Drought Early Warning and Forecasting - Chris Funk, Shraddhanand Shukla

Drought Early Warning and Forecasting

Theory and Practice
Buch | Softcover
238 Seiten
2020
Elsevier Science Publishing Co Inc (Verlag)
978-0-12-814011-6 (ISBN)
127,20 inkl. MwSt
Drought risk management involves three pillars: drought early warning, drought vulnerability and risk assessment, and drought preparedness, mitigation, and response. This book collects in one place a description of all the key components of the first pillar, and describes strategies for fitting these pieces together. The best modern drought early warning systems incorporate and integrate a broad array of environmental information sources: weather station observations, satellite imagery, land surface and crop model simulations, and weather and climate model forecasts, and analyze this information in context-relevant ways that take into account exposure and vulnerability. Drought Early Warning and Forecasting: Theory and Practice assembles a comprehensive overview of these components, providing examples drawn from the Famine Early Warning Systems Network and the United States Drought Monitor. This book simultaneously addresses the physical, social, and information management aspects of drought early warning, and informs readers about the tools, techniques, and conceptual models required to effectively identify, predict, and communicate potential drought-related disasters.

This book is a key text for postgraduate scientists and graduate and advanced undergraduate students in hydrology, geography, earth sciences, meteorology, climatology, and environmental sciences programs. Professionals dealing with disaster management and drought forecasting will also find this book beneficial to their work.

Chris Funk is a senior scientist with the U.S. Geological Survey Earth Resources Observation and Science Center and Research Director for the Climate Hazards Center at University of California, Santa Barbara, United States. Since 1999 he has worked closely with the Famine Early Warning Systems Network, developing new techniques, data sets, and methods for improved drought early warning. He has published over 140 papers and reports, and currently helps guide the development of early warning and climate adaptation science for the U.S. Geological Survey, working closely with partners from UCSB, USAID, NASA, and NOAA. Shraddhanand Shukla is a researcher with the Climate Hazards Center at the University of California, Santa Barbara, United States. He is a large-scale hydrologist with primary research interests and over 10 years of experience in drought monitoring and forecasting. He has published over 45 peer-reviewed journal articles. His current work, which is funded by NASA, NOAA, USAGS, USAID, NSF, etc., focuses primarily on improving existing drought monitoring and early warning capabilities nationally (California and Nevada region) and internationally (primarily Africa and the Middle East) using remote sensing datasets, large-scale hydrologic models, and weather/climate forecasts.

1. Droughts, governance, disasters, and response systems2. Drought early warning—definitions, challenges, and opportunities3. Drought early warning systems4. Tools of the trade 1—weather and climate forecasts5. Tools of the trade 2—land surface models6. Tools of the trade 3—mapping exposure and vulnerability7. Theory—understanding atmospheric demand in a warming world8. Theory—indices for measuring drought severity9. Sources of drought early warning skill, staged prediction systems, and an example for Somalia10. Practice—evaluating forecast skill11. Practice—integrating observations and climate forecasts12. Practice—actionable information and decision-making networks13. Final thoughts

Erscheinungsdatum
Sprache englisch
Maße 152 x 229 mm
Gewicht 390 g
Themenwelt Naturwissenschaften Biologie Ökologie / Naturschutz
Naturwissenschaften Geowissenschaften Hydrologie / Ozeanografie
Naturwissenschaften Geowissenschaften Meteorologie / Klimatologie
ISBN-10 0-12-814011-9 / 0128140119
ISBN-13 978-0-12-814011-6 / 9780128140116
Zustand Neuware
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