Format:
XV, 334 Seiten
,
Illustrationen
ISBN:
354058918X
,
978-3-662-03169-8
Note:
MAB0014.001: PIK N 456-97-0002
,
MAB0014.002: AWI S2-95-0215
,
Literaturverzeichnis S. 299-327
,
Contents
Foreword
Preface
Contributors
I Introduction
1 The Development of Climate Research / by ANTONIO NAVARRA
1.1 The Nature of Climate Studies
1.1.1 The Big Storm Controversy
1.1.2 The Great Planetary Oscillations
1.2 The Components of Climate Research
1.2.1 Dynamical Theory
1.2.2 Numerical Experimentation
1.2.3 Statistical Analysis
2 Misuses of Statistical Analysis in Climate Research / by HANS VON STORCH
2.1 Prologue
2.2 Mandatory Testing and the Mexican Hat
2.3 Neglecting Serial Correlation
2.4 Misleading Names: The Case of the Decorrelation Time
2.5 Use of Advanced Techniques
2.6 Epilogue
II Analyzing The Observed Climate
3 Climate Spectra and Stochastic Climate Models / by CLAUDE FRANKIGNOUL
3.1 Introduction
3.2 Spectral Characteristics of Atmospheric Variables
3.3 Stochastic Climate Model
3.4 Sea Surface Temperature Anomalies
3.5 Variability of Other Surface Variables
3.6 Variability in the Ocean Interior
3.7 Long Term Climate Changes
4 The Instrumental Data Record: Its Accuracy and Use in Attempts to Identify the "CO2 Signal" / by PHIL JONES
4.1 Introduction
4.2 Homogeneity
4.2.1 Changes in Instrumentation, Exposure and Measuring Techniques
4.2.2 Changes in Station Locations
4.2.3 Changes in Observation Time and the Methods Used to Calculate Monthly Averages
4.2.4 Changes in the Station Environment
4.2.5 Precipitation and Pressure Homogeneity
4.2.6 Data Homogenization Techniques
4.3 Surface Climate Analysis
4.3.1 Temperature
4.3.2 Precipitation
4.3.3 Pressure
4.4 The Greenhouse Detection Problem
4.4.1 Definition of Detection Vector and Data Used
4.4.2 Spatial Correlation Methods
4.5 Conclusions
5 Interpreting High-Resolution Proxy Climate Data - The Example of Dendr о climatology / by KEITH R. BRIFFA
5.1 Introduction
5.2 Background
5.3 Site Selection and Dating
5.4 Chronology Confidence
5.4.1 Chronology Signal
5.4.2 Expressed Population Signal
5.4.3 Subsample Signal Strength
5.4.4 Wider Relevance of Chronology Signal
5.5 "Standardization" and Its Implications for Judging Theoretical Signal
5.5.1 Theoretical Chronology Signal
5.5.2 Standardization of "Raw" Data Measurements
5.5.3 General Relevance of the "Standardization" Problem
5.6 Quantifying Climate Signals in Chronologies
5.6.1 Calibration of Theoretical Signal
5.6.2 Verification of Calibrated Relationships
5.7 Discussion
5.8 Conclusions
6 Analysing the Boreal Summer Relationship Between World wide Sea-Surface Temperature and Atmospheric Variability / by M. NEIL WARD
6.1 Introduction
6.2 Physical Basis for Sea-Surface Temperature Forcing of the Atmosphere
6.2.1 Tropics
6.2.2 Extratropics
6.3 Characteristic Patterns of Global Sea Surface Temperature: EOFs and Rotated EOFs
6.3.1 Introduction
6.3.2 SST Data
6.3.3 EOF method
6.3.4 EOFs p^→1 - p^→3
6.3.5 Rotation of EOFs
6.4 Characteristic Features in the Marine Atmosphere Associated with the SST Patterns p^→2, p ^→3 and p^→2R in JAS
6.4.1 Data and Methods
6.4.2 Patterns in the Marine Atmosphere Associated with EOF p^→2
6.4.3 Patterns in the Marine Atmosphere Associated with EOF p^→3
6.4.4 Patterns in the Marine Atmosphere Associated with Rotated EOF p^→2R
6.5 JAS Sahel Rainfall Links with Sea-Surface Temperature and Marine Atmosphere
6.5.1 Introduction
6.5.2 Rainfall in the Sahel of Africa
6.5.3 High Frequency Sahel Rainfall Variations
6.5.4 Low Frequency Sahel Rainfall Variations
6.6 Conclusions
III Simulating and Predicting Climate
7 The Simulation of Weather Types in GCMs : A Regional Approach to Control-Run Validation / by KEITH R. BRIFFA
7.1 Introduction
7.2 The Lamb Catalogue
7.3 An "Objective" Lamb Classification
7.4 Details of the Selected GCM Experiments
7.5 Comparing Observed and GCM Climates
7.5.1 Lamb Types
7.5.2 Temperature and Precipitation
7.5.3 Relationships Between Circulation Frequencies and Temperature and Precipitation
7.5.4 Weather-Type Spell Lengths and Storm Frequencies
7.6 Conclusions
7.6.1 Specific Conclusions
7.6.2 General Conclusions
8 Statistical Analysis of GCM Output / by CLAUDE FRANKIGNOUL
8.1 Introduction
8.2 Univariate Analysis
8.2.1 The i-Test on the Mean of a Normal Variable
8.2.2 Tests for Autocorrelated Variables
8.2.3 Field Significance
8.2.4 Example: GCM Response to a Sea Surface Temperature Anomaly
8.3 Multivariate Analysis
8.3.1 Test on Means of Multidimensional Normal Variables
8.3.2 Application to Response Studies
8.3.3 Application to Model Testing and Intercomparison
9 Field Intercomparison / by ROBERT E . LIVEZEY
9.1 Introduction
9.2 Motivation for Permutation and Monte Carlo Testing
9.2.1 Local vs. Field Significance
9.2.2 Test Example
9.3 Permutation Procedures
9.3.1 Test Environment
9.3.2 Permutation (PP) and Bootstrap (BP) Procedures
9.3.3 Properties
9.3.4 Interdependence Among Field Variables
9.4 Serial Correlation
9.4.1 Local Probability Matching
9.4.2 Times Series and Monte Carlo Methods
9.4.3 Independent Samples
9.4.4 Conservatism
9.5 Concluding Remarks
10 The Evaluation of Forecasts / by ROBERT E. LIVEZEY
10.1 Introduction
10.2 Considerations for Objective Verification
10.2.1 Quantification
10.2.2 Authentication
10.2.3 Description of Probability Distributions
10.2.4 Comparison of Forecasts
10.3 Measures and Relationships: Categorical Forecasts
10.3.1 Contingency and Definitions
10.3.2 Some Scores Based on the Contingency Table
10.4 Measures and Relationships: Continuous Forecasts
10.4.1 Mean Squared Error and Correlation
10.4.2 Pattern Verification (the Murphy-Epstein Decomposition)
10.5 Hindcasts and Cross-Validation
10.5.1 Cross-Validation Procedure
10.5.2 Key Constraints in Cross-Validation
11 Stochastic Modeling of Precipitation with Applications to Climate Model Downscaling / by DENNIS LETTENMAIER
11.1 Introduction
11.2 Probabilistic Characteristics of Precipitation
11.3 Stochastic Models of Precipitation
11.3.1 Background
11.3.2 Applications to Global Change
11.4 Stochastic Precipitation Models with External Forcing
11.4.1 Weather Classification Schemes
11.4.2 Conditional Stochastic Precipitation Models
11.5 Applications to Alternative Climate Simulation
11.6 Conclusions
IV Pattern Analysis
12 Teleconnections Patterns / by ANTONIO NAVARRA
12.1 Objective Teleconnections
12.2 Singular Value Decomposition
12.3 Teleconnections in the Ocean-Atmosphere System
12.4 Concluding Remarks
13 Spatial Patterns: EOFs and CCA / by HANS VON STORCH
13.1 Introduction
13.2 Expansion into a Few Guess Patterns
13.2.1 Guess Patterns, Expansion Coefficients and Explained Variance
13.2.2 Example: Temperature Distribution in the Mediterranean Sea
13.2.3 Specification of Guess Patterns
13.2.4 Rotation of Guess Patterns
13.3 Empirical Orthogonal Functions
13.3.1 Definition of EOFs
13.3.2 What EOFs Are Not Designed for
13.3.3 Estimating EOFs
13.3.4 Example: Central European Temperature
13.4 Canonical Correlation Analysis
13.4.1 Definition of Canonical Correlation Patterns
13.4.2 CCA in EOF Coordinates
13.4.3 Estimation: CCA of Finite Samples
13.4.4 Example: Central European Temperature
14 Patterns in Time : SSA and MSSA / by ROBERT VAUTARD
14.1 Introduction
14.2 Reconstruction and Approximation of Attractors
14.2.1 The Embedding Problem
14.2.2 Dimension and Noise
14.2.3 The Macroscopic Approximation
14.3 Singular Spectrum Analysis
14.3.1 Time EOFs
14.3.2 Space-Time EOFs
14.3.3 Oscillatory Pairs
14.3.4 Spectral Properties
14.3.5 Choice of the Embedding Dimension
14.3.6 Estimating Time and Space-Time Patterns
14.4 Climatic Applications of SSA
14.4.1 The Analysis of Intraseasonal Oscillations
14.4.2 Empirical Long-Range Forecasts Using MSSA Predictors
14.5 Conclusions
15 Multivariate Statistical Modeling : POP-Model as a First Order Approximation / by JIN-SONG VON STORCH
15.1 Introduction
15.2 The Cross-Covariance Matrix and the Cross-Spectrum Matrix
15.3 Multivariate AR(1) Process and its Cross-Covariance and Cross-Spectrum Matrices
15.3.1 The System Matrix A and its POPs
15.3.2 Cross-Spectrum Matrix in POP-Basis: Its Matrix Formulation
15.3.3 Cross-Spectrum Matrix in POP-Basis: Its Diagonal Components
15.3.4
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