ALBERT

Description / Table of Contents: Contents: 1. Introduction: Contours of the International Climate Movement - Conception and Contents of the Handbook ; Part 1 Theoretical Prospects of the Climate Movement ; 2. Framing Processes in the Climate Movement: from Climate Change to Climate Justice ; 3. Democratizing the Climate Negotiations System through Improved Opportunities for Participation ; 4. Antagonistic Standpoints: The Climate Justice Coalition Viewed in Light of a Theory of Societal Relationships with Nature ; 5. The Climate Justice Movement and the Hegemonic Discourse of Technology ; 6. Climate Justice from the Perspective of Philosophy ; Part 2 Components of the Climate Movement Regional Climate Movements ; 7. The Green Movement in Britain ; 8. The Climate Movement in Germany ; 9. Movements for Climate Justice in the US and Worldwide ; 10. The Australian Climate Movement: A disparate response to climate change and climate politics in a not so 'lucky country' ; 11. The Climate Movement in Brazil - Professionalism and Ideological Differences ; 12. India - The long march to a climate movement ; 13. China's Emerging Climate Change Movement - Finding a Place to Stand ; 14. Climate Justice In, By and For Africa ; 15. Activist Profile Bill McKibben ; 16. Activist Profile Naomi Klein ; 17. Activist Profile James Hansen ; 18. Activist Profile Gore ; Popular Activists 19. Activist Profile Tim DeChristopher ; 20. Activist Profile Anna Rose ; 21. Activist Profiles David Spratt und Phillip Sutton ; International NGOs and Network Organizations 22. Organization Profile Climate Action Network International ; 23. Organization Profile Climate Justice Now! ; 24. Organization Profile La Via Campesina ; 25. Organization Profile Friends of the Earth International ; 26. Organization Profile Climate Alliance ; Climate NGOs from the US 27. Organization Profile 350.org ; 28. Organization Profile Rising Tide ; 29. Organization Profile Energy Action Coalition ; Climate NGOs from Europe 30. Organization Profile Plane Stupid ; 31. Organization Profile Germanwatch ; Part 3 Arenas, Activities and Development of the Climate Movement ; 32. Between Pragmatism and Radicalization. NGOs and Social Movements in International Climate Politics ; 33. Re-Framing Climate Change: The Cochabamba Conference and Global Climate Politics ; 34. Debates and Conflicts in the Climate Movement ; 35. Small Island States and the new Climate Change: the Case of Kiribati ; 36. Ambivalent involvement: Civil-Society Actors in Forest Carbon Offsets. The case of the Climate Community and Biodiversity Standards (CCB) ; 37. In the Periphery of the Climate Movement - Humanitarian Organizations ; 38. Conclusion: Results of the Handbook - State, Influence and Future of the Climate Movement

Description / Table of Contents: The Caledonides are a major orogenic belt that stretches from the Arctic, through Scandinavia, East Greenland, Britain and Ireland into the Atlantic coast of North America. Following the break-up of Rodinia, the Caledonides formed in the Palaeozoic by the drifting of various continents and their eventualaggregation in the Silurian and Devonian. The orogen subsequently fragmented during the opening of the Atlantic Ocean. This volume brings together 25 papers presenting the results of modern research that investigates the orogenic processes and the provenance of specific components of the belt. The contributions reflect different lines of research, linking traditional field studies with modern analytical techniques.In addition three overview papers summarize the main features of the belts in Scandinavia, Svalbard,East Greenland, Britain and Ireland, highlighting the advances made since the last major synthesis of theScandinavian Caledonides 30 years ago, and discussing important open questions.

Description / Table of Contents: Contents: Background -- On the role(s) of energy in the economy -- A brief history of bubbles and busts through 1933 -- Post World War II -- After the end of Glass-Steagall -- The role of misbehavior -- Where do we stand today? -- A policy agenda for stabilization -- Economic growth -- Concluding thoughts about bubbles and energy.

Description / Table of Contents: Contents: PART 1 FUNDAMENTAL CONCEPTS. - 1 Introduction. - 1.1 Climate archives, variables and dating. - 1.2 Noise and statistical distribution. - 1.3 Persistence. - 1.4 Spacing. - 1.5 Aim and structure of this book. - 1.6 Background material. - 2 Persistence models. - 2.1 First-Order Autoregressive Model. - 2.1.1 Even spacing. - 2.1.2 Uneven Spacing. - 2.2 Second-Order Autoregressive Model. - 2.3 Mixed Autoregressive Moving Average Model. - 2.4 Other models. - 2.4.1 Long-memory process. - 2.4.2 Nonlinear and non-gaussian models. - 2.5 Climate theory. - 2.5.1 Stochastic climate models. - 2.5.2 Long memory of temperature fluctuations?. - 2.5.3 Long memory of river runoff. - 2.6 Background material. - 2.7 Technical issues. - 3 Bootstrap confidence intervals. - 3.1 Error bars and confidence intervals. - 3.1.1 Theoretical example: Mean estimation of Gaussian White Noise. - 3.1.2 Theoretical example: Standard deviation estimation of Gaussian White Noise. - 3.1.3 Real world. - 3.2 Bootstrap principle. - 3.3 Bootstrap resampling. - 3.3.1 Nonparametric: Moving block bootstrap. - 3.3.2 Parametric: Autoregressive Bootstrap. - 3.3.3 Parametric: Surrogate Data. - 3.4 Bootstrap Confidence Intervals. - 3.4.1 Normal confidence interval. - 3.4.2 Student's t confidence interval. - 3.4.3 Percentile confidence interval. - 3.4.4 BCa Confidence Interval. - 3.5 Examples. - 3.6 Bootstrap hypothesis tests. - 3.7 Notation. - 3.8 Background material. - 3.9 Technical issues. - PART 2 UNIVARIATE TIME SERIES. - 4 Regression I. - 4.1 Linear regression. - 4.1.1 Weighted least-squares and ordinary least-squares estimation. - 4.1.2 Generalized least-squares estimation. - 4.1.3 Other estimation types. - 4.1.4 Classical confidence intervals. - 4.1.5 Bootstrap confidence intervals. - 4.1.6 Monte Carlo Experiments: Ordinary least-squares estimation. - 4.1.7 Timescale errors. - 4.2 Nonlinear regression. - 4.2.1 Climate Transition Model: Ramp. - 4.2.2 Trend-Change Model: Break. - 4.3 Nonparametric regression or smoothing. - 4.3.1 Kernel estimation. - 4.3.2 Bootstrap confidence intervals and bands. - 4.3.3 Extremes or outlier detection. - 4.4 Background material. - 4.5 Technical issues. - 5 Spectral analysis. - 5.1 Spectrum. - 5.1.1 Example: AR(1) process, discrete time. - 5.1.2 Example: AR(2) process, discrete time. - 5.1.3 Physical meaning. - 5.2 Spectral estimation. - 5.2.1 Periodogram. - 5.2.2 Welch's overlapped segment averaging. - 5.2.3 Multitaper estimation. - 5.2.4 Lomb-Scargle estimation. - 5.2.5 Peak detection: red-noise hypthesis. - 5.2.6 Example: Peaks in monsoon spectrum. - 5.2.7 Aliasing. - 5.2.8 Timescale errors. - 5.2.9 Example: Peaks in monsoon spectrum (continued). - 5.3 Background material. - 5.4 Technical Issues. - 6 Extreme value time series. - 6.1 Data types. - 6.1.1 Event times. - 6.1.2 Peaks over threshold. - 6.1.3 Block extremes. - 6.1.4 Remarks on data selection. - 6.2 Stationary models. - 6.2.1 Generalized extreme value distribution. - 6.2.2 Generalized pareto distribution. - 6.2.3 Bootstrap confidence intervals. - 6.2.4 Example: Elbe summer floods, 1852-2002. - 6.2.5 Persisitence. - 6.2.6 Remark: Tail estimation. - 6.2.7 Remark: Optimal estimation. - 6.3 Nonstationary models. - 6.3.1 Time-dependent generalized extreme value distribution. - 6.3.2 Inhomogenous poisson process. - 6.3.3 Hybrid: Poisson-Extreme value distribution. - 6.4 Sampling and time spacing. - 6.5 Background material. - 6.6 Technical issues. - PART 3 BIVARIATE TIME SERIES. - 7. Correlation. - 7.1 Pearson's Correlation Coefficient. - 7.1.1 Remark: Alternative correlation measures. - 7.1.2 Classical confidence intervals, nonpersistent processes. - 7.1.3 Bivariate time series models. - 7 .1.4 Classical Confidence Intervals, Persistent Processes. - 7.1.5 Bootstrap Confidence Intervals. - 7.2 Spearman's Rank Correlation Coefficient. - 7.2.1 Classical Confidence Intervals, Nonpersistent Processes. - 7.2.2 Classical Confidence Intervals, Persistent Processes. - 7.2.3 Bootstrap Confidence Intervals. - 7.3 Monte Carlo Experiments. - 7.4 Example: Elbe Runoff Variations. - 7.5 Unequal Timescales. - 7.5.1 Binned Correlation. - 7.5.2 Synchrony Correlation. - 7.5.3 Monte Carlo Experiments. - 7.5.4 Example: Vostok Ice Core Records. - 7.6 Background Material. - 7. 7 Technical Issues. - 8 Regression II. - 8.1 Linear Regression. - 8.1.1 Ordinary Least-Squares Estimation. - 8.1.2 Weighted Least-Squares for Both Variables Estimation. - 8.1.3 Wald-Bartlett Procedure. - 8.2 Bootstrap Confidence lntervals. - 8.2.1 Simulating Incomplete Prior Knowledge. - 8.3 Monte Carlo Experiments. - 8.3.1 Easy Setting. - 8.3.2 Realistic Setting: Incomplete Prior Knowledge. - 8.3.3 Dependence on Accuracy of Prior Knowledge. - 8.3.4 Mis-Specified Prior Knowledge. - 8.4 Example: Climate Sensitivity. - 8.5 Prediction. - 8.5.1 Example: Calibration of a Proxy Variable. - 8.6 Lagged Regression. - 8.6.1 Example: CO2 and Temperature Variations in the Pleistocene. - 8.7 Background Material. - 8.8 Technical Issues. - PART 4 OUTLOOK. - 9 Future Directions. - 9 .1 Timescale Modeling. - 9.2 Novel Estimation Problems. - 9.3 Higher Dimensions. - 9.4 Climate Models. - 9.4.1 Fitting Climate Models to Observations. - 9.4.2 Forecasting with Climate Models. - 9.4.3 Design of the Cost Function. - 9.4.4 Climate Model Bias. -9.5 Optimal Estimation. - 9.6 Background Material. - References. - Author Index. - Subject Index.

Description / Table of Contents: Climate is a paradigm of a complex system. Analysing climate data is an exciting challenge, which is increased by non-normal distributional shape, serial dependence, uneven spacing and timescale uncertainties. This book presents bootstrap resampling as a computing-intensive method able to meet the challenge. It shows the bootstrap to perform reliably in the most important statistical estimation techniques: regression, spectral analysis, extreme values and correlation. This book is written for climatologists and applied statisticians. It explains step by step the bootstrap algorithms (including novel adaptions) and methods for confidence interval construction. It tests the accuracy of the algorithms by means of Monte Carlo experiments. It analyses a large array of climate time series, giving a detailed account on the data and the associated climatological questions.

Description / Table of Contents: Contents: Einleitung ; Theorie der Beschaffung ; Nachhaltigkeit ; Beschaffungspraxis ; Übungsfälle