Hydrometeorology (eBook, PDF)
Forecasting and Applications
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This book provides an introduction to recent developments in the area of hydrome- orological forecasting, with a focus on water-related applications of meteorological observation and forecasting techniques. The Encylopaedia Britannica de?nes hydrometeorology as a branch of met- rology that deals with problems involving the hydrologic cycle, the water budget and the rainfall statistics of storms...(continued). The topic spans a wide range of disciplines, including raingauge, weather radar, satellite, river and other monitoring techniques, rainfall-runoff, ?ow routing and hydraulic models, and n...
This book provides an introduction to recent developments in the area of hydrome- orological forecasting, with a focus on water-related applications of meteorological observation and forecasting techniques. The Encylopaedia Britannica de?nes hydrometeorology as a branch of met- rology that deals with problems involving the hydrologic cycle, the water budget and the rainfall statistics of storms...(continued). The topic spans a wide range of disciplines, including raingauge, weather radar, satellite, river and other monitoring techniques, rainfall-runoff, ?ow routing and hydraulic models, and nowcasting and Numerical Weather Prediction techniques. Applications include ?ood forecasting, drought forecasting, climate change impact assessments, reservoir management, and water resources and water quality studies. The emphasis in this book is on hydrometeorological forecasting techniques, which are usually distinguished from prediction or simulation studies in that es- mates are provided for a speci?c time or period in the future, rather than for typical past, current or future conditions. Often this requires the use of real-time obser- tions and/or forecasts of meteorological conditions as inputs to hydrological models. The availability of information on current conditions also means that - parti- larly for short lead times - data assimilation techniques can be used to improve model outputs; typically by adjusting the model inputs, states or parameters, or by post-processing the outputs based on the differences between observed and forecast values up to the time of the forecast.
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