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  • Format: ePub

Extreme 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…mehr

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  • Größe: 14.25MB
Produktbeschreibung
Extreme 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

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Autorenporträt
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 comeDr. 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