ALBERT

Note: In kyrill. Schr., russ.

Note: Ersch. unregelmäßig , Beiträge teilweise in Englisch

Note: In kyrill. Schr.

Note: Contents 1 End Poverty in All Its Forms Everywhere / Joel C. Gill, Sarah Caven, and Ekbal Hussain 2 Zero Hunger / Benson H. Chishala, Rhoda Mofya-Mukuka, Lydia M. Chabala, and Elias Kuntashula 3 Ensure Healthy Lives and Promote Well-Being for All At All Ages / Kim Dowling, Rachael Martin, Singarayer K. Florentine, and Dora C. Pearce 4 Quality Education / Ellen Metzger, David Gosselin, and Cailin Huyck Orr 5 Achieve Gender Equality and Empower All Women and Girls / Ezzoura Errami, Gerel Ochir, and Silvia Peppoloni 6 Clean Water and Sanitation / Kirsty Upton and Alan MacDonald 7 Affordable and Clean Energy / Michael H. Stephenson 8 Decent Work and Economic Growth / Katrien An Heirman, Joel C. Gill, and Sarah Caven 9 Infrastructure, Industry, and Innovation / Joel C. Gill, Ranjan Kumar Dahal, and Martin Smith 10 Reduce Inequality Within and Amongst Countries / Melissa Moreano and Joel C. Gill 11 Sustainable Cities and Communities / Martin Smith and Stephanie Bricker 12 Ensure Sustainable Consumption and Production Patterns / Joseph Mankelow, Martin Nyakinye, and Evi Petavratzi 13 Climate Action / Joy Jacqueline Pereira, T. F. Ng, and Julian Hunt 14 Conserve and Sustainably Use the Oceans, Seas, and Marine Resources / Michael G. Petterson, Hyeon-Ju Kim, and Joel C. Gill 15 Life on Land / Eric O. Odada, Samuel O. Ochola, and Martin Smith 16 Peace, Justice, and Strong Institutions / Joel C. Gill, Amel Barich, Nic Bilham, Sarah Caven, Amy Donovan, Marleen de Ruiter, and Martin Smith 17 Partnerships for the Goals / Susanne Sargeant, Joel C. Gill, Michael Watts, Kirsty Upton, and Richard Ellison 18 Reshaping Geoscience to Help Deliver the Sustainable Development Goals / Joel C. Gill Index

Note: Contents Part I Arctic Climate and Greenland 1 Arctic Climate Change, Variability, and Extremes / John E. Walsh 2 Precipitation Characteristics and Changes / Hengchun Ye, Daqing Yang, Ali Behrangi, Svetlana L. Stuefer, Xicai Pan, Eva Mekis, Yonas Dibike, and John E. Walsh 3 Snow Cover - Observations, Processes, Changes, and Impacts on Northern Hydrology / Ross Brown, Philip Marsh, Stephen Déry, and Daqing Yang 4 Evaporation Processes and Changes Over the Northern Regions / Yinsheng Zhang, Ning Ma, Hotaek Park, John E. Walsh, and Ke Zhang 5 Greenland Ice Sheet and Arctic Mountain Glaciers / Sebastian H. Mernild, Glen E. Liston, and Daqing Yang Part II Hydrology and Biogeochemistry 6 Regional and Basin Streamflow Regimes and Changes: Climate Impact and Human Effect / Michael Rawlins, Daqing Yang, and Shaoqing Ge 7 Hydrologic Extremes in Arctic Rivers and Regions: Historical Variability and Future Perspectives / Rajesh R. Shrestha, Katrina E. Bennett, Daniel L. Peters, and Daqing Yang 8 Overview of Environmental Flows in Permafrost Regions / Daniel L, Peters, Donald J. Baird, Joseph Culp, Jennifer Lento, Wendy A. Monk, and Rajesh R. Shrestha 9 Yukon River Discharge Response to Seasonal Snow Cover Change / Daqing Yang, Yuanyuan Zhao, Richard Armstrong, Mary J. Brodzik, and David Robinson 10 Arctic River Water Temperatures and Thermal Regimes / Daqing Yang, Hoteak Park, Amber Peterson, and Baozhong Liu 11 Changing Biogeochemical Cycles of Organic Carbon, Nitrogen, Phosphorus, and Trace Elements in Arctic Rivers / Jonathan O'Donnell, Thomas Douglas, Amanda Barker, and Laodong Guo 12 Arctic Wetlands and Lakes-Dynamics and Linkages / Kathy L. Young, Laura Brown, and Yonas Dibike 13 River Ice Processes and Changes Across the Northern Regions / Daqing Yang, Hotaek Park, Terry Prowse, Alexander Shiklomanov, and Ellie McLeod Part III Permafrost and Frozen Ground 14 Permafrost Features and Talik Geometry in Hydrologic System / Kenji Yoshikawa and Douglas L. Kane 15 Ground Temperature and Active Layer Regimes and Changes / Lin Zhao, Cangwei Xie, Daqing Yang, and Tingjun Zhang 16 Permafrost Hydrology: Linkages and Feedbacks / Tetsuya Hiyama, Daqing Yang, and Douglas L. Kane 17 Permafrost Hydrogeology / Barret L. Kurylyk and Michelle A. Walvoord Part IV Ecosystem Change and Impact 18 Greenhouse Gases and Energy Fluxes at Permafrost Zone / Masahito Ueyama, Hiroki Iwata, Hideki Kobayashi, Eugénie Euskirchen, Lutz Merbold, Takeshi Ohta, Takashi Machimura, Donatella Zona, Walter C. Oechel, and Edward A. G. Schuur 19 Spring Phenology of the Boreal Ecosystems / Nicolas Delbart 20 Diagnosing Environmental Controls on Vegetation Greening and Browning Trends Over Alaska and Northwest Canada Using Complementary Satellite Observations / Youngwook Kim, John S. Kimball, Nicholas Parazoo, and Peter Kirchner 21 Boreal Forest and Forest Fires / Yongwon Kim, Hideki Kobayashi, Shin Nagai, Masahito Ueyama, Bang-Yong Lee, and Rikie Suzuki 22 Northern Ecohydrology of Interior Alaska Subarctic / Jessica M. Young-Robertson, W. Robert Bolton, and Ryan Toohey 23 Yukon River Discharge-NDVI Relationship / Weixin Xu and Daqing Yang Part V Cross-System Linkage and Integration 24 River Freshwater Flux to the Arctic Ocean / Alexander Shiklomanov, Stephen Déry, Mikhail Tretiakov, Daqing Yang, Dmitry Magritsky, Alex Georgiadi, and Wenqing Tang 25 River Heat Flux into the Arctic Ocean / Daqing Yang, Shaoqing Ge, Hotaek Park, and Richard L. Lammers 26 Cold Region Hydrologic Models and Applications / Hotaek Park, Yonas Dibike, Fengge Su, and John Xiaogang Shi 27 Regional Climate Modeling in the Northern Regions / Zhenhua Li, Yanping Li, Daqing Yang, and Rajesh R. Shrestha 28 High-Resolution Weather Research Forecasting (WRF) Modeling and Projection Over Western Canada, Including Mackenzie Watershed / Yanping Li and Zhenhua Li 29 Responses of Boreal Forest Ecosystems and Permafrost to Climate Change and Disturbances: A Modeling Perspective / Shuhua Yi and Fengming Yuan 30 Future Trajectory of Arctic System Evolution / Kazuyuki Saito, John E. Walsh, Arvid Bring, Ross Brown, Alexander Shiklomanov, and Daqing Yang Correction to: Arctic Hydrology, Permafrost and Ecosystems / Daqing Yang, and Douglas L. Kane

Note: Dissertation, Universität Potsdam, 2021 , Table of Contents Abstract Zusammenfassung List of Figures List of Tables Abbreviations 1 Introduction 1.1 Scientific background and motivation 1.1.1 Permafrost and climate change 1.1.2 Permafrost thaw and disturbances 1.1.3 Abrupt permafrost disturbances 1.1.4 Remote sensing 1.1.5 Remote sensing of permafrost disturbances 1.2 Aims and objectives 1.3 Study area 1.4 General data and methods 1.4.1 Landsat and Sentinel-2 1.4.2 Google Earth Engine 1.5 Thesis structure 1.6 Overview of publications and authors’ contribution 1.6.1 Chapter 2 - Comparing Spectral Characteristics of Landsat-8 and Sentinel-2 Same-Day Data for Arctic-Boreal Regions 1.6.2 Chapter 3 - Mosaicking Landsat and Sentinel-2 Data to Enhance LandTrendr Time Series Analysis in Northern High Latitude Permafrost Regions 1.6.3 Chapter 4 - Remote Sensing Annual Dynamics of Rapid Permafrost Thaw Disturbances with LandTrendr 2 Comparing Spectral Characteristics of Landsat-8 and Sentinel-2 Same-Day Data for Arctic-Boreal Regions 2.1 Abstract 2.2 Introduction 2.3 Materials and Methods 2.3.1 Study Sites 2.3.2 Data 2.3.3 Data Processing 2.3.3.1 Filtering Image Collections 2.3.3.2 Creating L8, S2, and Site Masks 2.3.3.3 Preparing Sentinel-2 Surface Reflectance Images in SNAP 2.3.3.4 Applying Site Masks 2.3.4 Spectral Band Comparison and Adjustment 2.4 Results 2.4.1 Spectral Band Comparison 2.4.2 Spectral Band Adjustment 2.4.3 ES and HLS Spectral Band Adjustment 2.5 Discussion 2.6 Conclusions 2.7 Acknowledgements 2.8 Appendix Chapter 2 3 Mosaicking Landsat and Sentinel-2 Data to Enhance LandTrendr Time Series Analysis in Northern High Latitude Permafrost Regions 3.1 Abstract 3.2 Introduction 3.3 Materials and Methods 3.3.1 Study Sites 3.3.2 Data 3.3.3 Data Processing and Mosaicking Workflow 3.3.4 Data Availability Assessment 3.3.5 Mosaic Coverage and Quality Assessment 3.4 Results 3.4.1 Data Availability Assessment 3.4.2 Mosaic Coverage and Quality Assessment 3.5 Discussion 3.6 Conclusions 4 Remote Sensing Annual Dynamics of Rapid Permafrost Thaw Disturbances with LandTrendr 4.1 Abstract 4.2 Introduction 4.3 Study Area and Methods 4.3.1 Study area 4.3.2 General workflow and ground truth data 4.3.3 Data and LandTrendr 4.3.4 Index selection 4.3.5 Temporal Segmentation 4.3.6 Spectral Filtering 4.3.7 Spatial masking and filtering 4.3.8 Machine-learning object filter 4.4 Results 4.4.1 Focus sites 4.4.2 North Siberia 4.5 Discussion 4.5.1 Mapping of RTS 4.5.2 Spatio-temporal variability of RTS dynamics 4.5.3 LT-LS2 capabilities and limitations 4.6 Conclusion 4.7 Appendix 5 Synthesis and Discussion 5.1 Google Earth Engine 5.2 Landsat and Sentinel-2 5.3 Image mosaics and disturbance detection algorithm 5.4 Mapping RTS and their annual temporal dynamics 5.5 Limitations and technical considerations 5.6 Key findings 5.7 Outlook References Acknowledgements

Note: Contents: 1 Introduction ; I Continuous predictors ; 2 Continuous predictors: Linear ; 3 Continuous predictors: Polynomials ; 4 Continuous predictors: Piecewise models ; 5 Continuous by continuous interactions ; 6 Continuous by continuous by continuous interactions ; II Categorical predictors ; 7 Categorical predictors ; 8 Categorical by categorical interactions ; 9 Categorical by categorical by categorical interactions ; III Continuous and categorical predictors ; 10 Linear by categorical interactions ; 11 Polynomial by categorical interactions ; 12 Piecewise by categorical interactions ; 13 Continuous by continuous by categorical interactions ; 14 Continuous by categorical by categorical interactions ; IV Beyond ordinary linear regression ; 15 Multilevel models ; 16 Time as a continuous predictor ; 17 Time as a categorical predictor ; 18 Nonlinear models ; 19 Complex survey data ; V Appendices ; A Customizing output from estimation commands ; B The margins command ; C The marginsplot command ; D The contrast command ; E The pwcompare command ; References

Note: Contents General on Ocean Literacy Ocean Literacy: Background, Future Drivers, and Opportunities / Jan H. Stel Ocean Literacy: From a Ripple to a Wave / Diana L. Payne and Meghan E. Marrero A Framework for the Assessment of the Effectiveness of Ocean Literacy Initiatives / Owen Molloy, Matthew Ashley, and Conor McCrossan Exploring and Exploiting Deep Ocean Space / Jan H. Stel Ocean Literacy—In the Context of Naming of Seas: Case Study: The Sea Between Korea and Japan / Rainer Dormels Education Design-Based Implementation Research for Exploring the Ocean: A Geographical Perspective / Alfonso García de la Vega Innovative Education Strategies to Advance Ocean Literacy / Veronica McCauley, Kevin Davison, Patricia McHugh, Christine Domegan, and Anthony Grehan Sail Training Has Set Sail on a Course Towards Ocean Literacy / Laura Ellen Lyth Applications The Importance of Ocean Literacy in the Mediterranean Region—Steps Towards Blue Sustainability / Melita Mokos, Maria Cheimonopoulou, Panayota Koulouri, Monica Previati, Giulia Realdon, Francesca Santoro, Athanasios Mogias, Theodora Boubonari, Alessio Satta, and Christos Ioakeimidis Fostering Ocean-Literate Generations: The Portuguese Blue School / Raquel L. Costa, Bernardo Mata, Fernanda Silva, Patrícia Conceição, and Laura Guimarães Two Ocean Aquarium Academy: An Introduction to Ocean Literacy Programmes and a Marine Sciences Curriculum / Russell A. Stevens Index

Note: Contents Xu, J., Oppenheimer, C., Hammond, J.O.S. and Wei, H. / Perspectives on the active volcanoes of China Wei, H., Zhao, B., Chen, Z. and Yu, H. / Volcanic processes and magmatic evolution of Tianchi volcano, Changbaishan Zhao, B., Xu, D., Bai, Z. and Chen, Z. / Volcanism in the Longgang volcanic field of NE China: insights from eruption history, volcano types and geochemical characteristics Bai, X., Wei, W., Yu, H. and Chen, Z. / Petrogenesis and dynamic implications of the Cenozoic alkali basalts from the Jingpohu Volcanic Field, NE China Chen, Z., Zhao, Y., Bai, X., Wei, W., Liu, Y. and Bai, Z. / Wudalianchi volcanic field, NE China: tectonic setting, eruptive history, and geophysical insights Zhao, Y.-W., Zou, H. and Li, N. / Geomorphology and geochemistry of the Late Cenozoic volcanoes in the Halaha River–Chaoer River volcanic fields, western Greater Hinggan Mountain Range, NE China Li, N., Zhao, Y.-W., Gong, L.-W. and Wang, J.-L. / The Late Cenozoic volcanic groups in the South Daxing’anling, NE China: geology, geochemistry, and chronology Hong, L., Zhang, Y., Zhang, L., Xu, Y.-G., Liu, Z. and He, P. / Olivine chemistry of the Quaternary Datong basalts of the Trans-North China Orogen: insights into mantle source lithology and redox–hydration state Xu, J., Zhao, B., Yu, H., Wei, F. and Chen, Z. / Volcanic geology and petrochemistry of Ashikule volcanic field in western Kunlun Mountains of the Tibetan plateau Zhao, B., Wei, F., Yang, W., Xu, J. and Cui, X. / Cenozoic volcanism along Dahongliutan fault in the West Kunlun Mountains, China: implication from distribution of volcanic rocks, volcanic geology, and geochemistry Yu, H., Zhao, B., Chen, Z., Wei, H., Yang, W. and Bai, X. / Eruption history, petrogeochemistry, and geodynamic background of Tengchong volcanoes in Yunnan Province, SW China Wei, F., Wei, W. and Yu, H. / The Cenozoic volcanic fields in northern Hainan Island and the Leizhou Peninsula, south China: eruption history, magma source and dynamic background Yu, W., Wei, W., Wei, F., Bai, X., Liu, S. and Xu, D./ Magma plumbing system and origin of the intraplate volcanoes in Mainland China: an overview of constraints from geophysical imaging Ji, L., Xu, J., Liu, L. and Zhang, W. / A review of present-day deformation of active volcanoes in China between 1970 and 2013 Pan, B., Liu, G., Cheng, T., Zhang, J., Sun, Z., Ma, B., Wu, H., Liang, G., Guo, M., Kong, Q., Wei, F., Zhao, C. and Zhao, Q. / Development and status of active volcano monitoring in China Liang, Y. and Xu, J. / The impact of volcanic ash on the safety of aviation industry: review of China’s current situation Wang, X., Pan, B., Pan, M. and Liang, Y. / Current situation of early warning and emergency countermeasures of volcanic eruptions in China Chen, Z. and Chen, Z. / Identifying references to volcanic eruptions in Chinese historical records Pan, B., Cheng, T., Xu, J., Zhang, J. and Chen, Z. / Knowledge base of Cenozoic volcanoes in China Index

Note: Contents I Artificial Intelligence 1 Introduction 1.1 What Is AI? 1.2 The Foundations of Artificial Intelligence 1.3 The History of Artificial Intelligence 1.4 The State of the Art 1.5 Risks and Benefits of AI Summary Bibliographical and Historical Notes 2 Intelligent Agents 2.1 Agents and Environments 2.2 Good Behavior: The Concept of Rationality 2.3 The Nature of Environments 2.4 The Structure of Agents Summary Bibliographical and Historical Notes II Problem-solving 3 Solving Problems by Searching 3.1 Problem-Solving Agents 3.2 Example Problems 3.3 Search Algorithms 3.4 Uninformed Search Strategies 3.5 Informed (Heuristic) Search Strategies 3.6 Heuristic Functions Summary Bibliographical and Historical Notes 4 Search in Complex Environments 4.1 Local Search and Optimization Problems 4.2 Local Search in Continuous Spaces 4.3 Search with Nondeterministic Actions 4.4 Search in Partially Observable Environments 4.5 Online Search Agents and Unknown Environments Summary Bibliographical and Historical Notes 5 Constraint Satisfaction Problems 5.1 Defining Constraint Satisfaction Problems 5.2 Constraint Propagation: Inference in CSPs 5.3 Backtracking Search for CSPs 5.4 Local Search for CSPs 5.5 The Structure of Problems Summary Bibliographical and Historical Notes 6 Adversarial Search and Games 6.1 Game Theory 6.2 Optimal Decisions in Games 6.3 Heuristic Alpha-Beta Tree Search 6.4 Monte Carlo Tree Search 6.5 Stochastic Games 6.6 Partially Observable Games 6.7 Limitations of Game Search Algorithms Summary Bibliographical and Historical Notes III Knowledge, reasoning, and planning 7 Logical Agents 7.1 Knowledge-Based Agents 7.2 The Wumpus World 7.3 Logic 7.4 Propositional Logic: A Very Simple Logic 7.5 Propositional Theorem Proving 7.6 Effective Propositional Model Checking 7.7 Agents Based on Propositional Logic Summary Bibliographical and Historical Notes 8 First-Order Logic 8.1 Representation Revisited 8.2 Syntax and Semantics of First-Order Logic 8.3 Using First-Order Logic 8.4 Knowledge Engineering in First-Order Logic Summary Bibliographical and Historical Notes 9 Inference in First-Order Logic 9.1 Propositional vs. First-Order Inference 9.2 Unification and First-Order Inference 9.3 Forward Chaining 9.4 Backward Chaining 9.5 Resolution Summary Bibliographical and Historical Notes 10 Knowledge Representation 10.1 Ontological Engineering 10.2 Categories and Objects 10.3 Events 10.4 Mental Objects and Modal Logic 10.5 Reasoning Systems for Categories 10.6 Reasoning with Default Information Summary Bibliographical and Historical Notes 11 Automated Planning 11.1 Definition of Classical Planning 11.2 Algorithms for Classical Planning 11.3 Heuristics for Planning 11.4 Hierarchical Planning 11.5 Planning and Acting in Nondeterministic Domains 11.6 Time, Schedules, and Resources 11.7 Analysis of Planning Approaches Summary Bibliographical and Historical Notes IV Uncertain knowledge and reasoning 12 Quantifying Uncertainty 12.1 Acting under Uncertainty 12.2 Basic Probability Notation 12.3 Inference Using Full Joint Distributions 12.4 Independence 12.5 Bayes' Rule and Its Use 12.6 Naive Bayes Models 12.7 The Wumpus World Revisited Summary Bibliographical and Historical Notes 13 Probabilistic Reasoning 13.1 Representing Knowledge in an Uncertain Domain 13.2 The Semantics of Bayesian Networks 13.3 Exact Inference in Bayesian Networks 13.4 Approximate Inference for Bayesian Networks 13.5 Causal Networks Summary Bibliographical and Historical Notes 14 Probabilistic Reasoning over Time 14.1 Time and Uncertainty 14.2 Inference in Temporal Models 14.3 Hidden Markov Models 14.4 Kalman Filters 14.5 Dynamic Bayesian Networks Summary Bibliographical and Historical Notes 15 Making Simple Decisions 15.1 Combining Beliefs and Desires under Uncertainty 15.2 The Basis of Utility Theory 15.3 Utility Functions 15.4 Multiattribute Utility Functions 15.5 Decision Networks 15.6 The Value of Information 15.7 Unknown Preferences Summary Bibliographical and Historical Notes 16 Making Complex Decisions 16.1 Sequential Decision Problems 16.2 Algorithms for MDPs 16.3 Bandit Problems 16.4 Partially Observable MDPs 16.5 Algorithms for Solving POMDPs Summary Bibliographical and Historical Notes 17 Multiagent Decision Making 17.1 Properties of Multiagent Environments 17.2 Non-Cooperative Game Theory 17.3 Cooperative Game Theory 17.4 Making Collective Decisions Summary Bibliographical and Historical Notes 18 Probabilistic Programming 18.1 Relational Probability Models 18.2 Open-Universe Probability Models 18.3 Keeping Track of a Complex World 18.4 Programs as Probability Models Summary Bibliographical and Historical Notes V Machine Learning 19 Learning from Examples 19.1 Forms of Learning 19.2 Supervised Learning 19.3 Learning Decision Trees 19.4 Model Selection and Optimization 19.5 The Theory of Learning 19.6 Linear Regression and Classification 19.7 Nonparametric Models 19.8 Ensemble Learning 19.9 Developing Machine Learning Systems Summary Bibliographical and Historical Notes 20 Knowledge in Learning 20.1 A Logical Formulation of Learning 20.2 Knowledge in Learning 20.3 Explanation-Based Learning 20.4 Learning Using Relevance Information 20.5 Inductive Logic Programming Summary Bibliographical and Historical Notes 21 Learning Probabilistic Models 21.1 Statistical Learning 21.2 Learning with Complete Data 21.3 Learning with Hidden Variables: The EM Algorithm Summary Bibliographical and Historical Notes 22 Deep Learning 22.1 Simple Feedforward Networks 22.2 Computation Graphs for Deep Learning 22.3 Convolutional Networks 22.4 Learning Algorithms 22.5 Generalization 22.6 Recurrent Neural Networks 22.7 Unsupervised Learning and Transfer Learning 22.8 Applications Summary Bibliographical and Historical Notes 23 Reinforcement Learning 23.1 Learning from Rewards 23.2 Passive Reinforcement Learning 23.3 Active Reinforcement Learning 23.4 Generalization in Reinforcement Learning 23.5 Policy Search 23.6 Apprenticeship and Inverse Reinforcement Learning 23.7 Applications of Reinforcement Learning Summary Bibliographical and Historical Notes VI Communicating, perceiving, and acting 24 Natural Language Processing 24.1 Language Models 24.2 Grammar 24.3 Parsing 24.4 Augmented Grammars 24.5 Complications of Real Natural Language 24.6 Natural Language Tasks Summary Bibliographical and Historical Notes 25 Deep Learning for Natural Language Processing 25.1 Word Embeddings 25.2 Recurrent Neural Networks for NLP 25.3 Sequence-to-Sequence Models 25.4 The Transformer Architecture 25.5 Pretraining and Transfer Learning 25.6 State of the art Summary Bibliographical and Historical Notes 26 Robotics 26.1 Robots 26.2 Robot Hardware 26.3 What kind of problem is robotics solving? 26.4 Robotic Perception 26.5 Planning and Control 26.6 Planning Uncertain Movements 26.7 Reinforcement Learning in Robotics 26.8 Humans and Robots 26.9 Alternative Robotic Frameworks 26.10 Application Domains Summary Bibliographical and Historical Notes 27 Computer Vision 27.1 Introduction 27.2 Image Formation 27.3 Simple Image Features 27.4 Classifying Images 27.5 Detecting Objects 27.6 The 3D World 27.7 Using Computer Vision Summary Bibliographical and Historical Notes VII Conclusions 28 Philosophy, Ethics, and Safety of AI 28.1 The Limits of AI 28.2 Can Machines Really Think? 28.3 The Ethics of AI Summary Bibliographical and Historical Notes 29 The Future of AI 29.1 AI Components 29.2 AI Architectures A Mathematical Background A.1 Complexity Analysis and 0() Notation A.2 Vectors, Matrices, and Linear Algebra A.3 Probability Distributions Bibliographical and Historical Notes B Notes on Languages and Algorithms B. l Defining Languages with Backus-Naur Form (BNF) B.2 Describing Algorithms with Pseudocode B.3 Online Supplemental Material Bibliography Index

Note: Contents 1 Introduction 1.1 Shared Space 1.2 Motivation and Research Objectives 1.3 Proposals and Contributions 1.3.1 Interaction Detection 1.3.2 Trajectory Prediction 1.4 Structure of the Thesis 2 Concepts of Deep Learning and Fundamental Methods for Behavior Modeling 2.1 Introduction to Deep Learning 2.1.1 Feed-Forward Network with Backpropagation 2.1.2 Convolutional Neural Network 2.1.3 Recurrent Neural Network 2.2 Approaches for Object Detection and Classification 2.2.1 You Only Look Once 2.2.2 Multi-Level Feature Pyramid Network 2.3 Optical Flow 2.4 Spatial Clustering 2.5 Transformer Encoder with Self-Attention 2.6 Conditional Generative Model 2.6.1 Variational Auto-Encoder 2.6.2 Conditional Variational Auto-Encoder 3 Related Work 3.1 Interaction Detectio 3.1.1 Collisions, Conflicts, and Interactions 3.1.2 Automated Detection Using Computer Vision Methods 3.2 Trajectory Prediction 3.2.1 Expert vs. Data Driven 3.2.2 State-of-the-Art Deep Learning Approaches 4 Methodological Contributions 4.1 Interaction Detection 4.1.1 Problem Formulation and the Proposed Model 4.1.2 Sequence-to-Sequence Processing 4.1.3 Estimation of Uncertainty 4.1.4 Feature Extraction 4.2 Trajectory Prediction 4.2.1 Problem Formulation and the Proposed Model 4.2.2 Trajectory Ranking 4.2.3 Feature Extraction 5 Interaction Detection 5.1 Data Acquisition and Pre-processing 5.2 Experiments 5.2.1 Pipeline 5.2.2 CVAE Model for Interaction Detection 5.2.3 Baseline Model 5.2.4 Ablation Studies 5.2.5 Evaluation Metrics 5.3 Results 5.3.1 Quantitative Results 5.3.2 Qualitative Results 5.3.3 Analysis of the Results 5.4 Discussion 5.4.1 Failed Detection 5.4.2 Challenges of Cross-Dataset Generalization 5.5 Summary 6 Trajectory Prediction 6.1 Multi-Context Encoder Network 6.1.1 Framework 6.1.2 Experiments 6.1.3 Results 6.1.4 Discussion 6.1.5 Summary 6.2 Attentive Maps Encoder Network 6.2.1 Framework 6.2.2 Experiments 6.2.3 Results 6.2.4 Discussion 6.2.5 Summary 6.3 Dynamic Context Encoder Network 6.3.1 Framework 6.3.2 Experiments 6.3.3 Results 6.3.4 Discussion 6.3.5 Summary 7 Conclusion and Outlook 7.1 Conclusion 7.2 Outlook List of Figures List of Tables Acronyms Bibliography Acknowledgements Curriculum Vitae , Sprache der Kurzfassungen: Deutsch, Englisch

Note: Contents 1 Introduction 1.1 Motivation and objective 1.2 Problem statement and contributions 1.3 Reader's guide 2 State of the art 2.1 Image features and relative orientation 2.2 Efficient image matching 2.2.1 Reduction of the number of features per image 2.2.2 Reduction of the number of image pairs 2.2.3 Other integrated methods 2.3 Incremental and hierarchical image orientation 2.3.1 Incremental image orientation 2.3.2 Hierarchical image orientation 2.4 Global image orientation 2.4.1 Outlier detection in relative orientation 2.4.2 Global rotation estimation 2.4.3 Global translation estimation 2.5 Alternative solutions for image orientation 2.6 Discussion 3 Preprocessing 3.1 Time efficient image matching based on a random k-d forest 3.1.1 Construction of the random k-d forest 3.1.2 Determination of overlapping image pairs 3.1.3 Clustering images and discarding single images 3.1.4 Determination of relative orientation parameters 3.2 Robustifying the ROs for robust global image orientation 3.2.1 Detecting and eliminating RO outliers by checking compatibility of triplets 3.2.2 Detecting and eliminating RO outliers due to repetitive structure 3.2.3 Detecting and eliminating RO outliers of very short baselines and baselines parallel to the viewing direction 3.2.4 Identifying correct ROs of baselines parallel to the viewing direction 3.3 Discussion 4 Global image orientation 4.1 General Overview 4.2 Global rotation estimation 4.2.1 Rotation preliminaries and problem statement 4.2.2 Robust solution of global rotations 4.2.3 Discussion 4.3 Global translation estimation 4.3.1 Problem statements and relevant function model 4.3.2 Determination of globally consistent scale factors 4.3.3 Solving global translations based on relative translations 4.4 Robust bundle adjustment 4.5 Discussion 5 Experimental setup 5.1 Objectives of the designed experiments 5.2 Test datasets 5.3 Free parameter settings 5.4 Evaluation strategy and criteria 5.4.1 Preprocessing steps 5.4.2 Global image orientation 6 Evaluation 6.1 Evaluation of preprocessing steps 6.1.1 Performance of overlapping pair determination 6.1.2 Performance of the robustification of ROs 6.2 Evaluation of global image orientation 6.2.1 Ordered datasets 6.2.2 Unordered datasets 6.2.3 Problematic datasets 6.3 Synthesis 6.3.1 Preprocessing steps 6.3.2 Global image orientation 7 Conclusion and Outlook Appendix A. Proposition for very short baselines B. Calculation of the discrepancy between relative orientation and ground truth exterior orientation parameters B.l Discrepancy with respect to relative rotations B.2 Discrepancy with respect to relative translations C. Calculation of the mean translation errors References

Note: Contents 1. Introduction 1.1. Motivation 1.2. Main Contributions 1.3. Thesis Outline 2. Basics 2.1. Feature based Image Matching 2.1.1. Overview: What is Feature based Image Matching? 2.1.2. Desired Properties for Detected Features and Descriptors 2.1.3. Scale-Invariant Feature Detection 2.1.4. Feature Affine Shape Estimation 2.1.5. Feature Orientation Assignment 2.1.6. Feature Description 2.1.7. Descriptor Matching 2.2. Convolutional Neural Network (CNN) 2.2.1. Architecture of CNN 2.2.2. Training of CNN 2.3. Siamese Convolutional Neural Network 3. Related Work 3.1. Local Feature Detection 3.1.1. Translation and Rotation Invariant Features 3.1.2. Scale Invariant Features 3.1.3. Detectors based on a Comparison of Grey Values or Saliency 3.1.4. Detectors based on Machine Learning 3.2. Feature Orientation and Affine Shape Estimation 3.2.1. Orientation Assignment 3.2.2. Affine Shape Estimation 3.3. Local Feature Description 3.3.1. Hand Crafted Descriptors 3.3.2. Machine Learning based Descriptors 3.4. An Application: Orientation of Oblique Aerial Images 3.5. Discussion 3.5.1. Orientation Assignment and Affine Shape Estimation 3.5.2. Descriptor Learning 3.5.3. An Aerial Photogrammetric Benchmark 3.5.4. Ability to Transfer Learned Modules 4. Deep Learning Feature Representation 4.1. Overview of the Methodology 4.2. Descriptor Learning using Active Weak Match Finder - WeMNet 4.2.1. Descriptor Learning Architecture 4.2.2. Generation of Training Pairs 4.2.3. Loss Function 4.2.4. Weak Match Branch 4.3. Self Supervised Feature Affine Shape Learning - MoNet 4.3.1. Affine Transformation Decomposition 4.3.2. Self Supervised Affine Shape Estimation Module 4.4. Self Supervised Orientation Assignment Module - MGNet 4.5. Full Affine Estimation Network - Full-AfFNet 4.5.1. Full Affine Network 4.5.2. Training Loss 4.5.3. Data Augmentation 4.6. Inference based on the Trained Networks 4.7. Discussion 4.7.1. Descriptor Learning 4.7.2. Affine Shape Estimation 4.7.3. Orientation Assignment Learning 4.7.4. The Inference Pipeline 5. Experiments and Results 5.1. Datasets 5.1.1. Datasets for Training 5.1.2. Datasets for Testing 5.2. Evaluation and Analysis Criteria 5.2.1. Task A: Patch based Image Matching 5.2.2. Task B: Descriptor Distance Analysis 5.2.3. Task C: Feature based Image Matching 5.2.4. Task D: Image Orientation 5.2.5. Summary of Tasks and Involved Datasets 5.3. Descriptor Learning and Patch Based Image Matching 5.3.1. Parameter Study for WeMNet 5.3.2. Comparison to Related Work 5.4. Descriptor Distance Analysis 5.4.1. Translation 5.4.2. Rotation 5.4.3. Affine Shape Transformation 5.5. Image Matching Analysis 5.5.1. Parameter Study for Affine Shape Learning 5.5.2. Image Matching for Rotation Dataset 5.5.3. Image Matching for Hpatches Affine Dataset 5.6. Image Orientation 5.6.1. Determination of Image Orientation 5.6.2. Experiment Setup Details 5.6.3. Orientation Result of Different Blocks 5.6.4. Matching Quality Analysis 6. Discussion 6.1. Descriptor Learning and Patch Based Image Matching 6.1.1. Parameter Study 6.1.2. Comparison to Related Works 6.2. Descriptor Distance Analysis 6.2.1. Translation 6.2.2. Rotation 6.2.3. Affine Shape Transformation 6.3. Feature based Image Matching 6.3.1. Parameter Study 6.3.2. Rotation Set 6.3.3. Affine Set 6.4. Image Orientation 7. Conclusion and Outlook Bibliography A. Affine Shape Adaptation Theory A.l. transformation of affine Gaussian scale-space A.2. Local affine distortion measurement A.3. More affine transformation

Note: Contents 1 Introduction 1.1 Motivation 1.2 Objective & Research Questions 1.3 Outline of the Thesis 2 Related Work and Theory 2.1 GNSS Positioning 2.1.1 GNSS Constellations 2.1.2 Position Estimation 2.1.3 Measurement Errors in GPS Measurements 2.2 Reliability 2.3 Integrity 2.3.1 Conventional RAIM 2.3.2 Advanced RAIM 2.3.3 Augmentation Systems 2.3.4 Derivation of Conventional RAIM 2.3.5 Protection Level 2.4 Interval Mathematics 2.4.1 Basic Interval Mathematical Operations 2.4.2 Interval Vectors and Matrices 2.4.3 Interval Functions 2.4.4 Set Inversion via Interval Analysis 2.4.5 Contractors 2.4.6 Application of Interval Analysis to Navigation 2.5 Determination of Observation Interval Bounds 2.5.1 Probabilistic Approaches with a Priori Integrity Risk 2.5.2 Sensitivity Analysis of the Measurement Correction 2.5.2.1 Concept 2.5.2.2 Klobuchar Ionospheric Model 2.5.2.3 Saastamoinen Tropospheric Model 2.5.3 Expert Knowledge and Desired Size of the Bounding Zone 3 Integrity Approaches Based on Interval Mathematics and Set Theory 3.1 Interval Extension of Least-Squares Adjustment 3.2 Set Inversion Via Interval Analysis 3.3 Linear Programming Bounding Method 3.4 Developed Method Based on Primal-Dual Poly tope and Intervals 3.4.1 Polytopes and Zonotopes 3.4.2 Formulation and Methodology 3.4.3 Interpretation of Bounding Zones and Related Consistency Measures 3.4.4 Minimum Detectable Bias Definition 3.4.5 Integrity Measures Via Zonotopes and Polytopes 4 Performance Analysis of the Developed Methods by Monte Carlo Simulations 4.1 Introduction 4.2 Characterization of a Nominal Behavior 4.3 Proposal to Select the Critical Value of the Polytope Tests 4.4 Impact of Biases 4.4.1 Introductory Example 4.4.2 Impact of Different Biased Satellites and Observation Interval Bounds 4.4.3 Impact of Different Biased Satellites and Satellite Geometry 4.5 Analysis of the Polytope Global and Local Tests 4.5.1 General Proceeding 4.5.2 Critical Detection Scenarios - Correlated Satellites 4.5.3 Critical Detection Scenarios - Bad Geometry 4.6 Probabilistic Test Statistic Results 4.6.1 Results of Probabilistic Test Statistics 4.7 Comparison Between Probabilistic Tests and Polytopal Test 4.7.1 Good Satellite Geometry 4.7.2 Bad Satellite Geometry 4.8 Analysis of Protection Levels 4.8.1 Zonotopal Horizontal and Vertical Protection Levels 4.8.2 Statistical Based Horizontal and Vertical Protection Level 5 Real Data Analysis 5.1 Introduction 5.2 Positioning Analysis 5.2.1 Results from Scenario 1 - Urban Area 5.2.2 Results from Scenario 2 - Semi-Urban Area 5.3 Fault Detection and Exclusion 5.4 Minimum Detectable Bias 5.5 Protection Level 6 Conclusions and Outlook Bibliography Acknowledgments Curriculum Vitae

Note: Dissertation, Universität Potsdam, 2021 , CONTENTS 1 INTRODUCTION 1.1 Motivation: Aerosol and cloud relevance to Arctic amplification 1.2 Theoretical background 1.2.1 Atmospheric aerosol 1.2.2 Aerosol in the Arctic 1.2.3 Cirrus clouds 1.3 Research questions 2 METHODS 2.1 lidar remote sensing techniqu 2.1.1 Elastic and Raman lidar equations 2.1.2 lidar signal corrections 2.1.3 Derivation of particle optical properties and related uncertainties 2.2 Lidar systems 2.2.1 Ground-based system KARL 2.2.2 Air-borne system AMALi 2.2.3 Space-borne system CALIOP 2.3 Ancillary instrumentation 2.3.1 Radiosondes 2.3.2 Sun-photometers 2.3.3 Radiation sensors 2.4 Modeling tools 2.4.1 Air mass backward trajectories 2.4.2 Aerosol microphysics retrieval algorithm 2.4.3 Radiative transfer model SCIATRAN 2.4.4 Multiple-scattering correction model 2.4.5 Simplified cloud radiative effect model 3 ARCTIC AEROSOL PROPERTIES AND RADIATIVE EFFECT (CASE STUDIES) 3.1 Aerosol in the upper troposphere (Spring) 3.1.1 Overview of aerosol observations and air mass origin 3.1.2 Modification of aerosol optical and microphysical properties 3.1.3 Aerosol radiative effect (ARE) 3.2 Sensitivities of the spring-time Arctic ARE 3.2.1 Sensitivity on aerosol related parameters 3.2.2 Sensitivity on ambient conditions 3.3 Aerosol in the lower troposphere (Winter) 3.3.1 Overview of remote sensing and in-situ measurements 3.3.2 Aerosol properties from the remote sensing perspective: KARL and CALIOP 3.3.3 Aerosol microphysical properties from in-situ and remote sensing perspectives 3.4 Discussion and Conclusions 4 DEVELOPMENT OF A CIRRUS CLOUD RETRIEVAL SCHEME 4.1 Fine-scale cirrus cloud detection 4.1.1 Selection of cirrus clouds 4.1.2 Wavelet Covariance Transform method 4.1.3 Revised detection method: Dynamic Wavelet Covariance Transform 4.2 Comparison of dynamic and static cirrus detection 4.3 Cirrus cloud optical retrievals 4.3.1 Existing cirrus optical retrievals: double-ended Klett and Raman 4.3.2 Temporal averaging within stationary periods 4.3.3 Revised optical retrieval: constrained Klett method 4.4 Comparison to established optical retrievals 4.5 How uncertainties in cirrus detection affect the optical retrievals? 4.6 Discussion 4.6.1 Limitations of cirrus retrieval schemes 4.6.2 Strengths of the revised retrieval scheme 4.7 Conclusions 5 LONG-TERM ANALYSIS OF ARCTIC CIRRUS CLOUD PROPERTIES 5.1 Overview of cirrus occurrence and meteorological conditions over Ny-Ålesund 5.2 Quality assurance of optical properties 5.2.1 Specular reflection effect 5.2.2 Investigation of extreme cirrus lidar ratio values 5.2.3 Multiple-scattering correction 5.3 Overview of cirrus optical properties over Ny-Ålesund 5.4 Inter-relations of cirrus properties 5.5 Dependence on meteorological conditions 5.5.1 Cirrus clouds in the tropopause 5.6 CRE estimation at TOA: sensitivity analysis 5.7 Conclusions 6 CONCLUSIONS AND OUTLOOK A CIRRUS DETECTION SENSITIVITIES a.1 Wavelet Covariance Transform - dilation sensitivity a.2 Wavelet Covariance Transform - wavelength dependency B CIRRUS OPTICAL CHARACTERIZATION SENSITIVITIES b.1 Reference value accuracy and limitations b.2 Inherent uncertainties of constrained Klett C MULTIPLE-SCATTERING CORRECTION FOR CIRRUS CLOUDS D SEASONAL CIRRUS PROPERTIES: DESCRIPTIVE STATISTICS BIBLIOGRAPHY

Note: Dissertation, Universität Potsdam, 2021 , Contents List of abbreviations Acknowledgements Summary Zusammenfassung 1 Scientific background 1.1 Motivation 1.2 The arctic-boreal ecotone in time and space 1.2.1 Terrestrial plants composition and biodiversity 1.2.2. Lake macrophytes and diatoms 1.3 Sedimentary DNA metabarcoding as an ecologicalproxy 1.4 Study area 1.5 Objectives of the thesis 1.6 Methods 1.7 Thesis organizations 1.7.1 Manuscripts and chapters 1.7.2 Non-finalized research 1.7.2 Author contributions 2 Manuscript I: Genetic and morphological diatom composition in surface sediments from glacial and thermokarst lakes in the Siberian Arctic 2.1 Abstract 2.2 Introduction 2.3 Materials and methods 2.3.1 Sampling and collection of environmental data 2.3.2 Diatom genetic assessment 2.3.3 Raw sequence processing and taxonomic assignment 2.3.4 Morphological diatom identification 2.3.5 Statistical analyses 2.4 Results 2.4.1 Genetic-based diatom composition, diversityand diatom-environment relationship 2.4.2 Morphological-based diatom composition, diversity and diatom-environment relationship 2.4.3 Comparison of spatial diatom patterns obtained from the genetic and morphological approaches 2.5 Discussion 2.5.1 Genetic and morphological diatom composition and diversity 2.5.2 Diatom composition is affected by lake type and lake water parameters 2.6 Conclusions 2.7 Acknowledgments 3 Manuscript II: Plant sedimentary ancient DNA from Far East Russia covering the last 28 ka reveals different assembly rules in cold and warm climates 3.1 Abstract 3.2 Introduction 3.3 Methods 3.3.1 Study area 3.3.2 Sampling and dating 3.3.3 Genetic laboratory works 3.3.4 Processing the sequence data 3.3.5 Statistical analyses 3.4 Results 3.4.1 Overview of the sequencing data and taxonomic composition 3.4.2 Taxonomic alpha and beta diversity 3.4.3 Phylogenetic alpha and beta diversity 3.4.4 Relationship between taxonomic composition and phylogenetic diversity 3.5 Discussion 3.5.1 Vegetation history revealed by sedaDNA 3.5.2 Patterns oftaxonomic alpha diversity and their relationship to community composition 3.5.3 Relationship between richness and phylogenetic alpha and beta diversity 4 Manuscript III: Sedimentary DNA identifies modem and past macrophyte diversity and its environmental drivers in high latitude and altitude lakes in Siberia and China 4.1 Abstract 4.2 Introduction 4.3 Materialsand Methods 4.3.1 Field sampling of surface and core samples 4.3.2 Environmental data 4.3.3 Molecular genetic laboratory work 4.3.4 Bioinformatic analyses 4.3.5 Statistical analyses 4.4 Results 4.4.1 Macrophyte diversity in surface sediments inferred from sedDNA 4.4.2 Relationship of modem macrophyte richness and environmental variables 4.4.3 The relationship between modem macrophyte community and environmental variables 4.4.4 Past macrophyte richness and composition inferred from sedaDNA 4.4.5 Past macrophyte compositional changes and its environmental drivers 4.5 Discussion 4.5.1 Retrieval of aquatic plant diversity using the tmL P6 loop plant DNA metabarcode 4.5.2 Modem macrophyte diversity and its relation to environmental factors 4.5.3 Temporal macrophyte diversity as an indicator for past environmental change 4.6 Conclusion 5 Synopsis 5.1 Potential and limitations of sedimentary DNA in the applied study 5.1.1 Sedimentary DNA is a powerful proxy 5.1.2 Limitations in sedimentary DNA 5.2 Spatial patterns of vegetation, macrophytes and diatoms 5.2.1 Composition and diversity of vegetation 5.2.2 Composition and diversity of macrophytes 5.2.3 Composition and diversity of diatoms 5.3 Temporal patterns of vegetation, macrophytes and diatoms 5.3.1 Composition and diversity of vegetation 5.3.2 Composition and diversity of macrophytes 5.3.3 Composition and diversity of diatoms 5.4 Outlooks and conclusions Appendices Appendix 1 for Manuscript I Appendix 2 for Manuscript II Appendix 3 for Manuscript III References

Note: Dissertation, Universität Potsdam, 2021 , Table of Contents Acknowledgements Abstract Zusammenfassung List of figure List of tables List of abbreviation Chapter 1 1. Introduction 1.1 Research background 1.1.1 Response of mountain plant diversity to climate change 1.1.2 Response of Arctic vegetation composition and diversity to climate change 1.1.3 Understanding the critical mechanisms of community assembly are essential for sustaining ecosystem services 1.1.4 Pollen analysis as a traditional tool for representing palaeovegetation 1.1.5. Sedimentary ancient DNA (sedaDNA) is a useful tool for Quaternary ecology tracking 1.2 Study area 1.3 Aims and objectives 1.4 Structure of the thesis 1.4.1 Overview of the chapter 1.4.2 Author's contributions 1.4.3 Methods Chapter 2 2 Manuscript 1: Sedimentary ancient DNA reveals warming-induced alpine habitat loss threat to Tibetan Plateau plant diversity 2.1 Abstract 2.2 Introduction 2.3 Results and discussion 2.4 Methods 2.5 Acknowledgements · Chapter 3 3 Manuscript 2: Holocene vegetation and plant diversity changes in the north-eastern Siberian treeline region from pollen and sedimentary ancient DNA 3.1 Abstract 3.2 Introduction 3.3 Materials and methods 3.3.1 Study area 3.3.2 Lake sediment cores and subsampling 3.3.3 Dating 3.3.4 Pollen analysis 3.3.5 DNA extraction and amplification 3.3.6 Sequencing filtering and taxonomic assignment 3.3.7 Statistical analyses 3.4 Results 3.4.1 Chronology 3.4.2 SedaDNA and pollen assemblages 3.4.3 Gradient analysis and correlation analysis 3.5 Discussion 3 .5.1 Contributions of pollen and sedaDNA to vegetation reconstruction and taxon richness 3.5.2 Variation in Holocene vegetation composition in the Omoloy area, north-eastern Siberia 3.5.3 SedaDNA-based plant diversity changes within lake catchments of the Omoloy region 3.6 Conclusions 3.7 Acknowledgements Chapter 4 4 Manuscript 3: Vegetation reconstruction from Siberia and Tibetan Plateau using modern analogue technique - comparing sedimentary ancient DNA (sedaDNA) and pollen data 4.1 Abstract 4.2 Introduction 4.3 Materials and methods 4.3.1 Sites ofthe modern analogues 4.3.2 Sedimentary (ancient) DNA collection 4.3.3 Metabarcoding data processing and filtering 4.3.4 Pollen data collection 4.3.5 Numerical analysis 4.4 Results 4.4.1 Modern training-set, ROC curve analyses and AT results 4.4.2 Modern analogues for Lake Naleng and Omoloy lake II 4.4.3 Vegetation type reconstruction based on MAT 4.4.4 Projecting fossil samples in ordination space of modern assemblages 4.4.5 Comparing past and present intertaxa relationships 4.5 Discussion 4.5.1 Assessment of analogue quality using modem training-sets 4·5·2 Comparison of sed(a)DNA-based and pollen-based vegetation reconstruction for the Lake Naleng, Tibetan Plateau 4.5.3 Comparison of sedDNA based and pollen-based vegetation reconstruction for the Lake Omoloy, northern Siberia 4.6 Conclusions 4.7 Acknowledgements Chapter 5 5 Manuscript 4: Terrestrial-aquatic ecosystem links on the Tibetan Plateau inferred from sedaDNA shotgun sequencin 5.1 Abstract 5.2 Introduction 5.3 Results 5.4 Discussions 5.5 Methods 5.6 Acknowledgments Chapter 6 6 Synthesis 6.1 The ability of metabarcoding and metagenomic shotgun sequencing to reveal ecological community pattern 6.2 Driver of plant diversity change in high altitude and high latitudes 6.3 High-altitude and high-latitude vegetation type change 6.4 Past terrestrial and aquatic ecological change at ecosystem-scale 6.5 Conclusions and outlook Appendix 1 Appendix-1 Materials for Manuscript #1 1.1 Appendix discussion: Contamination in NTC6 2. Appendix-2 Materials for Manuscript #2 3. Appendix-3 Materials for Manuscript #3 4. Appendix-4 Materials for Manuscript #4 References Eidesstattliche Erklarung

Note: Common theoretical and practical basis -- The multifaceted nature of magma mixing -- The fundamental phenomenon -- The evolution of igneous rocks and in triggering explosive volcanic eruptions -- Draw the most complete picture about this natural process.

Note: Chapter 1: Reasons to conduct research in space -- Chapter 2: History of Human Space Exploration -- Chapter 3: Major frontiers in space science (I) -- Chapter 4: Major frontiers in space science (II) -- Chapter 5: Space Systems Engineering and Its Systems -- Chapter 6: Technical fundamentals (I): orbit, attitude and TT&C -- Chapter 7: Technical fundamentals (II): scientific payloads and its application environment -- Chapter 8: Technical fundamentals (III): Mission Planning and Operations -- Chapter 9: Managements (I): Call for Mission Proposals and Its Selection -- Chapter 10: Managements (II): Mission Development and the Duty of Scientists and Engineers -- Chapter 11: Managements (III): Quality Management and Risk Control -- Chapter 12: Managements (IV): Full Mission Lifecycle Management and Output Evaluation -- Chapter 13: International Cooperation -- Chapter 14: Strategic Planning of Space Science in China -- Chapter 15: Relations of Space science, Space Technology and Space Applications.

Note: 1 Introducing loss and damage 1 Meinhard Doelle and Sara L Seck PART I FRAMEWORKS 2 Equity considerations in loss and damage 18 Nathalie J. Chalifour 3 The sacrifice zones of carbon capitalism: race, expendability, and loss and damage 43 Carmen G. Gonzalez 4 Measuring the immeasurable: loss and damage from climate change in international law 60 Usha Natarajan PART II PUBLIC INTERNATIONAL LAW 5 Loss and damage under the Convention 75 Linda Siegele 6 Loss and damage under the Paris Agreement 100 Linda Siegele 7 Arrested development: the late and inequitable integration of loss and damage finance into the UNFCCC 127 Patricia Galvão Ferreira 8 Against the headwind: innovative sources of loss and damage finance 149 Patricia Galvão Ferreira 9 State responsibility for damages associated with climate change 166 Christina Voigt 10 Valuation of climate change loss and damage 184 Cymie R Payne 11 A rights-based approach to loss and damage due to climate change 201 Katherine Lofts, Sébastien Jodoin and Larissa Parker 12 Indigenous peoples, climate change loss and damage, and the responsibilities of states 223 Kyle Powys Whyte 13 Loss and damage, climate displacement and international law: addressing the protection gap 244 Sumudu Atapattu 14 Loss and damage, disaster law, and climate change 266 Anastasia Telesetsky 15 Solar radiation modification and loss & damage: mapping interactions between climate responses 286 Neil Craik PART III DOMESTIC, TRANSNATIONAL AND PRIVATE INTERNATIONAL LAW 16 Atmospheric recovery litigation around the world: gaining natural resource damages against carbon majors to fund a sky cleanup for climate restoration 303 Mary Christina Wood 17 Loss and damage in European litigation 331 Roda Verheyen and Johannes Franke 18 Towards a civil liability regime for climate-related loss and damage 349 Sharon Mascher 19 Think globally, sue locally: challenges and opportunities in international climate litigation in domestic courts 368 Andrew Gage 20 Carbon major companies and liability for loss and damage 390 Lisa Benjamin 21 Class actions and climate change loss and damage litigation 409 C. Cameron and R. Weyman PART IV CONCLUSIONS 22 Pathways and prospects for loss & damage and climate justice 433 Sara L Seck and Meinhard Doelle Index

Note: Contents Preface Introduction 1.1 Hazard and Risk Analysis 1.2 Uses of Hazard and Risk Infonnation 1.3 Detenninistic Analysis 1.4 Probabilistic Seismic Hazard Analysis 1.5 Probabilistic Risk Analysis 1.6 Benefits of Probabilistic Analysis I. 7 Uncertainties in Probabilistic Analysis 1.8 Validation Part I Hazard Inputs 2 Seismic Source Characterization 2.1 Introduction 2.2 Earth Structure and Plate Tectonics 2.3 Faults 2.4 Earthquake Processes 2.5 Earthquake Size 2.6 Definitions of Seismic Sources 2. 7 Source Characteristics 2.8 Conceptual Development of SSMs Exercises 3 Characterization of Earthquake Rates and Rupture Scenarios 3.1 Introduction 3.2 Approaches to Determining Rupture Rates 3.3 Constraints from Seismicity Data 3.4 Geological Constraints on Activity 3.5 Magnitude-Frequency Distributions 3.6 Rupture Scenarios and Computation of Rates 3.7 Generation of Rupture Scenarios 3.8 Time-Dependent Ruptw-e Rates Exercises 4 Empirical Ground-Motion Characterization 147 4.1 Introduction 147 4.2 Engineering Characterization of Ground Motion 149 4.3 Ground-Motion Databases 161 4.4 Mathematical Representation 166 4.5 General Trends in Empirical Data and Models 170 4.6 Prediction Using Empirical GMMs 179 4.7 Epistemic Uncertainty 186 4.8 Limitations of Empirical GMMs 192 Exercises 193 5 Physics-Based Ground-Motion Characterization 196 5.1 Introduction 196 5.2 Utility of Physics-Based Ground-Motion Simulation 198 5.3 Earthquake Source Representation 200 5.4 Seismic Wave Propagation 205 5.5 Methods for Physics-Based Ground-Motion Simulation 220 5.6 Prediction Using Physics-Based GMMs 233 Exercises Part II Hazard Calculations 247 6 PSHA Calculation 249 6.1 Introduction 249 6.2 The PSHA Calculation 250 6.3 Example Calculations 255 6.4 Hazard Curve Metrics 262 6.5 Sensitivity of Hazard Results to Inputs 266 6.6 Model Uncertainty 269 6.7 Logic Trees 272 6.8 PSHA with Epistemic Uncertainty 276 6.9 Monte Carlo PSHA 279 6.10 Discussion 280 Exercises 7 PSHA Products 286 7.1 Introduction 286 7.2 Disaggregation 287 7.3 Uniform Hazard Spectrum 301 7.4 Hazard Maps 306 7.5 Conditional Spectrum 307 7.6 VectorPSHA 312 7.7 Earthquake Sequences in PSHA 312 7.8 Implementation and Documentation of Hazard Studies 316 Exercises 8 Non-Ergodic Hazard Analysis 8.1 Introduction 8.2 Fundamental Concepts 8.3 Aleatory Variability versus Epistemic Uncertainty 8.4 When Can Non-Ergodic Approaches Be Applied? 8.5 Non-Ergodic Ground-Motion Models 8.6 Non-Ergodic Site Effects 8.7 Non-Ergodic Path Effects 8.8 Non-Ergodic Source Effects 8.9 Non-Ergodic Components in Seismic-Source Models Exercises Part Ill Risk 9 Seismic Risk 9.1 Introduction 9.2 Fragility and Vulnerability Functions 9.3 Calibrating Fragility and Vulnerability Functions 9.4 Risk Metrics 9.5 PEER Framework 9.6 Epistemic Uncertainty 9.7 Risk-Targeted Ground-Motion Intensity Exercises 10 Ground-Motion Selection I 0.1 Introduction I 0.2 Principles of Hazard-Consistent Ground-Motion Selection 10.3 Target Intensity Measure Distributions I 0.4 Selection Algorithms 10.5 Assessing Accuracy and Precision of Seismic Responses 10.6 Application-Specific Decisions 10.7 Design Code and Guideline Requirements 10.8 Documentation Exercises 11 Spatially Distributed Systems 11.1 Introduction 11.2 Parameterization Using Empirical Ground-Motion Models 11.3 Parameterization Using Physics-Based Simulations 11.4 Numerical Implementation 11.5 Coherency 11.6 Risk Exercises 12 Validation 12. l Introduction 12.2 Verification and Validation 12.3 Validation from Limited Observations 12.4 Direct Validation of Seismic Hazard Curves 12.5 Validation of Model Components 12.6 Do Failures of Past Calculations [nvalidate the PSHA Methodology? 12.7 Seismic Hazard and Risk Analysis for Decision-Making Exercises Appendix A Basics of Probability A. l Random Events A.2 Conditional Probability A.3 Random Variables A.4 Expectations and Moments A.5 Common Probability Distributions A.6 Random Number Generation Appendix B Basics of Statistics for Model Calibration 1 B.3 Statistical Estimation of m1,,x my,y B.5 Maximum Likelihood Estimation of Seismicity Parameters Estimation ofIM ofSymbols 433 484 486 494 514 519 523 529 533 578 viii Contents 12 Validation 12. l Introduction 12.2 Verification and Validation 12.3 Validation from Limited Observations 12.4 Direct Validation of Seismic Hazard Curves 12.5 Validation of Model Components 12.6 Do Failures of Past Calculations [nvalidate the PSHA Methodology? 12.7 Seismic Hazard and Risk Analysis for Decision-Making Exercises Appendix A Basics of Probability A. l Random Events A.2 Conditional Probability A.3 Random Variables A.4 Expectations and Moments A.5 Common Probability Distributions A.6 Random Number Generation Appendix B Basics of Statistics for Model Calibration B. l Confidence Intervals for the Sample Mean and Standard Deviation B.2 Hypothesis Testing for Statistical Significance B.3 Statistical Estimation of mmax B.4 Bayesian Estimation of lnmax B.5 Maximum Likelihood Estimation of Seismicity Parameters B.6 Empirical GMM Calibration B.7 Estimation of JM Correlations from GMMs B.8 Fragility Function Fitting References List of Symbols and Abbreviations Notation Conventions Index

Note: Contents Dedication Introduction Background and context Shumilovskikh, L., O’Keefe, J. M. K. and Marret, F. / An overview of the taxonomic groups of non-pollen palynomorphs Pound, M. J., O’Keefe, J. M. K. and Marret, F. / An overview of techniques applied to the extraction of non-pollen palynomorphs, their known taphonomic issues and recommendations to maximize recovery O’Keefe, J. M. K., Nuñez Otaño, N. B. and Virginia Bianchinotti, M. / Nomenclature: how do we designate NPP taxa? The major groups of NPPs Nuñez Otaño, N. B., Virginia Bianchinotti, M. and Saparrat, M. C. N. / Palaeomycology: a modern mycological view of fungal palynomorphs McCarthy, F. M. G., Pilkington, P. M., Volik, O., Heyde, A. and Cocker, S. L. / Non-pollen palynomorphs in freshwater sediments and their palaeolimnological potential and selected applications Andrews, L. O., Payne, R. J. and Swindles, G. T. / Testate amoebae as non-pollen palynomorphs in pollen slides: usefulness and application in palaeoenvironmental reconstruction Mudie, P. J., Marret, F., Gurdebeke, P. R., Hartman, J. D. and Reid, P. C. / Marine dinocysts, acritarchs and less well-known NPP: tintinnids, ostracod and foraminiferal linings, copepod and worm remains Application of NPPs to a variety of problems Gauthier, E. and Jouffroy-Bapicot, I. / Detecting human impacts: non-pollen palynomorphs as proxies for human impact on the environment van Asperen, E. N., Perrotti, A. and Baker, A. / Coprophilous fungal spores: non-pollen palynomorphs for the study of past megaherbivores Denison, C. N. / Stratigraphic and sedimentological aspects of the worldwide distribution of Apectodinium in Paleocene/Eocene Thermal Maximum deposits Wellman, C. H. and Ball, A. C. / Early land plant phytodebris Agić , H. and Cohen, P. A. / Non-pollen palynomorphs in deep time: unravelling the evolution of early eukaryotes Index

Note: Contents 1 Introduction 1.1 LEO satellites 1.2 ESA Swarm mission 1.3 Objectives and structure of this work 2 GPS data quality analysis of the Swarm satellite formation 2.1 Fundamentals of GPS 2.2 Tracking performance 2.2.1 Receiver settings 2.2.2 Number of satellites tracked 2.3 Observation Analysis 2.3.1 Signal strength 2.3.2 Code noise 2.3.3 Carrier phase noise 2.4 Geometry-free linear combination 2.5 Cycle Slip Detection/Repair 2.6 Outlier detection 3 Kinematic orbit determination 3.1 Observation modeling 3.1.1 Precise Point Positioning 3.1.2 Batch least-squares adjustment 3.2 Kinematic orbit results 3.2.1 Validation with reduced-dynamic orbits 3.2.2 Validation with external kinematic orbits 3.2.3 Evaluation of orbit quality with residuals of observations 3.2.4 Validation with Satellite Laser Ranging 3.2.5 Validation with gravity fields 3.2.6 Receiver clock 3.3 Covariance Information 4 Kinematic baseline determination 4.1 Relative positioning models 4.1.1 Single-difference model 4.1.2 Double-difference model 4.1.3 Processing strategy using LSA 4.2 Kinematic baseline results 4.2.1 Comparing PPP and DD float baseline 4.2.2 Comparing baselines with float and fixed ambiguities 5 Kinematic velocity determination 5.1 Observation modeling 5.2 Kinematic velocity results 6 Analysis and mitigation of ionospheric scintillation effects 6.1 Ionospheric scintillations characterized by the Swarm satellites 6.2 Phase tracking loop 6.3 Mitigation of high-frequency noise over the polar areas 6.4 Mitigation of tracking errors over the equatorial areas 7 Conclusions , Sprache der Kurzfassungen: Englisch, Deutsch

Note: Political economies of energy transition in Brazil and South Africa , Wind and solar power in the transition to a low-carbon economy , States, markets, and energy transition : good industrial policy? , Electricity consumption in Brazil and South Africa : distribution and prices , People and place : siting wind and solar plants in Brazil and South Africa , Political economies of energy transition

Note: Beiträge teilweise in deutscher, teilweise in englischer Sprache

Note: ОГЛАВЛЕНИЕ ВВЕДЕНИЕ 1. ГОСУДАРСТВЕННЫЙ ПРИРОДНЫЙ ЗАПОВЕДНИК «УСТЬ-ЛЕНСКИЙ)): СТРУКТУРА И ФИЗИКО-ГЕОГРАФИЧЕСКИЕ УСЛОВИЯ 2. КОНСПЕКТ ФЛОРЫ ОКРЕСТНОСТЕЙ МБС "ЛЕНА-НОРДЕНШЕЛЬД" З. РЕЗУЛЬТАТЫ ИССЛЕДОВАНИЙ ФЛОРЫ И ИХ ОБСУЖДЕНИЕ 4. СЕРГЕЙ ВЛАДИМИРОВИЧ ЛАРИОНОВ (1957-1995) БИБЛИОГРАФИЧЕСКИЙ СПИСОК , TABLE OF CONTENTS INTRODUCTION 1. STATE NATURE RESERVE "UST-LENSKY": STRUCTURE AND PHYSICAL AND GEOGRAPHICAL CONDITIONS 2. ABSTRACT OF THE FLORA OF THE SURROUNDINGS OF MBS "LENA-NORDENSHELD" 3. RESULTS OF STUDIES OF FLORA AND THEIR DISCUSSION 4. SERGEY VLADIMIROVICH LARIONOV (1957-1995) REFERENCES

Note: Contents Reolid, M., Mattioli, E., Duarte, L. V. and Ruebsam, W. / The Toarcian Oceanic Anoxic Event: where do we stand? Correia, V. F., Riding, J. B., Duarte, L. V., Fernandes, P. and Pereira, Z. / The effects of the Jenkyns Event on the radiation of Early Jurassic dinoflagellate cysts Fraguas, Á., Gómez, J. J., Goy, A. and Comas-Rengifo, M. J. / The response of calcareous nannoplankton to the latest Pliensbachian–early Toarcian environmental changes in the Camino Section (Basque Cantabrian Basin, northern Spain) Menini, A., Mattioli, E., Hesselbo, S. P., Ruhl, M. and Suan, G. / Primary v. carbonate production in the Toarcian, a case study from the Llanbedr (Mochras Farm) borehole, Wales Thuy, B. and Numberger-Thuy, L. D. / Brittlestar diversity at the dawn of the Jenkyns Event (early Toarcian Oceanic Anoxic Event): new microfossils from the Dudelange drill core, Luxembourg Bomou, B., Suan, G., Schlögl, J., Grosjean, A.-S., Suchéras-Marx, B., Adatte, T., Spangenberg, J. E., Fouché, S., Zacaï, A., Gibert, C., Brazier, J.-M., Perrier, V., Vincent, P., Janneau, K. and Martin, J. E. / The palaeoenvironmental context of Toarcian vertebrate-yielding shales of southern France (Hérault) Martin, J. E., Suan, G., Suchéras-Marx, B., Rulleau, L., Schlögl, J., Janneau, K., Williams, M., Léna, A., Grosjean, A.-S., Sarroca, E., Perrier, V., Fernandez, V., Charruault, A.-L., Maxwell, E. E. and Vincent, P. / Stenopterygiids from the lower Toarcian of Beaujolais and a chemostratigraphic context for ichthyosaur preservation during the Toarcian Oceanic Anoxic Event Fernández-Martínez, J., Rodríguez-Tovar, F. J., Piñuela, L., Martínez-Ruiz, F. and García-Ramos, J. C. / The Halimedides record in the Asturian Basin (northern Spain): supporting the Toarcian Oceanic Anoxic Event relationship Šimo, V. and Reolid, M. / Palaeogeographical homogeneity of trace-fossil assemblages in Lower Jurassic spotted marls and limestones: comparison of the Western Carpathians and the Betic Cordillera Reolid, M., Soussi, M., Reolid, J., Ruebsam, W., Taher, I. B., Mattioli, E., Saidi, M. and Schwark, L. / The onset of the Early Toarcian flooding of the Pliensbachian carbonate platform of central Tunisia (north–south axis) as inferred from trace fossils and geochemistry Boomer, I., Copestake, P., Page, K., Huxtable, J., Loy, T., Bown, P., Dunkley Jones, T., O’Callaghan, M., Hawkes, S., Halfacree, D., Reay, H. and Caughtry, N. / Biotic and stable-isotope characterization of the Toarcian Ocean Anoxic Event through a carbonate–clastic sequence from Somerset, UK Müller, T., Price, G. D., Mattioli, E., Leskó, M. Z., Kristály, F. and Pálfy, J. / Hardground, gap and thin black shale: spatial heterogeneity of arrested carbonate sedimentation during the Jenkyns Event (T-OAE) in a Tethyan pelagic Basin (Gerecse Mts, Hungary) Rodrigues, B., Silva, R. L., Mendonça Filho, J. G., Reolid, M., Sadki, D., Comas-Rengifo, M. J., Goy, A. and Duarte, L. V. / The Phytoclast Group as a tracer of palaeoenvironmental changes in the early Toarcian Fonseca, C., Mendonça Filho, J. G., Lézin, C., Baudin, F., de Oliveira, A. D., Souza, J. T. and Duarte, L. V. / Boosted microbial productivity during the Toarcian Oceanic Anoxic Event in the Paris Basin, France: new evidence from organic geochemistry and petrographic analysis Xu, W., Weijers, J. W. H., Ruhl, M., Idiz, E. F., Jenkyns, H. C., Riding, J. B., Gorbanenko, O. and Hesselbo, S. P. / Molecular and petrographical evidence for lacustrine environmental and biotic change in the palaeo-Sichuan mega-lake (China) during the Toarcian Oceanic Anoxic Event Ruebsam, W. and Schwark, L. / Impact of a northern-hemispherical cryosphere on late Pliensbachian–early Toarcian climate and environment evolution Silva, R. L., Ruhl, M., Barry, C., Reolid, M. and Ruebsam, W. / Pacing of late Pliensbachian and early Toarcian carbon cycle perturbations and environmental change in the westernmost Tethys (La Cerradura Section, Subbetic zone of the Betic Cordillera, Spain) Index

Note: Contents Dedication Preface Background and importance Fitzpatrick, R. W. and Donnelly, L. J. / An introduction to forensic soil science and forensic geology: a synthesis Kobus, H. and Robertson, J. / The importance of forensic soil science and geology being connected to mainstream forensic science Search for burials Ruffell, A. and Barry, L. / The desktop study – an essential element of geoforensic search: homicide and environmental cases (west Belfast, Northern Ireland, UK) McKinley, J. and Ruffell, A. / Geographical Information Science (GIS), spatial sampling and sediment variability examined using a case of manslaughter Donnelly, L. J., Cassella, J., Pirrie, D., Dawson, L., Blom, G., Davidson, A., Arnold, P., Harrison, M. and Hope, C. / Analysis of soil following a police-led open area search and the recovery of a cold-case homicide grave Barone, P. M. and Di Maggio, R. M. / Dealing with different forensic targets: geoscientists at crime scenes Canata, R. E., Salvador, F. A. S., Borges, W. R., Ferreira, F. J. F., Seimetz, E. X., Pinto, I. and Barros, E. O. / The forensic application of ground-penetrating radar, Tekoha Jevy indigenous village, Paraná, Brazil Molina, C. M. and Pringle, J. K. / Comparison of geophysical and botanical results in simulated clandestine graves in rural and tropical environments in Colombia, South America Donnelly, L. / A standard operating procedure (SOP), for soil sampling, for the detection of volatile organic compounds and leachate associated with human decomposition from a shallow, unmarked, homicide grave Trace evidence Dixon, R. D. and Merkle, R. K. W. / Identifying the source of illicit gold from South America Salvador, F. A. da S., Nogueira e Silva, M. P., de Oliveira Mascarenhas, R. and Rumbelsperger, A. M. B. / The application of forensic geology to investigate the substitution of zinc ingots between China and Brazil Guo, H., Wang, P., Hu, C., Zhu, J., Yang, X., Quan, Y., Mei, H. and Li, J. / A case study in forensic soil examination from China Raven, M. D., Fitzpatrick, R. W. and Self, P. G. / Trace evidence examination using laboratory and synchrotron X-ray diffraction technique Testoni, S. A., Melo, V. F., Dawson, L. A., Salvador, F. A. S. and Prandel, L. V. / Evaluation of forensic soil traces from a crime scene: robbery of a safety deposit box in Brazil Fitzpatrick, R. W. and Raven, M. D. / The forensic comparison of trace amounts of soil on a pyjama top with hypersulphidic subaqueous soil from a river as evidence in a homicide cold case Research developments Di Maggio, R. M. and Barone, P. M. / Geoforensics in Italy: education and research standards Bergslien, E. / Portable X-ray fluorescence (PXRF) spectrometry of earth materials: considerations for forensic analysis Young, J. M., Higgins, D. and Austin, J. J. / Soil DNA: advances in DNA technology offer a powerful new tool for forensic science Dawson, L. A., Macdonald, L. M. and Ritz, K. / Plant wax compounds and soil microbial DNA profiles to ascertain urban land use type Pirrie, D., Crean, D. E., Pidduck, A. J., Nicholls, T. M., Awbery, R. P. and Shail, R. K. / Automated mineralogical profiling of soils as an indicator of local bedrock lithology: a tool for predictive forensic geolocation Index

Note: Dissertation, Gottfried Wilhelm Leibniz Universität Hannover, 2021 , Contents 1. Introduction 1.1. Motivation and Research Goal 1.2. Outline 2. Basics 2.1. Archaeology 2.2. Geographic Information System 2.2.1. Spatial Reference System 2.2.2. Coordinate Reference Systems 2.2.3. Raster and Vector Data 2.2.4. GIS Software 2.2.5. GIS Data File Formats 2.3. Remote Sensing 2.3.1. Passive and Active Remote Sensing 2.3.2. LiDAR Systems 2.3.3. Processing LiDAR Data 2.3.4. Digital Terrain Models and Derived Rasters 2.4. Deep Learning 2.4.1. Neurons 2.4.2. Layers 2.4.3. Objective Functions 2.4.4. Evaluation Metrics 2.4.5. Backpropagation 2.4.6. Gradient Descent 2.4.7. Gradient Descent Optimization Algorithms 2.4.8. Supervised Learning 2.4.9. Transfer Learning 2.4.10. Unsupervised Learning 2.4.11. Self Supervised Learning 3. Related Work 3.1. Remote Sensing in Archaeology 3.2. Deep Learning in Remote Sensing 3.3. Deep Learning in Point Clouds and Digital Terrain Models 3.4. Deep Learning in Archaeology 4. Datasets 4.1. Digital Terrain Model and Relief Visualization Dataset 4.2. Archaeological Monuments in the Harz 4.2.1. Areal Dataset 4.2.2. Linear Dataset 4.2.3. Stone Quarries Dataset 4.3. Data Preparation for Deep Learning Models 4.3.1. Data Processing for Self Supervised Learning Pretext 4.3.2. Data Processing for Classification 4.3.3. Data Processing for Instance Segmentation 4.3.4. Data Processing for Semantic Segmentation 5. Methodology 5.1. Pretext Methods 5.1.1. Relief Visualization Network (RVNet) 5.1.2. Relief Visualization GAN (RVGan) 5.2. Downstream Method 5.2.1. Classification of Archaeological Monuments and Terrain Structures 5.2.2. Instance Segmentation of Archaeological Monuments and Terrain Structures 5.2.3. Semantic Segmentation of Archaeological Monuments and Terrain Structures 6. Experiments and Results 6.1. Self Supervised Learning Pretext Experiments 6.2. Classification 6.3. Instance Segmentation 6.3.1. Areal Dataset 6.3.2. Linear Dataset 6.4. Semantic Segmentation 6.4.1. Areal Dataset 6.4.2. Linear Dataset 6.4.3. Stone Quarries Dataset 6.5. Evaluation on 4 Test Regions with Distinct Objects 6.6. Qualitative Evaluations 6.6.1. Qualitative Results for Areal Dataset 6.6.2. Qualitative Results for the Linear Dataset 6.6.3. Qualitative Results for Stone Quarries Dataset 6.7. Summary 7. Discussions and Conclusions 7.1. Discussions 7.1.1. Assessment of Pretext Methods 7.1.2. Assessment of Downstream Methods 7.1.3. Assessment of Selected Core Deep Learning Architectures 7.1.4. Assessment of Predictions for each Category 7.2. Summary and Outlook List of Figures List of Tables Bibliography Acknowledgements Resume A. Appendix A.1. Self Supervised Learning Pretext A.2. Classification A.3. Areal Dataset A.4. Linear Dataset , Sprache der Kurzfassungen: Englisch, Deutsch

Note: Dissertation, Universität Potsdam, 2021 , Contents List of Figures List of Tables I Preamble 1 Introduction 1.1.1 The Journey from Weather to Climate 1.1.2 The Climate Background 1.1.3 Pollen as Quantitative Indicators of Past Changes 1.2 Overview and Aims of Manuscripts 1.2.1 List of Manuscripts 1.2.2 Short Summaries of the Manuscripts 1.3 Author Contributions to the Manuscripts II Manuscripts 2 Comparing estimation of techniques for temporal Scaling 2.1 Introduction 2.2 Data and Methods 2.2.1 Scaling estimation methods 2.2.2 Evaluation of the estimators 2.2.3 Data 2.3 Results 2.3.1 Effect of Regular and Irregular Sampling 2.3.2 Effect of Time series length 2.3.3 Application to database 2.4 Discussion 2.5 Conclusions 3 Land temperature variability driven by oceans at millennial timescales 4 Variability of surface climate in simulations of past and future 4.1 Introduction 4.2 Data and Method 4.2.1 Model simulations 4.2.2 The Last Glacial Maximum experiment 4.2.3 The mid Holocene experiment (midHolocene) 4.2.4 The warming experiments 1pctCO2 and abrupt4xCO2 4.2.5 Preprocessing of model simulations 4.2.6 Comparisons across the ensemble 4.2.7 Diagnosing variability changes 4.2.8 Changes in precipitation extremes 4.2.9 Timescale-dependence of the variability changes 4.3 Results 4.3.1 Hydrological sensitivity across the ensemble 4.3.2 Changes in local interannual variability 4.3.3 Changes in modes of variability 4.3.4 Circulation patterns underlying extratropical precipitation extremes 4.3.5 Changes in. the spectrum of variability 4.4 Discussion 4.4.1 Changes in climate variability with global mean temperature 4.4.2 Temperature vs. precipitation scaling 4.4.3 Comparison to climate reconstructions and observations 4.4.4 Limitations 4.5 Conclusions 5 Holocene vegetation variability in the Northern Hemisphere 5.1 Introduction 5.2 Data and Methods 5.2.1 Pollen Database 5.2.2 Principal Component Analysis 5.2.3 Timescale-dependent Estimates of Variability 5.2.4 Biome Classification 5.3 Results 5.3.1 General Vegetation Variability Analysis 5.3.2 Comparison of Forested and Open Land Vegetations 5.3.3 Comparison of Broadleaf and Needleleaf Fore ts 5.3.4 Comparison of Temperate and Boreal Coniferous Forests 5.3.5 Comparison of Evergreen and Deciduous Boreal Forests 5.4 Discussion 5.5 Conclusion III Postamble 6 General discussion and conclusion 6.1 Overview 6.2 Timescale-Dependent Estimates of Variability 6.3 Climate and Vegetation Variabilities in the Holocene 6.4 Implications for the 21th Century 6.5 Outlook IV Appendix A Supplementary figures from "Comparing estimation techniques for temporal scaling in paleo-climate timeseries" A.1 Block Average Results A.2 First-Order Correction for the Effect of Interpolation A.3 Change in Bias and Standard Deviation B Methods and supplementary information from "Land temperature variability driven by oceans at millennial timescales" B.1 Methods B.1.1 Reconstructions B.1.2 Significance Testing B.1.3 Testing for Anthropogenic Impacts B.1.4 Instrumental Data B.1.5 Model Data B.1.6 Spectral Estimates B.1.7 Variance Ratios B.1.8 Sub-Decadal Variability Binning B.1.9 Correlation B.1.10 Moran's I B.2 Supplementary Information B.2.1 Tree Ring Data Analysis B.2.2 Energy-Balance Equations B.3 Extended Data Figures C Supplementary figures from "Variability of surface climate in simulations of past and future" D Supplementary figures from "Characterization of holocene vegetation variability in the Northern Hemisphere" Bibliography

Note: Contents 1 Slow Viscous Flow 1.1 Introduction 1.2 Coordinate Systems and the Material Derivative 1.2.1 Eulerian and Lagrangian Coordinates 1.2.2 The Material Derivative 1.3 Mass Conservation 1.4 The Stress Tensor and Momentum Conservation 1.4.1 The Stress Tensor 1.4.2 Momentum Conservation 1.4.3 Rheology 1.4.4 The Navier-Stokes Equations 1.4.5 Stokes Flow 1.5 Boundary Conditions 1.5.1 The No-Slip Condition and the Sliding Law 1.5.2 Dynamic Boundary Conditions 1.5.3 Kinematic Boundary Conditions 1.6 Temperature and Energy Conservation 1.7 Glacier and Ice Sheet Flow 1.8 Examples 1.8.1 Uniform Flow on a Slope 1.8.2 Spreading Flow at an Ice Divide 1.8.3 Small-Amplitude Perturbations 1.9 The Shallow Ice Approximation 1.10 Conclusions and Outlook 1.11 Appendix: Non-dimensionalisation Exercises 2 Thermal Structure 2.1 Temperature Profiles 2.2 Boundary Conditions 2.2.1 The Thermal Near-Surface Wave 2.3 Models: Simple to Complicated 2.4 Basal Conditions 2.4.1 Polythermal Ice 2.5 Modelling Issues 2.5.1 Non-dimensionalisation 2.5.2 Thermomechanical Coupling 2.5.3 Thermal Runaway Exercises 3 Sliding, Drainage and Subglacial Geomorphology 3.1 Introduction 3.2 Sliding Over Hard Beds 3.2.1 Weertman Sliding 3.2.2 Nye-Kamb Theory 3.2.3 Sub-temperate Sliding 3.2.4 Nonlinear Sliding Laws 3.2.5 Cavitation 3.2.6 Comparison with Experiment 3.3 Subglacial Drainage Theory 3.3.1 Weertman Films 3.3.2 Röthlisberger Channels (or ‘R-Channels’) 3.3.3 Jökulhlaups 3.3.4 Subglacial Lakes 3.3.5 Linked Cavities 3.3.6 Drainage Transitions and Glacier Surges 3.3.7 Ongoing Developments 3.4 Basal Processes and Geomorphology 3.4.1 Soft Glacier Beds 3.4.2 Drainage Over Till 3.4.3 Geomorphological Processes Exercises 4 Tidewater Glaciers 4.1 Introduction 4.2 Calving 4.3 Tidewater Glacier Dynamics 4.3.1 Tidewater Glacier Retreat and Instability 4.3.2 Tidewater Glacier Advance 4.3.3 Flow Variability of Tidewater Glaciers 4.4 The Link to Climate: Triggers for Retreat 4.4.1 Ice Shelf Collapse and Backstress 4.4.2 Grounded Calving Fronts 4.5 Outlook 5 Interaction of Ice Shelves with the Ocean 5.1 Introduction 5.2 Impact of Melting Ice on the Ocean 5.3 Processes at the Ice-Ocean Interface 5.4 Buoyancy-Driven Flow on Geophysical Scales 5.5 Sensitivity to Ocean Temperature 5.6 Impact of Meltwater Outflow at the Grounding Line 5.7 Fundamentals of the Three-Dimensional Ocean Circulation 5.8 Some Properties and Limitations of the Geostrophic Equations 5.9 Effects of Stratification 5.10 Three-Dimensional Circulation in Sub-Ice-Shelf Cavities Exercises 6 Polar Meteorology 6.1 Introduction 6.2 Shortwave and Longwave Radiation 6.3 Radiation Climate at the Top of the Atmosphere 6.4 Large Scale Circulation 6.5 Surface Energy Balance 6.5.1 Shortwave Radiation 6.5.2 Surface Albedo 6.5.3 Longwave Radiation 6.5.4 Turbulent Fluxes 6.6 Temperature Inversion and Katabatic Winds 6.6.1 Surface Temperature Inversion and Deficit 6.6.2 Katabatic Winds 6.7 Precipitation 6.8 Notes and References Exercises 7 Mass Balance 7.1 Introduction 7.2 Definitions 7.3 Methods 7.3.1 In Situ Observations 7.3.2 Satellite/Airborne Altimetry 7.3.3 Satellite Gravimetry 7.3.4 Mass Budget Method 7.4 Valley Glaciers and Ice Caps 7.4.1 In Situ Observations 7.4.2 Modelling 7.4.3 Dynamical Response 7.4.4 Remote Sensing 7.5 Antarctic Ice Sheet 7.5.1 Spatial SSMB Variability 7.5.2 Blue Ice Areas 7.5.3 Temporal SSMB Variability 7.6 Greenland Ice Sheet 7.6.1 Spatial SSMB Variability 7.6.2 Temporal SSMB Variability 7.6.3 Role of the Liquid Water Balance 8 Numerical Modelling of Ice Sheets, Streams, and Shelves 8.1 Introduction 8.2 Ice Flow Equations 8.2.1 The Shallow Ice Approximation 8.2.2 Analogy with the Heat Equation 8.3 Finite Difference Numerics 8.3.1 Explicit Scheme for the Heat Equation 8.3.2 A First Implemented Scheme 8.3.3 Stability Criteria and Adaptive Time Stepping 8.3.4 Implicit Schemes 8.3.5 Numerical Solution of Diffusion Equations 8.4 Numerically Solving the SIA 8.5 Exact Solutions and Verification 8.5.1 Exact Solution of the Heat Equation 8.5.2 Halfar’s Exact Similarity Solution to the SIA 8.5.3 Using Halfar’s Solution 8.5.4 A Test of Robustness 8.6 Applying Our Numerical Ice Sheet Model 8.7 Shelves and Streams 8.7.1 The Shallow Shelf Approximation (SSA) 8.7.2 Numerical Solution of the SSA 8.7.3 Numerics of the Linear Boundary Value Problem 8.7.4 Solving the Stress Balance for an Ice Shelf 8.7.5 Realistic Ice Shelf Modelling 8.8 A Summary of Numerical Ice Flow Modelling 8.9 Notes Exercises 9 Least-Squares Data Inversion in Glaciology 9.1 Preamble 9.2 Introduction 9.3 The Roots of GPS in Glaciology 9.4 Introduction to GPS 9.4.1 History 9.4.2 Coarse Acquisition (C/A) Code 9.5 The Equations of Pseudorange 9.6 Least-Squares Solution of an Overdetermined System of Linear Equations 9.7 Observational Techniques to Improve GPS Accuracy 9.7.1 The Ionosphere-Free Combination 9.7.2 Carrier-Phase Determined Range and Integer Wavelength Ambiguity 9.7.3 Resolving Range Ambiguity by Phase Tracking 9.7.4 Differential GPS Exercises 10 Analytical Models of Ice Sheets and Ice Shelves 10.1 Introduction 10.2 Perfectly-Plastic Ice Sheet Model 10.3 The Height–Mass Balance Feedback 10.4 Ice-Sheet Profile for Plane Shear with Glen’s Law 10.5 Ice Shelves Exercise 11 Firn 11.1 Introduction 11.2 Firn Densification 11.2.1 Mechanisms of Firn Densification 11.2.2 Firn Densification Models 11.2.3 Firn Layering and Microstructure 11.3 Applications of Firn Models 11.3.1 Ice Sheet Surface Mass Balance from Altimetry 11.3.2 Delta Age Calculations in Deep Ice Cores 11.4 Summary and Conclusions 12 Ice Cores: Archive of the Climate System 12.1 Introduction 12.2 Dating Ice Cores 12.3 Stable Water Isotopes 12.3.1 Basics and Nomenclature 12.3.2 The Isotope Proxy Thermometer 12.3.3 Examples of Isotope Records 12.3.4 Isotope Diffusion in Firn and Ice 12.3.5 Diffusion Thermometry 12.4 Aerosols in Ice 12.4.1 Introduction and Origin of Aerosols in Ice 12.4.2 Aerosol Sources and Transport 12.4.3 Post-depositional Modification 12.4.4 Seasonal Cycles in Aerosol and Particle Constituents in Ice 12.4.5 The Volcanic Signal in Ice and Its Use for Chronological Control 12.4.6 Marine Biogenic MSA and Sea Salt as Sea-Ice Proxies 12.4.7 The Record of Anthropogenic Pollution 12.4.8 Long Aerosol Records from Greenland and Antarctica 12.4.9 Electrical Properties of Ice and Their Relationship to Chemistry 12.5 Gases Enclosed in Ice 12.5.1 Firn Gas and Gas Occlusion 12.5.2 Trace Gases 12.6 Timing of Climate Events Exercises 13 Satellite Remote Sensing of Glaciers and Ice Sheets 13.1 Introduction 13.2 Optical Sensors and Applications 13.2.1 Sensors and Satellites 13.2.2 Applications 13.3 SAR Methods and Applications 13.3.1 Radar Signal Interaction with Snow and Ice 13.3.2 SAR Sensor and Image Characteristics 13.3.3 InSAR Measurement Principles and Applications 13.4 Satellite Altimetry 13.4.1 Altimetry Missions 13.4.2 Measuring Elevation Change 14 Geophysics 14.1 Geophysical Methods: Overview 14.2 Passive Methods 14.2.1 Gravimetry 14.2.2 Magnetics 14.2.3 Seismology 14.3 Active Methods: Basics 14.3.1 Propagation Properties and Reflection Origin 14.3.2 Seismic System Set-Up 14.3.3 Radar System Set-Up 14.4 Data Acquisition and Processing 14.5 Seismic Applications in Ice 14.5.1 Ice Thickness and Basal Topography 14.5.2 Subglacial Structure and Properties 14.5.3 Rheological and Other Englacial Properties 14.6 Radar Applications in Ice 14.6.1 Internal Layer Architecture and Ice Dynamics 14.6.2 Subglacial Conditions 14.6.3 Englacial Conditions 14.7 Notes and References 14.7.1 Further Reading 14.7.2 Gravimetry 14.7.3 General Wave Equation and Solution 14.7.4 Seismic Waves 14.7.5 Electromagnetic Waves Exercises 15 Glacial Isostatic Adjustment 15.1 Introduction 15.2 Earth Response to Loading 15.2.1 Rheology of the Earth 15.2.2 Building an Earth Model 15.2.3 Earth Models Used in Glaciology and Glacial Isostatic Adjustment 15.3 The Cryosphere and Sea Level 15.3.1 Factors Affecting Sea-Level Change 15.3.2 Eu

Note: Dissertation, Fakultät für Bauingenieurwesen und Geodäsie der Gottfried Wilhelm Leibniz Universität Hannover, 2021 , 1 Introduction 1.1 Problem Statement 1.2 Contributions 1.3 Thesis Outline 2 Basics 2.1 Dense Stereo Matching 2.1.1 Terminology and Practical Simplifications 2.1.2 Taxonomy of the Matching Process 2.1.3 Challenges and Common Assumptions 2.2 Uncertainty Quantification 2.3 Deep Learning 2.3.1 Convolutional Neural Networks 2.3.2 Bayesian Neural Networks 3 Related Work 3.1 Dense Stereo Matching 3.2 Aleatoric Uncertainty Estimation 3.3 Epistemic Uncertainty Estimation 3.4 Discussion 4 Uncertainty Estimation for Dense Stereo Matching - A New Method 4.1 Overview 4.2 Aleatoric Uncertainty Estimation 4.2.1 CNN-based Cost Volume Analysis 4.2.2 Uncertainty Models 4.3 Epistemic Uncertainty Estimation 4.3.1 Functional Model 4.3.2 Stochastic Model 4.4 Joint Uncertainty Estimation 4.5 Discussion 5 Experimental Setup 5.1 Objectives 5.2 Datasets 5.3 Training and Hyper-parameter Settings 5.3.1 General Remarks 5.3.2 CVA-Net 5.3.3 Probabilistic GC-Net 5.3.4 Combined Approach 5.4 Evaluation Strategy andCriteria 5.4.1 Disparity Error Metrics 5.4.2 Confidence Error Metric 5.4.3 Uncertainty Error Metric 5.4.4 Region Masks 5.4.5 Monte Carlo Sampling 6 Results and Discussion 6.1 CVA-Net Architecture 6.2 Aleatoric Uncertainty Models 6.3 Dense Stereo Matching using a Bayesian Neural Network 6.3.1 Comparison to the Deterministic Baseline 6.3.2 On the Relevance of Aleatoric and Epistemic Uncertainty 6.3.3 The Kullback-Leibler Divergence and the Mode Collapse Problem 6.4 Discussion 7 Conclusions and Outlook Bibliography Acknowledgment

Note: Contents Dedication Bojar, A.-V., Pelc, A. and Lécuyer, C. / Stable isotope studies of the water cycle and terrestrial environments: introduction The water cycle Lécuyer, C., Bojar, A.-V., Daux, V. and Legendre, S. / Geographic variations in the slope of the δ2H–δ18O meteoric water line over Europe: a record of increasing continentality Nagavciuc, V., Bădăluță , C.-A. and Ionita, M. / The influence of the Carpathian Mountains on the variability of stable isotopes in precipitation and the relationship with large-scale atmospheric circulation Daux, V., Minster, B., Cauquoin, A., Jossoud, O., Werner, M. and Landais, A. / Oxygen and hydrogen isotopic composition of tap waters in France Marche, B. M., Rashid, H. and Parkinson, D.-R. / Correlation of seasonal precipitation isotopic profile with the modern climatological data: a case study from the western Newfoundland region of Canada Varlam, C., Duliu, O. G., Ionete, R. E. and Costinel, D. / Time series analysis of the δ2 H, δ18 O and dexcess values in correlation with monthly temperature, relative humidity and precipitation in Râmnicu Vâlcea, Romania: 2012–2018 Bojar, A.-V., Chmiel, S., Bojar, H.-P., Varlam, C. and Barbu, V. / Hydrological system in Quaternary clastic deposits, Mehedinţi County, Romania: isotope composition, chemistry and radiocarbon dating Bădăluț ă, C. A., Mihă ilă, D., Mihă ilă, D., Bădăluț ă, G. and Bistricean, P. I. 7 Stable isotopic and geochemical characterization of precipitation and riverine waters in the Eastern Carpathians and links with large-scale drivers Joshi, S. K., Rai, S. P. and Sinha, R. / Understanding groundwater recharge processes in the Sutlej-Yamuna plain in NW India using an isotopic approach Sironić, A., Bronić, I. K., Horvatinčić, N., Barešić, J., Borković, D., Vurnek, M. and Mikelić, I. L. / Carbon isotopes in dissolved inorganic carbon as tracers of carbon sources in karst waters of the Plitvice Lakes, Croatia Papp, D. C., Baciu, C., Turunen, K. and Kittilä, A. / Applicability of selected stable isotopes to study the hydrodynamics and contaminant transport within mining areas in Romania and Finland Terrestrial environments Bojar, A.-V., Lécuyer, C., Duliu, O. G., Bojar, H.-P. and Fourel, F. / Isotopic and time series investigations of recent stalagmites (1945–2018), Schlossberg tunnels, Graz, Austria: implications for climate change in Central Europe Cleary, D. M. and Onac, B. P. / Using ratios in cave guano to assess past environmental changes Tabor, N. J., Jahren, A. H., Wyman, L., Feseha, M., Todd, L. and Kappleman, J. / Stable isotope geochemistry of the modern Shinfa River, northwestern Ethiopian lowlands: a potential model for interpreting ancient environments of the Middle Stone Age Bayat, O., Karimi, A. and Amundson, R. / Stable isotope geochemistry of pedogenic carbonates in calcareous materials, Iran: a review and synthesis Dias Veras, J. D., de Souza Neto, J. A., Sial, A. N., Ferreira, V. P. and Neumann, V. H. de M. L. / Stable isotope and chemical stratigraphy of the Eocene Tambaba Formation: correlations with the Paleocene–Eocene Thermal Maximum event Yamamura, D., Suarez, C. A., Titus, A. L., Manlove, H. M. and Jackson, T. 7 Multiproxy approaches to investigating palaeoecology and palaeohydrology in the Upper Cretaceous Kaiparowits Formation, USA Suarez, M. B., Knight, J. A., Godet, A., Ludvigson, G. A., Snell, K. E., Murphy, L. and Kirkland, J. I. / Multiproxy strategy for determining palaeoclimate parameters in the Ruby Ranch Member of the Cedar Mountain Formation Suarez, C. A., Frucci, M. N., Tompkins, T. B. and Suarez, M. B. / Quantification of a North American greenhouse hydrological cycle: using oxygen isotopic composition of phosphate from Early Cretaceous (Aptian–Albian) turtles Index

Note: Contents Abstract Zusammenfassung List of Figures List of Tables Abbreviation Contents 1 Introduction 1.1 Motivation 1.2 Proposal and content 2 State of art in terrestrial laser scanning and finite element analysis 2.1 General surface measurements and TLS 2.1.1 Surface measurement 2.1.2 Geometric measurements with TLS and its technical fundamentals 2.2 FEA computations 2.2.1 FEA 2.2.2 FEA computation and the description of the boundary domain 2.3 TLS application in FEA 2.3.1 FEA parameter calibration with TLS 2.3.2 FEA geometric boundary modeling with TLS 2.3.3 Benefits of combination between TLS and FEA 3 Finite element analysis parametric geometric modeling and calibration based on terrestrial laser scanning 3.1 Fundamentals of polynomial and B-spline fitting 3.1.1 Polynomial fitting 3.1.2 B-spline fitting 3.2 Other parametric methods in fitting point clouds 3.3 Analysis and comparison between polynomial and B-spline approximations 3.4 Implementation of the calibration cases 3.5 Validation based on deformation analysis 3.5.1 General methods in deformation computation and analysis for TLS 3.5.2 Case implementation 4 Sequential calibration of finite element analysis results with terrestrial laser scanning reference based on deep learning 4.1 Employment of DL in FEA 4.1.1 Direct outputs corresponding to inputs by training neural networks 4.1.2 Material model 4.1.3 Other problems 4.1.4 Summary and analysis 4.2 DL sequential prediction and its potential in FEA 4.3 LSTM methods based on sequential prediction 4.3.1 Challenges and advanced variant models of LSTM 4.3.2 Effects of activation functions in convolutional LSTM 4.4 Sequential prediction and calibration of FEA results with a TLS reference based on convolutional LSTM 5 Conclusions and outlook Contributions of authors Paper 1 Paper 2 Paper 3 Paper 4 Bibliography Curriculum Vitae Acknowledgment

Note: Erscheint alle 2 Jahre , Text in deutscher und englischer Sprache

Note: The Economic-Legal System and the Role of Property Rights: An Introduction ; 1 Foundation Stones: Politically-Based Versus Judge-Made Law ; Efficiency ; Two Basic Propositions ; Two Major Theorems on Property Rights ; 2 Society's Machinery: Coordination and Constitutions ; Markets and Firms ; Political Processes ; 3 Property, Breach of Contract, Tort, Crime: Formalized Property Rights ; Injunctions ; Damages or Punishment? ; Negligence: The Simplest Case ; Joint Responsibility ; Intent, Strict Liability, Insurance ; The Stringency of Sanctions ; The Behavior of Disputant Parties and Courts ; 4 Contracts, Companies, Regulation: Contracts: Problems and Solutions ; The Contractual and Legal Structure of Firms ; Limits of Freedom of Contract ; 5 Epilogue: Conclusions and Final Comments

Note: Kaiserslautern, Technische Universität, Dissertation, 2003 (Nicht für den Austausch)

Note: Contents: Preface to the eighth edition. - Acknowledgements. - 1 INTRODUCTION AND HISTORY OF METEOROLOGY AND CLIMATOLOGY. - A The atmosphere. - B Solar energy. - C Global circulation. - D Climatology. - E Mid-latitude disturbances. - F Tropical weather. - G Palaeoclimates. - H The global climate system. - 2 ATMOSPHERIC COMPOSITION, MASS AND STRUCTURE. - A Composition of the atmosphere. - 1 Primary gases. - 2 Greenhouse gases. - 3 Reactive gas species. - 4 Aerosols. - 5 Variations with height. - 6 Variations with latitude and season. - 7 Variations with time. - B Mass of the atmosphere. - 1 Total pressure. - 2 Vapour pressure C The layering of the atmosphere. - 1 Troposphere. - 2 Stratosphere. - 3 Mesosphere. - 4 Thermosphere. - 5 Exosphere and magnetosphere. - 3 SOLAR RADIATION AND THE GLOBAL ENERGY BUDGET. - A Solar radiation. - 1 Solar output. - 2 Distance from the sun. - 3 Altitude of the sun. - 4 Length of day. - B Surface receipt of solar radiation and its effects. - 1 Energy transfer within the earth-atmosphere system. - 2 Effect of the atmosphere. - 3 Effect of cloud cover. - 4 Effect of latitude. - 5 Effect ofland and sea. - 6 Effect of elevation and aspect. - 7 Variation of free-air temperature with height. - C Terrestrial infra-red radiation and the greenhouse effect. - D Heat budget of the earth. - E Atmospheric energy and horizontal heat transport. - 1 The horizontal transport of heat. - 2 Spatial pattern of the heat budget components. - 4 ATMOSPHERIC MOISTURE BUDGET. - A The global hydrological cycle. - B Humidity. - 1 Moisture content. - 2 Moisture transport. - C Evaporation. - D Condensation. - E Precipitation characteristics and measurement. - 1 Forms of precipitation. - 2 Precipitation characteristics. - a Rainfall intensity. - b Areal extent of a rainstorm. - c Frequency of rainstorms. - 3 The world pattern of precipitation. - 4 Regional variations in the altitudinal maximum of precipitation. - 5 Drought. - 5 ATMOSPHERIC INSTABILITY, CLOUD FORMATION AND PRECIPITATION PROCESSES. - A Adiabatic temperature changes. - B Condensation level. - C Air stability and instability. - D Cloud formation. - 1 Condensation nuclei. - 2 Cloud types. - 3 Global cloud cover. - E Formation of precipitation. - 1 Bergeron-Findeisen theory. - 2 Coalescence theories. - 3 Solid precipitation. - F Precipitation types. - 1 'Convective type' precipitation. - 2 'Cyclonic type' precipitation. - 3 Orographic precipitation. - G Thunderstorms. - 1 Development. - 2 Cloud electrification and lightning. - 6 ATMOSPHERIC MOTION: PRINCIPLES. - A Laws of horizontal motion. - 1 The pressure-gradient force. - 2 The earth's rotational deflective (Coriolis) force. - 3 The geostrophic wind. - 4 The centripetal acceleration. - 5 Frictional forces and the planetary boundary layer. - B Divergence, vertical motion and vorticity. - 1 Divergence. - 2 Vertical motion. - 3 Vorticity. - C Local winds. - 1 Mountain and valley winds. - 2 Land and sea breezes. - 3 Winds due to topographic barriers. - 7 PLANETARY-SCALE MOTIONS IN THE ATMOSPHERE AND OCEAN. - A Variation of pressure and wind velocity with height. - 1 The vertical variation of pressure systems. - 2 Mean upper-air patterns. - 3 Upper wind conditions. - 4 Surface pressure conditions. - B The global wind belts. - 1 The trade winds. - 2 The equatorial westerlies. - 3 The mid-latitude (Ferrel) westerlies. - 4 The polar easterlies. - C The general circulation. - 1 Circulations in the vertical and horizontal planes. - 2 Variations in the circulation of the northern hemisphere. - a Zonal index variations. - b North Atlantic Oscillation. - D Ocean structure and circulation. - 1 Above the thermocline. - a Vertical. - b Horizontal. - 2 Deep ocean water interactions. - a Upwelling. - b Deep ocean circulation. - 3 The oceans and atmospheric regulation. - 8 NUMERICAL MODELS OF THE GENERAL CIRCULATION, CLIMATE AND WEATHER PREDICTION / T. N. Chase and R. G. Barry. - A Fundamentals of the GCM. - B Model simulations. - 1 GCMs. - 2 Simpler models. - 3 Regional models. - C Data sources for forecasting. - D Numerical weather prediction. - 1 Short- and medium-range forecasting. - 2 'Nowcasting'. - 3 Long-range outlooks. - 9 MID-LATITUDE SYNOPTIC AND MESOSCALE SYSTEMS. - A The airmass concept. - B Nature of the source area. - 1 Cold airmasses. - 2 Warm airmasses. - C Airmass modification. - 1 Mechanisms of modification. - a Thermodynamic changes. - b Dynamic changes. - 2 The results of modification: secondary airmasses. - a Cold air. - b Warm air. - 3 The age of the airmass. - D Frontogenesis. - 1 Frontal waves. - 2 The frontal-wave depression. - E Frontal characteristics. - 1 The warm front. - 2 The cold front. - 3 The occlusion. - 4 Frontal-wave families. - F Zones of wave development and frontogenesis. - G Surface/upper-air relationships and the formation of frontal cyclones. - H Non-frontal depressions. - 1 The lee cyclone. - 2 The thermal low. - 3 Polar air depressions. - 4 The cold low. - I Mesoscale convective systems. - 10 WEATHER AND CLIMATE IN MIDDLE AND HIGH LATITUDES. - A Europe. - 1 Pressure and wind conditions. - 2 Oceanicity and continentality. - 3 British airflow patterns and their climatic characteristics. - 4 Singularities and natural seasons. - 5 Synoptic anomalies. - 6 Topographic effects. - B North America. - 1 Pressure systems. - 2 The temperate west coast and Cordillera. - 3 Interior and eastern North America. - a Continental and oceanic influences. - b Warm and cold spells. - c Precipitation and the moisture balance. - C The subtropical margins. - 1 The semi-arid southwestern United States. - 2 The interior southeastern United States. - 3 The Mediterranean. - 4 North Africa. - 5 Australasia. - D High latitudes. - 1 The southern westerlies. - 2 The sub-Arctic. - 3 The polar regions. - a The Arctic. - b Antarctica. - 11 TROPICAL WEATHER AND CLIMATE. - A The intertropical convergence. - B Tropical disturbances. - 1 Wave disturbances. - 2 Cyclones. - a Hurricanes and typhoons. - b Other tropical disturbances. - 3 Tropical cloud clusters. - C The Asian monsoon. - 1 Winter. - 2 Spring. - 3 Early summer. - 4 Summer. - 5 Autumn. - D East Asian and Australian summer monsoons. - E Central and southern Africa. - 1 The African monsoon. - 2 Southern Africa. - F Amazonia. - G El Niño-Southern Oscillation (ENSO) events. - 1 The Pacific Ocean. - 2 Teleconnections. - H Other sources of climatic variations in the tropics. - 1 Cool ocean currents. - 2 Topographic effects. - 3 Diurnal variations. - I Forecasting tropical weather. - 1 Short- and extended-range forecasts. - 2 Long-range forecasts. - 12 BOUNDARY LAYER CLIMATES. - A Surface energy budgets. - B Non-vegetated natural surfaces. - 1 Rock and sand. - 2 Water. - 3 Snow and ice C Vegetated surfaces. - 1 Short green crops. - 2 Forests. - a Modification of energy transfers. - b Modification of airflow. - c Modification of the humidity environment. - d Modification of the thermal environment. - D Urban surfaces. - 1 Modification of atmospheric composition. - a Aerosols. - b Gases. - c Pollution distribution and impacts. - 2 Modification of the heat budget. - a Atmospheric composition. - b Urban surfaces. - c Human heat production. - d Heat islands. - 3 Modification of surface characteristics. - a Airflow. - b Moisture. - 4 Tropical urban climates. - 13 CLIMATE CHANGE. - A General considerations. - B Climate forcings and feedbacks. - 1 External forcing. - 2 Short-term forcing and feedback. - C The climatic record. - 1 The geological record. - 2 Late glacial and post-glacial conditions. - 3 The past 1000 years. - D Possible causes of recent climatic change. - 1 Circulation changes. - 2 Energy budgets. - 3 Anthropogenic factors. - E Model s

Note: Contents: 1 Background. - 2 Processing overview. - 2.1 AAPP. - 2.2 BUFR and CMA. - 2.3 Cloud mask and thinning in HIRLAM 3D-VAR. - 2.4 Radiative transfer calculations. - 2.5 Data selection. - 3 Bias correction and error statistics. - 3.1 The need for bias correction. - 3.2 Bias correction method. - 3.3 Background errors in observation space. - 3.4 Estimation of observation error covariance statistics. - 3.4.1 Rotated channels. - 3.4.2 Estimation from analysis departures (DNMI). - 3.4.3 Non-diagonal cost contributions. - 3.4.4 Approach using comparison with background error (SMHI). - 4 Impact studies. - 4.1 Overview. - 4.2 The May 2001 impact study at DNMI. - 4.3 December 1999 SMHI experiment. - 4.3.1 Data coverage and model area. - 4.3.2 Verification. - 4.3.3 Results. - 4.3.4 The "French storm". - 4.4 December 2001 NOAA 16 impact study at DMI. - 4.5 January 2002 NOAA 16 impact study at DMI. - 5 Ongoing and future work. - 5.1 Overview. - 5.2 Use of observations over ice. - 5.3 Moisture channels. - 5.4 Future sensors. - 6 Conclusions and outlook for the future. - Acknowledgment. - References.