ALBERT

Anmerkung: Chapter 1. Introduction: An Overview of Crisis Communication -- Part I. The Role of Communication in Fostering Resilience or Fomenting Resistance -- Chapter 2. Revisiting Crisis Communication and Integrating Social Media -- Chapter 3. Polluted Discourse:  Communication and Myths in a Climate of Denial -- Chapter 4. Public Perceptions of Global Warming: Understanding Survey Differences -- Chapter 5. Building Interfaces that Work: A Multi-Stakeholder Approach to Air Pollution and Climate Change Mitigation -- Part II. Before Disaster: Prediction, Preparation and Crisis Communication -- Chapter 6. Fostering Resilience in the Face of an Uncertain Future: Using Scenarios Planning to Communicate Climate Change Risks and Collaboratively Develop Adaptation Strategies -- Chapter 7. Barriers to Using Climate Information: Challenges in Communicating Probabilistic Forecasts to Decision Makers -- Chapter 8. Modeling Climate-Sensitive Disease Risk: A Decision Support Tool for Public Health Services -- Chapter 9. Shallow Landslide Hazard Mapping for Davao Oriental, Philippines Using a Deterministic GIS Model -- Part III. Mitigating Circumstances: Communicating Through Change, Uncertainty, Disaster and Recovery -- Chapter 10. Comparative Analysis of Virtual Relief Networks and Communication Channels During Disaster Recovery After a Major Flood in Galena, Alaska, Spring 2013 -- Chapter 11. Development of the Stakeholders’ Engagement Plan as a Mining Social Responsibility Practice -- Chapter 12. Controlling Environmental Crisis Messages in Uncontrollable Media Environments: The 2011 Case of Blue-Green Algae on Grand Lake O’ the Cherokees, OK -- Chapter 13. Characteristics of Extreme Monsoon Floods and Local Land Use in the Lower Mekong Basin, Cambodia -- Chapter 14. The Value of Earth Observations: Methods and Findings on the Value of Landsat  Imagery -- Part IV. Learning Forward: Advancing Climate Change Science Among Diverse Audiences -- Chapter 15. Carbon Offsets in California: Science in the Policy Development Process -- Chapter 16. Fostering Educator Resilience: Engaging the Educational Community to Address the Natural Hazards of Climate Change -- Chapter 17. Communicating Uncertainty: A Challenge for Science Communication -- Chapter 18. Science Diplomacy in the Geosciences -- Chapter 19. Stormy Seas, Rising Risks: Assessing Undisclosed Risk from Sea Level Risk and Storm Surge at Coastal U.S. Oil Refineries..

Anmerkung: Contents: 1 Computing with Formulas. - 1.1 The First Programming Encounter: a Formula. - 1.1.1 Using a Program as a Calculator. - 1.1.2 About Programs and Programming. - 1.1.3 Tools for Writing Programs. - 1.1.4 Writing and Running Your First Python Program. - 1.1.5 Warning About Typing Program Text. - 1.1.6 Verifying the Result. - 1.1.7 Using Variables. - 1.1.8 Names of Variables. - 1.1.9 Reserved Words in Python. - 1.1.10 Comments. - 1.1.11 Formatting Text and Numbers. - 1.2 Computer Science Glossary. - 1.3 Another Formula: Celsius-Fahrenheit Conversion. - 1.3.1 Potential Error: Integer Division. - 1.3.2 Objects in Python. - 1.3.3 Avoiding Integer Division. - 1.3.4 Arithmetic Operators and Precedence. - 1.4 Evaluating Standard Mathematical Functions. - 1.4.1 Example: Using the Square Root Function. - 1.4.2 Example: Computing with sinh x. - 1.4.3 A First Glimpse of Rounding Errors. - 1.5 Interactive Computing. - 1.5.1 Using the Python Shell. - 1.5.2 Type Conversion. - 1.5.3 IPython. - 1.6 Complex Numbers. - 1.6.1 Complex Arithmetics in Python. - 1.6.2 Complex Functions in Python. - 1.6.3 Unified Treatment of Complex and Real Functions. - 1.7 Symbolic Computing. - 1.7.1 Basic Differentiation and Integration. - 1.7.2 Equation Solving. - 1.7.3 Taylor Series and More. - 1.8 Summary. - 1.8.1 Chapter Topics. - 1.8.2 Example: Trajectory of a Ball. - 1.8.3 About Typesetting Conventions in This Book. - 1.9 Exercises. - 2 Loops and Lists. - 2.1 While Loops. - 2.1.1 A Naive Solution. - 2.1.2 While Loops. - 2.1.3 Boolean Expressions. - 2.1.4 Loop Implementation of a Sum. - 2.2 Lists. - 2.2.1 Basic List Operations. - 2.2.2 For Loops. - 2.3 Alternative Implementations with Lists and Loops. - 2.3.1 While Loop Implementation of a for Loop. - 2.3.2 The Range Construction. - 2.3.3 For Loops with List Indices. - 2.3.4 Changing List Elements. - 2.3.5 List Comprehension. - 2.3.6 Traversing Multiple Lists Simultaneously. - 2.4 Nested Lists. - 2.4.1 A table as a List of Rows or Columns. - 2.4.2 Printing Objects. - 2.4.3 Extracting Sublists. - 2.4.4 Traversing Nested Lists. - 2.5 Tuples. - 2.6 Summary. - 2.6.1 Chapter Topics. - 2.6.2 Example: Analyzing List Data. - 2.6.3 How to Find More Python Information. - 2.7 Exercises. - 3 Functions and Branching. - 3.1 Functions. - 3.1.1 Mathematical Functions as Python Functions. - 3.1.2 Understanding the Program Flow. - 3.1.3 Local and Global Variables. - 3.1.4 Multiple Arguments. - 3.1.5 Function Argument or Global Variable?. - 3.1.6 Beyond Mathematical Functions. - 3.1.7 Multiple Return Values. - 3.1.8 Computing Sums. - 3.1.9 Functions with No Return Values. - 3.1.10 Keyword Arguments. - 3.1.11 Doc Strings. - 3.1.12 Functions as Arguments to Functions. - 3.1.13 The Main Program. - 3.1.14 Lambda Functions. - 3.2 Branching. - 3.2.1 If-else Blocks. - 3.2.2 Inline if Tests. - 3.3 Mixing Loops, Branching, and Functions in Bioinformatics Examples. - 3.3.1 Counting Letters in DNA Strings. - 3.3.2 Efficiency Assessment. - 3.3.3 Verifying the Implementations. - 3.4 Summary. - 3.4.1 Chapter Topics. - 3.4.2 Example: Numerical Integration. - 3.5 Exercises. - 4 User Input and Error Handling. - 4.1 Asking Questions and Reading Answers. - 4.1.1 Reading Keyboard Input. - 4.2 Reading from the Command Line. - 4.2.1 Providing Input on the Command Line. - 4.2.2 A Variable Number of Command-Line Arguments. - 4.2.3 More on Command-Line Arguments. - 4.3 Turning User Text into Live Objects. - 4.3.1 The Magic Eval Function. - 4.3.2 The Magic Exec Function. - 4.3.3 Turning String Expressions into Functions. - 4.4 Option-Value Pairs on the Command Line. - 4.4.1 Basic Usage of the Argparse Module. - 4.4.2 Mathematical Expressions as Values. - 4.5 Reading Data from File. - 4.5.1 Reading a File Line by Line. - 4.5.2 Alternative Ways of Reading a File. - 4.5.3 Reading a Mixture of Text and Numbers. - 4.6 Writing Data to File. - 4.6.1 Example: Writing a Table to File. - 4.6.2 Standard Input and Output as File Objects. - 4.6.3 What is a File, Really?. - 4.7 Handling Errors. - 4.7.1 Exception Handling. - 4.7.2 Raising Exceptions. - 4.8 A Glimpse of Graphical User Interfaces. - 4.9 Making Modules. - 4.9.1 Example: Interest on Bank Deposits. - 4.9.2 Collecting Functions in a Module File. - 4.9.3 Test Block. - 4.9.4 Verification of the Module Code. - 4.9.5 Getting Input Data. - 4.9.6 Doc Strings in Modules. - 4.9.7 Using Modules. - 4.9.8 Distributing Modules. - 4.9.9 Making Software Available on the Internet. - 4.10 Making Code for Python 2 and 3. - 4.10.1 Basic Differences Between Python 2 and 3. - 4.10.2 Turning Python 2 Code into Python 3 Code. - 4.11 Summary. - 4.11.1 Chapter Topics. - 4.11.2 Example: Bisection Root Finding. - 4.12 Exercises. - 5 Array Computing and Curve Plotting. - 5.1 Vectors. - 5.1.1 The Vector Concept. - 5.1.2 Mathematical Operations on Vectors. - 5.1.3 Vector Arithmetics and Vector Functions. - 5.2 Arrays in Python Programs. - 5.2.1 Using Lists for Collecting Function Data. - 5.2.2 Basics of Numerical Python Arrays. - 5.2.3 Computing Coordinates and Function Values. - 5.2.4 Vectorization. - 5.3 Curve Plotting. - 5.3.1 MATLAB-Style Plotting with Matplotlib. - 5.3.2 Matplotlib; Pyplot Prefix. - 5.3.3 SciTools and Easyviz. - 5.3.4 Making Animations. - 5.3.5 Making Videos. - 5.3.6 Curve Plots in Pure Text. - 5.4 Plotting Difficulties. - 5.4.1 Piecewisely Defined Functions. - 5.4.2 Rapidly Varying Functions. - 5.5 More Advanced Vectorization of Functions. - 5.5.1 Vectorization of StringFunction Objects. - 5.5.2 Vectorization of the Heaviside Function. - 5.5.3 Vectorization of a Hat Function. - 5.6 More on Numerical Python Arrays. - 5.6.1 Copying Arrays. - 5.6.2 In-Place Arithmetics. - 5.6.3 Allocating Arrays. - 5.6.4 Generalized Indexing. - 5.6.5 Testing for the Array Type. - 5.6.6 Compact Syntax for Array Generation. - 5.6.7 Shape Manipulation. - 5.7 High-Performance Computing with Arrays. - 5.7.1 Scalar Implementation. - 5.7.2 Vectorized Implementation. - 5.7.3 Memory-Saving Implementation. - 5.7.4 Analysis of Memory Usage. - 5.7.5 Analysis of the CPU Time. - 5.8 Higher-Dimensional Arrays. - 5.8.1 Matrices and Arrays. - 5.8.2 Two-Dimensional Numerical Python Arrays. - 5.8.3 Array Computing. - 5.8.4 Matrix Objects. - 5.9 Some Common Linear Algebra Operations. - 5.9.1 Inverse, Determinant, and Eigenvalues. - 5.9.2 Products. - 5.9.3 Norms. - 5.9.4 Sum and Extreme Values. - 5.9.5 Indexing. - 5.9.6 Transpose and Upper/Lower Triangular Parts. - 5.9.7 Solving Linear Systems. - 5.9.8 Matrix Row and Column Operations. - 5.9.9 Computing the Rank of a Matrix. - 5.9.10 Symbolic Linear Algebra. - 5.10 Plotting of Scalar and Vector Fields. - 5.10.1 Installation. - 5.10.2 Surface Plots. - 5.10.3 Parameterized Curve. - 5.10.4 Contour Lines. - 5.10.5 The Gradient Vector Field. - 5.11 Matplotlib. - 5.11.1 Surface Plots. - 5.11.2 Contour Plots. - 5.11.3 Vector Field Plots. - 5.12 Mayavi. - 5.12.1 Surface Plots. - 5.12.2 Contour Plots. - 5.12.3 Vector Field Plots. - 5.12.4 A 3D Scalar Field and Its Gradient Field. - 5.12.5 Animations. - 5.13 Summary. - 5.13.1 Chapter Topics. - 5.13.2 Example: Animating a Function. - 5.14 Exercises. - 6 Dictionaries and Strings. - 6.1 Dictionaries. - 6.1.1 Making Dictionaries. - 6.1.2 Dictionary Operations. - 6.1.3 Example: Polynomials as Dictionaries. - 6.1.4 Dictionaries with Default Values and Ordering. - 6.1.5 Example: Storing File Data in Dictionaries. - 6.1.6 Example: Storing File Data in Nested Dictionaries. - 6.1.7 Example: Reading and Plotting Data Recorded at Specific Dates. - 6.2 Strings. - 6.2.1 Common Operations on Strings. - 6.2.2 Example: Reading Pairs of Numbers. - 6.2.3 Example: Reading Coordinates. - 6.3 Reading Data fromWeb Pages. - 6.3.1 About Web Pages. - 6.3.2 How to Access Web Pages

Anmerkung: Table of Contents Abstract Kurzfassung Abbreviations and nomenclature 1. Introduction 2. Scientific Background 2.1. Permafrost 2.2.Retrogressive Thaw Slumps 2.3. Inputs of Freshwater, Sediment and Carbon into the Canadian Beaufort Sea 3. Study Area 3.1. Regional Setting: Yukon Coast and Herschel Island 3.2. Retrogressive Thaw Slumps 4. Material and Methods 4.1. Field Work 4.1.1. Terrain Photography 4.1.2. Differential Global Positioning System (DGPS) 4.1.3. Light Detection And Ranging (LiDAR) and Digital Elevation Model (DEM) 4.1.4. Micrometeorology 4.1.5. Discharge Measurement 4.1.6. Multiple Regression-Statistical Relationships between Micrometeorological Variables and Discharge 4.1.7. Sampling 4.2. Laboratory Analyses 4.2.1. Sedimentological Analyses 4.2.2. Hydrochemical Analyses 4.3. Fluxes of Sediment and (In-) Organic Matter 5. Results 5.1. Field Work 5.1.1. Terrain Photography 5.1.2. Differential Global Positioning System (DGPS) 5.1.3. Light Detecting And Ranging (LiDAR) and Digital Elevation Model (DEM) 5.1.4. Micrometeorology 5.1.5. Discharge 5.1.6. Multiple Regression - Statistical Relationships between Micrometeorology and Discharge 5.2. Laboratory Analyses 5.2.1. Sedimentological Analyses 5.2.2. Hydrochemical Analyses 5.3. Fluxes of Sediment-meltwater 6. Discussion 6.1. Microclimatological and Geomorphological Factors Controlling Discharge 6.1.1. Diurnal Variations 6.1.2. Seasonal Variations 6.2. Contribution of Retrogressive Thaw Slumps to the Sediment Budget of the Yukon Coast 6.2.1. Origin of Outflow Material 6.2.2. Slump D in the Regional Context 6.2.3. Seasonal Sediment Budget Compilation for Slump D 6.2.4. Retrogressive Thaw Slump Occurrence along the Yukon Coast 6.2.5. Input to the Beaufort Sea 6.3. Projected Climatic Change and its Impact on Retrogressive Thaw Slump Outflow 6.4. Uncertainties and Limitations 6.5. Future Research 7. Conclusion 8. Appendix 8.1. Field Work 8.1.1. Slump D's northern headwall profile 8.1.2. Collinson Head slump 8.1.3. Herschel Island West Coast slump 8.1.4. Roland Bay slump 8.1.5. Kay Point slump 8.2. Laboratory Work 8.2.1. Volumetric Ice Content 8.2.2. Grain Size 8.3. Evolution of Slump D 8.3.1. Geo Eye satellite of Slump D 8.3.2. Aerial Oblique Photography of Slump D 8.3.3. LiDAR of Slump D 8.3.4. Time Lapse Photography of Slump D's Headwall 9. References 10. Financial and technical support 11. Acknowledgement - Danksagung