ALBERT

Note: Contents: Contributors. - Preface. - Acknowledgements. - PART I SETTING THE SCENE. - 1. Introduction: Why Sub-seasonal to Seasonal Prediction (S2S)? / Frédéric Vitart, Andrew W. Robertson. - 1 History of Numerical Weather and Climate Forecasting. - 2 Sub-seasonal to Seasonal Forecasting. - 3 Recent National and International Efforts on Sub-seasonal to Seasonal Prediction. - 4 Structure of This Book. - 2. Weather Forecasting: What Sets the Forecast Skill Horizon? / Zoltan Toth, Roberto Buizza. - 1 Introduction. - 2 The Basics of Numerical Weather Prediction. - 3 The Evolution of NWP Technique. - 4 Enhancement of Predictable signals. - 5 Ensemble Techniques: Brief Introduction. - 6 Expanding the forecast skill Horizon. - 7 Concludmg Remarks: Lessons for S2S Forecasting. - Acknowledgements. - 3. Weather Within Climate: Sub-seasonal Predictability of Tropical Daily Rainfall Characteristics / Vincent Moron, Andrew W. Robertson, Lei Wang. - 1 Introduction. - 2 Data and Methods. - 3 Results. - 4 Discussion and Concluding Remarks. - 4. Identifying Wave Processes Associated With Predictability Across Time Scales: An Empirical Normal Mode Approach / Gilbert Brunet, John Methven. - 1 Introduction. - 2 Partitioning Atmospheric Behavior Using Its Conservation Properties. - 3 The ENM Approach to Observed Data and Models and Its Relevance to S2S Dynamics and Predictability. - 4 Conclusion. - Acknowledgments. - PART II SOURCES OF S2S PREDICTABILITY. - 5. The Madden-Julian Oscillation / Steven J. Woolnough. - 1 Introduction. - 2 The Real-Time Multivariate MJO Index. - 3 Observed MJO Structure. - 4 The Relationship Between the MJO and Tropical and Extratropical Weather. - 5 Theories and Mechanisms for MJO Initiation, Maintenance, and Propagation. - 6 The Representation of the MJO in Weather and Climate Models. - 7 MJO Prediction. - 8 Future Priorities for MJO Research for S2S Prediction. - Acknowledgments. - 6. Extratropical Sub-seasonal to Seasonal Oscillations and Multiple Regimes: The Dynamical Systems View / Michael Ghil, Andreas Groth, Dmitri Kondrashov, Andrew W. Robertson. - 1 Introduction and Motivation. - 2 Multiple Midlatitude Regimes and Low-Frequency Oscillations. - 3 Extratropical Oscillations in the S2S Band. - 4 Low-Order, Data-Driven Modeling, Dynamical Analysis, and Prediction. - 5 Concluding Remarks. - Acknowledgments. - 7. Tropical-Extratropical Interactions and Teleconnections / Hai Lin, Jorgen Frederiksen, David Straus, Christiana Stan. - 1 Introduction. - 2 Tropical Influence on the Extratropical Atmosphere. - 3 Extratropical Influence on the Tropics. - 4 Tropical-Extratropical, Two-Way Interactions. - 5 Summary and Discussion. - Appendix. Technical Matters Relating to Section 4.2. - 8. Land Surface Processes Relevant to Sub-seasonal to Seasonal (S2S) Prediction / Paul A. Dirmeyer, Pierre Gentine, Michael B. Ek, Gianpaolo Balsamo. - 1 Introduction. - 2 Process of Land-Atmosphere Interaction. - 3 A Brief History of Land-Surface Models. - 4 Predictability and Prediction. - 5 Improving Land-Driven Prediction. - 9. Midlatitude Mesoscale Ocean-Atmosphere Interaction and Its Relevance to S2S Prediction / R. Saravanan, P. Chang. - 1 Introduction. - 2 Data and Models. - 3 Mesoscale Ocean-Atmosphere Interaction in the Atmospheric Boundary Layer. - 4 Local Tropospheric Response. - 5 Remote Tropospheric Response. - 6 Impact on Ocean Circulation. - 7 Implications for S2S Prediction. - 8 Summary and Conclusions. - Acknowledgments. - 10. The Role of Sea Ice in Sub-seasonal Predictability / Matthieu Chevallier, François Massonnet, Helge Goessling, Virginie Guémas, Thomas Jung. - 1 Introduction. - 2 Sea Ice in the Coupled Atmosphere-Ocean System. - 3 Sea Ice Distribution, Seasonality, and Variability. - 4 Sources of Sea Ice Predictability at the Sub-seasonal to Seasonal Timescale. - 5 Sea Ice Sub-seasonal to Seasonal - Predictability and Prediction Skill in Models. - 6 Impact of Sea Ice on Sub-seasonal Predictability. - 7 Concluding Remarks. - Acknowledgments. - 11. Sub-seasonal Predictability and the Stratosphere / Amy Butler, Andrew Charlton-Perez, Daniela I. V. Domeisen, Chaim Garfinkel, Edwin P. Gerber, Peter Hitchcock, Alexey Yu. Karpechko, Amanda C. Maycock, Michael Sigmond, Isla Simpson, Seok-Woo Son. - 1 Introduction. - 2 Stratosphere-Troposphere Coup ling in the Tropics. - 3 Stratosphere-Troposphere Coupling in the Extratropics. - 4 Predictability Related to Extratropical Stratosphere-Troposphere Coupling. - 5 Summary and Outlook. - PART Ill S2S MODELING AND FORECASTING. - 12. Forecast System Design, Configuration, and Complexity / Yuhei Takaya. - 1 Introduction. - 2 Requirements and Constraints of the Operational Sub-seasonal Forecast. - 3 Effect of Ensemble Size and Lagged Ensemble. - 4 Real-Time Forecast Configuration. - 5 Reforecast Configuration. - 6 Summary and Concluding Remarks. - Acknowledgments. - 13. Ensemble Generation: The TIGGE and S2S Ensembles / Roberto Buizza. - 1 Global Sub-seasonal and Seasonal Prediction Is an Initial Value Problem. - 2 Ensembles Provide More Complete and Valuable Information Than Single States. - 3 A Brief Introduction to Data Assimilation. - 4 A Brief Introduction to Model Uncertainty Simulation. - 5 An Overview of Operational, Global, Sub-seasonal, and Seasonal Ensembles, and Their Initialization and Generation Methods. - 6 Ensembles: Considerations About Their Future. - 7 Summary and Key Lessons. - 14. GCMs With Full Representation of Cloud Microphysics and Their MJO Simulations / In-Sik Kang, Min-Seop Ahn, Hiroaki Miura, Aneesh Subramanian. - 1 Introduction. - 2 Global CRM. - 3 Superparameterized GCM. - 4 GCM With Full Representation of Cloud Microphysics and Scale-Adaptive Convection. - 5 Summary and Conclusion. - Acknowledgments. - 15. Forecast Recalibration and Multimodel Combination / Stefan Siegert, David B. Stephenson. - 1 Introduction. - 2 Statistical Methods for Forecast Recalibration. - 3 Regression Methods. - 4 Forecast Combination. - 5 Concluding Remarks. - Acknowledgments. - 16. Forecast Verification for S2S Timescales / Caio A. S. Coelho, Barbara Brown, Laurie Wilson, Marion Mittermaier, Barbara Casati. - 1 Introduction. - 2 Factors Affecting the Design of Verification Studies. - 3 Observational References. - 4 Review of the Most Common Verification Measures. - 5 Types of S2S Forecasts and Current Verification Practices. - 6 Summary, Challenges, and Recommendations in S2S Verification. - PART IV S2S APPLICATIONS. - 17. Sub-seasonal to Seasonal Prediction of Weather Extremes / Frédérik Vitart, Christopher Cunningham, Michael Deflorio, Emanuel Dutra, Laura Ferranti, Brian Golding, Debra Hudson, Charles Jones, Christophe Lavaysse, Joanne Robbins, Michael K. Tippett. - 1 Introduction. - 2 Prediction of Large-Scale, Long-Lasting Extreme Events. - 3 Prediction of Mesoscale Events. - 4 Display and Verification of Sub-seasonal Forecasts of Extreme Events. - 5 Conclusions. - 18. Pilot Experiences in Using Seamless Forecasts for Early Action: The "Ready-Set-Go!" Approach in the Red Cross / Juan Bazo, Roop Singh, Mathieu Destrooper, Erin Coughlan de Perez. - 1 Introduction. - 2 Why Sub-seasonal?. - 3 Case Study: Peru El Niño. - 4 Reflections on the Use of S2S Forecasts. - 5 Conclusions. - 19. Communication and Dissemination of Forecasts and Engaging User Communities / Joanne Robbins, Christopher Cunningham, Rutger Dankers, Matthew Degennaro, Giovanni Dolif, Robyn Duell, Victor Marchezini, Brian Mills, Juan Pablo Sarmiento, Amber Silver, Rachel Trajber, Andrew Watkins. - 1 Introduction. - 2 Sector-Specific Methods and Practices in S2S Forecast Communication, Dissemination, and Engagement. - 3 Guiding principles for improved communication Practices. - 4 Summary and Recommendations for Future Research. - 20. Seamless Prediction of Monsoon Onset and Active/Break Phases / A.

Note: 1. Introduction 2. Overview of Linear Algebra 3. Univariate Distribution Theory 4. Multivariate Distribution Theory 5. Introduction to Calculus of Variation 6. Introduction to Control Theory 7. Optimal Control Theory 8. Numerical Solutions to Initial Value Problems 9. Numerical Solutions to Boundary Problems 10. Introduction to Semi-Langrangian Advection Methods 11. Introduction to Finite Element Modeling 12. Numerical Modeling of the Sphere 13. Tangent Linear Modeling and Adjoints 14. Observations 15. Non-variational Sequential Data Assimilation Methods 16. Variational Data Assimilation 17. Subcomponents of Variational Data Assimilation 18. Observation of Space Variation Data Assimilation Methods 19. Kalman Filter and Smoother 20. Ensemble-Based Data Asssimilation 21. Non-Gaussian Variational Data Assimilation 22. Markov Chain Monte Carlo and Particle Filter Methods 23. Applications of Data Asssimilation in the Geosciences 24. Solutions to Select Exercise Bibliography Index

Note: Contents: Section 3: Financial-Real Connections ; Chapter 17: "Wholesale Banking and Bank Runs in Macroeconomic Modelling of Financial Crises" ; Chapter 18: "Housing and Credit Markets: Bubbles and Crashes" ; Chapter 19: Macro, Money and Finance: A Continuous-Time Approach ; Chapter 20: Housing and Macroeconomics ; Chapter 21: Term Structure of Uncertainty in the Macroeconomy ; Chapter 22: Quantitative Models of Sovereign Debt Crises ; Section 4: Models of Economic Growth and Fluctuations ; Chapter 23: Families in Macroeconomics ; Chapter 24: Environmental Macroeconomics ; Chapter 25: The Staying Power of Staggered Wage and Price Setting Models in Macroeconomics ; Chapter 26: Neoclassical Models in Macroeconomics ; Chapter 27: Macroeconomics of Persistent Slumps ; Chapter 28: Macroeconomics and the Labor Market ; Section 5: Macroeconomic Policy ; Chapter 29: Challenges for Central Banks' Macro Models ; Chapter 30: Liquidity requirements, liquidity choice and financial stability ; Chapter 31: "Understanding Inflation as a Joint Monetary-Fiscal Phenomenon" ; Chapter 32: "Fiscal Multipliers: Liquidity Traps and Currency Unions" ; Chapter 33: What is a Sustainable Public Debt? ; Chapter 34: The Political Economy of Government Debt

Note: Front Cover --- Introduction to Satellite Remote Sensing --- Introduction to Satellite Remote Sensing: Atmosphere, Ocean, Land and Cryosphere Applications --- Copyright --- Dedication --- Contents --- 1 - THE HISTORY OF SATELLITE REMOTE SENSING --- 1.1 THE DEFINITION OF REMOTE SENSING --- 1.2 THE HISTORY OF SATELLITE REMOTE SENSING --- 1.2.1 THE NATURE OF LIGHT AND THE DEVELOPMENT OF AERIAL PHOTOGRAPHY --- 1.2.2 THE BIRTH OF EARTH-ORBITING SATELLITES --- 1.2.3 THE FUTURE OF POLAR-ORBITING SATELLITES --- 1.2.3.1 The Cross-Track Infrared Sounder --- 1.2.4 OTHER HISTORICAL SATELLITE PROGRAMS --- 1.2.4.1 The NIMBUS Program --- 1.2.4.2 The Landsat Program --- 1.2.4.3 The Defense Meteorological Satellite Program --- 1.2.4.4 Geostationary Weather Satellites --- 1.2.4.4.1 GOES-R --- 1.3 STUDY QUESTIONS --- 2 - BASIC ELECTROMAGNETIC CONCEPTS AND APPLICATIONS TO OPTICAL SENSORS --- 2.1 MAXWELL'S EQUATIONS --- 2.2 THE BASICS OF ELECTROMAGNETIC RADIATION --- 2.3 THE REMOTE SENSING PROCESS --- 2.4 THE CHARACTER OF ELECTROMAGNETIC WAVES --- 2.4.1 DEFINITION OF RADIOMETRIC TERMS --- 2.4.2 POLARIZATION AND THE STOKES VECTOR --- 2.4.3 REFLECTION AND REFRACTION AT THE INTERFACE OF TWO FLAT MEDIA --- 2.4.4 BREWSTER'S ANGLE --- 2.4.5 CRITICAL ANGLE --- 2.4.6 ALBEDO VERSUS REFLECTANCE --- 2.5 ELECTROMAGNETIC SPECTRUM: DISTRIBUTION OF RADIANT ENERGIES --- 2.5.1 GAMMA, X-RAY, AND ULTRAVIOLET PORTIONS OF THE ELECTROMAGNETIC SPECTRUM --- 2.5.2 VISIBLE SPECTRUM --- 2.5.3 THERMAL INFRARED SPECTRUM --- 2.5.4 MICROWAVE SPECTRUM --- 2.6 ATMOSPHERIC TRANSMISSION --- 2.6.1 SPECTRAL WINDOWS --- 2.6.2 ATMOSPHERIC EFFECTS --- 2.6.2.1 Beer-Lambert Absorption Law --- 2.6.2.2 Beer-Lambert Absorption Law: Opacity --- 2.6.2.3 Atmospheric Scattering --- 2.7 SENSORS TO MEASURE PARAMETERS OF THE EARTH'S SURFACE --- 2.8 INCOMING SOLAR RADIATION --- 2.9 INFRARED EMISSIONS --- 2.10 SURFACE REFLECTANCE: LAND TARGETS --- 2.10.1 LAND SURFACE MIXTURES --- 2.11 STUDY QUESTIONS --- 3 - OPTICAL IMAGING SYSTEMS --- 3.1 PHYSICAL MEASUREMENT PRINCIPLES --- 3.2 BASIC OPTICAL SYSTEMS --- 3.2.1 PRISMS --- 3.2.2 FILTER-WHEEL RADIOMETERS --- 3.2.2.1 An Example: The Cloud Absorption Radiometer --- 3.2.2.2 Filters --- 3.2.3 GRATING SPECTROMETER --- 3.2.4 INTERFEROMETER --- 3.3 SPECTRAL RESOLVING POWER --- THE RAYLEIGH CRITERION --- 3.4 DETECTING THE SIGNAL --- 3.5 VIGNETTING --- 3.6 SCAN GEOMETRIES --- 3.7 FIELD OF VIEW --- 3.8 OPTICAL SENSOR CALIBRATION --- 3.8.1 VISIBLE WAVELENGTHS CALIBRATION --- 3.8.2 POLARIZATION FILTERS --- 3.9 LIGHT DETECTION AND RANGING --- 3.9.1 PHYSICS OF THE MEASUREMENT --- 3.9.2 OPTICAL AND TECHNOLOGICAL CONSIDERATIONS --- 3.9.3 APPLICATIONS OF LIDAR SYSTEMS --- 3.9.4 WIND LIDAR --- 3.9.4.1 Vector Wind Velocity Determination --- 3.9.4.1.1 Velocity Azimuth Display LIDAR Vector Wind Method --- 3.9.4.1.2 Doppler Beam Swinging LIDAR Vector Wind Method --- 3.9.4.2 Direct Detection Doppler Wind LIDAR --- 3.9.4.3 LIDAR Wind Summary --- 3.10 STUDY QUESTIONS --- 4 - Microwave Radiometry --- 4.1 Basic Concepts on Microwave Radiometry --- 4.1.1 Blackbody Radiation --- 4.1.2 Gray-body Radiation: Brightness Temperature and Emissivity --- 4.1.3 General Expressions for the Emissivity --- 4.1.3.1 Simple Emissivity Models: Emission From a Perfect Specular Surface --- 4.1.3.2 Simple Emissivity Models: Emission From a Lambertian Surface --- 4.1.3.1 Simple Emissivity Models: Emission From a Perfect Specular Surface --- 4.1.3.2 Simple Emissivity Models: Emission From a Lambertian Surface --- 4.1.4 Power Collected by an Antenna Surrounded by a Blackbody --- 4.1.5 Power Collected by an Antenna Surrounded by a Gray body: Apparent Temperature and Antenna Temperature --- 4.2 The Radiative Transfer Equation --- 4.2.1 The Complete Polarimetric Radiative Transfer Equation --- 4.2.2 Usual Approximations to the Radiative Transfer Equation --- 4.3 Emission Behavior of Natural Surfaces --- 4.3.1 The Atmosphere --- 4.3.1.1 Attenuation by Atmospheric Gases --- 4.3.1.2 Attenuation by Rain --- 4.3.1.3 Attenuation by Clouds and Fog --- 4.3.2 The Ionosphere --- 4.3.2.1 Faraday Rotation --- 4.3.2.2 Ionospheric Losses: Absorption and Emission --- 4.3.3 Land Emission --- 4.3.3.1 Soil Dielectric Constant Models --- 4.3.3.2 Bare Soil Emission --- 4.3.3.3 Vegetated Soil Emission --- 4.3.3.4 Snow-Covered Soil Emission --- 4.3.3.5 Topography Effects --- 4.3.4 Ocean Emission --- 4.3.4.1 Water Dielectric Constant Behavior --- 4.3.4.2 Calm Ocean Emission --- 4.3.4.2.1 Influence of the Salinity --- 4.3.4.2.2 Influence of Frequency --- 4.3.4.2.3 Influence of the Water Temperature --- 4.3.4.3 Influence of the Sea State --- 4.3.4.3.1 Influence of the Look Angle --- 4.3.4.4 Emissivity of the Sea Surface Covered With Oil --- 4.3.4.5 Emissivity of the Sea Ice Surface --- 4.4 Understanding Microwave Radiometry Imagery --- 4.5 Applications of Microwave Radiometry --- 4.6 Sensors --- 4.6.1 Historical Review of Microwave Radiometers and Frequency Bands Used --- 4.6.2 Microwave Radiometers: Basic Performance --- 4.6.2.1 Spatial Resolution --- 4.6.2.1.1 Real Aperture Radiometers --- 4.6.2.1.2 Synthetic Aperture Radiometers --- 4.6.2.2 Radiometric Resolution --- 4.6.2.2.1 Real Aperture Radiometers --- 4.6.2.2.2 Synthetic Aperture Radiometers --- 4.6.2.3 Trade-off Between Spatial Resolution and Radiometric Precision --- 4.6.3 Real Aperture Radiometers --- 4.6.3.1 Instrument Considerations --- 4.6.3.1.1 Antenna Considerations --- 4.6.3.1.2 Receiver Considerations --- 4.6.3.1.3 Sampling Considerations --- 4.6.3.2 Types of Real Aperture Radiometers --- 4.6.3.3 Radiometer Calibration --- 4.6.3.3.1 External Calibration --- 4.6.3.3.1.1 Using Hot and Cold Targets --- 4.6.3.3.1.2 Fully Polarimetric Radiometer Calibration Using External Targets --- 4.6.3.3.1.3 Tip Curves --- 4.6.3.3.1.4 Earth Targets: Vicarious Calibration --- 4.6.3.3.2 Internal Calibration --- 4.6.3.3.3 Radiometer Linearity --- 4.6.3.4 Radio Frequency Interference Detection and Mitigation --- 4.6.3.5 Example: Special Sensor Microwave Imager Radiometric and Geometric Corrections --- 4.6.4 Synthetic Aperture Radiometers --- 4.6.4.1 Types of Synthetic Aperture Radiometers --- 4.6.4.1.1 Mills Cross --- 4.6.4.1.2 Synthetic Aperture Radiometers using Matched Filtering --- 4.6.4.1.3 Synthetic Aperture Radiometers using Fourier Synthesis --- 4.6.4.1.3.1 1D Synthetic Aperture Radiometers: Array Thinning --- 4.6.4.1.3.2 2D Synthetic Aperture Radiometers: Array Topologies --- 4.6.4.1.3.3 Other Synthetic Aperture Radiometer Concepts --- 4.6.4.2 Radiometer Calibration --- 4.6.4.2.1 Internal Calibration --- 4.6.4.2.2 External Calibration --- 4.6.4.3 Image Reconstruction --- 4.6.4.4 ESA's SMOS Mission and the MIRAS Instrument --- 4.6.5 Future Trends in Microwave Radiometers --- 4.7 Study Questions --- 5 - RADAR --- 5.1 A COMPACT INTRODUCTION TO RADAR THEORY --- 5.1.1 REMOTE RANGING --- 5.1.2 DOPPLER ANALYSIS --- 5.2 RADAR SCATTERING --- 5.2.1 RADAR FREQUENCY BANDS --- 5.2.2 NORMALIZATIONS OF THE RADAR REFLECTIVITY --- 5.2.3 POINT VERSUS DISTRIBUTED SCATTERERS --- 5.2.4 SPECKLE, MULTILOOK, AND RADIOMETRIC RESOLUTION --- 5.2.5 RADAR EQUATION --- 5.2.6 RADAR WAVES AT AN INTERFACE --- 5.2.7 MULTIPLE REFLECTIONS: DOUBLE BOUNCE, TRIPLE BOUNCE, AND URBAN AREAS --- 5.2.8 BACKSCATTERING OF SURFACES --- 5.2.9 PERIODIC SCATTERING: THE BRAGG MODEL --- 5.2.10 BACKSCATTERING OF VOLUMES --- 5.2.11 OVERALL SUMMARY OF RADAR BACKSCATTER --- 5.2.12 DEPOLARIZATION OF RADAR WAVES --- 5.3 RADAR SYSTEMS --- 5.3.1 RANGE-DOPPLER RADARS --- 5.3.2 OPTIMAL RECEIVER FOR A SINGLE ECHO: THE MATCHED FILTER --- 5.3.3 MATCHED FILTER VERSUS INVERSE FILTER --- 5.3.4 OPTIMAL RECEIVER FOR RANGE-DOPPLER RADAR ECHOES: THE BACKPROJECTION OPERATOR --- 5.3.5 RADAR WAVEFORMS --- 5.3.6 A PARADIGMATIC EXAMPLE: LINEAR FREQUENCY MODULATED PULSES (CHIRPS) --- 5.3.7 GEOMET

Note: Contents: Section 1: The Facts of Economic Growth and Economic Fluctuation ; Chapter 1: RBC Methodology and the Development of Aggregate Economic Theory ; Chapter 2: The Facts of Economic Growth ; Chapter 3: Macroeconomic Shocks and Their Propagation ; Chapter 4: Macroeconomic Regimes and Regime Shifts ; Chapter 5: The Macroeconomics of Time Allocation ; Chapter 6: "Who Bears the Cost of Recessions? The Role of House Prices and Household Debt" ; Chapter 7: "Allocative and Remitted Wages: New Facts and Challenges for Keynesian Models" ; Chapter 8: Financial and Fiscal Crises ; Section 2: The Methodology of Macroeconomics ; Chapter 9: Factor Models and Structural Vector Autoregressions in Macroeconomics ; Chapter 10: Solution and Estimation Methods for DSGE Models ; Chapter 11: Recursive Contracts and Endogenously Incomplete Markets ; Chapter 12: Macroeconomics and Household Heterogeneity ; Chapter 13: Natural Experiments in Macroeconomics ; Chapter 14: Accounting for Business Cycles ; Chapter 15: "Incomplete Information in Macroeconomics: Accommodating Frictions in Coordination" ; Chapter 16: New Methods for Macro-Financial Model Comparison and Policy Analysis