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  • 1
    Call number: AWI G8-23-95167
    Description / Table of Contents: The Arctic nearshore zone plays a key role in the carbon cycle. Organic-rich sediments get eroded off permafrost affected coastlines and can be directly transferred to the nearshore zone. Permafrost in the Arctic stores a high amount of organic matter and is vulnerable to thermo-erosion, which is expected to increase due to climate change. This will likely result in higher sediment loads in nearshore waters and has the potential to alter local ecosystems by limiting light transmission into the water column, thus limiting primary production to the top-most part of it, and increasing nutrient export from coastal erosion. Greater organic matter input could result in the release of greenhouse gases to the atmosphere. Climate change also acts upon the fluvial system, leading to greater discharge to the nearshore zone. It leads to decreasing sea-ice cover as well, which will both increase wave energy and lengthen the open-water season. Yet, knowledge on these processes and the resulting impact on the nearshore zone is scarce, because access to and instrument deployment in the nearshore zone is challenging. Remote sensing can alleviate these issues in providing rapid data delivery in otherwise non-accessible areas. However, the waters in the Arctic nearshore zone are optically complex, with multiple influencing factors, such as organic rich suspended sediments, colored dissolved organic matter (cDOM), and phytoplankton. The goal of this dissertation was to use remotely sensed imagery to monitor processes related to turbidity caused by suspended sediments in the Arctic nearshore zone. In-situ measurements of water-leaving reflectance and surface water turbidity were used to calibrate a semi-empirical algorithm which relates turbidity from satellite imagery. Based on this algorithm and ancillary ocean and climate variables, the mechanisms underpinning nearshore turbidity in the Arctic were identified at a resolution not achieved before. The calibration of the Arctic Nearshore Turbidity Algorithm (ANTA) was based on in-situ measurements from the coastal and inner-shelf waters around Herschel Island Qikiqtaruk (HIQ) in the western Canadian Arctic from the summer seasons 2018 and 2019. It performed better than existing algorithms, developed for global applications, in relating turbidity from remotely sensed imagery. These existing algorithms were lacking validation data from permafrost affected waters, and were thus not able to reflect the complexity of Arctic nearshore waters. The ANTA has a higher sensitivity towards the lowest turbidity values, which is an asset for identifying sediment pathways in the nearshore zone. Its transferability to areas beyond HIQ was successfully demonstrated using turbidity measurements matching satellite image recordings from Adventfjorden, Svalbard. The ANTA is a powerful tool that provides robust turbidity estimations in a variety of Arctic nearshore environments. Drivers of nearshore turbidity in the Arctic were analyzed by combining ANTA results from the summer season 2019 from HIQ with ocean and climate variables obtained from the weather station at HIQ, the ERA5 reanalysis database, and the Mackenzie River discharge. ERA5 reanalysis data were obtained as domain averages over the Canadian Beaufort Shelf. Nearshore turbidity was linearly correlated to wind speed, significant wave height and wave period. Interestingly, nearshore turbidity was only correlated to wind speed at the shelf, but not to the in-situ measurements from the weather station at HIQ. This shows that nearshore turbidity, albeit being of limited spatial extent, gets influenced by the weather conditions multiple kilometers away, rather than in its direct vicinity. The large influence of wave energy on nearshore turbidity indicates that freshly eroded material off the coast is a major contributor to the nearshore sediment load. This contrasts results from the temperate and tropical oceans, where tides and currents are the major drivers of nearshore turbidity. The Mackenzie River discharge was not identified as a driver of nearshore turbidity in 2019, however, the analysis of 30 years of Landsat archive imagery from 1986 to 2016 suggests a direct link between the prevailing wind direction, which heavily influences the Mackenzie River plume extent, and nearshore turbidity around HIQ. This discrepancy could be caused by the abnormal discharge behavior of the Mackenzie River in 2019. This dissertation has substantially advanced the understanding of suspended sediment processes in the Arctic nearshore zone and provided new monitoring tools for future studies. The presented results will help to understand the role of the Arctic nearshore zone in the carbon cycle under a changing climate.
    Type of Medium: Dissertations
    Pages: xv, ii, 85, xvii Seiten , Illustrationen, Diagramme, Karten
    Language: English
    Note: Dissertation, Universität Potsdam, 2022 (kumulative Dissertation) , TABLE OF CONTENTS Abstract Zusammenfassung Allgemeinverständliche Zusammenfassung List of Figures List of Tables Funding Chapter 1 Introduction 1.1 Scientific Background 1.1.1 Arctic Climate Change 1.1.2 The Arctic Nearshore Zone 1.1.3 Ocean Color Remote Sensing 1.2 Objectives 1.3 Study Area 1.4 Methods 1.4.1 Field Sampling 1.4.2 Data Processing 1.4.3 Satellite Imagery Processing 1.5 Thesis Structure 1.6 Author Contributions Chapter 2 Long-Term High-Resolution Sediment and Sea Surface Temperature Spatial Patterns in Arctic Nearshore Waters retrived using 30-year Landsat Archive Imagery 2.1 Abstract 2.2 Introduction 2.3 Material and Methods 2.3.1 Regional Setting 2.3.2 Landsat Images Acquisition and Processing 2.3.3 Landsat Turbidity Retrieval 2.3.4 Transects in the nearshore zone 2.3.5 Wind Data 2.4 Results 2.4.1 Brightness Temperature 2.4.2 Surface Reflectance and Turbidity Mapping 2.4.3 Gradients in the nearshore zone 2.5 Discussion 2.6 Conclusion Appendix A Chapter 3 The Arctic Nearshore Turbidity Algorithm (ANTA) - A Multi Sensor Turbidity Algorithm for Arctic Nearshore Environments 3.1 Abstract 3.2 Introduction 3.3 Methods 3.3.1 Regional setting 3.3.2 In-situ sampling 3.3.3 Optical data processing 3.3.4 Algorithm tuning 3.3.5 Satellite imagery processing 3.4 Results and Discussion 3.4.1 Turbidity and SPM 3.4.2 ANTA performance 3.4.3 Comparison with the Dogliotti et al., (2015) algorithm 3.4.4 Test and transfer of the ANTA 3.5 Conclusion Chapter 4 Drivers of Turbidity and its Seasonal Variability in the Nearshore Zone of Herschel Island Qikiqtaruk (western Canadian Arctic) 4.1 Abstract 4.2 Introduction 4.3 Methods 4.3.1 Study Area 4.3.2 Satellite Imagery 4.3.3 In-situ data 4.3.4 Reanalysis data 4.4 Results and Discussion 4.4.1 Time Series Analysis 4.4.2 Drivers of turbidity 4.5 Conclusion Chapter 5 Synthesis 5.1 Applicability of Remote Sensing Algorithms in the Arctic Nearshore Zone 5.2 Drivers of Nearshore Turbidity 5.3 Spatial Variations of Nearshore Turbidity 5.4 Challenges and Outlook List of Acronyms Bibliography Danksagung
    Location: AWI Reading room
    Branch Library: AWI Library
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  • 2
    Publication Date: 2015-09-15
    Description: We investigated 32 net primary productivity (NPP) models by assessing skills to reproduce integrated NPP in the Arctic Ocean. The models were provided with two sources each of surface chlorophyll-a concentration (chlorophyll), photosynthetically available radiation (PAR), sea surface temperature (SST), and mixed-layer depth (MLD). The models were most sensitive to uncertainties in surface chlorophyll, generally performing better with in situ chlorophyll than with satellite-derived values. They were much less sensitive to uncertainties in PAR, SST, and MLD, possibly due to relatively narrow ranges of input data and/or relatively little difference between input data sources. Regardless of type or complexity, most of the models were not able to fully reproduce the variability of in situ NPP, whereas some of them exhibited almost no bias (i.e., reproduced the mean of in situ NPP). The models performed relatively well in low-productivity seasons as well as in sea ice-covered/deep-water regions. Depth-resolved models correlated more with in situ NPP than other model types, but had a greater tendency to overestimate mean NPP whereas absorption-based models exhibited the lowest bias associated with weaker correlation. The models performed better when a subsurface chlorophyll-a maximum (SCM) was absent. As a group, the models overestimated mean NPP, however this was partly offset by some models underestimating NPP when a SCM was present. Our study suggests that NPP models need to be carefully tuned for the Arctic Ocean because most of the models performing relatively well were those that used Arctic-relevant parameters. This article is protected by copyright. All rights reserved.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev , info:eu-repo/semantics/article
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  • 3
    Publication Date: 2023-08-28
    Description: Climate warming and related drivers of soil thermal change in the Arctic are expected to modify the distribution and dynamics of carbon contained in perennially frozen grounds. Thawing of permafrost in the Mackenzie River watershed of northwestern Canada, coupled with increases in river discharge and coastal erosion, triggers the release of terrestrial organic matter (OMt) from the largest Arctic drainage basin in North America into the Arctic Ocean. While this process is ongoing and its rate is accelerating, the fate of the newly mobilized organic matter as it transits from the watershed through the delta and into the marine system remains poorly understood. In the framework of the European Horizon 2020 Nunataryuk programme, and as part of the Work Package 4 (WP4) Coastal Waters theme, four field expeditions were conducted in the Mackenzie Delta region and southern Beaufort Sea from April to September 2019. The temporal sampling design allowed the survey of ambient conditions in the coastal waters under full ice cover prior to the spring freshet, during ice breakup in summer, and anterior to the freeze-up period in fall. To capture the fluvial-marine transition zone, and with distinct challenges related to shallow waters and changing seasonal and meteorological conditions, the field sampling was conducted in close partnership with members of the communities of Aklavik, Inuvik and Tuktoyaktuk, using several platforms, namely helicopters, snowmobiles, and small boats. Water column profiles of physical and optical variables were measured in situ, while surface water, groundwater, and sediment samples were collected and preserved for the determination of the composition and sources of OMt, including particulate and dissolved organic carbon (POC and DOC), and colored dissolved organic matter (CDOM), as well as a suite of physical, chemical, and biological variables. Here we present an overview of the standardized datasets, including hydrographic profiles, remote sensing reflectance, temperature and salinity, particle absorption, nutrients, dissolved organic carbon, particulate organic carbon, particulate organic nitrogen, CDOM absorption, fluorescent dissolved organic matter intensity, suspended particulate matter, total particulate carbon, total particulate nitrogen, stable water isotopes, radon in water, bacterial abundance, and a string of phytoplankton pigments including total chlorophyll. Datasets and related metadata can be found in (10.1594/PANGAEA.937587).
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
    Format: application/pdf
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  • 4
    Publication Date: 2022-05-26
    Description: © The Author(s), 2016. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Earth System Science Data 8 (2016): 235-252, doi:10.5194/essd-8-235-2016.
    Description: A compiled set of in situ data is important to evaluate the quality of ocean-colour satellite-data records. Here we describe the data compiled for the validation of the ocean-colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI). The data were acquired from several sources (MOBY, BOUSSOLE, AERONET-OC, SeaBASS, NOMAD, MERMAID, AMT, ICES, HOT, GeP&CO), span between 1997 and 2012, and have a global distribution. Observations of the following variables were compiled: spectral remote-sensing reflectances, concentrations of chlorophyll a, spectral inherent optical properties and spectral diffuse attenuation coefficients. The data were from multi-project archives acquired via the open internet services or from individual projects, acquired directly from data providers. Methodologies were implemented for homogenisation, quality control and merging of all data. No changes were made to the original data, other than averaging of observations that were close in time and space, elimination of some points after quality control and conversion to a standard format. The final result is a merged table designed for validation of satellite-derived ocean-colour products and available in text format. Metadata of each in situ measurement (original source, cruise or experiment, principal investigator) were preserved throughout the work and made available in the final table. Using all the data in a validation exercise increases the number of matchups and enhances the representativeness of different marine regimes. By making available the metadata, it is also possible to analyse each set of data separately. The compiled data are available at doi:10.1594/PANGAEA.854832 (Valente et al., 2015).
    Description: We thank NASA for project funding for data collection.
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 5
    Publication Date: 2022-05-26
    Description: © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Earth System Science Data 11(3), (2019): 1037-1068, doi: 10.5194/essd-11-1037-2019.
    Description: A global compilation of in situ data is useful to evaluate the quality of ocean-colour satellite data records. Here we describe the data compiled for the validation of the ocean-colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI). The data were acquired from several sources (including, inter alia, MOBY, BOUSSOLE, AERONET-OC, SeaBASS, NOMAD, MERMAID, AMT, ICES, HOT and GeP&CO) and span the period from 1997 to 2018. Observations of the following variables were compiled: spectral remote-sensing reflectances, concentrations of chlorophyll a, spectral inherent optical properties, spectral diffuse attenuation coefficients and total suspended matter. The data were from multi-project archives acquired via open internet services or from individual projects, acquired directly from data providers. Methodologies were implemented for homogenization, quality control and merging of all data. No changes were made to the original data, other than averaging of observations that were close in time and space, elimination of some points after quality control and conversion to a standard format. The final result is a merged table designed for validation of satellite-derived ocean-colour products and available in text format. Metadata of each in situ measurement (original source, cruise or experiment, principal investigator) was propagated throughout the work and made available in the final table. By making the metadata available, provenance is better documented, and it is also possible to analyse each set of data separately. This paper also describes the changes that were made to the compilation in relation to the previous version (Valente et al., 2016). The compiled data are available at https://doi.org/10.1594/PANGAEA.898188 (Valente et al., 2019).
    Description: This research has been supported by the ESA Climate Change Initiative – Ocean Colour project (ref: AO-1/6207/09/I-LG).
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 6
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    PANGAEA
    In:  Supplement to: Valente, André; Sathyendranath, Shubha; Brotas, Vanda; Groom, Steve; Grant, Michael; Taberner, Malcolm; Antoine, David; Arnone, Robert; Balch, William M; Barker, Kathryn; Barlow, Raymond G; Bélanger, Simon; Berthon, Jean-François; Besiktepe, Sukru; Brando, Vittorio E; Canuti, Elisabetta; Chavez, Francisco P; Claustre, Hervé; Crout, Richard; Frouin, Robert; García-Soto, Carlos; Gibb, Stuart W; Gould, Richard; Hooker, Stanford B; Kahru, Mati; Klein, Holger; Kratzer, Susanne; Loisel, Hubert; McKee, David; Mitchell, Brian G; Moisan, Tiffany; Muller-Karger, Frank E; O'Dowd, Leonie; Ondrusek, Michael; Poulton, Alex J; Repecaud, Michel; Smyth, Timothy J; Sosik, Heidi; Twardowski, Michael S; Voss, Kenneth; Werdell, P Jeremy; Wernand, Marcel Robert; Zibordi, Giuseppe (2016): A compilation of global bio-optical in situ data for ocean-colour satellite applications. Earth System Science Data, 8(1), 235-252, https://doi.org/10.5194/essd-8-235-2016
    Publication Date: 2023-05-12
    Description: A compiled set of in situ data is important to evaluate the quality of ocean-colour satellite-data records. Here we describe the data compiled for the validation of the ocean-colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI). The data were acquired from several sources (MOBY, BOUSSOLE, AERONET-OC, SeaBASS, NOMAD, MERMAID, AMT, ICES, HOT, GeP&CO), span between 1997 and 2012, and have a global distribution. Observations of the following variables were compiled: spectral remote-sensing reflectances, concentrations of chlorophyll a, spectral inherent optical properties and spectral diffuse attenuation coefficients. The data were from multi-project archives acquired via the open internet services or from individual projects, acquired directly from data providers. Methodologies were implemented for homogenisation, quality control and merging of all data. No changes were made to the original data, other than averaging of observations that were close in time and space, elimination of some points after quality control and conversion to a standard format. The final result is a merged table designed for validation of satellite-derived ocean-colour products and available in text format. Metadata of each in situ measurement (original source, cruise or experiment, principal investigator) were preserved throughout the work and made available in the final table. Using all the data in a validation exercise increases the number of matchups and enhances the representativeness of different marine regimes. By making available the metadata, it is also possible to analyse each set of data separately.
    Type: Dataset
    Format: application/zip, 3 datasets
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  • 7
    Publication Date: 2023-02-25
    Keywords: Absorption coefficient, colored dissolved organic matter at given wavelength; Algal pigment absorption coefficient at given wavelength; Backscattering coefficient of particles at given wavelength; Comment; DATE/TIME; DEPTH, water; Identification; Irradiance coefficient, diffuse downwelling at given wavelength; LATITUDE; LONGITUDE; Quality flag, time; Suspended matter, total; Wavelength
    Type: Dataset
    Format: text/tab-separated-values, 439720 data points
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  • 8
    Publication Date: 2023-02-25
    Keywords: Absorption coefficient, colored dissolved organic matter at given wavelength; Algal pigment absorption coefficient at given wavelength; Backscattering coefficient of particles at given wavelength; Comment; DATE/TIME; DEPTH, water; Identification; Irradiance coefficient, diffuse downwelling at given wavelength; LATITUDE; LONGITUDE; Quality flag, time; Suspended matter, total; Wavelength
    Type: Dataset
    Format: text/tab-separated-values, 497100 data points
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  • 9
    Publication Date: 2023-02-25
    Keywords: Absorption coefficient, colored dissolved organic matter at given wavelength; Algal pigment absorption coefficient at given wavelength; Backscattering coefficient of particles at given wavelength; Comment; DATE/TIME; DEPTH, water; Identification; Irradiance coefficient, diffuse downwelling at given wavelength; LATITUDE; LONGITUDE; Quality flag, time; Suspended matter, total
    Type: Dataset
    Format: text/tab-separated-values, 311040 data points
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  • 10
    Publication Date: 2023-02-25
    Keywords: Comment; DATE/TIME; DEPTH, water; Identification; LATITUDE; LONGITUDE; Remote sensing reflectance at given wavelength; Wavelength
    Type: Dataset
    Format: text/tab-separated-values, 2137110 data points
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