Radar Hydrology Principles, Models, and Applications

Radar Hydrology: Principles, Models, and Applications provides graduate students, operational forecasters, and researchers with a theoretical framework and practical knowledge of radar precipitation estimation. The only text on the market solely devoted to radar hydrology, this comprehensive reference:

• Begins with a brief introduction to radar
• Focuses on the processing of radar data to arrive at accurate estimates of rainfall
• Addresses advanced radar sensing principles and applications
• Covers radar technologies for observing each component of the hydrologic cycle
• Examines state-of-the-art hydrologic models and their inputs, parameters, state variables, calibration procedures, and outputs
• Discusses contemporary approaches in data assimilation
• Concludes with methods, case studies, and prediction system design
• Includes downloadable MATLAB® content

Flooding is the #1 weather-related natural disaster worldwide. Radar Hydrology: Principles, Models, and Applications aids in understanding the physical systems and detection tools, as well as designing prediction systems.

Introduction to Basic Radar Principles. Radar Quantitative Precipitation Estimation. Polarimetric Radar Quantitative Precipitation Estimation. Multi-Radar Multi-Sensor (MRMS) Algorithm. Advanced Radar Technologies for Quantitative Precipitation Estimation. Radar Technologies for Observing the Water Cycle. Radar QPE for Hydrologic Modeling. Flash Flood Forecasting.

Yang Hong is a professor of hydrometeorology and remote sensing in the School of Civil Engineering and Environmental Sciences, adjunct faculty member with the School of Meteorology, co-director of the WaTER Center, faculty member with the Advanced Radar Research Center, and affiliated member of the Center for Analysis and Prediction of Storms at the University of Oklahoma. Dr. Hong also directs the HyDROS Lab at the National Weather Center. Previously, he was a research scientist at NASA's Goddard Space Flight Center and postdoctoral researcher at University of California, Irvine. He holds a BS and MS from Peking (Beijing) University, China and Ph.D from the University of Arizona.

Jonathan J. Gourley is a research hydrologist with the NOAA/National Severe Storms Laboratory and affiliate associate professor with the School of Meteorology at the University of Oklahoma. His research interests include hydrologic prediction across scales ranging from water resources management to early warning of extreme events. Dr. Gourley was the principal inventor of a multisensor rainfall algorithm that was expanded to encompass all radars in North America and deployed to several foreign countries for operational use. He also assembled a comprehensive database that is being used to develop FLASH—a real-time flash flood forecasting system. He holds a BS, MS, and Ph.D from the University of Oklahoma.