Acknowledgments 1 Droughts, governance, disasters, and response systems 1.1 20th-century droughts—disasters and the El Niño–Southern Oscillation 1.2 21st-century droughts—developing effective early warning systems References 2 Drought early warning—definitions, challenges, and opportunities 2.1 Definitions—supply and demand, the many flavors of “dry” 2.2 Droughts—when water demand exceeds water supply 2.3 Slow-onset disasters 2.4 Quantifying drought magnitude in multiple dimensions 2.5 Impact-based sectoral or disciplinary definitions of drought 2.6 Contrasting recent U.S. and southern African droughts 2.7 Chapter review References 3 Drought early warning systems 3.1 The U.S. National Integrated Drought Information System 3.2 The Famine Early Warning Systems Network 3.3 Famine Early Warning Systems Network Food Security Outlooks 3.4 Multistage early warning—an Ethiopia example References Further reading 4 Tools of the trade 1—weather and climate forecasts 4.1 Examples of operational drought forecasting systems 4.1.1 U.S. Climate Prediction Center’s monthly and seasonal drought outlook 4.1.2 Famine Early Warning Systems Network food insecurity outlook 4.1.3 Miscellaneous application of weather and climate forecasts for drought forecasting 4.2 Methods of weather and climate forecasts 4.2.1 Climatological forecasts 4.2.2 Persistence-based forecasts 4.2.3 Analog forecasts 4.2.4 Statistical forecasts 4.2.5 Dynamical forecasting 4.3 Sources of weather and climate forecast skill 4.4 Summary References Further reading 5 Tools of the trade 2—land surface models 5.1 Introduction 5.2 An overview of land surface models 5.3 Operational land surface models–based drought monitors 5.3.1 National Center for Environmental Prediction’s North American Land Data Assimilation System (NLDAS) drought monitor 5.3.2 Africa Flood and Drought monitor 5.3.3 Global soil moisture monitoring 5.3.4 The Famine Early Warning Systems Network land data assimilation system 5.4 Limitations of drought monitoring using land surface models 5.5 Summary References 6 Tools of the trade 3—mapping exposure and vulnerability 6.1 Exposure and vulnerability 6.1.1 Exposure—an example for East Africa 6.1.2 Vulnerability 6.1.3 An Ethiopia case study 6.2 Conclusion References 7 Theory—understanding atmospheric demand in a warming world 7.1 Background 7.2 Reference evapotranspiration resistance terms 7.3 Defining reference crop evapotranspiration 7.4 The FAO 56 Penman–Monteith formulation 7.5 Temperature alone is insufficient to estimate reference evapotranspiration 7.6 Reference evapotranspiration decompositions and Morton’s complementary hypothesis 7.7 Spatiotemporal variations in reference evapotranspiration and actual evapotranspiration, and their relationship to vuln... References 8 Theory—indices for measuring drought severity 8.1 Introduction 8.1.1 Consider multiple expressions of each individual data source 8.2 Length of record and nonstationary systematic errors 8.2.1 Frequently used satellite and “combination” drought indicators and indices 8.3 Per capita water availability 8.4 Summary and discussion References 9 Sources of drought early warning skill, staged prediction systems, and an example for Somalia 9.1 The ocean as a source of skill 9.2 Skill from persistent atmospheric conditions 9.3 Predictive skill from the land surface 9.4 Staged opportunities for prediction support defense-in-depth 9.4.1 Stage 1: long-lead climate forecast 9.4.2 Stage 2: short-lead climate forecasts 9.4.3 Stage 3: mid-season climate/weather forecasts 9.4.4 Stage 4: late-season impact assessments 9.5 Summary: staged strategies for effective early warning 9.6 Conclusion References 10 Practice—evaluating forecast skill 10.1 Introduction 10.2 Deterministic forecast skill scores 10.2.1 Pearson’s correlation 10.2.1.1 Higher skill at lower lead 10.2.1.2 Lower skill in forecasting terrestrial precipitation 10.2.2 Spearman’s rank correlation 10.2.3 Equitable threat score (Gilbert skill score) 10.3 Probabilistic forecast skill scores 10.3.1 Brier skill score 10.3.2 Ranked probability skill score 10.3.3 Reliability diagram 10.4 Summary References 11 Practice—integrating observations and climate forecasts 11.1 Approach 11.2 Bias-correction and downscaling methods 11.2.1 Bias-correction and spatial downscaling method 11.2.1.1 Bias-correction 11.2.1.2 Spatial downscaling 11.2.2 Constructed analog method 11.2.3 Multivariate Adaptive Constructed Analogs 11.2.4 Bayesian merging 11.3 An example: The NASA Hydrological and Forecast Analysis System 11.4 Summary References 12 Practice—actionable information and decision-making networks 12.1 Actionable information and the three pillars 12.2 Actionable information and decision-making networks—an example from famine early warning in East Africa 12.3 Conclusion