M93_376-2; M93_378-2; M93_380-3; M93_399-4; M93_411-6; M93_420-1; M93_422-1; M93_430-1; M93_436-1; M93_441-4; M93_448-5; M93_456-1; M93_463-1; M93_468-1; Meteor (1986); Nitrate; Nitrite; Nitrogen oxide; Number; Oxygen; Oxygen, dissolved; PCTD-RO; Phosphate; Profile ID; PumpCTD/Rosette; Sample code/label; SFB754; Silicate; South Pacific Ocean; Standard deviation; Station label; Temperature, water; δ13C, particulate organic carbon; δ15N; δ15N, nitrate; δ15N, nitrite; δ15N, particulate organic nitrogen; δ15N, standard deviation; δ18O; δ18O, standard deviation
    Type: Dataset
    Format: text/tab-separated-values, 3779 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 51
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    Unknown
    Hydrochemistry of water samples during METEOR cruise M106 (2021)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: Nutrient samples were frozen at -20˚C and transported to the home laboratory where they were measured using a QuAAtro gas segmented continuous flow analyzer (AutoAnalyzer) from SEAL Analytical. Particulate organic matter (POM) distribution in the water column was determined after filtration onto pre combusted, acid-washed GF/F filters (Franz et al., 2012a). For particulate organic carbon (POC) and particulate nitrogen (PN), filters were exposed to fuming hydrochloric acid for 12 h to remove carbonate and subsequently dried (60 °C, 12 h). Analyses were carried out with a Euro EA elemental analyser calibrated with an acetanilide standard. Particulate organic phosphorus (POP) collected on GF/F filters was determined colorimetrically as ortho-phosphate after potassium peroxydisulphate digestion following the method of Hansen and Koroleff (1999).
    Keywords: Bottle number; Carbon, organic, particulate; Climate - Biogeochemistry Interactions in the Tropical Ocean; CTD; CTD_1; CTD_10; CTD_100; CTD_101; CTD_102; CTD_103; CTD_104; CTD_105; CTD_106; CTD_107; CTD_108; CTD_109; CTD_11; CTD_110; CTD_111; CTD_112; CTD_113; CTD_114; CTD_115; CTD_116; CTD_117; CTD_118; CTD_12; CTD_13; CTD_14; CTD_15; CTD_16; CTD_17; CTD_18; CTD_19; CTD_2; CTD_20; CTD_21; CTD_22; CTD_23; CTD_24; CTD_25; CTD_26; CTD_27; CTD_28; CTD_29; CTD_3; CTD_30; CTD_31; CTD_32; CTD_33; CTD_34; CTD_35; CTD_36; CTD_37; CTD_38; CTD_39; CTD_4; CTD_40; CTD_41; CTD_42; CTD_43; CTD_44; CTD_45; CTD_46; CTD_47; CTD_48; CTD_49; CTD_5; CTD_50; CTD_51; CTD_52; CTD_53; CTD_55; CTD_56; CTD_57; CTD_58; CTD_59; CTD_6; CTD_60; CTD_61; CTD_62; CTD_63; CTD_64; CTD_65; CTD_66; CTD_67; CTD_68; CTD_69; CTD_7; CTD_70; CTD_71; CTD_72; CTD_73; CTD_74; CTD_75; CTD_76; CTD_77; CTD_78; CTD_79; CTD_8; CTD_80; CTD_81; CTD_82; CTD_83; CTD_84; CTD_85; CTD_86; CTD_87; CTD_88; CTD_89; CTD_9; CTD_90; CTD_91; CTD_92; CTD_93; CTD_94; CTD_95; CTD_96; CTD_97; CTD_98; CTD_99; CTD/Rosette; CTD-RO; DATE/TIME; DEPTH, water; Event label; Flag; LATITUDE; LONGITUDE; M106; M106_322-2; M106_322-3; M106_322-5; M106_326-1; M106_326-3; M106_327-1; M106_328-1; M106_329-1; M106_330-1; M106_331-1; M106_332-1; M106_333-1; M106_334-2; M106_335-1; M106_337-2; M106_337-4; M106_337-8/9; M106_338-1; M106_339-1; M106_340-2; M106_341-1; M106_342-1; M106_343-1; M106_344-1; M106_345-1; M106_347-1; M106_347-2; M106_349-1; M106_351-1; M106_352-2; M106_352-4; M106_352-7; M106_352-8; M106_354-1; M106_355-1; M106_356-1; M106_357-1; M106_357-3; M106_358-1; M106_359-1; M106_360-1; M106_360-2; M106_361-1; M106_362-1; M106_363-2; M106_364-1; M106_365-1; M106_366-4; M106_367-2; M106_368-1; M106_369-2; M106_371-1; M106_371-3; M106_372-1-CTD55; M106_372-3; M106_373-1; M106_374-1; M106_375-1; M106_376-1; M106_377-1; M106_378-1; M106_379-1; M106_380-1; M106_380-3; M106_381-1; M106_382-1; M106_383-1; M106_384-1; M106_385-1; M106_386-1; M106_387-1; M106_388-1; M106_389-1; M106_389-3; M106_390-1; M106_391-1; M106_392-1; M106_393-2; M106_394-1; M106_395-1; M106_396-1; M106_397-1; M106_398-1; M106_403-1; M106_404-1; M106_405-1; M106_406-1; M106_407-1; M106_410-1; M106_411-1; M106_411-3; M106_412-1; M106_413-1; M106_414-1; M106_415-1; M106_416-2; M106_417-1; M106_418-1; M106_419-1; M106_420-1; M106_421-1; M106_422-1; M106_423-1; M106_424-1; M106_424-2; M106_425-1; M106_426-1; M106_427-1; M106_428-1; M106_428-2; M106_429-1; M106_430-1; M106_431-1; M106_432-1; M106_432-3; M106_433-1; M106_434-1; Meteor (1986); Nitrate; Nitrate and Nitrite; Nitrite; Nitrogen, organic, particulate; Oxygen; Phosphate; Phosphorus, organic, particulate; Pressure, water; Profile ID; Salinity; Sample code/label; SFB754; Silicate; Temperature, water; Titration, Winkler
    Type: Dataset
    Format: text/tab-separated-values, 21496 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 52
    facet.materialart.
    Unknown
    Ozone sonde profiles during MOSAiC Leg 4-5 (2022)
    PANGAEA
    In:  Alfred Wegener Institute - Research Unit Potsdam
    Details
    Publication Date: 2024-06-10
    Description: Vertical profiles of ozone (up to 36 km) measured by ozone sondes (manufactured by Science Pump Corporation) launched during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition (leg 4 - 5) from board R/V Polarstern in the Arctic sea between 12 June and 28 Sept 2020. Additionally, temperature, pressure, relative humidity and wind profiles are provided as level 2 data from the Vaisala RS41 radiosonde measurements. The ozone measurements complement the suit of measurements at the ground and the boundary layer of the atmosphere during the campaign.
    Keywords: ALTITUDE; Arctic Ocean; Atmosphere; Battery, voltage; Calculated from GPS; DATE/TIME; Elapsed time; Event label; GPS receiver mounted on radiosonde RS41; Height, geometric; Humidity, relative; integrated from pressure and temperature; LATITUDE; LONGITUDE; Mosaic; MOSAiC; MOSAiC20192020; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Ozone, partial pressure; Ozone, raw current; ozone sonde; Ozonesonde, Science Pump Corporation, ECC6A; Interface, Vaisala, OIF411; Polarstern; Pressure, at given altitude; Profile ID; PS122/4; PS122/4_44-100; PS122/4_44-152; PS122/4_44-229; PS122/4_44-57; PS122/4_45-128; PS122/4_46-145; PS122/4_47-116; PS122/4_48-172; PS122/4_50-5; PS122/4_50-70; PS122/5; PS122/5_59-262; PS122/5_59-70; PS122/5_60-29; PS122/5_61-98; PS122/5_62-82; PS122/5_63-120; Pump current; RADIO; Radiosonde; Radiosonde, Vaisala, RS41; Temperature, air; Temperature, internal pump; vertical profiles; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 1302028 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 53
    facet.materialart.
    Unknown
    Local snow dunes / sastrugi heights across the plateau of Dronning Maud Land, East Antarctica (2023)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: Local snow surface heights were sampled in December 2018 across a traverse of ~ 100 km near Kohnen Station. They were used to quantify surface roughness and its relation to stratigraphic noise in isotope records from firn cores. At six different locations (D2, C4, C5, D7, D24, D38) snow heights were measured along the positioning of the firn cores (along 60 m), with a 1-2 m horizontal resolution and an accuracy of ∓ 1 cm using a Geodät levelling device. The measurements were done perpendicularly to the overall large scale wind direction.
    Keywords: 2018_Kohnen_C4; 2018_Kohnen_C5; 2018_Kohnen_D2; 2018_Kohnen_D24; 2018_Kohnen_D38; 2018_Kohnen_D7; Antarctica; AWI_Envi; AWI_SPACE; Dronning Maud Land; Dunes; East Antarctic plateau; Event label; FIRNC; Firn corer; Kohnen_based; Kohnen Station; Location ID; Polar Terrestrial Environmental Systems @ AWI; Position; Profile ID; sastrugi; snow height; Snow height; Space-time structure of climate change @ AWI
    Type: Dataset
    Format: text/tab-separated-values, 858 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 54
    facet.materialart.
    Unknown
    2D multichannel seismic reflection processed data (GI Gun entire dataset) of RV METEOR during cruise M94, Campeche Bank, Gulf of Mexico (2023)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: Seismic reflection data were collected during RV METEOR expedition M94 in 2013 (Hübscher et al., 2014) at the eastern Campeche Bank in the southern Gulf of Mexico. The source signal was generated by two GI-Guns with generator volumes of 45 in3 and injector volumes of 105 in3. Both BI-Guns were operated in true "GI-Mode". The 16-channel analog streamer had an active length of 100 m. Sample rate was 1 ms. The weather conditions were rather harsh, so noise level was high. The undamped passband of the frequency filter was between 20 and 200 Hz. Further processing steps included predictive deconvolution, spherical divergence correction, stacking, time-migration, white-noise suppression by the technique described by Butler (2012) as implemented in Schlumbergers VISTA® processing package, and fx-deconvolution. The purpose was to image mass failures at the eastern rim of the Campeche Bank as the consequence of the Chicxulub meteorite impact at the Cretaceous-Paleogene boundary, and the plastered contourite drift that developed at the collapsed carbonate platform. The data are uploaded as SEG-Y data. Shot, receiver and CMP coordinates are in UTM27 at standard binary positions.
    Keywords: Binary Object; Campeche Bank; Common Midpoint; Event label; Extracted from file; Gulf of Mexico; M94; M94_472; M94_479; M94_483; M94_485; MCSEIS; Meteor (1986); Multichannel seismics; Profile/sampling length; Profile ID; Seismic reflection data; Start of data file recording, date/time; Start of data file recording, latitude; Start of data file recording, longitude; Stop of data file recording, date/time; Stop of data file recording, latitude; Stop of data file recording, longitude
    Type: Dataset
    Format: text/tab-separated-values, 90 data points
    Location Call Number Expected Availability
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  • 55
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    Unified Airborne Active and Passive Microwave Measurements over Arctic Sea Ice and Ocean during the HALO-(AC)³ Campaign in Spring 2022 (2023)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: The Halo Microwave Package (HAMP), deployed onboard the High Altitude and LOng range research aircraft (HALO), performed measurements over the Arctic ocean and sea-ice during the HALO-(AC)³ campaign in March and April 2022. After the transfer flight (RF01) from Oberpfaffenhofen (Germany), 17 research flight (RF) days started from Kiruna, Sweden and heading northwards to the Fram Strait and central Arctic. Here, HAMP measurements were taken in different weather conditions comprising high impact synoptic events such as warm air intrusions, atmospheric rivers, cold air outbreaks or polar lows. We provide a dataset of active and passive microwave HAMP measurements, i.e. from the cloud and precipitation radar and the radiometers respectively. The radar operates at a frequency of 35 GHz while the microwave radiometer measurements comprise 25 channels in the frequency range between 22 and 190 GHz. Our dataset delivers time-series of brightness temperatures from the radiometers, and the radar reflectivity factor and linear depolarization ratio from the radar in a unified format. The unified and processed dataset provides the post-calibrated and quality-controlled measurements from both devices in a collocated temporal 1 Hz resolution applicable for joint analysis. An adherent surface mask distinguishes between three predominant overpassed surface types (land, sea, and sea-ice). The radar measurements are further unified in a vertical grid having 30 m resolution. Our unified dataset allows for wide-spread analysis of evolving arctic cloud and moisture properties over the remote Arctic ocean.
    Keywords: AC; AC3; Airborne Data; Aircraft; Arctic Amplification; Arctic clouds; Atmospheric and Earth System Research with HALO – High Altitude and Long Range Research Aircraft; Date/Time of event; Event label; HALO; HALO_220311a; HALO_220312a; HALO_220313a; HALO_220314a; HALO_220315a; HALO_220316a; HALO_220320a; HALO_220321a; HALO_220328a; HALO_220329a; HALO_220330a; HALO_220401a; HALO_220404a; HALO_220407a; HALO_220408a; HALO_220410a; HALO_220411a; HALO_220412a; HALO_AC3; HALO-(AC)³; Image; microwave radiometer; Microwave Radiometer; MRA; netCDF file; radar; Radar; RF01; RF02; RF03; RF04; RF05; RF06; RF07; RF08; RF09; RF10; RF11; RF12; RF13; RF14; RF15; RF16; RF17; RF18; SPP1294
    Type: Dataset
    Format: text/tab-separated-values, 72 data points
    Location Call Number Expected Availability
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  • 56
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    Airborne in-situ measurement of particle number concentration and size distribution using an optical particle counter during HALO-AC3 (2023)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: During the HALO-(AC)³ campaign in March/ April 2022, in-situ particle number concentration and size distribution of ambient aerosol particles and cloud residual particles were measured using a Grimm Sky OPC (model 1.129 Sky-OPC). This data set provides the particle size distribution divided in 31 size bins between 0.25 µm and 40 µm. Particle number concentrations are pressure-corrected to standard temperature and pressure (STP). The time resolution of the instrument is 6 seconds. Each data point is given at the end of the corresponding measurement interval.
    Keywords: AC; AC3; aerosol; Aircraft; Arctic; Arctic Amplification; Date/Time of event; Event label; Grimm Sky Optical Particle Counter (model 1.129 Sky-OPC); HALO - (AC)3; HALO-(AC)³; HALO-AC3_20220320_P6_RF01; HALO-AC3_20220322_P6_RF02; HALO-AC3_20220324_P6_RF03; HALO-AC3_20220326_P6_RF04; HALO-AC3_20220328_P6_RF05; HALO-AC3_20220329_P6_RF06; HALO-AC3_20220330_P6_RF07; HALO-AC3_20220401_P6_RF08; HALO-AC3_20220404_P6_RF09; HALO-AC3_20220405_P6_RF10; HALO-AC3_20220408_P6_RF11; HALO-AC3_20220409_P6_RF12; HALO-AC3_20220410_P6_RF13; netCDF file; netCDF file (File Size); OPC; Optional event label; P6_231_HALO_2022_2203200401; P6_231_HALO_2022_2203220501; P6_231_HALO_2022_2203240601; P6_231_HALO_2022_2203260702; P6_231_HALO_2022_2203280801; P6_231_HALO_2022_2203290901; P6_231_HALO_2022_2203301001; P6_231_HALO_2022_2204011101; P6_231_HALO_2022_2204041201; P6_231_HALO_2022_2204051301; P6_231_HALO_2022_2204081401; P6_231_HALO_2022_2204091501; P6_231_HALO_2022_2204101601; P6-231_HALO_2022; Polar 6; POLAR 6
    Type: Dataset
    Format: text/tab-separated-values, 13 data points
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  • 57
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    Aircraft-based measurement of particle size and chemical composition for individual aerosol particles during the HALO-AC3 campaign 2022 (2023)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: This data set contains in-situ analysis of individual particles measured during HALO-(AC)³ in March/April 2022. Using the single particle aerosol mass spectrometer ALABAMA, particle size and chemical composition of single particles were analyzed onboard of the research aircraft Polar 6. The data provides time, location, particle size (if available), an integer value inlet_pos as indicator for the position of the ALABAMA inlet switch (2: CVI inlet, 4: standard aerosol inlet) as well as counts of different cluster types for each analyzed particle. The 38 clusters were determined by using a fuzzy-c-means algorithm, a method for grouping data points with similar signal pattern. The key chemical species of each cluster are given in the longname version of the cluster variables in the data files. A detailed description of the data processing will be done in an upcoming data paper.
    Keywords: AC; AC3; aerosol; Aircraft; Aircraft-based laser ablation aerosol mass spectrometer (ALABAMA); ALABAMA; Arctic; Arctic Amplification; Date/Time of event; Event label; HALO - (AC)3; HALO-(AC)³; HALO-AC3_20220320_P6_RF01; HALO-AC3_20220322_P6_RF02; HALO-AC3_20220324_P6_RF03; HALO-AC3_20220328_P6_RF05; HALO-AC3_20220329_P6_RF06; HALO-AC3_20220330_P6_RF07; HALO-AC3_20220401_P6_RF08; HALO-AC3_20220404_P6_RF09; HALO-AC3_20220405_P6_RF10; HALO-AC3_20220408_P6_RF11; HALO-AC3_20220409_P6_RF12; HALO-AC3_20220410_P6_RF13; netCDF file; netCDF file (File Size); Optional event label; P6_231_HALO_2022_2203200401; P6_231_HALO_2022_2203220501; P6_231_HALO_2022_2203240601; P6_231_HALO_2022_2203280801; P6_231_HALO_2022_2203290901; P6_231_HALO_2022_2203301001; P6_231_HALO_2022_2204011101; P6_231_HALO_2022_2204041201; P6_231_HALO_2022_2204051301; P6_231_HALO_2022_2204081401; P6_231_HALO_2022_2204091501; P6_231_HALO_2022_2204101601; P6-231_HALO_2022; Polar 6; POLAR 6
    Type: Dataset
    Format: text/tab-separated-values, 12 data points
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  • 58
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    Ice Thickness from downstream of the EastGRIP ice core site, North East Greenland Ice Stream, recorded with the airborne AWI UWB radar system (2023)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: This project aims to acquire airborne data with AWI's UWB (ultrawideband) ice-penetrating radar to extend the knowledge of detailed subglacial topography downstream of the EastGRIP ice core site, following on from a previous UWB radar survey in 2018. The ice thickness data also opportunistically includes profiles that were flown in different survey modes, both upstream and surrounding EastGRIP. The majority of profiles are oriented parallel or perpendicular to ice flow direction.
    Keywords: AC; Aircraft; Arctic; AWI UWB; Date/Time of event; East Greenland Ice-core Project; EGRIP; Event label; ice thickness; Ice thickness; Ice thickness, uncertainty; LATITUDE; LONGITUDE; NEGIS-FLOW, NEGIS-ANISO, NEGIS Folds; North East Greenland Ice Stream (NEGIS); P5_233_NEGIS_2022_2206030202; P5_233_NEGIS_2022_2206070301; P5_233_NEGIS_2022_2206080401; P5_233_NEGIS_2022_2206090501; P5_233_NEGIS_2022_2206100601; P5_233_NEGIS_2022_2206110701; P5_233_NEGIS_2022_2206120801; P5_233_NEGIS_2022_2206130901; P5_233_NEGIS_2022_2206161001; P5-233_NEGIS_2022; POLAR 5; Profile ID; radio echo-sounding; Time in seconds; Trace Number; Two-way traveltime; Ultra-wideband radar (UWB), MCoRDS 5
    Type: Dataset
    Format: text/tab-separated-values, 4228281 data points
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  • 59
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    Mid- Holocene stable isotope records (ẟ18O and ẟ13C) of speleothem VEAJ from Alfredo Jahn Cave, northern Venezuela (2023)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: The stable isotope records for mid- and late- Holocene are based on two stalagmites, VEAJ collected in Alfredo Jahn cave and VECA collected in Caripe Cave, respectively. Both caves are located in northern Venezuela, adjacent to Cariaco Basin. The ẟ18O record was interpreted as a proxy for the proximity of the Intertropical Convergence Zone (ITCZ) to our study sites, and the ẟ13C record as a proxy for vegetation changes, as discussed in the paper 'Atlantic ITCZ variability during the Holocene based on high-resolution speleothem isotope records from northern Venezuela' (Medina et al., 2023). The ẟ18O and ẟ13C analyses were performed at the Stable Isotope Laboratory at the Institute of Geoscience of the University of São Paulo (Brazil) using a Thermo-Finnigan Delta Plus Advantage mass spectrometer. ẟ-notation in per mil units (‰) was used to express the sample isotopic ratios deviation from the Vienna Pee Dee Belemnite (VPDB) standard. Approximately 200 μg of CaCO3-powder subsamples for ẟ18O and ẟ13C stable isotopic analyses were collected using a manually controlled Sherline 5400 milling at a resolution of 0.4 mm for VEAJ and 0.5 mm for VECA. The ẟ18O and ẟ13C isotopic profiles of VEAJ-base, VEAJ-top left and VEAJ-top right are based on 530, 310 and 250 samples, respectively. VECA isotopic profiles consist of 670 samples. Since VEAJ-top left overlaps with some sections of the -top right record, we merged them through normalization (i.e., by subtracting the mean and dividing by the standard deviation) of the data inside the overlapping period, averaging both series and then reconstructing the shorter time series with the mean and standard deviation of the longer one. The geochronology was established by means of the U/Th dating method, using a multicollector inductively-coupled plasma mass spectrometers (MC-ICP-MS-Thermo-Finnigan NEPTUNE) at the Institute of Global Environmental Change, Xi'an Jiaotong University (China). The sampling for the U/Th dating was performed by extracting ~0.100 g of powdered carbonate with a handheld drill of the least porous and colored, most traceable layers along or at the side of each speleothem growth axis. A total of 42 U/Th ages were used to construct the age model for VEAJ and 25 for VECA, yielding an mean temporal stable isotope sampling resolutions of 3 and 23 years for VEAJ-base & top-composite, respectively, and 1.5 years for VECA. Some age reversals along the stalagmites were flagged as outliers using Bayesian statistics, and consequently removed from the age models. For other age inversions, an iterative procedure was applied to increase the range of uncertainty in order to fulfill the monotonicity criterion (Scholz and Hoffmann, 2011).
    Keywords: AGE; Age, dated; Age, dated standard error; Age, Uranium-Thorium; Alfredo Jahn cave; Cariaco Basin; Caribbean; d13C; d18O; DISTANCE; Holocene climate; Intertropical Convergence Zone (ITCZ); Mass spectrometer Thermo Finnigan DELTA plus Advantage; paleoenvironment; Profile ID; Speleothems; Speleothem sample; SPS; stable isotope data; VEAJ; Venezuela; δ13C, carbonate; δ18O, carbonate
    Type: Dataset
    Format: text/tab-separated-values, 2562 data points
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  • 60
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    Nevzorov LWC and TWC data from the HALO-AC3 campaign in March and April 2022 (2024)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: Liquid water content and total water content from the Nevzorov probe, collected during the HALO-AC³ campaign out of Longyearbyen, Svalbard in April 2022. The dataset contains measurements from the three collector sensors of the Nevzorov probe. These are the cylindrical LWC sensor, the 8 mm TWC cone and the 12 mm TWC cone (for a description of the probe see doi:10.1175/1520-0426(1998)015〈1495:TNAHWL〉2.0.CO;2, doi:10.5194/egusphere-2022-647 ). Furthermore, corrected LWC and TWC values are contained in the dataset. These values are best estimates of LWC and TWC. They are computed by solving a system of equations and they consider collection efficiencies, the different latent heats of water and ice and the sensitivity of the LWC sensor to ice particles. For a description of the computation see Lucke et al. (2023) (doi:10.4271/2023-01-1485). However, for this data, the 12 mm cone was not included in the computation, as its data were deemed to be too unreliable in conditions where droplet diameters are low. NaNs are represented as 9999.999 in the dataset. The dataset only contains research flight 8 - 13. For the previous flights a problem with the probe existed and no data was recorded.
    Keywords: AC; Aircraft; Arctic; Arctic Amplification; Date/Time of event; Event label; HALO - (AC)3; HALO-(AC)³; HALO-AC3_20220401_P6_RF08; HALO-AC3_20220404_P6_RF09; HALO-AC3_20220405_P6_RF10; HALO-AC3_20220408_P6_RF11; HALO-AC3_20220409_P6_RF12; HALO-AC3_20220410_P6_RF13; ice water content; IWC; liquid water content; LWC; mixed-phase clouds; netCDF file; netCDF file (File Size); NEVZ; Nevzorov probe; P6_231_HALO_2022_2204011101; P6_231_HALO_2022_2204041201; P6_231_HALO_2022_2204051301; P6_231_HALO_2022_2204081401; P6_231_HALO_2022_2204091501; P6_231_HALO_2022_2204101601; P6-231_HALO_2022; Polar 6; POLAR 6; Polarimetric Radar Observations meet Atmospheric Modelling (PROM) - Fusion of Radar Polarimetry and Numerical Atmospheric Modelling Towards an Improved Understanding of Cloud and Precipitation Processes; SPP2115_PROM; Svalbard; total water content; TWC
    Type: Dataset
    Format: text/tab-separated-values, 6 data points
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  • 61
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    Aircraft measurements of backscatter ratio, particle depolarization and water vapour molecular density profiles over Arctic sea ice and ocean during the HALO-(AC)³ campaign in spring 2022 (2024)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: During the HALO-(AC)³ campaign in March and April 2022 downward looking lidar profiles were measured onboard of the High Altitude LOng range research aircraft (HALO) over the Arctic sea ice and ocean using the airborne demonstrator for the WAter vapour Lidar Experiment in Space (WALES). The data set gives time series of profiles of backscatter ratio, particle depolarization and water vapour molecular density measured along the flight path of HALO on 17 days. All flights started from Kiruna, Sweden and headed into the Fram Straight and towards the central Arctic. The goal of the campaign was to study warm air intrusions and cold air outbreaks to and from the Arctic and to follow those air masses over several days with remote sensing instrumentation aboard HALO. The first research flight (RF) was RF02. RF01 was the transfer flight from Oberpfaffenhofen, Germany to Kiruna. Backscatter ratio and aerosol depolarization data is given with at one second time resolution and 15 m vertical binning at a wavelength of 532 nm. The backscatter profiles are extinction corrected using the High Spectral Resolution Lidar (HSRL) method. The water vapour profiles have a time resolution of 12 s and a vertical binning of 15 m. For H2O the vertical resolution is lower than given by the binning, where the real resolution is determined by an averaging kernel which is constant over height and has a full width at half maximum (FWHM) of 250 m. All data is regridded to a constant altitude scale over mean sea level, irrespective of the actual flight altitude.
    Keywords: AC; AC3; airborne measurements; Aircraft; Arctic; Arctic Amplification; Atmospheric and Earth System Research with HALO – High Altitude and Long Range Research Aircraft; Date/Time of event; Event label; File content; HALO; HALO_220312a; HALO_220313a; HALO_220314a; HALO_220315a; HALO_220316a; HALO_220320a; HALO_220321a; HALO_220328a; HALO_220329a; HALO_220330a; HALO_220401a; HALO_220404a; HALO_220407a; HALO_220408a; HALO_220410a; HALO_220411a; HALO_220412a; HALO_AC3; HALO-(AC)³; Lidar; LiDAR; netCDF file; netCDF file (File Size); Remote sensing (Light detection and ranging, LiDAR); RF02; RF03; RF04; RF05; RF06; RF07; RF08; RF09; RF10; RF11; RF12; RF13; RF14; RF15; RF16; RF17; RF18; SPP1294
    Type: Dataset
    Format: text/tab-separated-values, 102 data points
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  • 62
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    Predicted subglacial lakes in Antarctica (2023)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: This data set comprises the geographical coordinates of modelled outlines of 31 new subglacial lakes in Dronning Maud Land, Antarctica, using the general hydraulic potential equation (Shreve 1972), Bedmap2 data sets (Fretwell and others, 2013), and AWI airborne radio-echo sounding data collected between 1994–2013. The modelling was conducted in 2015 using the Bedmap2 bedrock topography and ice thickness data (Fretwell and others, 2013) at 5 km grid cell size. Determined sinks in the hydraulic potential were checked for coverage by AWI airborne radio-echo sounding data. Based on the structure of the subglacial reflexions, sinks were classified as subglacial lakes. The outline of like that identified subglacial lakes are presented here. Not all calculated sinks were covered by AWI airborne radio-echo sounding data.
    Keywords: Antarctica; Helmholtz-Verbund Regionale Klimaänderungen = Helmholtz Climate Initiative (Regional Climate Change); Identification; LATITUDE; LONGITUDE; Modelling; Profile ID; REKLIM; Shot number range; subglacial lakes; Text file; Text file (File Size)
    Type: Dataset
    Format: text/tab-separated-values, 208 data points
    Location Call Number Expected Availability
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  • 63
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    Locations and thickness of sediment-laden basal ice zones at Jutulstraumen Glacier onset (East Antarctica) (2024)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: Understanding the material properties and physical conditions of basal ice is crucial for a comprehensive understanding of Antarctic ice-sheet dynamics. Yet, direct data are sparse and difficult to acquire, necessitating geophysical data for analysis. Here, we employed high-resolution ultra-wideband radar to map high-backscatter zones near the glacier bed within East Antarctica's Jutulstraumen drainage basin. Our results revealed that the basal ice in an area of ~ 10,000 square kilometers is composed of along-flow oriented sediment-laden basal ice units connected to the basal substrate, extending up to several hundred meters of thickness. Three-dimensional thermomechanical modeling suggests these units formed via basal freeze-on of subglacial water originating further upstream. Our findings suggest that basal freeze-on, and the entrainment and transport of subglacial material play a significant role for an accurate representation of material, physical, and rheological properties of the Antarctic ice sheet's basal ice, ultimately enhancing the accuracy and reliability of ice-sheet modeling. Here, we publish locations and thickness of high-backscatter zones at the onset of the Jutulstraumen glacier in East Antarctica.
    Keywords: 20197001_002; 20197002_003; 20197002_005; 20197002_007; 20197002_009; 20197002_011; 20197002_012; 20197003_004; 20197003_006; 20197003_008; 20197003_010; 20197004_001; 20197004_003; 20197004_004; 20197005_001; 20197006_001; 20197006_002; 20197006_004; 20197006_006; 20197007_005; AC; Aircraft; Antarctica; basal freeze-on; basal ice; DML_20197001_002; DML_20197002_003; DML_20197002_005; DML_20197002_007; DML_20197002_009; DML_20197002_011; DML_20197002_012; DML_20197003_004; DML_20197003_006; DML_20197003_008; DML_20197003_010; DML_20197004_001; DML_20197004_003; DML_20197004_004; DML_20197005_001; DML_20197006_001; DML_20197006_002; DML_20197006_004; DML_20197006_006; DML_20197007_005; Event label; High backscatter zone, thickness; JuRaS, CHIRP; Jutulstraumen; LATITUDE; LONGITUDE; P6_215_UWB_2018_1812220301; P6_215_UWB_2018_1812260501; P6_215_UWB_2018_1812260602; P6_215_UWB_2018_1812270701; P6_215_UWB_2018_1812270802; P6_215_UWB_2018_1812300901; P6-215_UWB_2018; POLAR 6; Profile ID; radio-echo sounding; Radio-echo sounding; RES; Season; Subglacial sediments; Trace Number
    Type: Dataset
    Format: text/tab-separated-values, 101008 data points
    Location Call Number Expected Availability
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  • 64
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    Physical oceanography of a 24 hours vertical yo-yo CTD cast during METEOR cruise M183 (2023)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: Physical oceanography data was acquired by a ship-based CTD-Rosette-System onboard RV METEOR during research cruise M183. A 24 hours yo-yo CTD cast was performed with a total of 20 vertical profiles.
    Keywords: AIMS3; CDRmare; Conductivity; CTD, SEA-BIRD SBE 9 plus; CTD/Rosette; CTD profiles; CTD-RO; DAM CDRmare - AIMS3: Alternate scenarios, Innovative technologies, and Monitoring approaches for Sub-Seabed Storage of carbon dioxide; DATE/TIME; DEPTH, water; Dissolved Oxygen Sensor, Sea-Bird, SBE 43; GeoB25135-1; LATITUDE; LONGITUDE; M183; M183_35-1; Meteor (1986); Mid-Atlantic Ridge; Oxygen; Oxygen saturation; Pressure, water; Profile ID; Research Mission of the German Marine Research Alliance (DAM): Marine carbon sinks in decarbonisation pathways; RIFLOR_1; Salinity; Station label; Temperature, water
    Type: Dataset
    Format: text/tab-separated-values, 651880 data points
    Location Call Number Expected Availability
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  • 65
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    Radar reflectivities at 94 GHz and microwave brightness temperature measurements at 89 GHz during the HALO-AC3 Arctic airborne campaign (2024)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: The published data set consists of measurements performed by the active cloud radar as part of the Microwave Radar and radiometer for Arctic Clouds (MiRAC; Mech et al., 2019) operated on board the Polar 5 research aircraft during 11 flights of the HALO-AC3 airborne campaign, carried out in early spring 2022 northwest of Svalbard (Norway). The measurement campaign is embedded in the Transregional Collaborative Research Centre TR 172 (ArctiC Amplification: Climate Relevant Atmospheric and SurfaCe Processes, and Feedback Mechanisms (AC)3. The published data set consists of radar reflectivities of the FMCW 94 GHz cloud radar transformed to nadir view and brightness temperature measurements at 89 GHz with a 25 deg backward inclination with respect to the aircraft's fuselage. It should be considered that the brightness temperatures have not been corrected for aircraft attitude. The data set has been quality-checked and is available in NetCDF format for each flight separately. Details on the instrument can be found in Mech et al. (2019).
    Keywords: AC; AC3; airborne; Aircraft; Arctic; Arctic Amplification; brightness temperature; clouds; CloudSat; CloudSat cloud-profiling radar; Date/Time of event; Doppler cloud radar, Radiometer Physics GmbH, RPG-FMCW-94-SP; Event label; HALO-AC3_20220320_P5_RF01; HALO-AC3_20220322_P5_RF03; HALO-AC3_20220325_P5_RF04; HALO-AC3_20220328_P5_RF05; HALO-AC3_20220329_P5_RF07; HALO-AC3_20220330_P5_RF08; HALO-AC3_20220401_P5_RF09; HALO-AC3_20220404_P5_RF10; HALO-AC3_20220405_P5_RF11; HALO-AC3_20220407_P5_RF12; HALO-AC3_20220410_P5_RF13; microwave; microwave radiometer; MiRAC-A; netCDF file; netCDF file (File Size); Optional event label; P5_232_HALO_2022_2203200401; P5_232_HALO_2022_2203220602; P5_232_HALO_2022_2203250701; P5_232_HALO_2022_2203280801; P5_232_HALO_2022_2203291002; P5_232_HALO_2022_2203301101; P5_232_HALO_2022_2204011201; P5_232_HALO_2022_2204041301; P5_232_HALO_2022_2204051401; P5_232_HALO_2022_2204071501; P5_232_HALO_2022_2204101601; P5-232_HALO_2022; Polar 5; POLAR 5; radar; radar reflectivity; remote sensing; Svalbard
    Type: Dataset
    Format: text/tab-separated-values, 11 data points
    Location Call Number Expected Availability
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  • 66
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    Underway CTD data during Maria S. Merian cruise MSM72 (2020)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Keywords: CTD, underway; CTD-UW; DATE/TIME; DEPTH, water; Event label; LATITUDE; LONGITUDE; long term changes; Maria S. Merian; Mediterranean Sea; MSM72; MSM72_100-2; MSM72_100-3; MSM72_101-2; MSM72_102-2; MSM72_103-2; MSM72_103-3; MSM72_104-2; MSM72_105-2; MSM72_106-2; MSM72_106-3; MSM72_107-2; MSM72_108-2; MSM72_109-2; MSM72_109-3; MSM72_110-2; MSM72_111-2; MSM72_112-2; MSM72_112-3; MSM72_113-3; MSM72_114-2; MSM72_115-2; MSM72_115-3; MSM72_116-2; MSM72_117-2; MSM72_118-2; MSM72_118-3; MSM72_119-2; MSM72_120-2; MSM72_121-2; MSM72_12-2; MSM72_128-2; MSM72_128-3; MSM72_129-2; MSM72_129-3; MSM72_15-2; MSM72_16-2; MSM72_17-2; MSM72_18-2; MSM72_19-4; MSM72_20-2; MSM72_22-1; MSM72_22-10; MSM72_22-12; MSM72_22-13; MSM72_22-14; MSM72_22-15; MSM72_22-16; MSM72_22-17; MSM72_22-18; MSM72_22-19; MSM72_22-2; MSM72_22-20; MSM72_22-21; MSM72_22-22; MSM72_22-23; MSM72_22-24; MSM72_22-25; MSM72_22-26; MSM72_22-27; MSM72_22-28; MSM72_22-29; MSM72_22-3; MSM72_22-30; MSM72_22-31; MSM72_22-32; MSM72_22-4; MSM72_22-5; MSM72_22-7; MSM72_22-8; MSM72_22-9; MSM72_23-2; MSM72_24-2; MSM72_25-2; MSM72_26-2; MSM72_27-2; MSM72_29-1; MSM72_29-10; MSM72_29-11; MSM72_29-12; MSM72_29-13; MSM72_29-14; MSM72_29-15; MSM72_29-16; MSM72_29-17; MSM72_29-18; MSM72_29-2; MSM72_29-3; MSM72_29-4; MSM72_29-5; MSM72_29-6; MSM72_29-7; MSM72_29-8; MSM72_29-9; MSM72_30-2; MSM72_31-2; MSM72_32-3; MSM72_33-2; MSM72_34-4; MSM72_35-2; MSM72_36-2; MSM72_37-2; MSM72_38-2; MSM72_43-10; MSM72_43-11; MSM72_43-12; MSM72_43-13; MSM72_43-14; MSM72_43-15; MSM72_43-2; MSM72_43-3; MSM72_43-4; MSM72_43-5; MSM72_43-6; MSM72_43-7; MSM72_43-8; MSM72_43-9; MSM72_44-2; MSM72_45-2; MSM72_46-2; MSM72_47-3; MSM72_48-2; MSM72_49-2; MSM72_50-3; MSM72_51-2; MSM72_52-2; MSM72_53-2; MSM72_54-4; MSM72_59-2; MSM72_64-2; MSM72_64-3; MSM72_65-2; MSM72_66-2; MSM72_67-2; MSM72_68-2; MSM72_69-2; MSM72_70-2; MSM72_70-3; MSM72_71-2; MSM72_72-2; MSM72_72-3; MSM72_75-4; MSM72_76-2; MSM72_76-3; MSM72_78-1; MSM72_78-2; MSM72_78-3; MSM72_78-4; MSM72_78-5; MSM72_78-6; MSM72_78-7; MSM72_78-8; MSM72_78-9; MSM72_83-3; MSM72_83-4; MSM72_84-2; MSM72_85-2; MSM72_85-3; MSM72_86-2; MSM72_87-2; MSM72_88-2; MSM72_88-3; MSM72_89-2; MSM72_90-2; MSM72_91-3; MSM72_91-4; MSM72_92-2; MSM72_93-2; MSM72_94-2; MSM72_94-3; MSM72_95-2; MSM72_96-2; MSM72_97-3; MSM72_97-4; MSM72_98-2; MSM72_99-2; Pressure, water; Profile ID; Salinity; Sample code/label; Temperature, water
    Type: Dataset
    Format: text/tab-separated-values, 607585 data points
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  • 67
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    January average paleotemperatures in northwestern Yakutia (2020)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Keywords: Accelerator mass spectrometry (AMS); Age, comment; air temperature; Batagay; Batagay_1; Buor-Khaya_1; Event label; ice‐wedge; Kular; Location; Mamontov_Klyk_1; Mamontova_Khayata; Mass spectrometer Finnigan Delta-V; North Yakutia, Russia; Pleistocene; radiocarbon age; Reference/source; stable water isotopes; Temperature, air, calculated; yedoma megaslump; δ18O, water
    Type: Dataset
    Format: text/tab-separated-values, 48 data points
    Location Call Number Expected Availability
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  • 68
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    Hysteresis parameters of the site Balta Alba Kurgan (2020)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Keywords: Balta_Alba_Kurgan; Coercive force after paramagnetic correction; Depth, bottom/max; DEPTH, sediment/rock; Depth, top/min; Holocene-Pleistocene; Loess-paleosol-sequence (LPS); magnetic susceptibility; Mass; Mineral magnetic data; Our Way to Europe: Culture-Environment Interaction and Human Mobility in the Late Quaternary; OUTCROP; Outcrop sample; Paleomagnetic data; paleomagnetic secular variation stratigraphy; Profile ID; Quaternary; relative paleointensity (RPI); Remanent coercive force; Remanent magnetization; Romania; Sample ID; Saturation magnetization after paramagnetic correction; SFB806
    Type: Dataset
    Format: text/tab-separated-values, 108 data points
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  • 69
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    Lithology of gravel pit Northeim_SiteC profiles (2020)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Keywords: Comment; DATE/TIME; Depth, bottom/max; DEPTH, sediment/rock; Depth, top/min; Gravel pit; GRAVPIT; Lithology/composition/facies; Northeim_SiteC; Northeim, Lower Saxony; Profile ID
    Type: Dataset
    Format: text/tab-separated-values, 68 data points
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  • 70
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    Intercalibrated dataset of in situ dissolved organic matter fluorescence from ice tethered profile 60 in the Central Arctic (2012) (2021)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: Here we present a merged and calibrated dataset of temperature, practical salinity and dissolved organic matter (DOM) fluorescence obtained from several Ice Tethered Profilers (ITPs) deployed across the central Arctic (2011-2016). The data offer a unique spatial coverage of the distribution of DOM in the surface 800 m below Arctic sea ice. A total of 5044 profiles are gathered. The ITP data are level 3 data products pressure-bin-averaged at 1-db vertical resolution with depth down to either 200 or approximately 750 m. Data (max 800m depth) from CTD casts made during two oceanographic cruises are also included. These were used as part of the calibration and validation of the ITP calibration routines. The cruises were PS94 (ARK-XXIX/3) with POLARSTERN in 2015 and NAACOS with DANA in 2012. The presented DOM fluorescence data are smoothed, corrected for instrument drift and calibrated to provide intercomparable data across the sensors. Fluorescence is reported in Raman Units (nm-1), and comparable to laboratory measurements conducted according to current community recommendations.
    Keywords: Advective Pathways of nutrients and key Ecological substances in the ARctic; APEAR; Arctic; CDOM; DATE/TIME; DEPTH, water; Fluorescence, colored dissolved organic matter; FRAM; FRontiers in Arctic marine Monitoring; hydrography; Ice-Tethered Profiler; Identification; ITP; ITP60-TransArc-NAACOS; LATITUDE; LONGITUDE; particulate matter; Pressure, water; Profile ID; RACE; Regional Atlantic Circulation and global Change; Salinity; Temperature, water; Temperature, water, potential; water masses
    Type: Dataset
    Format: text/tab-separated-values, 715727 data points
    Location Call Number Expected Availability
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  • 71
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    Intercalibrated dataset of in situ dissolved organic matter fluorescence from ice tethered profile 69 in the Central Arctic (2013-2014) (2021)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: Here we present a merged and calibrated dataset of temperature, practical salinity and dissolved organic matter (DOM) fluorescence obtained from several Ice Tethered Profilers (ITPs) deployed across the central Arctic (2011-2016). The data offer a unique spatial coverage of the distribution of DOM in the surface 800 m below Arctic sea ice. A total of 5044 profiles are gathered. The ITP data are level 3 data products pressure-bin-averaged at 1-db vertical resolution with depth down to either 200 or approximately 750 m. Data (max 800m depth) from CTD casts made during two oceanographic cruises are also included. These were used as part of the calibration and validation of the ITP calibration routines. The cruises were PS94 (ARK-XXIX/3) with POLARSTERN in 2015 and NAACOS with DANA in 2012. The presented DOM fluorescence data are smoothed, corrected for instrument drift and calibrated to provide intercomparable data across the sensors. Fluorescence is reported in Raman Units (nm-1), and comparable to laboratory measurements conducted according to current community recommendations.
    Keywords: Advective Pathways of nutrients and key Ecological substances in the ARctic; APEAR; Arctic; CDOM; DATE/TIME; DEPTH, water; Fluorescence, colored dissolved organic matter; FRAM; FRontiers in Arctic marine Monitoring; hydrography; Ice-Tethered Profiler; Identification; ITP; ITP69-TransArc-NAACOS; LATITUDE; LONGITUDE; particulate matter; Pressure, water; Profile ID; RACE; Regional Atlantic Circulation and global Change; Salinity; Temperature, water; Temperature, water, potential; water masses
    Type: Dataset
    Format: text/tab-separated-values, 1066781 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 72
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    Soil profile meta data from samples in Lora del Rio, Andalusia, Spain (2021)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Keywords: AUG; Auger; Comment; Depth, bottom/max; DEPTH, sediment/rock; Depth, top/min; Increment number; Laboratory code/label; LATITUDE; LONGITUDE; Lora_del_Rio; Lora del Rio, Analusia, Spain; Profile ID; ResourceCultures; Sample code/label; SFB1070; UTM Easting, Universal Transverse Mercator; UTM Northing, Universal Transverse Mercator; UTM Zone, Universal Transverse Mercator
    Type: Dataset
    Format: text/tab-separated-values, 4620 data points
    Location Call Number Expected Availability
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  • 73
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    Estimated dry mass based on length-mass relationships of zooplankton during POLARSTERN cruise PS78 (ARK-XXVI/1) (2022)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Keywords: Abundance; Aeginidae, biomass as dry weight; Aetideidae, biomass as dry weight; Aetideopsis rostrata, female, biomass as dry weight; Aglantha digitale, biomass as dry weight; Appendicularia, biomass as dry weight; ARK-XXVI/1; Atolla tenella, biomass as dry weight; Augaptilidae, biomass as dry weight; Biomass; biovolume; Bivalvia, larvae, biomass as dry weight; Botrynema spp., biomass as dry weight; Calanidae, biomass as dry weight; Calanidae, c1-c3, biomass as dry weight; Calanoida indeterminata, copepodites, biomass as dry weight; Calanoida indeterminata, female, biomass as dry weight; Calanoida indeterminata, male, biomass as dry weight; Calanus hyperboreus, c4, biomass as dry weight; Calanus hyperboreus, c5, biomass as dry weight; Calanus hyperboreus, female, biomass as dry weight; Calanus spp., c4, biomass as dry weight; Calanus spp., c5, biomass as dry weight; Calanus spp., female, biomass as dry weight; Calanus spp., male, biomass as dry weight; Chaetognatha, biomass as dry weight; Chiridius obtusifrons, female, biomass as dry weight; Clione limacina, biomass as dry weight; Cnidaria indeterminata, biomass as dry weight; Comment; Copepoda; Copepoda, nauplii, biomass as dry weight; Copepoda indeterminata, biomass as dry weight; Cyclocaris guilelmi, biomass as dry weight; Date/Time of event; Depth, bottom/max; Depth, top/min; DEPTH, water; Echinodermata, larvae, biomass as dry weight; Elevation of event; Eukrohnia hamata, biomass as dry weight; Euphausiacea, biomass as dry weight; Event label; Fram Strait; Fritillariidae, biomass as dry weight; Gaetanus brevispinus, female, biomass as dry weight; Gaetanus tenuispinus, female, biomass as dry weight; Harpacticoida, biomass as dry weight; Heterorhabdidae, copepodites, biomass as dry weight; Heterorhabdus norvegicus, female, biomass as dry weight; Heterorhabdus norvegicus, male, biomass as dry weight; Hymenodora glacialis, biomass as dry weight; Isopoda, biomass as dry weight; Lanceola clausi, biomass as dry weight; Latitude of event; Limacina helicina, biomass as dry weight; Longitude of event; Lucicutiidae, biomass as dry weight; Metridia longa, biomass as dry weight; Metridia longa, c1-c3, biomass as dry weight; Metridia longa, c4, biomass as dry weight; Metridia longa, c5, biomass as dry weight; Metridia longa, female, biomass as dry weight; Metridia longa, male, biomass as dry weight; Metridia lucens, biomass as dry weight; Microcalanus spp., biomass as dry weight; Mormonilloida, biomass as dry weight; MSN; Multiple opening/closing net; Mysida, biomass as dry weight; North Greenland Sea; Oikopleuridae, biomass as dry weight; Oithonidae, biomass as dry weight; Oncaeidae, biomass as dry weight; Ostracoda, biomass as dry weight; Paraeuchaeta spp., copepodites, biomass as dry weight; Paraeuchaeta spp., female, biomass as dry weight; Paraeuchaeta spp., male, biomass as dry weight; Paraheterorhabdus compactus, female, biomass as dry weight; Parasagitta elegans, biomass as dry weight; Pelagobia cf. longicirrata, biomass as dry weight; Pleuromamma sp., biomass as dry weight; Polarstern; Polychaeta, larvae, biomass as dry weight; PS78; PS78/019-5; PS78/025-3; PS78/035-2; PS78/039-5; PS78/044-4; PS78/054-5; PS78/071-5; PS78/075-5; PS78/127-7; Pseudocalanus spp., copepodites, biomass as dry weight; Pseudocalanus spp., female, biomass as dry weight; Pseudocalanus spp., male, biomass as dry weight; Pseudochirella spectabilis, biomass as dry weight; QUAntifying Rapid Climate Change in the Arctic: regional feedbackS and large-scale impacts; QUARCCS; Rhabdoon reesi, biomass as dry weight; Scaphocalanus magnus, biomass as dry weight; Scaphocalanus magnus, female, biomass as dry weight; Scaphocalanus spp., copepodites, biomass as dry weight; Scaphocalanus spp., female, biomass as dry weight; Scaphocalanus spp., male, biomass as dry weight; Scolecithricella minor, biomass as dry weight; Scolecitrichopsis polaris, biomass as dry weight; Siphonophorae, biomass as dry weight; Sminthea spp., biomass as dry weight; Solmundella bitentaculata, biomass as dry weight; Spinocalanus antarcticus, biomass as dry weight; Spinocalanus antarcticus, female, biomass as dry weight; Spinocalanus elongatus, female, biomass as dry weight; Spinocalanus longicornis, female, biomass as dry weight; Spinocalanus longispinus, female, biomass as dry weight; Spinocalanus spp., copepodites, biomass as dry weight; Spinocalanus spp., male, biomass as dry weight; Temorites brevis, biomass as dry weight; Temorites brevis, female, biomass as dry weight; Tharybis sp., copepodites, biomass as dry weight; Tharybis sp. female, biomass as dry weight; Themisto abyssorum, biomass as dry weight; Themisto libellula, biomass as dry weight; Tomopteris sp., biomass as dry weight; Typhloscolex cf. muelleri, biomass as dry weight; Zooplankton; ZOOSCAN
    Type: Dataset
    Format: text/tab-separated-values, 4455 data points
    Location Call Number Expected Availability
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  • 74
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    Upper-ocean microstructure data from the tropical Angolan upwelling system during METEOR cruise M181 (2023)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: Microstructure data was collected using a microstructure profiler MSS90D manufactured by Sea&Sun Technology in cooperation with ISW-Wassermesstechnik. Dissipation rates of turbulent kinetic energy are calculated as described in Schafstall et al. (Journal of Geophysical Research, 2010). Stored parameters include: Dissipation rate of turbulent kinetic energy from 3 microstructure shear sensors, temperature, salinity and depth.
    Keywords: BANINO; Benguela Niños: Physikalische Prozesse und langperiodische Variabilität; DATE/TIME; DEPTH, water; Dissipation rate; Event label; LATITUDE; LONGITUDE; M181; M181_15-1; M181_18-1; M181_20-1; M181_22-1; M181_24-1; M181_26-1; M181_28-1; M181_34-1; M181_36-1; M181_37-1; M181_39-1; M181_41-1; M181_46-1; Meteor (1986); Microstructure Profiler; MSSP; Pressure, water; Profile ID; SACUS/SACUS-II; Salinity; South Atlantic Ocean; Southwest African Coastal Upwelling System and Benguela Niños; Temperature, water; TRATLEQ 2; TRIATLAS; Tropical and South Atlantic climate-based marine ecosystem predictions for sustainable management
    Type: Dataset
    Format: text/tab-separated-values, 145537 data points
    Location Call Number Expected Availability
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  • 75
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    Physical oceanographyand anthropogenic tracers measured on water bottle samples during Maria S. Merian cruise MSM09/1 (2020)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: Temperature, salinity, oxygen data and anthropogenic tracers measured on the RV Maria S. Merian Cruise MSM09/1 Bremen - St. John's 07/23 - 08/18/2008 Chief Scientist: Monika Rhein Region: Subpolar North Atlantic
    Keywords: anthropogenic tracers; Bottle number; Calculated; Capillary-chromatographic system with electron capture detector; CTD, Seabird; CTD, SEA-BIRD SBE 9 plus, SBE 11 plus deck unit; CTD-R; CTD-yoyo; Date/Time of event; Density, sigma-theta (0); DEPTH, water; Der Nordatlantik als Teil des Erdsystems; Elevation of event; Event label; Freon-12 (dichlorodifluoromethane); Latitude of event; Longitude of event; Maria S. Merian; MSM09/1; MSM09/1_342-1; MSM09/1_343-1; MSM09/1_344-1; MSM09/1_345-1; MSM09/1_346-1; MSM09/1_347-1; MSM09/1_348-1; MSM09/1_349-1; MSM09/1_350-1; MSM09/1_351-1; MSM09/1_352-1; MSM09/1_353-1; MSM09/1_354-1; MSM09/1_355-1; MSM09/1_356-1; MSM09/1_357-1; MSM09/1_358-1; MSM09/1_359-1; MSM09/1_360-1; MSM09/1_362-1; MSM09/1_363-1; MSM09/1_364-1; MSM09/1_366-2; MSM09/1_367-1; MSM09/1_368-1; MSM09/1_369-1; MSM09/1_370-1; MSM09/1_371-1; MSM09/1_372-1; MSM09/1_373-1; MSM09/1_376-1; MSM09/1_377-1; MSM09/1_378-1; MSM09/1_380-1; MSM09/1_381-1; MSM09/1_382-1; MSM09/1_383-1; MSM09/1_384-1; MSM09/1_385-1; MSM09/1_386-1; MSM09/1_387-1; MSM09/1_388-1; MSM09/1_389-1; MSM09/1_390-1; MSM09/1_391-1; MSM09/1_392-1; MSM09/1_393-1; MSM09/1_394-1; MSM09/1_395-1; MSM09/1_396-1; MSM09/1_397-1; MSM09/1_401-1; MSM09/1_403-1; MSM09/1_404-1; MSM09/1_405-1; MSM09/1_406-1; MSM09/1_407-1; MSM09/1_408-1; MSM09/1_409-1; MSM09/1_410-1; MSM09/1_411-1; MSM09/1_412-1; MSM09/1_413-1; MSM09/1_414-1; Nordatlantik; Pressure, water; Profile ID; Salinity; South Atlantic Ocean; Station label; subpolar North Atlantic; Sulfur hexafluoride, SF6; Temperature, water; Temperature, water, potential; Time in days; Yoyo-CTD
    Type: Dataset
    Format: text/tab-separated-values, 14444 data points
    Location Call Number Expected Availability
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  • 76
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    Physical oceanography, CFC-12 and nutrients measured on water bottle samples during Pelagia cruise PE278 (2020)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: Physical oceanography, CFC-12 and nutrients measured on the RV Pelagia Cruise PE278 Galway - Canical/Madeira 10/26 - 11/17/2007 Chief Scientist: Dagmar Kieke Region: Subpolar Northeastern Atlantic
    Keywords: 1; 10; 11; 12; 13; 14; 15; 16; 17; 18; 19; 2; 20; 21; 22; 23; 24; 25; 26; 27; 28; 29; 3; 30; 31; 32; 33; 34; 35; 36; 37; 38; 39; 4; 40; 41; 42; 43; 44; 45; 46; 47; 48; 49; 50; 51; 52; 7; 8; 9; anthropogenic tracers; Bottle number; Calculated; Capillary-chromatographic system with electron capture detector; CTD, SEA-BIRD SBE 9 plus, SBE 11 plus deck unit; CTD/Rosette; CTD-RO; Date/Time of event; Density, sigma-theta (0); DEPTH, water; Der Nordatlantik als Teil des Erdsystems; Elevation of event; Event label; Freon-12 (dichlorodifluoromethane); Latitude of event; Longitude of event; Nitrate; Nordatlantik; Oxygen; Oxygen, Winkler (Culberson, 1991, WOCE Report 68/91); PE278; PE278_1; PE278_10; PE278_11; PE278_12; PE278_13; PE278_14; PE278_15; PE278_16; PE278_17; PE278_18; PE278_19; PE278_2; PE278_20; PE278_21; PE278_22; PE278_23; PE278_24; PE278_25; PE278_26; PE278_27; PE278_28; PE278_29; PE278_3; PE278_30; PE278_31; PE278_32; PE278_33; PE278_34; PE278_35; PE278_36; PE278_37; PE278_38; PE278_39; PE278_4; PE278_40; PE278_41; PE278_42; PE278_43; PE278_44; PE278_45; PE278_46; PE278_47; PE278_48; PE278_49; PE278_50; PE278_51; PE278_52; PE278_7; PE278_8; PE278_9; Pelagia; Phosphate; Pressure, water; Profile ID; Salinity; Silicate; South Atlantic Ocean; Station label; subpolar North Atlantic; Temperature, water; Temperature, water, potential; Time in days
    Type: Dataset
    Format: text/tab-separated-values, 13672 data points
    Location Call Number Expected Availability
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  • 77
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    Physical oceanography, CFC-11 and CFC-12 measured on water bottle samples during Maria S. Merian cruise MSM38 (2020)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: Temperature, salinity and the anthropogenic tracers measured on the RV Maria S. Merian Cruise MSM38 Cadiz - St. John's 05/07 - 06/05/2014 Chief Scientist: Dagmar Kieke Region: Subpolar North Atlantic
    Keywords: 0; 1; 10; 100; 101; 102; 103; 104; 105; 106; 109; 11; 110; 111; 112; 113; 114; 115; 116; 117; 118; 119; 12; 120; 121; 122; 124; 125; 126; 127; 13; 14; 15; 16; 17; 18; 19; 2; 20; 21; 22; 23; 24; 25; 26; 27; 28; 29; 3; 30; 31; 32; 33; 34; 35; 36; 37; 38; 39; 4; 40; 41; 42; 43; 44; 45; 46; 47; 48; 49; 5; 50; 51; 52; 53; 54; 55; 56; 57; 58; 6; 66; 67; 68; 69; 7; 70; 71; 72; 73; 74; 8; 80; 81; 82; 83; 84; 85; 86; 87; 88; 89; 9; 90; 91; 92; 93; 94; 95; 96; 97; 98; 99; anthropogenic tracers; Bottle number; Calculated; Capillary-chromatographic system with electron capture detector; CTD, SEA-BIRD SBE 9 plus, SBE 11 plus deck unit; CTD/Rosette; CTD-RO; Date/Time of event; Density, sigma-theta (0); DEPTH, water; Elevation of event; Event label; Freon-11 (trichorofluoromethane); Freon-12 (dichlorodifluoromethane); Latitude of event; Longitude of event; Maria S. Merian; MSM38; MSM38_343; MSM38_344; MSM38_345; MSM38_347; MSM38_348; MSM38_349; MSM38_350; MSM38_354; MSM38_355; MSM38_358; MSM38_359; MSM38_360; MSM38_361; MSM38_363; MSM38_364; MSM38_365; MSM38_366; MSM38_367; MSM38_368; MSM38_369; MSM38_370; MSM38_372; MSM38_373; MSM38_374; MSM38_375; MSM38_376; MSM38_377; MSM38_378; MSM38_379; MSM38_380; MSM38_381; MSM38_382; MSM38_383; MSM38_384; MSM38_385; MSM38_386; MSM38_387; MSM38_388; MSM38_389; MSM38_390; MSM38_391; MSM38_392; MSM38_393; MSM38_394; MSM38_395; MSM38_396; MSM38_397; MSM38_398; MSM38_399; MSM38_400; MSM38_401; MSM38_402; MSM38_403; MSM38_404; MSM38_405; MSM38_406; MSM38_407; MSM38_408; MSM38_409; MSM38_418; MSM38_419; MSM38_420; MSM38_421; MSM38_422; MSM38_423; MSM38_424; MSM38_425; MSM38_426; MSM38_432; MSM38_433; MSM38_434; MSM38_435; MSM38_436; MSM38_437; MSM38_438; MSM38_439; MSM38_440; MSM38_441; MSM38_442; MSM38_443; MSM38_444; MSM38_445; MSM38_446; MSM38_447; MSM38_448; MSM38_449; MSM38_450; MSM38_451; MSM38_452; MSM38_453; MSM38_454; MSM38_455; MSM38_456; MSM38_457; MSM38_458; MSM38_461; MSM38_462; MSM38_463; MSM38_464; MSM38_465; MSM38_466; MSM38_467; MSM38_468; MSM38_469; MSM38_470; MSM38_471; MSM38_472; MSM38_473; MSM38_474; MSM38_476; MSM38_477; MSM38_478; MSM38_479; Oxygen; Oxygen, Winkler (Culberson, 1991, WOCE Report 68/91); Oxygen sensor, SBE 43; Pressure, water; Profile ID; RACE; Regional Atlantic Circulation and global Change; Salinity; Station label; subpolar North Atlantic; Temperature, water; Temperature, water, potential; Time in days
    Type: Dataset
    Format: text/tab-separated-values, 26513 data points
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  • 78
    facet.materialart.
    Unknown
    Physical oceanography, CFC-11 and CFC-12 measured on water bottle samples during cruise SUBPOLAR with RV Thalassa (2020)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: Temperature, salinity, oxygen data and anthropogenic tracers measured on the RV Thalassa Cruise Subpolar Brest - St. John's 06/04 - 07/12/2005 Chief Scientist: Monika Rhein Region: Subpolar North Atlantic
    Keywords: anthropogenic tracers; Bottle number; Calculated; Capillary-chromatographic system with electron capture detector; Celtic Sea; CTD, SEA-BIRD SBE 9 plus, SBE 11 plus deck unit; CTD/Rosette; CTD-RO; Date/Time of event; Davis Strait; Density, sigma-theta (0); DEPTH, water; Elevation of event; Event label; Freon-11 (trichorofluoromethane); Freon-12 (dichlorodifluoromethane); Labrador Sea; Latitude of event; Longitude of event; Oxygen; Oxygen, Winkler (Culberson, 1991, WOCE Report 68/91); Oxygen sensor, SBE 43; Pressure, water; Profile ID; Salinity; South Atlantic Ocean; Station label; SUBPOLAR; SUBPOLAR_001; SUBPOLAR_002; SUBPOLAR_003; SUBPOLAR_004; SUBPOLAR_005; SUBPOLAR_006; SUBPOLAR_007; SUBPOLAR_008; SUBPOLAR_009; SUBPOLAR_010; SUBPOLAR_011; SUBPOLAR_012; SUBPOLAR_013; SUBPOLAR_014; SUBPOLAR_015; SUBPOLAR_016; SUBPOLAR_017; SUBPOLAR_018; SUBPOLAR_019; SUBPOLAR_020; SUBPOLAR_021; SUBPOLAR_022; SUBPOLAR_023; SUBPOLAR_024; SUBPOLAR_025; SUBPOLAR_026; SUBPOLAR_027; SUBPOLAR_028; SUBPOLAR_029; SUBPOLAR_030; SUBPOLAR_031; SUBPOLAR_032; SUBPOLAR_033; SUBPOLAR_034; SUBPOLAR_035; SUBPOLAR_036; SUBPOLAR_037; SUBPOLAR_038; SUBPOLAR_039; SUBPOLAR_040; SUBPOLAR_041; SUBPOLAR_042; SUBPOLAR_043; SUBPOLAR_044; SUBPOLAR_045; SUBPOLAR_046; SUBPOLAR_047; SUBPOLAR_048; SUBPOLAR_049; SUBPOLAR_050; SUBPOLAR_051; SUBPOLAR_052; SUBPOLAR_053; SUBPOLAR_054; SUBPOLAR_055; SUBPOLAR_056; SUBPOLAR_057; SUBPOLAR_058; SUBPOLAR_059; SUBPOLAR_060; SUBPOLAR_061; SUBPOLAR_062; SUBPOLAR_063; SUBPOLAR_064; SUBPOLAR_065; SUBPOLAR_066; SUBPOLAR_067; SUBPOLAR_068; SUBPOLAR_069; SUBPOLAR_070; SUBPOLAR_071; SUBPOLAR_072; SUBPOLAR_073; SUBPOLAR_074; SUBPOLAR_075; SUBPOLAR_076; SUBPOLAR_077; SUBPOLAR_078; SUBPOLAR_079; SUBPOLAR_080; SUBPOLAR_081; SUBPOLAR_082; SUBPOLAR_083; SUBPOLAR_084; SUBPOLAR_085; SUBPOLAR_086; SUBPOLAR_087; SUBPOLAR_088; SUBPOLAR_089; SUBPOLAR_090; SUBPOLAR_091; SUBPOLAR_092; SUBPOLAR_093; SUBPOLAR_094; SUBPOLAR_095; SUBPOLAR_096; SUBPOLAR_097; SUBPOLAR_098; SUBPOLAR_099; SUBPOLAR_100; SUBPOLAR_101; SUBPOLAR_102; SUBPOLAR_103; SUBPOLAR_104; SUBPOLAR_105; SUBPOLAR_106; SUBPOLAR_107; SUBPOLAR_108; SUBPOLAR_109; SUBPOLAR_110; SUBPOLAR_111; SUBPOLAR_112; SUBPOLAR_113; SUBPOLAR_114; SUBPOLAR_115; SUBPOLAR_116; SUBPOLAR_117; SUBPOLAR_118; SUBPOLAR_119; SUBPOLAR_120; SUBPOLAR_121; SUBPOLAR_122; SUBPOLAR_123; SUBPOLAR_124; SUBPOLAR_125; SUBPOLAR_126; SUBPOLAR_127; SUBPOLAR_128; SUBPOLAR_129; subpolar North Atlantic; Temperature, water; Temperature, water, potential; Thalassa; Time in days
    Type: Dataset
    Format: text/tab-separated-values, 27579 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 79
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    Unknown
    Continuous VM-ADCP (vessel-mounted Acoustic Doppler Current Profiler) profile during Maria S. Merian cruise MSM76 (2023)
    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven
    Details
    Publication Date: 2024-06-10
    Keywords: -; Acoustic Doppler Current Profiler; Acoustic Doppler Current Profiling, vessel-mounted (VM-ADCP); ADCP; AWI_PhyOce; Bin number; Current velocity, east-west; Current velocity, error; Current velocity, north-south; Current velocity, standard deviation; Current velocity, vertical; DATE/TIME; Depth, relative; DEPTH, water; LATITUDE; LONGITUDE; Maria S. Merian; MSM76; MSM76_0_underway-2; North Atlantic; Number; Percentage; Physical Oceanography @ AWI; Profile ID; Quality; SADCP; Ship speed; Ship speed, standard deviation; Ship velocity, East; Ship velocity, North; Ship velocity, vertical; VM-ADCP
    Type: Dataset
    Format: text/tab-separated-values, 10766304 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 80
    facet.materialart.
    Unknown
    Physical oceanography, CFC-12 and SF6 measured on water bottle samples during Maria S. Merian cruise MSM12/3 (2020)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: Temperature, salinity, oxygen data and anthropogenic tracers measured on the Maria S. Merian Cruise MSM12/3 Reykjavik - Bremerhaven 07/14 - 08/22/2009 Region: Subpolar North Atlantic
    Keywords: anthropogenic tracers; Bottle number; Calculated; Capillary-chromatographic system with electron capture detector; CTD, SEA-BIRD SBE 9 plus, SBE 11 plus deck unit; CTD/Rosette; CTD-RO; Date/Time of event; Davis Strait; Density, sigma-theta (0); DEPTH, water; Der Nordatlantik als Teil des Erdsystems; Elevation of event; Event label; Freon-12 (dichlorodifluoromethane); Greenland Sea; Labrador Sea; Latitude of event; Longitude of event; Maria S. Merian; MSM12/3; MSM12/3_658; MSM12/3_659; MSM12/3_660; MSM12/3_661; MSM12/3_662; MSM12/3_663; MSM12/3_664; MSM12/3_665; MSM12/3_666; MSM12/3_667; MSM12/3_668; MSM12/3_669; MSM12/3_670; MSM12/3_671; MSM12/3_672; MSM12/3_673; MSM12/3_674; MSM12/3_675; MSM12/3_676; MSM12/3_677; MSM12/3_678; MSM12/3_679; MSM12/3_680; MSM12/3_681; MSM12/3_682; MSM12/3_683; MSM12/3_684; MSM12/3_685; MSM12/3_686; MSM12/3_687; MSM12/3_688; MSM12/3_689; MSM12/3_690; MSM12/3_691; MSM12/3_692; MSM12/3_693; MSM12/3_694; MSM12/3_695; MSM12/3_696; MSM12/3_697; MSM12/3_698; MSM12/3_699; MSM12/3_700; MSM12/3_701; MSM12/3_702; MSM12/3_703; MSM12/3_704; MSM12/3_705; MSM12/3_706; MSM12/3_707; MSM12/3_708; MSM12/3_709; MSM12/3_710; MSM12/3_711; MSM12/3_712; MSM12/3_713; MSM12/3_714; MSM12/3_715; MSM12/3_716; MSM12/3_717; MSM12/3_718; MSM12/3_719; MSM12/3_720; MSM12/3_721; MSM12/3_722; MSM12/3_723; MSM12/3_724; MSM12/3_725; MSM12/3_726; MSM12/3_727; MSM12/3_728; MSM12/3_733; MSM12/3_734; MSM12/3_735; MSM12/3_736; MSM12/3_737; MSM12/3_738; MSM12/3_739; MSM12/3_741; MSM12/3_742; MSM12/3_743; MSM12/3_744; MSM12/3_745; MSM12/3_747; MSM12/3_748; MSM12/3_749; MSM12/3_750; MSM12/3_751; MSM12/3_752; MSM12/3_753; MSM12/3_754; Nordatlantik; Oxygen; Oxygen, Winkler (Culberson, 1991, WOCE Report 68/91); Oxygen sensor, SBE 43; Pressure, water; Profile ID; Salinity; South Atlantic Ocean; Station label; subpolar North Atlantic; Sulfur hexafluoride, SF6; Temperature, water; Temperature, water, potential; Time in days
    Type: Dataset
    Format: text/tab-separated-values, 20467 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 81
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    Unknown
    Physical oceanography and anthropogenic tracers measured on water bottle samples during Maria S. Merian cruise MSM28 (2020)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: Temperature, salinity and the anthropogenic tracers measured on the RV Maria S. Merian Cruise MSM28 St. John's - Tromsö 05/09 - 06/20/2013 Chief Scientist: Dagmar Kieke Region: Subpolar North Atlantic
    Keywords: anthropogenic tracers; Bottle number; Calculated; Capillary-chromatographic system with electron capture detector; Celtic Sea; CTD, SEA-BIRD SBE 9 plus, SBE 11 plus deck unit; CTD/Rosette; CTD-RO; Date/Time of event; Davis Strait; Density, sigma-theta (0); DEPTH, water; Elevation of event; Event label; Freon-11 (trichorofluoromethane); Freon-12 (dichlorodifluoromethane); Labrador Sea; Latitude of event; Longitude of event; Maria S. Merian; MSM28; MSM28_271-1; MSM28_272-1; MSM28_273-1; MSM28_274-1; MSM28_275-1; MSM28_276-1; MSM28_277-1; MSM28_278-1; MSM28_279-1; MSM28_280-1; MSM28_281-1; MSM28_282-1; MSM28_283-1; MSM28_284-1; MSM28_285-1; MSM28_287-1; MSM28_288-1; MSM28_289-1; MSM28_290-1; MSM28_291-1; MSM28_292-1; MSM28_293-1; MSM28_294-1; MSM28_295-1; MSM28_296-1; MSM28_297-1; MSM28_298-1; MSM28_299-1; MSM28_300-1; MSM28_301-1; MSM28_302-1; MSM28_303-1; MSM28_304-1; MSM28_305-1; MSM28_306-1; MSM28_307-1; MSM28_308-1; MSM28_309-1; MSM28_310-1; MSM28_311-1; MSM28_312-1; MSM28_313-1; MSM28_314-1; MSM28_315-1; MSM28_316-1; MSM28_317-1; MSM28_318-1; MSM28_319-1; MSM28_320-1; MSM28_321-1; MSM28_322-1; MSM28_323-1; MSM28_324-1; MSM28_325-1; MSM28_326-1; MSM28_327-1; MSM28_328-1; MSM28_329-1; MSM28_330-1; MSM28_331-1; MSM28_332-1; MSM28_333-1; MSM28_334-1; MSM28_335-1; MSM28_336-1; MSM28_337-1; MSM28_338-1; MSM28_339-1; MSM28_340-1; MSM28_341-1; MSM28_342-1; MSM28_343-1; MSM28_344-1; MSM28_345-1; MSM28_346-1; MSM28_347-1; MSM28_348-1; MSM28_349-1; MSM28_350-2; MSM28_351-1; MSM28_352-2; MSM28_353-1; MSM28_354-1; MSM28_355-1; MSM28_356-1; MSM28_357-1; MSM28_358-1; MSM28_359-1; MSM28_360-1; MSM28_361-1; MSM28_362-1; MSM28_363-1; MSM28_364-1; MSM28_365-1; MSM28_366-1; MSM28_367-1; MSM28_368-1; MSM28_369-1; MSM28_370-1; MSM28_371-1; MSM28_372-1; MSM28_373-1; MSM28_374-1; MSM28_375-1; MSM28_376-1; MSM28_377-1; MSM28_378-1; MSM28_379-1; MSM28_380-1; MSM28_381-1; MSM28_382-1; MSM28_383-1; MSM28_384-1; MSM28_385-1; MSM28_386-1; MSM28_387-1; MSM28_388-1; MSM28_389-1; MSM28_390-1; MSM28_391-1; MSM28_392-1; MSM28_393-1; MSM28_394-1; MSM28_395-1; MSM28_396-1; MSM28_397-1; MSM28_398-1; MSM28_399-1; MSM28_400-1; MSM28_401-1; MSM28_402-1; MSM28_403-1; MSM28_404-1; MSM28_405-1; MSM28_406-1; MSM28_407-1; MSM28_408-1; MSM28_409-1; MSM28_410-1; MSM28_411-1; MSM28_412-1; MSM28_413-1; MSM28_414-1; MSM28_415-1; MSM28_416-1; MSM28_417-1; MSM28_418-1; MSM28_419-1; MSM28_420-1; MSM28_421-1; MSM28_422-1; Oxygen; Oxygen, Winkler (Culberson, 1991, WOCE Report 68/91); Oxygen sensor, SBE 43; Pressure, water; Profile ID; RACE; Regional Atlantic Circulation and global Change; Salinity; South Atlantic Ocean; Station label; subpolar North Atlantic; Sulfur hexafluoride, SF6; Temperature, water; Temperature, water, potential; Time in days
    Type: Dataset
    Format: text/tab-separated-values, 37127 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 82
    facet.materialart.
    Unknown
    Physical oceanography, CFC-11 and CFC-12 measured on water bottle samples during Maria S. Merian cruise MSM39 (2020)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: Temperature, salinity and CFCs measured on the RV Maria S. Merian Cruise MSM39 St. John's - St. John's 06/07 - 06/25/2014 Chief Scientist: Stefan Mulitza Region: Northwestern Atlantic
    Keywords: 481-1; 482-1; 483-1; 484-1; 485-1; 486-1; 487-1; 488-1; 489-1; 490-1; 491-1; 492-1; 497-1; 498-1; 499-1; 500-1; 501-1; 502-1; 503-1; 504-1; 505-1; 506-2; 507-1; 508-1; 514-2; 515-1; 516-1; 517-1; 518-1; 519-1; 520-1; 521-1; 522-1; 523-1; 524-1; 525-1; 526-1; 527-1; anthropogenic tracers; Bottle number; Calculated; Capillary-chromatographic system with electron capture detector; CTD, SEA-BIRD SBE 9 plus, SBE 11 plus deck unit; CTD/Rosette; CTD-RO; Date/Time of event; Density, sigma-theta (0); DEPTH, water; Elevation of event; Event label; Flemish Cap/Orphan Knoll; Freon-11 (trichorofluoromethane); Freon-12 (dichlorodifluoromethane); GeoB18502-1; GeoB18503-1; GeoB18504-1; GeoB18505-1; GeoB18506-1; GeoB18507-1; GeoB18508-1; GeoB18509-1; GeoB18510-1; GeoB18511-1; GeoB18512-1; GeoB18513-1; GeoB18518-1; GeoB18519-1; GeoB18520-1; GeoB18521-1; GeoB18522-1; GeoB18523-1; GeoB18524-1; GeoB18525-1; GeoB18526-1; GeoB18527-2; GeoB18528-1; GeoB18529-1; GeoB18535-2; GeoB18536-1; GeoB18537-1; GeoB18538-1; GeoB18539-1; GeoB18540-1; GeoB18541-1; GeoB18542-1; GeoB18543-1; GeoB18544-1; GeoB18545-1; GeoB18546-1; GeoB18547-1; GeoB18548-1; Latitude of event; Longitude of event; Maria S. Merian; MSM39; Pressure, water; Profile ID; RACE; Regional Atlantic Circulation and global Change; Salinity; SE Grand Banks Slope; Station label; subpolar North Atlantic; SW Grand Banks Slope; Temperature, water; Temperature, water, potential; Time in days
    Type: Dataset
    Format: text/tab-separated-values, 8699 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 83
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    Unknown
    Microstructure measurements during METEOR cruise M106 (2020)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: 118 profiles of post-processed upper-ocean microstructure data from a loosely-tethered profiler (MSS90-D, manufactured by Sea & Sun Technology) collected in the central and western tropical Atlantic. Dissipation rates of turbulent kinetic energy are calculated as described in Schafstall et al. (Journal of Geophysical Research, 2010). Stored parameters include: Dissipation rate of turbulent kinetic energy in m^2 s^(-3) from 3 microstructure shear sensors, temperature, salinity and depth.
    Keywords: Climate - Biogeochemistry Interactions in the Tropical Ocean; DATE/TIME; DEPTH, water; Dissipation rate; Event label; LATITUDE; LONGITUDE; M106; M106_324-3; M106_337-5/6; M106_346-1; M106_352-1; M106_353-1; M106_366-1; M106_367-3; M106_368-3; M106_371-2; M106_372-2; M106_403-2; M106_404-2; M106_405-2; M106_406-2; M106_407-2; M106_410-2; M106_411-4; M106_412-2; M106_413-2; M106_414-2; M106_415-2; M106_416-4; M106_417-2; M106_418-2; M106_419-2; M106_422-2; M106_423-2; M106_424-3; M106_425-2; M106_426-2; M106_427-2; M106_428-3; M106_429-2; M106_430-2; M106_431-2; M106_432-2; M106_433-2; M106_434-2; Meteor (1986); Micro structure probe; MSS; MSS_1; MSS_10; MSS_11; MSS_12; MSS_13; MSS_14; MSS_15; MSS_16; MSS_18; MSS_19; MSS_2; MSS_20; MSS_21; MSS_22; MSS_23; MSS_24; MSS_25; MSS_26; MSS_27; MSS_28; MSS_29; MSS_3; MSS_30; MSS_31; MSS_32; MSS_33; MSS_34; MSS_35; MSS_36; MSS_37; MSS_38; MSS_39; MSS_4; MSS_5; MSS_6; MSS_7; MSS_8; MSS_9; Pressure, water; Profile ID; Salinity; SFB754; Temperature, water; tropical Atlantic
    Type: Dataset
    Format: text/tab-separated-values, 684121 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 84
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    Unknown
    Microstructure measurements during METEOR cruise M119 (2020)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: 170 profiles of post-processed upper-ocean microstructure data from a loosely-tethered profiler (MSS90-D, manufactured by Sea & Sun Technology) collected in the central and western tropical Atlantic. Dissipation rates of turbulent kinetic energy are calculated as described in Schafstall et al. (Journal of Geophysical Research, 2010). Stored parameters include: Dissipation rate of turbulent kinetic energy in m^2 s^(-3) from 3 microstructure shear sensors, temperature, salinity and depth.
    Keywords: Climate - Biogeochemistry Interactions in the Tropical Ocean; DATE/TIME; DEPTH, water; Dissipation rate; Event label; LATITUDE; LONGITUDE; M119; M119_687-1; M119_711-1; M119_751-1; M119_767-1; M119_773-1; M119_777-1; M119_813-1; M119_815-1; M119_817-1; M119_819-1; M119_826-1; M119_828-1; M119_831-1; M119_834-1; M119_836-1; M119_839-1; M119_841-1; M119_843-1; M119_847-1; M119_849-1; M119_851-1; M119_854-1; M119_856-1; M119_858-1; M119_860-1; M119_862-1; M119_864-1; M119_866-1; Meteor (1986); Micro structure probe; MSS; Pressure, water; Profile ID; Salinity; SFB754; Temperature, water; tropical Atlantic
    Type: Dataset
    Format: text/tab-separated-values, 798407 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 85
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    Unknown
    Microstructure measurements during METEOR cruise M135 (2020)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: 97 profiles of post-processed upper-ocean (〈250m depth) microstructure data from a loosely-tethered profiler (MSS90-D, manufactured by Sea & Sun Technology) collected in the central tropical Atlantic. Dissipation rates of turbulent kinetic energy are calculated as described in Schafstall et al. (Journal of Geophysical Research, 2010). Stored parameters include: Dissipation rate of turbulent kinetic energy in m^2 s^(-3) from 3 microstructure shear sensors, temperature, salinity and depth.
    Keywords: Climate - Biogeochemistry Interactions in the Tropical Ocean; DATE/TIME; DEPTH, water; Dissipation rate; Event label; LATITUDE; LONGITUDE; M135; M135_236-2; M135_247-2; M135_249-5; M135_252-4; M135_254-4; M135_255-2; M135_257-2; M135_258-2; M135_284-1; M135_285-1; M135_286-1; M135_287-2; M135_288-3; M135_289-2; M135_326-1; M135_327-1; M135_328-2; M135_329-1; M135_330-1; M135_331-1; M135_332-1; M135_333-1; Meteor (1986); Micro structure probe; MSS; Pressure, water; Profile ID; Salinity; SFB754; SFB754/POSTRE-II; Temperature, water
    Type: Dataset
    Format: text/tab-separated-values, 237907 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 86
    facet.materialart.
    Unknown
    Seawater carbonate chemistry and mussel respiration and calcification rates (2020)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: Marine habitat‐forming species often play critical roles on rocky shores by ameliorating stressful conditions for associated organisms. Such ecosystem engineers provide structure and shelter, for example, by creating refuges from thermal and desiccation stresses at low tide. Less explored is the potential for habitat formers to alter interstitial seawater chemistry during their submergence. Here, we quantify the capacity for dense assemblages of the California mussel, Mytilus californianus, to change seawater chemistry (dissolved O2, pH, and total alkalinity) within the interiors of mussel beds at high tide via respiration and calcification. We established a living mussel bed within a laboratory flow tank and measured vertical pH and oxygen gradients within and above the mussel bed over a range of water velocities. We documented decreases of up to 0.1 pH and 25 μmol O2/kg internal to the bed, along with declines of 100 μmol/kg in alkalinity, when external flows were  95% of the time. Reductions in pH and O2 inside mussel beds may negatively impact resident organisms and exacerbate parallel human‐induced perturbations to ocean chemistry while potentially selecting for improved tolerance to altered chemistry conditions.
    Keywords: Alkalinity, total; Animalia; Aragonite saturation state; Benthic animals; Benthos; Bicarbonate ion; Bodega_Bay; Brackish waters; Calcification/Dissolution; Calcification rate of calcium carbonate; Calcite saturation state; Calculated using seacarb after Nisumaa et al. (2010); Carbon, inorganic, dissolved; Carbonate ion; Carbonate system computation flag; Carbon dioxide; DATE/TIME; Difference; EXP; Experiment; Flow velocity, water; Fugacity of carbon dioxide (water) at sea surface temperature (wet air); Laboratory experiment; Location; Maximal differences in pH; Mesocosm or benthocosm; Mollusca; Mytilus californianus; North Pacific; OA-ICC; Ocean Acidification International Coordination Centre; Oxygen; Partial pressure of carbon dioxide (water) at sea surface temperature (wet air); pH; Profile ID; Registration number of species; Respiration; Respiration rate, oxygen; Salinity; Single species; Species; Temperate; Temperature, water; Type; Uniform resource locator/link to reference
    Type: Dataset
    Format: text/tab-separated-values, 774 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 87
    facet.materialart.
    Unknown
    Microstructure data from a MicroRider/Glider package (METEOR cruise M105 and M106) (2020)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: 146 profiles of post-processed upper-ocean (3m- 200m depth) microstructure data from a MicroRider/glider package collected in the central tropical Atlantic at 11°N, 21°W in April 2014. The glider used was GEOMAR's ifm03, deployment 10 (see https://gliderweb.geomar.de/html/real_glider.html). It was deployed during R/V Meteor cruise M105 and retrieved during R/V Meteor cruise M106. Dissipation rates of turbulent kinetic energy are calculated as described in Foltz et al. (2020, Vertical turbulent cooling of the mixed layer in the Atlantic ITCZ and trade wind regions. Journal of Geophysical Research: Oceans, 125, e2019JC015529). Stored parameters include: Dissipation rate of turbulent kinetic energy in m^2 s^(-3) averaged from the 2 microstructure shear sensors mounted to the MicroRider and temperature, salinity and depth as measured by the glider.
    Keywords: Cape Verde; Cast number; Climate - Biogeochemistry Interactions in the Tropical Ocean; DATE/TIME; DEPTH, water; Dissipation rate; GLD; Glider; Ifm03; LATITUDE; LONGITUDE; M105; M105_203-2; M106; M106_348-1; Meteor (1986); Profile ID; Salinity; SFB754; Temperature, water; tropical Atlantic
    Type: Dataset
    Format: text/tab-separated-values, 145020 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 88
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    Unknown
    Hydrochemistry measured on water bottle samples during the cruise Hai Yang Di Zhi Shi Hao in South China Sea in September 2018 (2021)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: During the cruise H10-2018 on board the Chinese R/V Hai Yang Di Zhi Shi Hao, we collected water with a CTD SBE911 rosette system in 64 stations distributed along the shelf, shelf edge and deep-sea of the northern South China Sea. We aimed to study the nutrients availability and primary production distribution under the influence of the strong typhoon Mangkhut, in September 2018. The influence of the Mangkhut typhoon over the upper 100 m of the water column was accessed before and after its passage. The physical oceanography during the survey is available at PANGAEA (Waniek et al., 2021). Brief description of the methodology used: - Nitrate, nitrite, phosphate and silicate were measured by continuous flow analysis. - Oxygen was measured on one sample at each station by potentiometric Winkler titration. - DOC and DN were measured by catalytic oxidation after filtered with GF/F-filters. - POC and PON were measured by means of an elemental analyser after filtered with pre-combusted GF/F-filters. - Suspended particulate material (SPM) was determined gravimetrically after pre-combusted and weighted GF/F-filters filtration. - Chlorophyll a and phaeopigments were measured using a fluorometer after ethanol extraction of the GF/F-filters. More information regarding the methodology used can be seen in Kuss et al. (in review).
    Keywords: biogeochemistry; Calculated; Carbon, organic, dissolved; Carbon, organic, particulate; catalytic oxidation (GF/F-filtered) (Grasshoff et al., 1999); Chlorophyll a; CTD, Sea-Bird, SBE 911plus; measured with Dissolved oxygen sensor, Sea-Bird, SBE 43; CTD, Sea-Bird SBE 911plus; CTD/Rosette; CTD-RO; DATE/TIME; Depth, bottom/max; DEPTH, water; elemental analyzer (GF/F- filtered) (Grasshoff et al., 1999); Event label; File name; fluorometer (ethanol extraction; GF/F-filtered) (Grasshoff et al., 1999); gravimetrically (GF/F-filtered) (Grasshoff et al., 1999); H10-2018; H10-2018_SCS-1; H10-2018_SCS-10; H10-2018_SCS-11; H10-2018_SCS-12; H10-2018_SCS-14; H10-2018_SCS-15; H10-2018_SCS-16; H10-2018_SCS-17; H10-2018_SCS-18; H10-2018_SCS-19; H10-2018_SCS-2; H10-2018_SCS-20; H10-2018_SCS-21; H10-2018_SCS-22; H10-2018_SCS-23; H10-2018_SCS-24; H10-2018_SCS-25; H10-2018_SCS-26; H10-2018_SCS-27; H10-2018_SCS-28; H10-2018_SCS-29; H10-2018_SCS-3; H10-2018_SCS-30A; H10-2018_SCS-32; H10-2018_SCS-33; H10-2018_SCS-34; H10-2018_SCS-35; H10-2018_SCS-36; H10-2018_SCS-37; H10-2018_SCS-38; H10-2018_SCS-39; H10-2018_SCS-4; H10-2018_SCS-40; H10-2018_SCS-41; H10-2018_SCS-42; H10-2018_SCS-42A; H10-2018_SCS-43; H10-2018_SCS-44; H10-2018_SCS-45; H10-2018_SCS-46; H10-2018_SCS-47; H10-2018_SCS-48; H10-2018_SCS-49; H10-2018_SCS-5; H10-2018_SCS-50; H10-2018_SCS-51; H10-2018_SCS-52; H10-2018_SCS-53; H10-2018_SCS-54; H10-2018_SCS-55; H10-2018_SCS-56; H10-2018_SCS-57; H10-2018_SCS-58_1; H10-2018_SCS-58_2; H10-2018_SCS-59; H10-2018_SCS-6; H10-2018_SCS-60; H10-2018_SCS-61; H10-2018_SCS-62; H10-2018_SCS-63; H10-2018_SCS-64; H10-2018_SCS-7; H10-2018_SCS-8; H10-2018_SCS-9; Hai Yang Di Zhi Shi Hao; LATITUDE; LONGITUDE; Megacity's fingerprint in Chinese marginal seas: Investigation of pollutant fingerprints and dispersal; MEGAPOL; Nitrate; Nitrate and Nitrite; Nitrite; Nitrogen, organic, particulate; Nitrogen, total dissolved; Oxygen, dissolved; Phaeopigments; Phosphate; Profile ID; Salinity; Sample volume; Silicate; South China Sea; Station label; Suspended particulate matter; Temperature, water; wet chemical treatment; Continuous flow analysis (Grasshoff et al., 1999); Winkler titration (Grasshoff et al., 1999)
    Type: Dataset
    Format: text/tab-separated-values, 9092 data points
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    DATA PANGAEA
  • 89
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    Seismic reflection data over Azores Plateau (2022)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: This are composite seismic reflection data crossing the Azore Plateau. Data have been collected in 2016 during RV Meteor expedition M113/1. Two GI-Guns (45/105 cin; true GI-Mode) pops were recordeed by a digital streamer of 600 m length. For details see reference. Numbers in the file names refer to profiles as described in cruise report and Hübscher et al. (2018).
    Keywords: Azores; Binary Object; Binary Object (File Size); Event label; LATITUDE; LONGITUDE; M113/1; M113/1_01-1; M113/1_05-1; Meteor (1986); Profile ID; Seismic reflection data; Seismic reflection profile; SEISREFL
    Type: Dataset
    Format: text/tab-separated-values, 4 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 90
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    Unknown
    Mercury and explosive compound 4-aminodinitrotoluene (4-ADNT) in dab (Limanda limanda) caught at munition dumping site Kolberger Heide in the Kiel Bight, Baltic Sea (2022)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: Dumped munitions contain various harmful substances which can affect marine biota like fish. One of them is mercury (Hg), included in the common explosive primer. Another is 4-aminodinitrotoluene (4-ADNT), an explosive-metabolite. 251 individual dab (Limanda limanda L.) caught at the dump site Kolberger Heide a and nearby reference sites in 2017 and 2018 were analysed. The table contain individual data on Hg, 4-aminodinitrotoluene, age, length, weight, sex and condition factor.
    Keywords: Age; Atomic absorption spectrometry (AAS), Direct Mercury Analyzer (DMA-80); B01; Baltic Sea; Code; Condition factor; dab; Date/Time of event; Determined by visual inspection of otholiths; Event label; explosive; fisch; Fresh weight; Fulton's condition factor (K = 100 x somatic weight / length^3); KH_01; KH_02; KH_03; KH_04; KH_05; KH_06; KH_07; KH_08; KH_09; KH_10; KH_11; KH_12; KH_13; Latitude of event; Limanda imanda, bile, 4-amino-2,6-dinitrolouene; Limanda limanda, mercury in biomass, wet mass; Limanda limanda, total length; Limanda limanda, wet mass; Liquid Chromatography with tandem mass spectrometry (LC-MS/MS); Longitude of event; Measured; mercury; munitions; Net; NET; Sex; SG_01; SG_02; SG_03; SG_04; SG_05; SG_06; SG_07; SG_08; SG_09; SG_10; SG_11
    Type: Dataset
    Format: text/tab-separated-values, 1992 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 91
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    Aircraft measurements of spectral downward solar irradiance over Arctic sea ice and ocean during the HALO-(AC)³ campaign in spring 2022 (2023)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: During the HALO-(AC)³ campaign in March and April 2022 spectral solar downward irradiances were measured onboard of the High Altitude LOng range research aircraft (HALO) over the Arctic sea ice and ocean using the Spectral Modular Airborne Radiation measurement sysTem (SMART). The data set gives time series of spectral irradiances measured along the flight path of HALO on 17 days. All flights started from Kiruna, Sweden and headed into the Fram Straight and towards the central Arctic. The goal of the campaign was to study warm air intrusions and cold air outbreaks to and from the Arctic and to follow those air masses over several days with remote sensing instrumentation aboard HALO. The first research flight (RF) was RF02. RF01 was the transfer flight from Oberpfaffenhofen, Germany to Kiruna. The irradiance inlet of SMART was actively stabilized and connected to two spectrometers of which one measured radiation in the visible to near infrared range (VNIR) between 180 and 1014 nm and the other radiation in the shortwave to infrared range (SWIR) between 890 and 2200 nm. The data was merged at 990 nm and cut to 320 to 2100 nm because of high uncertainties at the spectrometer edges. The spectral resolution below 900 nm is 1nm and above 5 nm due to technical limitations of the SWIR spectrometer. The data is corrected for the dark current of the spectrometers and calibrated using in field transfer calibrations connected to a laboratory calibration after the campaign.
    Keywords: AC; AC3; airborne measurements; Aircraft; Arctic; Arctic Amplification; Atmospheric and Earth System Research with HALO – High Altitude and Long Range Research Aircraft; Binary Object; Binary Object (File Size); Date/Time of event; Date/Time of event 2; Event label; HALO; HALO_220312a; HALO_220313a; HALO_220314a; HALO_220315a; HALO_220316a; HALO_220320a; HALO_220321a; HALO_220328a; HALO_220329a; HALO_220330a; HALO_220401a; HALO_220404a; HALO_220407a; HALO_220408a; HALO_220410a; HALO_220411a; HALO_220412a; HALO_AC3; HALO-(AC)³; Image; irradiance; Latitude of event; Longitude of event; RF02; RF03; RF04; RF05; RF06; RF07; RF08; RF09; RF10; RF11; RF12; RF13; RF14; RF15; RF16; RF17; RF18; SMART; solar; spectral irradiance; SPP1294
    Type: Dataset
    Format: text/tab-separated-values, 34 data points
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    DATA PANGAEA
  • 92
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    Stable water isotopologues of arrays of high resolution 1 m snow cores from across Dronning Maud Land, East Antarctic Plateau (2023)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: A set of 1 m firn profiles was sampled in December 2018 across a traverse of ~ 100 km near Kohnen Station to quantify stratigraphic noise in high resolution isotope records. At each of six different locations (D2, C4, C5, D7, D24, D38), 5 profiles were extracted on one line, perpendicularly to the overall large scale wind direction and with an interprofile spacing of 10 m. Each firn profile was vertically extracted from the snow surface by inserting a 1 m pipe of carbon fiber at the sidewall of a snow-pit. Vertical target resolution was 1.1 cm in the upper 16.5 cm and 3.3 cm in the lower part. Due compression and expanding while handling, transportation and cutting at site, we assume a maximum depth uncertainty from these steps of 2 cm. All samples (N = 1249) were packed in plastic bags and transported to Germany in a constantly frozen state. Measurements of the stable water isotopic composition (δ¹⁸O, δD) of the firn samples were done using a Cavity Ring-Down Spectroscopy instrument (CRDS) of PICARRO Inc (model L2140-i) in the Stable Isotope Facility at the Alfred Wegener Institute in Potsdam, Germany. Post-run correction was done as described in Münch et al., (2016 - doi:10.5194/cp-12-1565-2016). Scaling to the VSMOW/SLAP (Vienna Standard Mean Ocean Water/StandardLight Antarctic Precipitation) scale results in the δ-notation, describing the ratio of heavy to light isotopes in ‰. In-house standards were used for quality control. The mean combined measurement uncertainty is 0.07‰ for δ¹⁸O and 0.5‰ for δD (root mean square deviation, RMSD).
    Keywords: 2018_Kohnen_C4; 2018_Kohnen_C5; 2018_Kohnen_D2; 2018_Kohnen_D24; 2018_Kohnen_D38; 2018_Kohnen_D7; AWI_Envi; AWI_SPACE; Cavity Ring-Down Spectrometer (CRDS), PICARRO, L2140i; Date/Time of event; DEPTH, ice/snow; Depth, ice/snow, bottom/maximum; Depth, ice/snow, top/minimum; Deuterium excess; Deuterium excess, standard deviation; Dronning Maud Land; East Antarctic plateau; Event label; FIRNC; Firn corer; Kohnen_based; Kohnen Station; LATITUDE; Location ID; LONGITUDE; Polar Terrestrial Environmental Systems @ AWI; Position; Profile ID; Sample number; snow cores; Snow height; Space-time structure of climate change @ AWI; stable water isotopes; δ18O, water; δ18O, water, standard deviation; δ Deuterium, standard deviation; δ Deuterium, water
    Type: Dataset
    Format: text/tab-separated-values, 16237 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 93
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    Quasi-Lagrangian air mass matches during HALO-(AC)3: Matches occuring over consecutive days (2024)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: One of the main goals of the HALO-(AC)3 Arctic airborne campaign conducted in spring 2022 was a quasi-Lagrangian sampling of air masses. This means that the same air masses were to be sampled twice. Such a measurement strategy allows for concrete observations of air mass transformations, which can for example be used to benchmark weather models. After finishing the campaign, trajectory calculations were conducted for all flights of the HALO aircraft to check whether the flight strategy was a success. For this, the trajectory calculation tool Lagranto was used in conjunction with wind fields from the ERA5 reanalysis. Latter has an output resolution of around 30 km and one hour. The hourly data was bi-linearly interpolated to one minute resolution. Air masses were initialized temporally every one minute along the flight track of HALO, and vertically every 5 hPa between 250 hPa and 10 hPa above the ground level. Horizontally, air masses were started within a 30 km radius circle centered around the location of HALO. In each circle, 30 air masses were initialized evenly spaced approximately every 10 km, allowing for a better statistical analysis. Trajectories were then calculated in one-minute steps up to 32 hours forward in time. At typical HALO flight times of up to 10 hours, around 2.7 million trajectories were calculated per research flight. A quasi-Lagrangian match is registered if the same air mass is seen again below HALO on the subsequent day and within the same 30 km radius.
    Keywords: AC; AC3; Aircraft; Arctic; Arctic Amplification; Date/Time of event; Event label; HALO; HALO_220312a; HALO_220313a; HALO_220314a; HALO_220315a; HALO_220320a; HALO_220328a; HALO_220329a; HALO_220407a; HALO_220410a; HALO_220411a; HALO_AC3; HALO-(AC)³; Image; Lagrangian data; Optional event label; RF02; RF03; RF04; RF05; RF07; RF09; RF10; RF14; RF16; RF17; Text file; trajectories
    Type: Dataset
    Format: text/tab-separated-values, 30 data points
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    DATA PANGAEA
  • 94
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    Oxygen microprofiles measured in situ in sediments of Kermadec Trench and adjacent abyssal plains (2024)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    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 ID; 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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    DATA PANGAEA
  • 95
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    One-dimensional cloud-top or surface brightness temperature with 20 Hz temporal resolution derived at flight altitude from VELOX-KT19 during the HALO-(AC)³ field campaign (2024)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: During the HALO-(AC)³ campaign in March-April 2022 airborne observations were performed with the High Altitude LOng range research aircraft (HALO) covering the Fram Strait and north polar regions. The flight tracks covered open ocean areas, the marginal sea ice zone, and closed sea ice cover. Furthermore, cloud conditions were observed during air mass transformation events as marine cold air outbreaks and warm air intrusions. On HALO, thermal infrared radiance, spectrally integrated over the wavelength range from 9.6 µm to 11.5 µm in nadir direction (field of view of 2.3°), was measured by the infrared pyrometer KT19 (model KT19.85 II). The given dataset comprises brightness temperature measurements with a temporal resolution of 20 Hz, provided for 16 HALO research flights (RF) during HALO-(AC)³.
    Keywords: AC; AC3; Aircraft; Arctic Amplification; Atmospheric and Earth System Research with HALO – High Altitude and Long Range Research Aircraft; brightness temperature; Date/Time of event; Event label; HALO; HALO_220313a; HALO_220314a; HALO_220315a; HALO_220316a; HALO_220320a; HALO_220321a; HALO_220328a; HALO_220329a; HALO_220330a; HALO_220401a; HALO_220404a; HALO_220407a; HALO_220408a; HALO_220410a; HALO_220411a; HALO_220412a; HALO_AC3; HALO-(AC)³; Infrared radiation pyrometer, Heitronics, KT19.85II; netCDF file; netCDF file (File Size); Optional event label; RF03; RF04; RF05; RF06; RF07; RF08; RF09; RF10; RF11; RF12; RF13; RF14; RF15; RF16; RF17; RF18; SPP1294
    Type: Dataset
    Format: text/tab-separated-values, 16 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 96
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    Polarization measurements with the hyperspectral and polarized imaging system specMACS during the HALO-(AC)3 field campaign (2024)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: During the HALO-(AC)3 campaign, the hyperspectral and polarized imaging system specMACS was integrated into the German research aircraft HALO. This dataset contains videos with measurements of the two polarization resolving cameras of specMACS which measure the two-dimensional distribution of the I, Q, and U components of the Stokes vector at red, green, and blue color channels with an acquisition rate of 8Hz. Both cameras are operated in a nadir looking perspective and have a combined field of view of 91 x 117 degree in along and across track direction. The videos include RGB images as well as images of the degree of linear polarization derived from the measurements.
    Keywords: AC; AC3; airborne measurements; Aircraft; Arctic; Arctic Amplification; Atmospheric and Earth System Research with HALO – High Altitude and Long Range Research Aircraft; Date/Time of event; Event label; HALO; HALO_220311a; HALO_220312a; HALO_220313a; HALO_220314a; HALO_220315a; HALO_220316a; HALO_220320a; HALO_220321a; HALO_220328a; HALO_220329a; HALO_220330a; HALO_220401a; HALO_220404a; HALO_220407a; HALO_220408a; HALO_220410a; HALO_220411a; HALO_220412a; HALO_220414a; HALO_AC3; HALO-(AC)³; Hyperspectral and polarization resolving imager, Munich Aerosol Cloud Scanner; Latitude of event; Longitude of event; Optional event label; polarization; RF01; RF02; RF03; RF04; RF05; RF06; RF07; RF08; RF09; RF10; RF11; RF12; RF13; RF14; RF15; RF16; RF17; RF18; RF19; specMACS; SPP1294; Video, earth surface (water, ice, land); Video, earth surface (water, ice, land) (File Size)
    Type: Dataset
    Format: text/tab-separated-values, 38 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 97
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    Spectral radiance measurements with the hyperspectral and polarized imaging system specMACS during the HALO-(AC)3 field campaign (2024)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Description: During the HALO-(AC)3 campaign, the hyperspectral and polarized imaging system specMACS was integrated into the German research aircraft HALO in a nadir-looking perspective. This dataset contains calibrated spectral radiances in mW/(m2 nm sr) for the shortwave infrared wavelength range between about 1000 and 2400nm measured by the SWIR spectrometer of specMACS. The spectrometer has 320 spatial pixels along a spatial line oriented in across-track direction with a field of view of 35.5 degree and measures at an acquisition frequency of 30Hz. The calibration of the data was performed as described in Ewald et al. (2016). Because of the large size of the data, the calibrated radiances for each research flight were split into different files along the wavelength dimension. Each dataset contains measurements of 20 wavelength channels for the wavelength range given in the file name. Additionally, the dataset includes georeferencing information with viewing zenith and viewing azimuth angles as well as sensor latitude, longitude, and height above WGS84 for every measured pixel as a separate file for every flight. Note that during the first three flights there was some icing of the window in front of the cameras which is visible in the data.
    Keywords: AC; AC3; airborne measurements; Aircraft; Arctic; Arctic Amplification; Atmospheric and Earth System Research with HALO – High Altitude and Long Range Research Aircraft; DATE/TIME; Event label; File content; HALO; HALO_220311a; HALO_220312a; HALO_220313a; HALO_220314a; HALO_220315a; HALO_220316a; HALO_220320a; HALO_220321a; HALO_220328a; HALO_220329a; HALO_220330a; HALO_220401a; HALO_220404a; HALO_220407a; HALO_220408a; HALO_220410a; HALO_220411a; HALO_220412a; HALO_220414a; HALO_AC3; HALO-(AC)³; Hyperspectral and polarization resolving imager, Munich Aerosol Cloud Scanner; Latitude of event; Longitude of event; netCDF file; Optional event label; RF01; RF02; RF03; RF04; RF05; RF06; RF07; RF08; RF09; RF10; RF11; RF12; RF13; RF14; RF15; RF16; RF17; RF18; RF19; specMACS; spectral radiance; SPP1294
    Type: Dataset
    Format: text/tab-separated-values, 456 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 98
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    Oxygen microprofiles measured in situ in sediments of Atacama Trench and adjacent abyssal plains (2024)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    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 ID; 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
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 99
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    Fig. 8 RPI Süttö compared to Glopis and Piso data (2020)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Keywords: data correlation; DEPTH, sediment/rock; Hungary; Piso and Glopis data stack; Profile ID; Relative paleointensity proxy; RPI; Suettoe; Süttö; Year of observation
    Type: Dataset
    Format: text/tab-separated-values, 825 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 100
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    Mean January paleotemperatures in northwestern Yakutia from 42 to 47 cal ka BP (2020)
    PANGAEA
    Details
    Publication Date: 2024-06-10
    Keywords: accelerator mass spectrometry (AMS); Accelerator mass spectrometry (AMS); Age, comment; AWI Arctic Land Expedition; Batagay; Batagay_1; Event label; Ice wedges; Kular; Kurungnakh_Island; Late Pleistocene; Latitude of event; Lena2013; Location; Longitude of event; Mamontova_Khayata; Mass spectrometer Finnigan Delta-V; micro-inclusions; North Yakutia, Russia; Oyogos_Yar; radiocarbon; Reference/source; RU-Land_2013_Lena; SAT; Satellite remote sensing; Syngenetic; Temperature, air, calculated; δ18O, water
    Type: Dataset
    Format: text/tab-separated-values, 48 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
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