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  • 2020-2024  (29)
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  • 1
    Online-Ressource
    Online-Ressource
    Les Ulis :EDP Sciences,
    Schlagwort(e): Lamiaceae. ; Lamiaceae-Classification. ; Microtoena-Classification. ; Electronic books.
    Beschreibung / Inhaltsverzeichnis: No detailed description available for "A Monograph of the genus Microtoena (Lamiaceae)".
    Materialart: Online-Ressource
    Seiten: 1 online resource (150 pages)
    Ausgabe: 1st ed.
    ISBN: 9782759825295
    Serie: Current Natural Sciences Series
    Sprache: Englisch
    Anmerkung: Intro -- A Monograph of the Genus Microtoena (Lamiaceae) -- DEDICATION -- PREFACE -- ACKNOWLEDGEMENTS -- CONTENTS -- CHAPTER I. TAXONOMIC HISTORY AND QUESTIONS TO BE ADDRESSED -- TAXONOMIC HISTORY -- CIRCUMSCRIPTION AND PHYLOGENETICAL POSITION -- SUBDIVISION -- SPECIES DELIMITATION -- QUESTIONS TO BE ADDRESSED -- CHAPTER II. MORPHOLOGY -- ROOTS -- STEMS -- LEAVES -- LEAF LENGTH -- LEAF SHAPE -- LEAF MARGIN -- LEAF BASE -- LEAF SURFACE -- INFLORESCENCE -- BRACTS -- BRACT LENGTH -- BRACT SHAPE -- CALYX -- CALYX LENGTH -- CALYX SPLIT RATIO -- CALYX TOOTH RATIO -- COROLLA -- COROLLA COLOUR -- COROLLA LENGTH -- COROLLA TUBE RATIO -- APEX OF THE UPPER LIP OF THE COROLLA -- HAIRS OF THE UPPER LIP OF THE COROLLA -- MIDDLE LOBE OF THE LOWER LIP OF THE COROLLA -- STAMENS -- ANTHERS -- HAIRS ON THE FILAMENTS -- STYLE -- POLLEN -- FRUITS -- CHAPTER III. MOLECULAR PHYLOGENY, BIOGEOGRAPHY AND CHARACTER EVOLUTION -- PHYLOGENETICAL POSITION AND SUBDIVISION -- ORIGIN AND DIVERSIFICATION -- CHARACTER EVOLUTION -- CHAPTER IV. TAXONOMIC REVISION OF MICROTOENA -- MICROTOENA PRAIN -- KEY TO SECTIONS AND SPECIES OF MICROTOENA -- SECTION 1. Microtoena -- 1. Microtoena esquirolii -- 2. Microtoena insuavis -- 3. Microtoena patchoulii -- 4. Microtoena mollis -- SECTION. 2. Delavayana -- 5. Microtoena delavayi -- 6. Microtoena wardii -- 7. Microtoena urticifolia -- 8. Microtoena albescens -- 9. Microtoena stenocalyx -- 10. Microtoena miyiensis -- 11. Microtoena megacalyx -- 12. Microtoena moupinensis -- 14. Microtoena muliensis -- 13. Microtoena prainiana -- 15. Microtoena omeiensis -- 16. Microtoena brevipedunculata -- 17. Microtoena nepalensis -- 18. Microtoena robusta -- 19. Microtoena vanchingshanensis -- EXCLUDED NAME -- BIBLIOGRAPHY -- INDEX TO SPECIMENS CITED -- INDEX TO BOTANICAL NAMES AND SYNONYMS -- DATA OF STANDARD DEVIATION ANALYSIS.
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  • 2
    Online-Ressource
    Online-Ressource
    Oxford :CAB International,
    Schlagwort(e): Electronic books.
    Beschreibung / Inhaltsverzeichnis: This book features recent developments from cyanobacteria to eukaryotic algae, from theoretical biology to applied biology. It also includes the latest advancements in algal-based synthetic biology, including metabolic engineering, artificial biological system construction and green chemicals production.
    Materialart: Online-Ressource
    Seiten: 1 online resource (325 pages)
    Ausgabe: 1st ed.
    ISBN: 9781800621954
    Serie: CABI Biotechnology Series
    Sprache: Englisch
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  • 3
    Online-Ressource
    Online-Ressource
    Singapore :Springer Singapore Pte. Limited,
    Schlagwort(e): Photosynthesis. ; Electronic books.
    Materialart: Online-Ressource
    Seiten: 1 online resource (346 pages)
    Ausgabe: 1st ed.
    ISBN: 9789811531101
    DDC: 581.13342
    Sprache: Englisch
    Anmerkung: Intro -- Preface -- Contents -- Part I: Photosynthesis and Energy Transfer -- Molecular Mechanism of Photosynthesis Driven by Red-Shifted Chlorophylls -- 1 General Knowledge of Photosynthesis -- 2 Photosynthetic Organisms -- 2.1 Photosynthetic Eukaryotes -- 2.2 Photosynthetic Prokaryotes -- 2.2.1 Anoxygenic Photosynthetic Prokaryotes -- 2.2.2 Oxygenic Photosynthetic Prokaryotes (Cyanobacteria) -- 3 Photopigments -- 3.1 Carotenoids -- 3.2 Phycobiliprotein Complexes -- 3.3 Chlorophylls -- 3.3.1 Chl a and Its Spectral Properties -- 3.3.2 Formyl Substitution in Chl b, Chl d, and Chl f -- 3.3.3 Diformyl Variants -- 3.3.4 Chl c Family -- 3.3.5 Other Chlorophyll Variants (Including Chemically Modified) -- 4 Photopigment-Binding Protein Complexes -- 4.1 Photosystem I -- 4.2 Photosystem II -- 4.3 Chlorophyll-Binding Light-Harvesting Protein Complexes (CBPs) -- 4.3.1 Inner Antenna Complexes -- 4.3.2 Chl-Binding Proteins in Cyanobacteria -- 4.3.3 Iron-Stress-Induced Chlorophyll-binding Protein A (IsiA) -- 4.4 Phycobilisomes (PBSs) -- 5 Acaryochloris marina -- 5.1 Light-Harvesting Systems -- 5.1.1 Chl d-Binding Light-Harvesting Proteins -- 5.1.2 Phycobiliproteins -- 5.2 Photosystems -- 5.3 Biochemistry of Chlorophyll d -- 6 Chl f-Producing Cyanobacteria -- 6.1 Occurrence of Chl f-Producing Cyanobacteria -- 6.2 Chl f and Photosynthetic Reactions -- 6.3 Biochemistry of Chl f -- 7 Applications of Red-Shifted Chlorophylls -- References -- Cyanobacterial NDH-1-Photosystem I Supercomplex -- 1 Introduction -- 2 Identification -- 3 Function -- 4 Assembly -- 5 Evolutional Change -- 6 Concluding Remarks -- References -- Recent Progress on the LH1-RC Complexes of Purple Photosynthetic Bacteria -- 1 Introduction -- 2 Structure of the LH1-RC Complexes -- 2.1 Overall Structure of LH1-RC Complex -- 2.2 Novel Structural Features of the Intact RC Complex. , 2.3 Potential Exchange Pathway for Quinones -- 2.4 Structural Basis for the Redshift and Enhanced Thermostability -- 3 Dynamic Process Involved in the LH1-RC -- 3.1 Exciton Delocalization and Relaxation on the LH1 Ring -- 3.2 LH1 → RC Energy Trapping -- 3.3 Charge Separation and Electron Transfer in RC -- 3.4 Carotenoid and Photo-Protection -- 4 Concluding Remarks -- References -- Composition, Organisation and Function of Purple Photosynthetic Machinery -- 1 General Introduction -- 2 Structural Components -- 2.1 Peripheral Antenna Complexes -- 2.1.1 Light-Harvesting Complex 2 -- 2.1.2 Light-Harvesting Complexes 3 and 4 -- 2.2 The Core Complex of Purple Bacterial Photosynthesis -- 2.2.1 Light-Harvesting Complex 1 -- 2.2.2 The Photochemical Reaction Centre -- 2.2.2.1 Quinones -- 2.2.3 Additional Core Complex Components -- 2.2.3.1 PufX -- 2.2.3.2 Protein W -- 2.2.3.3 The Gamma Subunit -- 2.2.4 Architectures of Core Complexes -- 2.3 Cofactors and Pigments -- 2.3.1 Carotenoids -- 2.3.2 Bacteriochlorophylls -- 2.3.3 Bacteriopheophytins -- 2.4 Cofactor-Cofactor and Protein-Protein Interactions -- 2.5 Assembly of Complexes -- 2.6 Spectroscopic Properties of Light-Harvesting Complexes -- 2.7 Cytochrome bc1 -- 2.8 ATP Synthase -- 2.9 Cytochrome c2 -- 3 Organisation and Assembly of Photosynthetic Membranes -- 3.1 Common Features of the Photosynthetic Membranes -- 3.2 Functional Importance of Photosynthetic Membrane Organisation -- 4 Energy Transfer -- 4.1 Transfer of Excitation Energy -- 4.2 Charge Separation in the RC -- 4.3 Electron Transfer in Cytochrome c2 -- 4.4 Modified Q Cycle -- 4.5 Proton Translocation and ATP Synthase -- 5 Calvin-Benson-Bassham Cycle -- References -- Redox Potentials of Quinones in Aqueous Solution: Relevance to Redox Potentials in Protein Environments -- 1 Introduction -- 2 Em for Quinones in Water and in Protein Environments. , 3 Alternative Approach for Calculating Em of Quinones and Other Cofactors -- References -- Photosynthesis in Chlamydomonas reinhardtii: What We Have Learned So Far? -- 1 Introduction -- 2 Photosynthetic Complexes Biogenesis and Regulation -- 2.1 Photosynthetic Genes Expression -- 2.2 Photosynthetic Pigments Biosynthesis -- 2.3 PSI Biogenesis and Functional Regulation -- 2.4 PSII Biogenesis and Functional Regulation -- 2.5 Photosynthetic Electron Transport -- 3 Concluding Remarks -- References -- Part II: Photosynthesis and the Environment -- Photosynthetic Performances of Marine Microalgae Under Influences of Rising CO2 and Solar UV Radiation -- 1 Introduction -- 2 Effects of Increasing CO2 Concentration and Declining pH -- 3 UV and Its Effect on Marine Photosynthetic Carbon Fixation -- 4 The Combined Effects of OA and UV Radiation -- 5 Perspectives -- References -- Acquisition of Inorganic Carbon by Microalgae and Cyanobacteria -- 1 Introduction -- 2 Rubisco and the Calvin Cycle Are Central Features of C Acquisition in All Cyanobacteria and Microalgae -- 3 Rubisco Also Has an Oxygenase Activity Which Leads to Inefficiencies in C Assimilation -- 4 Cyanobacteria and Microalgae Possess Mechanisms That Minimise the Effects of Unfavourable Rubisco Kinetics and Photorespiration -- 4.1 Evolution of Rubiscos More Favourable to the  Carboxylase Activity -- 4.2 CO2 Concentrating Mechanisms Increase CO2:O2 at the Rubisco Active Site -- 4.2.1 Biochemical CCMs -- 4.2.2 Biophysical CCMs -- 4.2.3 The Extent of CCM Activity -- 4.3 Heterotrophic Carbon Assimilation -- 4.3.1 Dark Carbon Fixation -- References -- Circadian Clocks in Cyanobacteria -- 1 Introduction -- 2 Kai-Based Oscillator -- 3 Synchronization with the Environment -- 4 Coordination of Cellular Activities -- 5 Conclusions -- References -- Iron Deficiency in Cyanobacteria. , 1 The Challenges of Iron Deficiency in Cyanobacteria -- 2 The Strategies for Adaptation to Iron Deficiency in Cyanobacteria -- 2.1 Retrenchment -- 2.2 Compensation -- 2.3 Acquisition -- 3 Important Iron-Deficiency Proteins in Cyanobacteria -- 3.1 IsiA -- 3.2 Fur -- 3.3 IdiA -- 3.4 PfsR -- 4 Conclusion -- References -- Adaptive Mechanisms of the Model Photosynthetic Organisms, Cyanobacteria, to Iron Deficiency -- 1 The Feature of Cyanobacterial Cell Wall -- 2 The Distribution of Cyanobacteria and Its Significance in Global Primary Productivity -- 3 The Indissoluble Bond Between Cyanobacteria and Iron -- 4 Existence Form and Availability of Iron -- 5 The Physiological Functions of Iron in Cyanobacteria -- 6 Iron Limitation Hypothesis -- 7 Physiological Response of Cyanobacteria to Iron Limitation -- 7.1 Photosynthesis -- 7.2 Respiration -- 7.3 Nitrogen Fixation -- 7.4 Oxidative Stress -- 8 Adaptative Strategies of Cyanobacteria to Iron Limitation -- 8.1 Biosynthesis and Secretion of Iron Chelators -- 8.1.1 Types of Siderophores -- 8.1.2 Siderophore Biosynthesis and Phylogenetical Distribution in Cyanobacteria -- 8.1.3 Siderophore Secretion and Uptake in Cyanobacteria -- 8.2 Induction of Protective Proteins Such as IsiA to Avoid Photooxidation of Photosystem I -- 8.3 Decrease Iron Demand and Maintain a Lower Metabolic Level -- 8.4 Increase of Iron Uptake Capacity and Balance Active and Passive Transport -- 8.4.1 Active Transport of Siderophore-Chelated Iron and Unchelated, Inorganic Iron (Fe′) -- 8.4.2 Passive Diffusion: Uptake of Inorganic Free Iron -- 8.5 Optimize Ferrous and Ferric Iron Transport -- 8.6 Development of Special Cell Surface Structure to Facilitate Iron Adhesion and Uptake -- 8.7 Reduce the Cell Size and Increase Specific Surface Area to Facilitate Passive Diffusion of Iron -- 9 Signal Transduction of Iron Deficiency in Cyanobacteria. , 9.1 The Global Regulator Fur -- 9.2 PfsR -- 9.3 Noncoding RNA -- 10 Outlooks on Cyanobacterial Adaptive Strategies to Marine Iron Limitation -- References -- The Roles of sRNAs in Regulating Stress Responses in Cyanobacteria -- 1 Introduction -- 2 Methods for Studying the Noncoding Transcriptomes of Cyanobacteria and Identifying Stress-Responsive sRNAs -- 3 sRNAs Involved in Stress Response Pathways -- 3.1 Light-Dependent Stress -- 3.2 Nitrogen Stress -- 3.3 Iron Homeostasis -- 4 Conclusions and Perspectives -- References -- Part III: Artificial Photosynthesis and Light-driven Biofactory -- Mimicking the Mn4CaO5-Cluster in Photosystem II -- 1 Introduction -- 2 Structure of the OEC -- 3 Mechanism for the Water-Splitting Reaction in the OEC -- 4 Challenge for the Synthesis of the OEC in Laboratory -- 5 Closer Mimicking of the OEC -- 6 Implications for the Mechanism of the Water-Splitting Reaction in OEC -- 7 Conclusion -- References -- Photosynthetic Improvement of Industrial Microalgae for Biomass and Biofuel Production -- 1 Introduction -- 2 Genetic and Biological Engineering of Photosynthesis in Microalgae -- 2.1 Photoprotection Mechanisms and Antenna Size -- 2.2 Manipulation of Antenna and Its Size -- 2.3 Engineering of PS Pigments -- 2.4 Delivery of Heterologous Proteins to the Plastids of Target Species -- 3 Photosynthesis and Lipids -- 3.1 Classification of Lipids -- 3.2 Storage Lipids in Microalgae: Triacylglycerol -- 3.3 Functional Lipids in Microalgae -- 3.3.1 Membrane Lipids for Photosynthesis -- 3.3.2 Polyunsaturated Fatty Acids (PUFAs) for Plant Defense -- 3.3.3 Carotenoids for Stress Response and Photosynthesis -- References -- Self-Assembly, Organisation, Regulation, and Engineering of Carboxysomes: CO2-Fixing Prokaryotic Organelles -- 1 Bacterial Microcompartments -- 1.1 The BMC Shells -- 1.2 The BMC Cargo Enzymes. , 2 CO2-Concentrating Mechanisms and CO2 Uptake Systems.
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  • 4
    Publikationsdatum: 2023-12-05
    Beschreibung: The Arctic is warming much faster than the global average. This is known as Arctic Amplification and is caused by feedbacks in the local climate system. In this study, we explore a previously proposed hypothesis that an associated wind feedback in the Barents Sea could play an important role by increasing the warm water inflow into the Barents Sea. We find that the strong recent decrease in Barents Sea winter sea ice cover causes enhanced ocean‐atmosphere heat flux and a local air temperature increase, thus a reduction in sea level pressure and a local cyclonic wind anomaly with eastward winds in the Barents Sea Opening. By investigating various reanalysis products and performing high‐resolution perturbation experiments with the ocean and sea ice model FESOM2.1, we studied the impact of cyclonic atmospheric circulation changes on the warm Atlantic Water import into the Arctic via the Barents Sea and Fram Strait. We found that the observed wind changes do not significantly affect the warm water transport into the Barents Sea, which rejects the wind‐feedback hypothesis. At the same time, the cyclonic wind anomalies in the Barents Sea increase the amount of Atlantic Water recirculating westwards in Fram Strait by a downslope shift of the West Spitsbergen Current, and thus reduce Atlantic Water reaching the Arctic basin via Fram Strait. The resulting warm‐water anomaly in the Greenland Sea Gyre drives a local anticyclonic circulation anomaly.
    Beschreibung: Plain Language Summary: The Barents Sea has been experiencing a rapid decrease in its winter sea ice extent during the last 30 years. The loss of sea ice creates new areas where, in winter, the relatively warm ocean loses heat to the cold atmosphere. As warm air rises, the warming reduces the sea level air pressure, changing the atmospheric circulation to develop a local anticlockwise wind system centered over the northern Barents Sea. The associated eastward winds in the Barents Sea Opening and southeastward winds in Fram Strait affect how warm water from the North Atlantic moves toward the Arctic. There has been a long debate on whether this wind anomaly can increase the warm Atlantic Water transport into the Barents Sea and thus cause a positive feedback mechanism for further reducing the sea ice through melting. We find that the observed atmospheric circulation changes have no significant impact on the Barents Sea warm water inflow and thus reject the wind feedback as a strong player in contributing to Arctic Amplification. However, strong anomalous southeastward winds in Fram Strait and the northern Nordic Seas cause a southward shift of the warm Atlantic Water recirculation and reduce its flow toward the Arctic.
    Beschreibung: Key Points: A hypothesis that a wind feedback contributes to Arctic Amplification is rejected by performing dedicated wind perturbation simulations. Winter sea ice retreat in the northern Barents Sea causes anomalous cyclonic winds by locally enhancing ocean heat loss. Anomalous cyclonic winds result in less Atlantic Water transport through Fram Strait.
    Beschreibung: Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659
    Beschreibung: North‐German Supercomputing Alliance
    Beschreibung: https://github.com/FESOM/fesom2
    Beschreibung: https://doi.org/10.7265/N5K072F8
    Beschreibung: https://doi.org/10.5065/D6HH6H41
    Beschreibung: https://doi.org/10.5065/D6WH2N0S
    Beschreibung: https://github.com/FESOM/pyfesom2
    Beschreibung: https://doi.org/10.5281/zenodo.7458143
    Schlagwort(e): ddc:551 ; Barents Sea ; Arctic Amplification ; feedback ; Atlantic water ; modeling ; Fram Strait
    Sprache: Englisch
    Materialart: doc-type:article
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  • 5
    Publikationsdatum: 2024-04-30
    Beschreibung: Mesoscale eddies are important for many aspects of the dynamics of the Arctic Ocean. These include the maintenance of the halocline and the Atlantic Water boundary current through lateral eddy fluxes, shelf-basin exchanges, transport of biological material and sea ice, and the modification of the sea-ice distribution. Here we review what is known about the mesoscale variability and its impacts in the Arctic Ocean in the context of an Arctic Ocean responding rapidly to climate change. In addition, we present the first quantification of eddy kinetic energy (EKE) from moored observations across the entire Arctic Ocean, which we compare to output from an eddy resolving numerical model. We show that EKE is largest in the northern Nordic Seas/Fram Strait and it is also elevated along the shelfbreak of the Arctic Circumpolar Boundary Current, especially in the Beaufort Sea. In the central basins it is 100-1000 times lower. Except for the region affected by southward sea-ice export south of Fram Strait, EKE is stronger when sea-ice concentration is low compared to dense ice cover. Areas where conditions typical in the Atlantic and Pacific prevail will increase. Hence, we conclude that the future Arctic Ocean will feature more energetic mesoscale variability. This table provides (eddy) kinetic energy in the Arctic Ocean calculated from moorings and a numerical model across the entire record and averaged over certain conditions (seasons, ice concentration). The calculations are explained in the manuscript (Eddies and the distribution of eddy kinetic energy in the Arctic Ocean). The used mooring data was compiled from six different sources as listed below and identified in the table based on the Source ID.
    Schlagwort(e): 250_MOOR; 293-S1_MOOR; 293-X1_MOOR; 293-X2_MOOR; 293-X3_MOOR; 295-S2_MOOR; A01_MOOR; AK1-1_MOOR; AK2-1_MOOR; AK3-1_MOOR; AK4-1_MOOR; AK5-1_MOOR; AK6-1_MOOR; AK7-1_MOOR; Akademik Tryoshnikov; AM1-91_MOOR; AM2-91_MOOR; AO1-92_MOOR; Arctic Ocean; ARK-XIV/2; ARK-XVIII/1; ARK-XXIX/3; ARK-XXX/1.2; ARK-XXX/2, GN05; ARK-XXXI/4; ATWAIN200_MOOR; AWI_PhyOce; AWI401-1_MOOR; AWI402-1_MOOR; AWI403-1_MOOR; AWI403-2_MOOR; AWI404-1_MOOR; AWI406-1_MOOR; AWI410-2_MOOR; AWI411-2_MOOR; AWI412-4_MOOR; AWI413-4_MOOR; AWI415-1_MOOR; AWI416-1_MOOR; AWI417-1_MOOR; AWI418-1_MOOR; BaffinBay_2_MOOR; BaffinBay_MOOR; BarrowSt_81_MOOR; BarrowSt_C_MOOR; BarrowSt_N_MOOR; BarrowSt_S_MOOR; BarrowSt_SC_MOOR; BarrowSt_Ss_MOOR; BG_a_MOOR; BG_b_MOOR; BG_c_MOOR; BG_d_MOOR; BI3_MOOR; BR1_MOOR; BR2_MOOR; BR3_MOOR; BRA_MOOR; BRB_MOOR; BRG_MOOR; BRK_MOOR; BS2_MOOR; BS3_MOOR; BS4_MOOR; BS5_MOOR; BS6_MOOR; BSO1_MOOR; BSO2_MOOR; BSO3_MOOR; BSO4_MOOR; BSO5_MOOR; C1_MOOR; C2_MOOR; C3_MOOR; C4_MOOR; C5_MOOR; C6_MOOR; CA04_MOOR; CA05_MOOR; CA06_MOOR; CA07_MOOR; CA08_MOOR; CA10_MOOR; CA11_MOOR; CA12_MOOR; CA13_MOOR; CA15_MOOR; CA16_MOOR; CA20_MOOR; CM-1_MOOR; CM-2_MOOR; CS1_MOOR; CS-1A_MOOR; CS2_MOOR; CS-2A_MOOR; CS3_MOOR; CS-3A_MOOR; CS4_MOOR; CS5_MOOR; Depth, bottom/max; Depth, top/min; DEPTH, water; DS_TUBE8_MOOR; Duration; EA1_MOOR; EA2_MOOR; EA3_MOOR; EA4_MOOR; EBC_MOOR; eddies; eddy kinetic energy; Eddy kinetic energy, 2000-2010; Eddy kinetic energy, 2010-2020; Eddy kinetic energy, at depth; Eddy kinetic energy, autumn; Eddy kinetic energy, ice; Eddy kinetic energy, mean; Eddy kinetic energy, model bandpass; Eddy kinetic energy, model online; Eddy kinetic energy, no ice; Eddy kinetic energy, some ice; Eddy kinetic energy, spring; Eddy kinetic energy, summer; Eddy kinetic energy, winter; EGN-1; EGS-1; EGS1-2; EGS2-1; EGS4-1; ELEVATION; F10-1; F1-1; F11_MOOR; F11-2; F12_MOOR; F12-1; F13_MOOR; F13-1; F14_MOOR; F14-1; F15-1; F16-1; F17_MOOR; F2-1; F3-1; F4-1; F5-1; F6-1; F7-1; F8-1; F9-1; FB2b_MOOR; FB6_MOOR; First year of observation; FRAM; FRontiers in Arctic marine Monitoring; FRS782_MOOR; FSC1_MOOR; FSC2_MOOR; FSC3_MOOR; FSC4_MOOR; GS-3_2_MOOR; HG-IV-S-1; High-frequency kinetic energy; HSNE60_MOOR; HudsonBay_MOOR; HudsonStrait_MOOR; I1_MOOR; I2_MOOR; I3_MOOR; IdF1-1; IdF2-1; IdF3-1; IdF4-1; ISWRIG_MOOR; Karasik-2015; KS02_MOOR; KS04_MOOR; KS06_MOOR; KS08_MOOR; KS10_MOOR; KS12_MOOR; KS14_MOOR; L97; LA97/2; Lance; Last year of observation; LATITUDE; LM3_MOOR; LONGITUDE; Low-frequency kinetic energy; M11_MOOR; M12_MOOR; M13_MOOR; M14_MOOR; M15_MOOR; M16_MOOR; M3_MOOR; M5_MOOR; M6_MOOR; M9a_MOOR; MA2B_MOOR; MB1B_MOOR; MB2B_MOOR; MB4B_MOOR; Mean kinetic energy; MOOR; Mooring; Mooring (long time); MOORY; N198_2_MOOR; N198_MOOR; N525_MOOR; N541_MOOR; NABOS_2015_AK1-1, NABOS_2018_AK1-1; NABOS_2015_AK2-1, NABOS_2018_AK2-1; NABOS_2015_AK3-1, NABOS_2018_AK3-1; NABOS_2015_AK4-1, NABOS_2018_AK4-1; NABOS_2015_AK5-1, NABOS_2018_AK5-1; NABOS_2015_AK6-1,NABOS_2018_AK6-1; NABOS_2015_AK7-1, NABOS_2018_AK7-1; NABOS, AT2015; NABOS 2015; Nansen-2015; North Greenland Sea; NPEO_MOOR; NWNA_MOOR; NWNB_MOOR; NWNC_MOOR; NWND_MOOR; NWNE_MOOR; NWNF_MOOR; NWNG_MOOR; NWSB_MOOR; NWSD_MOOR; NWSE_2_MOOR; NWSE_MOOR; OLIK-1_MOOR; OSL2a_MOOR; OSL2f_MOOR; Physical Oceanography @ AWI; Polarstern; PS100; PS100/039-2, PS114_25-1,ARKR02-01; PS100/045-1, PS114_29-2; PS100/047-1, PS114_40-2; PS100/053-1, PS114_36-1; PS100/073-1, PS109_20-1; PS100/106-1, PS114_23-2; PS100/142-1, PS109_139-1; PS100/180-2, PS109_111-1; PS100/181-1, PS109_112-1; PS100/182-1, PS109_113-1; PS100/183-1, PS109_114-1; PS109; PS109_133-1, PS114_52-1; PS109_138-2, PS114_53-1; PS109_148-1, PS114_60-2; PS114; PS52; PS62; PS94; PS99/070-1, PS107_3-1; PS99.2; R071_MOOR; R1-1; R2-1; R290_MOOR; R3-1; R333_MOOR; R356_MOOR; R4-1; R5-1; Reference/source; SS-5_MOOR; StA_MOOR; Station label; Stor_MOOR; Total kinetic energy; V-319_MOOR; Velocity, east; Velocity, north; Vilk_MOOR; WBC_MOOR; WG1_MOOR; WG15_MOOR; WG4_MOOR; Wunsch-NN1_MOOR; Wunsch-NN2_MOOR; Y1_MOOR; Y2_MOOR; YP_MOOR
    Materialart: Dataset
    Format: text/tab-separated-values, 4806 data points
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  • 6
    facet.materialart.
    Unbekannt
    American Geophysical Union (AGU)
    In:  EPIC3Journal of Advances in Modeling Earth Systems, American Geophysical Union (AGU), 13(10), ISSN: 1942-2466
    Publikationsdatum: 2023-06-21
    Beschreibung: We propose to make the damping time scale, which governs the decay of pseudo-elastic waves in the Elastic Viscous Plastic (EVP) sea-ice solvers, independent of the external time step and large enough to warrant numerical stability for a moderate number of internal time steps. A necessary condition is that the forcing on sea ice varies slowly on the damping time scale, in which case an EVP solution may still approach a Viscous Plastic one, but on a time scale longer than a single external time step. In this case, the EVP method becomes very close to the recently proposed modified EVP (mEVP) method in terms of stability and simulated behavior. In a simple test case dealing with sea ice breaking under the forcing of a moving cyclone, the EVP method with an enlarged damping time scale can simulate linear kinematic features which are very similar to those from the traditional EVP implementation, although a much smaller number of internal time steps is used. There is more difference in sea-ice thickness and linear kinematic features simulated in a realistic Arctic configuration between using the traditional and our suggested choices of EVP damping time scales, but it is minor considering model uncertainties associated with choices of many other parameters in sea-ice models.
    Repository-Name: EPIC Alfred Wegener Institut
    Materialart: Article , NonPeerReviewed
    Format: application/pdf
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  • 7
    facet.materialart.
    Unbekannt
    Copernicus GmbH
    In:  EPIC3Geoscientific Model Development, Copernicus GmbH, 13(7), pp. 3337-3345, ISSN: 1991-959X
    Publikationsdatum: 2023-06-21
    Beschreibung: 〈jats:p〉Abstract. Computation of barotropic and meridional overturning streamfunctions for models formulated on unstructured meshes is commonly preceded by interpolation to a regular mesh. This operation destroys the original conservation, which can be then artificially imposed to make the computation possible. An elementary method is proposed that avoids interpolation and preserves conservation in a strict model sense. The method is described as applied to the discretization of the Finite volumE Sea ice – Ocean Model (FESOM2) on triangular meshes. It, however, is generalizable to colocated vertex-based discretization on triangular meshes and to both triangular and hexagonal C-grid discretizations. 〈/jats:p〉
    Repository-Name: EPIC Alfred Wegener Institut
    Materialart: Article , NonPeerReviewed
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  • 8
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    The Oceanography Society
    In:  EPIC3Oceanography, The Oceanography Society, 35(2), ISSN: 1042-8275
    Publikationsdatum: 2023-06-21
    Beschreibung: 〈jats:p〉Mesoscale eddies are important to many aspects of the dynamics of the Arctic Ocean. Among others, they maintain the halocline and interact with the Atlantic Water circumpolar boundary current through lateral eddy fluxes and shelf-basin exchanges. Mesoscale eddies are also important for transporting biological material and for modifying sea ice distribution. Here, we review what is known about eddies and their impacts in the Arctic Ocean in the context of rapid climate change. Eddy kinetic energy (EKE) is a proxy for mesoscale variability in the ocean due to eddies. We present the first quantification of EKE from moored observations across the entire Arctic Ocean and compare those results to output from an eddy resolving numerical model. We show that EKE is largest in the northern Nordic Seas/Fram Strait and it is also elevated along the shelf break of the Arctic Circumpolar Boundary Current, especially in the Beaufort Sea. In the central basins, EKE is 100–1,000 times lower. Generally, EKE is stronger when sea ice concentration is low versus times of dense ice cover. As sea ice declines, we anticipate that areas in the Arctic Ocean where conditions typical of the North Atlantic and North Pacific prevail will increase. We conclude that the future Arctic Ocean will feature more energetic mesoscale variability.〈/jats:p〉
    Repository-Name: EPIC Alfred Wegener Institut
    Materialart: Article , NonPeerReviewed
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  • 9
    Publikationsdatum: 2023-06-21
    Beschreibung: 〈jats:p〉Abstract. We developed a new version of the Alfred Wegener Institute Climate Model (AWI-CM3), which has higher skills in representing the observed climatology and better computational efficiency than its predecessors. Its ocean component FESOM2 (Finite-volumE Sea ice–Ocean Model) has the multi-resolution functionality typical of unstructured-mesh models while still featuring a scalability and efficiency similar to regular-grid models. The atmospheric component OpenIFS (CY43R3) enables the use of the latest developments in the numerical-weather-prediction community in climate sciences. In this paper we describe the coupling of the model components and evaluate the model performance on a variable-resolution (25–125 km) ocean mesh and a 61 km atmosphere grid, which serves as a reference and starting point for other ongoing research activities with AWI-CM3. This includes the exploration of high and variable resolution and the development of a full Earth system model as well as the creation of a new sea ice prediction system. At this early development stage and with the given coarse to medium resolutions, the model already features above-CMIP6-average skills (where CMIP6 denotes Coupled Model Intercomparison Project phase 6) in representing the climatology and competitive model throughput. Finally we identify remaining biases and suggest further improvements to be made to the model. 〈/jats:p〉
    Repository-Name: EPIC Alfred Wegener Institut
    Materialart: Article , NonPeerReviewed
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  • 10
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    Springer Science and Business Media LLC
    In:  EPIC3Ocean Dynamics, Springer Science and Business Media LLC, 73(3-4), pp. 219-230, ISSN: 1616-7341
    Publikationsdatum: 2023-06-23
    Beschreibung: We develop a single-class ice and snow model embedded inside a 3D hydrodynamic model on unstructured grids and apply it to lake studies using highly variable mesh resolution. The model is able to reasonably capture the ice fields observed in both small and large lakes. For the first time, we attempt simulation of ice processes on very small scales (~ 1 m). Physically sound results are obtained at the expense of moderately increased computational cost, although more rigorous validation nearshore is needed due to lack of observation. We also outline challenges on developing new process-based capabilities for accurately simulating nearshore ice.
    Repository-Name: EPIC Alfred Wegener Institut
    Materialart: Article , isiRev
    Format: application/pdf
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