Forecast Verification A Practitioner s Guide in Atmospheric Science 1st Edition by Ian T Jolliffe, David B Stephenson ISBN 0471497592 9780471497592

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ISBN 10: 0471497592 
ISBN 13: 9780471497592
Author:  Ian T Jolliffe, David B Stephenson

This handy reference introduces the subject of forecast verification and provides a review of the basic concepts, discussing different types of data that may be forecast.

Each chapter covers a different type of predicted quantity (predictand), then looks at some of the relationships between economic value and skill scores, before moving on to review the key concepts and summarise aspects of forecast verification that receive the most attention in other disciplines.

The book concludes with a discussion on the most important topics in the field that are the subject of current research or that would benefit from future research.

• An easy to read guide of current techniques with real life case studies

• An up-to-date and practical introduction to the different techniques and an examination of their strengths and weaknesses

• Practical advice given by some of the world?s leading forecasting experts

• Case studies and illustrations of actual verification and its interpretation

• Comprehensive glossary and consistent statistical and mathematical definition of commonly used terms

Forecast Verification A Practitioner s Guide in Atmospheric Science 1st Table of contents:

Part I: General Principles

• Chapter 1: Introduction

  • What is Forecast Verification?
  • Why Verify?
  • Goodness, Quality, and Value
  • Different Types of Forecasts
  • Elements of the Verification Process
  • Structure of the Book

• Chapter 2: Basic Concepts

  • Forecast and Observation Types
  • Contingency Tables
  • Joint and Conditional Probabilities
  • Attributes of Forecasts
  • The Verification Dataset
  • Reference Forecasts
  • Sampling Issues
  • Statistical Significance

• Chapter 3: Decision Making and Economic Value

  • The Cost/Loss Model
  • Decision Theory and Utility Functions
  • Economic Value of Forecasts
  • Value of Different Forecast Types
  • Relationship between Quality and Value

Part II: Verification of Different Types of Forecasts

• Chapter 4: Verification of Deterministic Forecasts for Continuous Variables

  • Errors and Error Measures (e.g., Mean Error, MAE, RMSE)
  • Skill Scores
  • Decomposition of Error Scores (e.g., MSE decomposition)
  • Measures of Association (e.g., Correlation Coefficient)
  • Spatial Verification
  • Time Series Verification

• Chapter 5: Verification of Deterministic Forecasts for Categorical Variables

  • Metrics from Contingency Tables (e.g., POD, FAR, CSI, Bias Score)
  • Skill Scores for Categorical Forecasts (e.g., Peirce Skill Score, Equitable Threat Score)
  • Measures for Rare Events
  • Multiple Categories

• Chapter 6: Verification of Probability Forecasts

  • The Attributes Diagram (Reliability Diagram, Resolution, Discrimination)
  • Brier Score and its Decomposition
  • Ranked Probability Score
  • Ignorance Score
  • ROC Curves (Receiver Operating Characteristic)
  • Cost-Loss Ratio and Economic Value for Probabilistic Forecasts

• Chapter 7: Verification of Ensemble Forecasts

  • Measures of Ensemble Reliability and Resolution
  • Rank Histogram (Talagrand Diagram)
  • Spread-Skill Relationship
  • Measures for Probabilistic Forecasts from Ensembles
  • Quantile Forecasts
  • Verification of Extreme Events

• Chapter 8: Verification of Forecasts for Special Phenomena

  • Verification of Climate Forecasts (longer timescales, calibration)
  • Verification of High-Impact Weather (e.g., severe storms, floods)
  • Verification of Short-Range Forecasts (Nowcasting)
  • Verification of Spatial Fields

Part III: Practical Aspects and Advanced Topics

• Chapter 9: The Verification System

  • Designing a Verification Scheme
  • Data Requirements and Management
  • Software Tools for Verification
  • Reporting and Communication of Verification Results
  • Ethical Issues in Verification

• Chapter 10: Advanced Topics in Verification

  • Attribution and Decomposition of Skill
  • Covariance and Correlation-Based Approaches
  • Resampling and Bootstrapping for Uncertainty Estimation
  • Advanced Spatial Verification Techniques
  • Object-Based Verification
  • Fuzzy Verification
  • Verification of Forecast Extremes
  • Combining Multiple Verification Metrics

• Chapter 11: Case Studies and Examples

  • Illustrative examples applying different verification methods to real-world scenarios.

• Chapter 12: Future Directions in Forecast Verification

  • Emerging Challenges and Research Areas
  • Integration of Verification into the Forecasting Process

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Tags: Ian T Jolliffe, David B Stephenson, Forecast, Verification