Extreme Weather Forecasting
- 1st Edition - October 11, 2022
- Imprint: Elsevier
- Editors: Marina Astitha, Efthymios I. Nikolopoulos
- Language: English
- Paperback ISBN:9 7 8 - 0 - 1 2 - 8 2 0 1 2 4 - 4
- eBook ISBN:9 7 8 - 0 - 1 2 - 8 2 0 2 4 3 - 2
Extreme Weather Forecasting reviews current knowledge about extreme weather events, including key elements and less well-known variables to accurately forecast them. The book c… Read more
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Request a sales quoteExtreme Weather Forecasting reviews current knowledge about extreme weather events, including key elements and less well-known variables to accurately forecast them. The book covers multiple temporal scales as well as components of current weather forecasting systems. Sections cover case studies on successful forecasting as well as the impacts of extreme weather predictability, presenting a comprehensive and model agnostic review of best practices for atmospheric scientists and others who utilize extreme weather forecasts.
- Reviews recent developments in numerical prediction for better forecasting of extreme weather events
- Covers causes and mechanisms of high impact extreme events and how to account for these variables when forecasting
- Includes numerous case studies on successful forecasting, outlining why they worked
Atmospheric Sciences. Earth Sciences, Environmental Engineering, Environmental Sciences
- Cover image
- Title page
- Table of Contents
- Copyright
- List of contributors
- Foreword
- Preface
- Chapter 1. Overview of extreme weather events, impacts and forecasting techniques
- Abstract
- Subchapter 1.1. Definition of extreme weather events
- 1.1.1 Extreme heat
- 1.1.2 Extreme cold—severe winter storms
- 1.1.3 Tropical and extratropical storms
- 1.1.4 Severe convective storms
- 1.1.5 Extreme rainfall
- Subchapter 1.2. Weather forecasting
- Subchapter 1.3. Extreme weather forecasting in urban areas
- 1.3.1 Introduction
- 1.3.2 Urban heat island
- 1.3.3 Heat wave forecasting
- 1.3.4 Air quality modeling and prediction
- 1.3.5 Forecasting urban precipitation
- 1.3.6 Forecasting coastal urban flooding
- Subchapter 1.4. Wildfires and weather
- 1.4.1 Introduction: wildfires and weather—a coupled system
- 1.4.2 Wildfire prediction and risk assessment
- 1.4.3 Data requirements and data quality
- 1.4.4 Wildfire prediction sensitivities and uncertainties
- 1.4.5 Improved wildfire modeling for improved wildfire preparedness
- Chapter 2. Operational multiscale predictions of hazardous events
- Abstract
- 2.1 Introduction
- 2.2 Example case: 2015 European heatwave
- 2.3 Key factors of predictability
- 2.4 Hazard forecasting
- 2.5 Evaluation of hazardous events
- 2.6 Conclusion
- 2.7 Summary
- References
- Chapter 3. Forecasting extreme weather events and associated impacts: case studies
- Subchapter 3.1. Extreme heat
- 3.1.1 Introduction
- 3.1.2 Data
- 3.1.3 Methodology
- 3.1.4 Results
- 3.1.5 Conclusions
- Acronyms
- Subchapter 3.2. Atmospheric rivers
- 3.2.1 Introduction
- 3.2.2 Atmospheric river evolution
- 3.2.3 Forecasting atmospheric rivers
- 3.2.4 Regional models
- 3.2.5 Ensemble forecast systems
- 3.2.6 Verification
- 3.2.7 Decision support
- 3.2.8 Summary
- Subchapter 3.3. The hydrological Hillslope-Link Model for space-time prediction of streamflow: insights and applications at the Iowa Flood Center
- 3.3.1 Introduction
- 3.3.2 A generic set of ordinary differential equations to model water flows in the landscape and the river network
- 3.3.3 Domain decomposition and model inputs for the implementation of Hillslope-Link Model
- 3.3.4 Example of model performance using different configurations of vertical and horizonal fluxes at the hillslope scale
- 3.3.5 Insights and real-time applications of the Hillslope-Link Model at the Iowa Flood Center
- 3.3.6 Summary and conclusions
- 3.3.7 Future work and upcoming challenges
- Acknowledgments
- Subchapter 3.4. Social impacts: integrating dynamic social vulnerability in impact-based weather forecasting
- 3.4.1 Drivers of social impacts from extreme weather events
- 3.4.2 The need for integrated forecasting tools to anticipate social impacts
- 3.4.3 Insights of methodological advances in modeling the coupled sociohydrometeorological system in high-impact weather events
- 3.4.4 Toward operational decision-making in high-impact weather events: insights from a participatory role-playing experiment
- 3.4.5 Conclusion
- Subchapter 3.5. Landslides and debris flows
- 3.5.1 Introduction
- 3.5.2 Data and methodology
- 3.5.3 Results
- 3.5.4 Discussion
- 3.5.5 Conclusions
- Acknowledgments
- Subchapter 3.6. Weather-induced power outages
- 3.6.1 Power grid outages and severe weather
- 3.6.2 Modeling weather impact on the electric grid
- Afterword
- Index
- Edition: 1
- Published: October 11, 2022
- Imprint: Elsevier
- No. of pages: 358
- Language: English
- Paperback ISBN: 9780128201244
- eBook ISBN: 9780128202432
MA
Marina Astitha
Dr. Marina Astitha is an Associate Professor and the Associate Department Head at the Department of Civil and Environmental Engineering, University of Connecticut (UConn). Dr. Astitha’s expertise lie in the areas of atmospheric numerical modeling (weather and air quality) from regional to global scales. She is leading the Atmospheric Modeling and Air Quality Group since joining UConn in 2013. Her research program focuses on improving the prediction of extreme weather events, wind prediction for wind farm facilities, and integration of multi-media modeling systems with machine learning to solve environmental problems. She is committed in supporting, mentoring, and inspiring the next generation of engineers to innovate, lead and thrive in solving complex environmental problems and sustain a healthy, diverse and equitable society in the years to come
Affiliations and expertise
Associate Professor, Associate Department Head, Department of Civil and Environmental Engineering, School of Engineering, University of Connecticut, CT, USAEN
Efthymios I. Nikolopoulos
Dr. Efthymios Nikolopoulos is Associate Professor at the Department of Civil and Environmental Engineering at Rutgers University. His research focuses on the integration of remote sensing observations with numerical and statistical modeling to advance understanding and predictability of water cycle components and weather-related hazards. Dr. Nikolopoulos has authored/co-authored more than 70 peer-reviewed publications and 8 book chapters in the areas of hydrometeorology, remote sensing of precipitation, flood hydrology and landslide/debris flow prediction. He is an Associate Editor for the Journal of Hydrology and the recipient of the NASA Earth System Science Graduate Fellowship and the Marie Curie Postdoctoral fellowship
Affiliations and expertise
Civil and Environmental Engineering, Rutgers University, New Brunswick, NJ, USARead Extreme Weather Forecasting on ScienceDirect