Note: Intro -- Preface -- Contents -- About the Editors -- Keynote -- 1 Fifty Years of Paleoceanography: Major Achievements in Our Understanding of Past and Future Climate Change-Some Memories and Hearsay -- Abstract -- 1 Preliminary Note -- 2 Early Efforts -- 3 Sample Basis to Gain Empiric Proxy Data from Deep-Sea Sediments -- 4 Great Advances in the 1970s and 1980s -- 5 Some Contributions of Kiel University (Germany) -- 6 Selection of Major Findings Over the Last 20 Years -- References -- Paleoceanographic Evolution -- 2 Orbital-Scale Paleoceanographic Response to the Indian Monsoon in the Laxmi Basin of the Eastern Arabian Sea -- Abstract -- 1 Introduction -- 2 Materials and Methods -- 3 Results and Discussion -- 3.1 Age Reconstruction at Site U1456 -- 3.2 Orbital-Scale Paleoceanographic Changes -- References -- 3 The 4.2 ka Event in the Euro-Mediterranean Region-A Study from the MISTRALS/ PALEOMEX Program -- Abstract -- 1 Introduction -- 2 Materials and Methods -- 3 Results and Discussion -- 4 Conclusions -- Acknowledgments -- References -- 4 Record of Early Cretaceous Oceanic Anoxic Events in Adriatic Platform, Croatia -- Abstract -- 1 Introduction -- 2 Methods -- 3 Results -- 4 Discussion -- 5 Conclusion -- References -- 5 Sedimentological and Geochemical Records of Lower Cretaceous Carbonate Successions Around Trabzon (NE Turkey): Implications for Paleoenvironmental Evolution and Paleoclimatological Conditions of Tethys -- Abstract -- 1 Introduction -- 2 Methods -- 3 Results -- 3.1 Microfacies -- 3.2 Stable Isotope Analysis -- 4 Discussion -- 5 Conclusions -- Acknowledgements -- References -- Paleoclimate Evolution -- 6 Paleoclimate Evolution of the Kordofan Region (Sudan), During the Last 13 ka -- Abstract -- 1 Introduction -- 2 Methodology -- 3 Results -- 3.1 Sedimentology and Stratigraphy -- 3.2 Paleobiology -- 3.3 Stable Isotopes. , 3.4 Geochemistry and Clay Mineralogy -- 4 Discussion -- 5 Conclusion -- References -- 7 Use of Paleoclimate Rainfall Data to Detect Mega Drought Signals -- Abstract -- 1 Introduction -- 2 Data and Methods -- 2.1 Chuk-Woo-Kee (Korean Ancient Rain Gauge) -- 2.2 Precipitation -- 2.3 Drought Index -- 3 Results -- 3.1 Drought Periodicity -- 3.2 Mega Drought -- 4 Conclusions -- Acknowledgements -- References -- 8 Paleoclimatology Evidence of Eocene from Jaddala Formation in Northwestern Iraq -- Abstract -- 1 Introduction -- 2 Materials and Methods -- 3 Results -- References -- 9 Holocene Paleoclimatic Variation Inferred from Study of Sediments in the Gulf of Tunis (North Africa) -- Abstract -- 1 Introduction -- 2 Materials and Methods -- 3 Results -- 3.1 Lithological Changes and Climatic Fluctuations -- 3.2 Mineralogical Study of Holocene Sediments -- 3.3 Evolution of the Lake Environment Recorded by Macrofauna Study -- 3.4 Study of the Organic Content of the Holocene Sediments -- 4 Results and Discussion -- 5 Conclusion -- References -- 10 Noble Gas Recharge Temperature of Sfax Deep Groundwater (Southeastern of Tunisia) -- Abstract -- 1 Introduction -- 2 Settings, Sampling and Analysis -- 3 Results -- 4 Discussion -- 5 Conclusions -- References -- 11 Time Analysis of Emberger's Pluviothermic Q Index in the SW of the Iberian Peninsula -- Abstract -- 1 Introduction -- 2 Study Area and Method -- 3 Results and Valuation -- 4 Conclusion -- References -- 12 Systematic and Palaeoclimatic Investigations of Sivalhippus from the Late Miocene Siwaliks (Pakistan) -- Abstract -- 1 Introduction -- 2 Materials and Methods -- 3 Results -- 3.1 Systematic Palaeontology -- 4 Discussion -- 5 Conclusion -- References -- 13 The Thar Desert Calcretes: A Proxy for Understanding Late Quaternary Paleoclimate Shifts -- Abstract -- 1 Introduction -- 2 Materials and Methods. , 3 Results -- 4 Discussion -- 5 Conclusion -- References -- Paleoenvironmental Evolution -- 14 Using Environmental Isotopes and Krypton-81 to Characterize and Date Continental Intercalaire Paleogroundwater (Southern Tunisia) -- Abstract -- 1 Introduction -- 2 Settings, Sampling and Analysis -- 3 Results -- 3.1 Chemical Composition -- 3.2 Environmental Isotopes (δ18O, δ2H, 14C, δ13C) -- 3.3 Concentration of 81Kr -- 4 Discussion -- 5 Conclusion -- References -- 15 Water Column Chemistry of Late Holocene Lake Bafa, Eastern Coast of the Aegean Sea (Turkey) -- Abstract -- 1 Introduction -- 2 Materials and Methods -- 3 Results -- 4 Discussion -- 5 Conclusions -- Acknowledgements -- References -- 16 New Reports of Messinian Lago-Mare Episodes from Tunisia: Ostracods and Paleoenvironmental Implications -- Abstract -- 1 Introduction -- 2 Materials and Methods -- 3 Results -- 3.1 Wadi El Kebir Section -- 3.2 Salakta Section -- 4 Discussion (Paleontology) -- 5 Conclusions -- References -- 17 Geochemical Evidences of Paleoenvironmental Changes in Late Quaternary Lacustrine Sediments of the Konya Closed Basin (Konya, Turkey) -- Abstract -- 1 Introduction -- 2 Materials and Methods -- 3 Results -- 3.1 Detrital Influx Proxies -- 3.2 Redox Proxies -- 3.3 Paleoproductivity Proxies -- 4 Conclusions -- References -- 18 Reconstruction of Holocene Paleoenvironmental Changes Along Northern Coast of Sfax: Analysis of Foraminiferal Associations -- Abstract -- 1 Introduction -- 2 Settings -- 3 Results -- 4 Discussion -- 4.1 Tyrrhenian Sea-Level High Stand, Substage 5e -- 4.2 First Holocene Marine Transgression 2018-2419a Cal BP in Age -- 4.3 Period of Sand Spits Development, Between 2018-2419 and 1001-1804 a Cal BP) -- 4.4 Second Marine Transgression Towards 1001-1804 a Cal BP -- 4.5 High Energy Extreme Event Towards 0-502 a Cal BP -- 5 Conclusion -- References. , 19 Evolution of Korba Lagoon (Cap Bon, Tunisia) During the Last Millennia Based on the Analysis of Foraminiferal Assemblages -- Abstract -- 1 Introduction -- 2 Materials and Methods -- 3 Results -- 3.1 Lithology, Geochemistry and Sedimentology -- 3.2 Distribution of Foraminiferal Associations -- 4 Discussion -- 5 Conclusions -- References -- 20 Paleoenvironment Evolution of a Paralic System, El Guettiate and Dreïaa Sebkhas (Gulf of Gabès, Tunisia) -- Abstract -- 1 Introduction -- 2 Materials and Methods -- 3 Results and Discussion -- 4 Conclusions -- References -- Spatio-temporal Patterns of Climate Change -- 21 Testing for Collective Statistical Significance in Climate Change Detection Studies -- Abstract -- 1 Introduction -- 2 Statistical Tests and Synthetic Data -- 3 Application to Real-World Data -- 4 Conclusions -- Acknowledgements -- References -- 22 Long-Term Variability of Gauged Precipitation Over California and Its Links to Circulation Patterns -- Abstract -- 1 Introduction -- 2 Data and Methods -- 3 Results -- 4 Discussion -- 5 Conclusions -- References -- 23 Sensitivity of IDF Curves to Rainfall Gauge Type -- Abstract -- 1 Introduction -- 2 Materials and Method -- 3 Results and Discussion -- 4 Conclusions -- References -- 24 Structural Characteristics of Precipitation in Jordan -- Abstract -- 1 Introduction -- 2 Study Area and Methodology -- 3 Results -- 3.1 Consistency -- 3.2 Randomness -- 3.3 Trend -- 4 Discussion -- 5 Conclusions -- References -- 25 The Shift of the Atmospheric Circulation Patterns and Its Impacts on Western Mediterranean -- Abstract -- 1 Introduction -- 2 Data and Methods -- 3 The New Meridian Atmospheric Circulation (MAC) and Its Effects on Floods and Drought in Western Mediterranean -- 3.1 "Normal" Atmospheric Circulation -- 3.2 "Current" Atmospheric Circulation -- 4 Conclusion -- References. , 26 Recent Rainfall Variability in the South-West Mediterranean Region and Links with Teleconnection Patterns -- Abstract -- 1 Introduction -- 2 Methods -- 3 Results -- 3.1 Rainfall Variability Analysis -- 3.2 Links Between Rainfall and Climate Indices -- 4 Discussion -- 5 Conclusions -- References -- 27 Regionalization of Precipitation in Jordan -- Abstract -- 1 Introduction -- 2 Study Area and Methodology -- 3 Results and Discussion -- 3.1 Temporal Analysis (Months Clusters) -- 3.2 Spatial Analysis -- 4 Conclusions -- References -- 28 Correlation Between NAO and Radio Refractive Index Over Africa -- Abstract -- 1 Introduction -- 2 Methodology -- 3 Results -- 4 Discussion -- 5 Conclusions -- References -- 29 Convective Cloud Climatology Over Indian Tropics and Nearby Regions Using Multi-spectral Satellite Observations -- Abstract -- 1 Introduction -- 2 Study Area and Data Sets -- 3 Methodology -- 4 Results and Discussion -- 5 Conclusions -- References -- 30 Analysis of Trend and Variability in Time Series of Extreme Daily Temperature of Abu Dhabi City (UAE) -- Abstract -- 1 Introduction -- 2 Methodology -- 3 Results and Discussion -- 4 Conclusion -- References -- 31 Black Carbon Aerosol Characteristics and Its Radiative Effect in Xuzhou City, China -- Abstract -- 1 Introduction -- 2 Data and Method -- 3 Results -- 3.1 Seasonal Variation of Black Carbon Aerosol Concentration -- 3.2 Radiative Forcing Caused by Black Carbon Aerosol -- 4 Discussion and Conclusions -- Acknowledgements -- References -- Sea Level Variability: Past, Present and Future -- 32 On the Long-Term Mediterranean Sea Level Variability -- Abstract -- 1 Introduction -- 2 The Data -- 3 Results -- 4 Conclusions -- References -- 33 Impacts of Relative Sea Level Change and Sedimentary Dynamic on an Historic Site Expansion Along the Coast Between Sfax and Jebeniena, Tunisia -- Abstract. , 1 Introduction.

Note: Front Cover -- Big Data Mining for Climate Change -- Copyright -- Contents -- Preface -- 1 Big climate data -- 1.1 Big data sources -- 1.1.1 Earth observation big data -- 1.1.2 Climate simulation big data -- 1.2 Statistical and dynamical downscaling -- 1.3 Data assimilation -- 1.3.1 Cressman analysis -- 1.3.2 Optimal interpolation analysis -- 1.3.3 Three-dimensional variational analysis -- 1.3.4 Four-dimensional variational analysis -- 1.4 Cloud platforms -- 1.4.1 Cloud storage -- 1.4.2 Cloud computing -- Further reading -- 2 Feature extraction of big climate data -- 2.1 Clustering -- 2.1.1 K-means clustering -- 2.1.2 Hierarchical clustering -- 2.2 Hidden Markov model -- 2.3 Expectation maximization -- 2.4 Decision trees and random forests -- 2.5 Ridge and lasso regressions -- 2.6 Linear and quadratic discriminant analysis -- 2.6.1 Bayes classi er -- 2.6.2 Linear discriminant analysis -- 2.6.3 Quadratic discriminant analysis -- 2.7 Support vector machines -- 2.7.1 Maximal margin classi er -- 2.7.2 Support vector classi ers -- 2.7.3 Support vector machines -- 2.8 Rainfall estimation -- 2.9 Flood susceptibility -- 2.10 Crop recognition -- Further reading -- 3 Deep learning for climate patterns -- 3.1 Structure of neural networks -- 3.2 Back propagation neural networks -- 3.2.1 Activation functions -- 3.2.2 Back propagation algorithms -- 3.3 Feedforward multilayer perceptrons -- 3.4 Convolutional neural networks -- 3.5 Recurrent neural networks -- 3.5.1 Input-output recurrent model -- 3.5.2 State-space model -- 3.5.3 Recurrent multilayer perceptrons -- 3.5.4 Second-order network -- 3.6 Long short-term memory neural networks -- 3.7 Deep networks -- 3.7.1 Deep learning -- 3.7.2 Boltzmann machine -- 3.7.3 Directed logistic belief networks -- 3.7.4 Deep belief nets -- 3.8 Reinforcement learning -- 3.9 Dendroclimatic reconstructions. , 3.10 Downscaling climate variability -- 3.11 Rainfall-runoff modeling -- Further reading -- 4 Climate networks -- 4.1 Understanding climate systems as networks -- 4.2 Degree and path -- 4.3 Matrix representation of networks -- 4.4 Clustering and betweenness -- 4.5 Cut sets -- 4.6 Trees and planar networks -- 4.7 Bipartite networks -- 4.8 Centrality -- 4.8.1 Degree centrality -- 4.8.2 Closeness centrality -- 4.8.3 Betweenness centrality -- 4.9 Similarity -- 4.9.1 Cosine similarity -- 4.9.2 Pearson similarity -- 4.10 Directed networks -- 4.11 Acyclic directed networks -- 4.12 Weighted networks -- 4.12.1 Vertex strength -- 4.12.2 Weight-degree/weight-weight correlation -- 4.12.3 Weighted clustering -- 4.12.4 Shortest path -- 4.13 Random walks -- 4.14 El Niño southern oscillation -- 4.15 North Atlantic oscillation -- Further reading -- 5 Random climate networks and entropy -- 5.1 Regular networks -- 5.1.1 Fully connected networks -- 5.1.2 Regular ring-shaped networks -- 5.1.3 Star-shaped networks -- 5.2 Random networks -- 5.2.1 Giant component -- 5.2.2 Small component -- 5.3 Con guration networks -- 5.3.1 Edge probability and common neighbor -- 5.3.2 Degree distribution -- 5.3.3 Giant components -- 5.3.4 Small components -- 5.3.5 Directed random network -- 5.4 Small-world networks -- 5.4.1 Main models -- 5.4.2 Degree distribution -- 5.4.3 Clustering -- 5.4.4 Mean distance -- 5.5 Power-law degree distribution -- 5.5.1 Price's models -- 5.5.2 Barabasi-Albert models -- 5.6 Dynamics of random networks -- 5.7 Entropy and joint entropy -- 5.8 Conditional entropy and mutual information -- 5.9 Entropy rate -- 5.10 Entropy-based climate network -- 5.11 Entropy-based decision tree -- Further reading -- 6 Spectra of climate networks -- 6.1 Understanding atmospheric motions via network spectra -- 6.2 Adjacency spectra -- 6.2.1 Maximum degree -- 6.2.2 Diameter. , 6.2.3 Paths of length k -- 6.3 Laplacian spectra -- 6.3.1 Maximum degree -- 6.3.2 Connectivity -- 6.3.3 Spanning tree -- 6.3.4 Degree sequence -- 6.3.5 Diameter -- 6.4 Spectrum centrality -- 6.4.1 Eigenvector centrality -- 6.4.2 Katz centrality -- 6.4.3 Pagerank centrality -- 6.4.4 Authority and hub centralities -- 6.5 Network eigenmodes -- 6.6 Spectra of complete networks -- 6.7 Spectra of small-world networks -- 6.8 Spectra of circuit and wheel network -- 6.9 Spectral density -- 6.10 Spectrum-based partition of networks -- Further reading -- 7 Monte Carlo simulation of climate systems -- 7.1 Random sampling -- 7.1.1 Uniform distribution -- 7.1.2 Nonuniform distribution -- 7.1.3 Normal distribution -- 7.2 Variance reduction technique -- 7.2.1 Control variable method -- 7.2.2 Control vector method -- 7.3 Strati ed sampling -- 7.4 Sample paths for Brownian motion -- 7.4.1 Cholesky and Karhounen-Loève expansions -- 7.4.2 Brownian bridge -- 7.5 Quasi-Monte Carlo method -- 7.5.1 Discrepancy -- 7.5.2 Koksma-Hlawka inequality -- 7.5.3 Van der Corput sequence -- 7.5.4 Halton sequence -- 7.5.5 Faure sequence -- 7.6 Markov chain Monte Carlo -- 7.7 Gibbs sampling -- Further reading -- 8 Sparse representation of big climate data -- 8.1 Global positioning -- 8.1.1 Multidimensional scaling -- 8.1.2 Local rigid embedding -- 8.2 Embedding rules -- 8.2.1 Attractors and fractal dimension -- 8.2.2 Delay embedding -- 8.2.3 Multichannel singular spectrum analysis -- 8.2.4 Recurrence networks -- 8.3 Sparse recovery -- 8.3.1 Sparse interpolation -- 8.3.2 Sparse approximation -- 8.3.3 Greedy algorithms -- 8.4 Sparse representation of climate modeling big data -- 8.5 Compressive sampling of remote sensing big data -- 8.5.1 s-Sparse approximation -- 8.5.2 Minimal samples -- 8.5.3 Orthogonal matching pursuit -- 8.5.4 Compressive sampling matching pursuit. , 8.5.5 Iterative hard thresholding -- 8.6 Optimality -- 8.6.1 Optimization algorithm for compressive sampling -- 8.6.2 Chambolle and Pock's primal-dual algorithm -- Further reading -- 9 Big-data-driven carbon emissions reduction -- 9.1 Precision agriculture -- 9.2 Oil exploitation -- 9.3 Smart buildings -- 9.4 Smart grids -- 9.5 Smart cities -- Further reading -- 10 Big-data-driven low-carbon management -- 10.1 Large-scale data envelopment analysis -- 10.2 Natural resource management -- 10.3 Roadway network management -- 10.4 Supply chain management -- 10.5 Smart energy management -- Further reading -- 11 Big-data-driven Arctic maritime transportation -- 11.1 Trans-Arctic routes -- 11.2 Sea-ice remote-sensing big data -- 11.2.1 Arctic sea-ice concentration -- 11.2.2 Melt ponds -- 11.2.3 Arctic sea-ice extent -- 11.2.4 Arctic sea-ice thickness -- 11.2.5 Arctic sea-ice motion -- 11.2.6 Comprehensive integrated observation system -- 11.3 Sea-ice modeling big data -- 11.4 Arctic transport accessibility model -- 11.5 Economic and risk assessments of Arctic routes -- 11.6 Big-data-driven dynamic optimal trans-Arctic route system -- 11.7 Future prospects -- Further reading -- Index -- Back Cover.

Note: Intro -- Preface -- Contents -- 1 Artificial Neural Network -- 1.1 Network Architectures -- 1.1.1 Multilayer Feedforward Networks -- 1.1.2 Recurrent Networks -- 1.2 Perceptrons -- 1.2.1 Rosenblatt's Perceptron -- 1.2.2 Multilayer Perceptron -- 1.3 Linear Network and Bayes Classifier -- 1.4 Radial Basis Function Network -- 1.4.1 Radial Basis Function -- 1.4.2 Interpolation -- 1.4.3 Receptive Field -- 1.5 Generalized Regression Network -- 1.6 Self-organizing Network -- 1.6.1 Kohonen Self-organizing Map Network -- 1.6.2 Learning Vector Quantization Network -- 1.7 Hopfield Network -- 1.7.1 Continuous Hopfield Network -- 1.7.2 Discrete Hopfield Network -- Further Reading -- 2 Multivariate Harmonic Analysis -- 2.1 Fourier Transform -- 2.2 Discrete Fourier Transform -- 2.3 Discrete Cosine/Sine Transform -- 2.3.1 Four Forms of DCTs -- 2.3.2 Four Forms of DSTs -- 2.4 Filtering -- 2.5 Fractional Fourier Transform -- 2.5.1 Continuous FRFT -- 2.5.2 Discrete FRFT -- 2.5.3 Multivariate FRFT -- 2.6 Space--Frequency Distribution -- 2.6.1 Multivariate Windowed Fourier Transform -- 2.6.2 General Form -- 2.6.3 Popular Distributions -- 2.7 Multivariate Interpolation -- 2.7.1 Multivariate Polynomial Interpolation -- 2.7.2 Schoenberg Interpolation -- 2.7.3 Micchelli Interpolation -- 2.7.4 Interpolation on Spheres -- 2.8 Sparse Approximation -- 2.8.1 Approximation Kernels -- 2.8.2 Sparse Schemes -- 2.8.3 Greedy Algorithm -- 2.9 Spherical Harmonics -- 2.9.1 Spherical Harmonic Functions -- 2.9.2 Invariant Subspace under Fourier Transform -- 2.10 Harmonic Analysis on General Domains -- 2.10.1 Symmetric Kernels -- 2.10.2 Smooth Extensions and Approximation -- 2.11 Harmonic Analysis on Graphs -- 2.11.1 The Laplacian of a Graph -- 2.11.2 Eigenvalues and Eigenfunctions -- 2.11.3 Fourier Expansions -- Further Reading -- 3 Multivariate Wavelets -- 3.1 Multiresolution Analysis. , 3.1.1 Structure of MRA -- 3.1.2 Scaling Functions -- 3.2 Multivariate Orthogonal Wavelets -- 3.2.1 Separable Wavelets -- 3.2.2 Non-separable Wavelets -- 3.2.3 p-Band Wavelets -- 3.3 Biorthogonal Wavelets -- 3.3.1 Univariate Biorthogonal Wavelets -- 3.3.2 Multivariate Biorthogonal Wavelets -- 3.3.3 p-Band Biorthogonal Wavelets -- 3.3.4 Semi-orthogonal Wavelets -- 3.4 Wavelets on Domains -- 3.4.1 Continuous Extension -- 3.4.2 Wavelet Expansion -- 3.5 Discrete Wavelet Transforms -- 3.5.1 Discrete Orthogonal Wavelet Transforms -- 3.5.2 Discrete Biorthogonal Wavelet Transforms -- 3.5.3 Discrete Biorthogonal Periodic Wavelets Transforms -- 3.5.4 Discrete Harmonic Wavelet Transforms -- 3.6 Wavelet Packets -- 3.6.1 Continuous Wavelet Packets -- 3.6.2 Discrete Wavelet Packets -- 3.7 Wavelet Variance -- 3.7.1 Generalized Wavelet Decomposition -- 3.7.2 Maximal Overlap Discrete Wavelet Transform -- 3.7.3 Wavelet Variance -- 3.8 Significant Tests -- 3.8.1 Haar Wavelet Analysis -- 3.8.2 Morlet Wavelet Analysis -- 3.9 Wavelet Threshold and Shrinkage -- 3.9.1 Wavelet Threshold -- 3.9.2 Wavelet Shrinkage -- 3.9.3 Minimax Estimation -- 3.9.4 Adaptive Denoising Algorithm -- 3.10 Shearlets, Bandelets, and Curvelets -- 3.10.1 Shearlets -- 3.10.2 Bandelets -- 3.10.3 Curvelets -- Further Reading -- 4 Stochastic Representation and Modeling -- 4.1 Stochastic Processes -- 4.1.1 Vector Stochastic Processes -- 4.1.2 Gaussian, Markov, and Wiener Processes -- 4.2 Stationarity and Trend Tests -- 4.2.1 Stationarity Tests -- 4.2.2 Trend Tests -- 4.3 Patterns and Classification -- 4.3.1 Principal Component Analysis -- 4.3.2 Factor Analysis -- 4.3.3 Cluster Analysis -- 4.3.4 Discriminant Analysis -- 4.3.5 Canonical Correlation Analysis -- 4.4 Multidimensional Scaling -- 4.5 Vector ARMA Processes -- 4.5.1 Vector MA(q) Processes -- 4.5.2 Vector AR(p) Processes. , 4.5.3 Vector ARMA(p,q) Processes -- 4.6 Monte Carlo Methods -- 4.7 Black--Scholes Models -- 4.8 Stochastic Optimization -- Further Reading -- 5 Multivariate Spectral Analysis -- 5.1 Power Spectral Density -- 5.2 Periodogram and Correlogram -- 5.2.1 Algorithms -- 5.2.2 Bias Analysis -- 5.2.3 Variance Analysis -- 5.3 Blackman--Tukey Method -- 5.3.1 Blackman--Tukey Estimator -- 5.3.2 Several Common Windows -- 5.3.3 Positive Semidefinite Window -- 5.4 Welch Method -- 5.5 Multitaper Method -- 5.6 Maximum Entropy Method -- 5.7 Rational Spectral Estimation -- 5.8 Discrete Spectral Estimation -- 5.9 Vector ARMA Spectrum -- 5.10 Multichannel Singular Spectrum Analysis -- Further Reading -- 6 Climate Modeling -- 6.1 Greenhouse Gases -- 6.2 Impacts and Feedback of Climate Change -- 6.3 Framework of Climate Models -- 6.3.1 Basic Physical Laws Used in Climate Models -- 6.3.2 Discretization and Parameterization -- 6.3.3 The Hierarchy of Climate Models -- 6.4 Coupled Model Intercomparison Project -- Further Reading -- 7 Regional Climate Change -- 7.1 Middle East and Mediterranean Region -- 7.1.1 Precipitation -- 7.1.2 Air Temperature -- 7.1.3 Climate Modeling -- 7.1.4 Desert Dust -- 7.1.5 Water Resources -- 7.1.6 Soil Temperature -- 7.2 Asia-Pacific Region -- 7.2.1 Tibetan Plateau -- 7.2.2 El Nitildeno--Southern Oscillation -- 7.2.3 Indian Monsoon -- 7.2.4 Modeling Sea Surface Temperature -- 7.3 Arctic Region -- 7.3.1 Sea Ice -- 7.3.2 Permafrost Carbon -- Further Reading -- 8 Ecosystem and Carbon Cycle -- 8.1 Terrestrial Ecosystems -- 8.1.1 Terrestrial Hydrologic Cycle -- 8.1.2 Photosynthesis -- 8.1.3 Gross and Net Primary Production -- 8.1.4 Net Ecosystem Production -- 8.1.5 Terrestrial Nutrient Cycle -- 8.2 Ocean Ecosystems -- 8.2.1 Solubility and Air--Sea Gas Exchange -- 8.2.2 Oceanic Carbon Sink -- 8.2.3 Compounds in Seawater -- 8.2.4 Biogeochemical Cycles. , Further Reading -- 9 Paleoclimate Proxies -- 9.1 Tree-Rings -- 9.1.1 Field Works -- 9.1.2 Statistical Analysis -- 9.2 Ice Cores -- 9.2.1 Ice and Isotopes -- 9.2.2 Ice Core Samples -- 9.3 Speleothems -- 9.3.1 Oxygen Isotope Ratio -- 9.3.2 Carbon Isotope Ratio -- 9.3.3 Hydrogen Isotope Ratio -- Further Reading -- 10 Strategies for Climate Change Mitigation -- 10.1 Assessment Methods and Tools -- 10.1.1 Data Envelopment Analysis -- 10.1.2 Risk Assessment -- 10.1.3 Life Cycle Assessment -- 10.2 Carbon Emissions Reduction -- 10.2.1 Industrial Sector -- 10.2.2 Agriculture Sector -- 10.2.3 The Building Sector -- 10.2.4 The Transportation Sector -- 10.2.5 The Household Sector -- 10.2.6 Low-Carbon Energy -- 10.3 Carbon Capture, Transport, Utilization, and Storage -- 10.3.1 Carbon Capture -- 10.3.2 Transport of CO2 -- 10.3.3 Geological Storage of CO2 -- 10.3.4 Utilization of CO2 -- 10.4 Geoengineering -- 10.4.1 Space-Based Geoengineering -- 10.4.2 Atmosphere-Based Geoenginnering -- 10.4.3 Land-Based Geoengineering -- 10.4.4 Ocean-Based Geoengineering -- 10.4.5 Conclusions -- Further Reading.

Note: Intro -- Preface -- Contents -- 1 Time series analysis -- 1.1 Stationary time series -- 1.2 Prediction of time series -- 1.3 Spectral analysis -- 1.4 Autoregressive moving average models -- 1.5 Prediction and modeling of ARMA processes -- 1.6 Multivariate ARMA processes -- 1.7 State-space models -- 2 Chaos and dynamical systems -- 2.1 Dynamical systems -- 2.2 Henon and logistic maps -- 2.3 Lyapunov exponents -- 2.4 Fractal dimension -- 2.5 Prediction -- 2.6 Delay embedding vectors -- 2.7 Singular spectrum analysis -- 2.8 Recurrence networks -- 3 Approximation -- 3.1 Trigonometric approximation -- 3.2 Multivariate approximation and dimensionality reduction -- 3.3 Polynomial approximation -- 3.4 Spline approximation and rational approximation -- 3.5 Wavelet approximation -- 3.6 Greedy algorithms -- 4 Interpolation -- 4.1 Curve fitting -- 4.2 Lagrange interpolation -- 4.3 Hermite interpolation -- 4.4 Spline interpolation -- 4.5 Trigonometric interpolation and fast Fourier transform -- 4.6 Bivariate interpolation -- 5 Statistical methods -- 5.1 Linear regression -- 5.2 Multiple regression -- 5.3 Case study: Tree-ring-based climate reconstructions -- 5.4 Covariance analysis -- 5.5 Discriminant analysis -- 5.6 Cluster analysis -- 5.7 Principal component analysis -- 5.8 Canonical correlation analysis -- 5.9 Factor analysis -- 6 Numerical methods -- 6.1 Numerical integration -- 6.2 Numerical differentiation -- 6.3 Iterative methods -- 6.4 Difference methods -- 6.5 Finite element methods -- 6.6 Wavelet methods -- 7 Optimization -- 7.1 Newton's method and steepest descent method -- 7.2 The variational method -- 7.3 The simplex method -- 7.4 Fermat rules -- 7.5 Karush-Kuhn-Tucker optimality conditions -- 7.6 Primal and dual pairs of linear optimization -- 7.7 Case studies -- 8 Data envelopment analysis -- 8.1 Charnes-Cooper-Rhodes DEA models. , 8.2 Banker-Charnes-Cooper DEA models -- 8.3 One-stage and two-stage methods -- 8.4 Advanced DEA models -- 8.5 Software and case studies -- 9 Risk assessments -- 9.1 Decision rules under uncertainty -- 9.2 Decision trees -- 9.3 Fractile and triangular methods -- 9.4 The ε-constraint method -- 9.5 The uncertainty sensitivity index method -- 9.6 The partitioned multiobjective risk method -- 9.7 The multiobjective multistage impact analysis method -- 9.8 Multiobjective risk impact analysis method -- 9.9 The Leslie model -- 9.10 Leontief's and inoperability input-output models -- 10 Life cycle assessments -- 10.1 Classic life cycle assessment -- 10.2 Exergetic life cycle assessment -- 10.3 Ecologically-based life cycle assessment -- 10.4 Case studies -- Index.

Note: Literaturangaben