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Cover image for Radar hydrology :    principles, models, and applications
Title:
Radar hydrology : principles, models, and applications
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Publication Information:
Boca Raton, FL: CRC Press, 2015
Physical Description:
xiv, 182 pages : illustrations, maps ; 24 cm.
ISBN:
9781466514614
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30000010342001 GB656.2.R3 H66 2015 Open Access Book Book
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Summary

Summary

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 MATLABĀ® 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.


Author Notes

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.


Table of Contents

Prefacep. ix
Acknowledgmentsp. xi
About the Authorsp. xiii
1 Introduction to Basic Radar Principlesp. 1
1.1 Radar Componentsp. 1
1.2 The Radar Beamp. 3
1.3 The Radar Pulsep. 8
1.4 Signal Processingp. 11
Referencesp. 16
2 Radar Quantitative Precipitation Estimationp. 17
2.1 Radar Calibrationp. 17
2.2 Quality Controlp. 19
2.2.1 Signal Processingp. 19
2.2.2 Fuzzy Logicp. 20
2.3 Precipitation Rate Estimationp. 24
2.4 Vertical Profile of Reflectivityp. 26
2.5 Rain Gauge Adjustmentp. 28
2.6 Space-Time Aggregationp. 30
2.7 Remaining Challengesp. 32
2.8 Uncertainty Estimationp. 34
Referencesp. 37
3 Polarimetric Radar Quantitative Precipitation Estimationp. 41
3.1 Polarimetric Radar Variablesp. 41
3.2 Polarimetric Radar Data Quality Controlp. 43
3.2.1 Noise Effect and Reductionp. 44
3.2.2 Clutter Detection and Removalp. 44
3.2.3 Attenuation Correctionp. 45
3.2.4 Calibrationp. 47
3.2.5 Self-Consistency Checkp. 47
3.3 Hydrometeor Classificationp. 48
3.3.1 Polarimetric Characteristics of Radar Echoesp. 49
3.3.2 Classification Algorithmsp. 49
3.4 Polarimetric Radar-Based QPEp. 51
3.5 Microphysical Retrievalsp. 55
3.5.1 Raindrop Size Distribution Modelp. 55
3.5.2 DSD Retrievalp. 56
3.5.3 Snowfall and Hail Estimationp. 58
3.5.4 Validationp. 59
Referencesp. 61
4 Multi-Radar Multi-Sensor (MRMS) Algorithmp. 67
4.1 Single-Radar Processingp. 69
4.1.1 Dual-Polarization Quality Controlp. 69
4.1.2 Vertical Profile of Reflectivity Correctionp. 70
4.1.3 Product Generationp. 73
4.2 Precipitation Typologyp. 75
4.3 Precipitation Estimationp. 77
4.4 Verificationp. 80
4.5 Discussionp. 84
Referencesp. 85
5 Advanced Radar Technologies for Quantitative Precipitation Estimationp. 87
5.1 Mobile and Gap-Filling Radarsp. 88
5.1.1 ARRC's Shared Mobile Atmospheric Research and Teaching Radar (SMART-R)p. 88
5.1.2 NSSL's X-Band Polarimetric Mobile Radar (NOXP)p. 90
5.1.3 ARRC's Atmospheric Imaging Radar (AIR)p. 91
5.1.4 ARRC's Polarimetric X-Band 1000 (PX-1000)p. 93
5.1.5 Collaborative Adaptive Sensing of the Atmosphere (CASA)p. 94
5.2 Spaceborne Radarsp. 95
5.2.1 Precipitation Radar aboard TRMMp. 95
5.2.2 Dual-Frequency Precipitation Radar aboard NASA GPMp. 100
5.3 Fhased-Atray Radarp. 101
5.3.1 Design Aspects and Product Resolutionp. 101
5.3.2 Dual Polarizationp. 102
5.3.3 Impact on Hydrologyp. 104
Referencesp. 106
6 Radar Technologies for Observing the Water Cyclep. 109
6.1 The Hydrologic Cyclep. 109
6.2 Surface Waterp. 112
6.2.1 Stream flow Radarp. 112
6.2.2 Surface Water Altimetryp. 114
6.2.3 Synthetic Aperture Radarp. 116
6.3 Subsurface Waterp. 117
6.3.1 L-Band Radarp. 118
6.3.2 C-Band Radarp. 118
6.3.3 Ground-Penetrating Radarp. 119
6.4 Subsurface Waterp. 124
Referencesp. 126
7 Radar QPE for Hydrologic Modelingp. 129
7.1 Overview of Hydrological Modelsp. 129
7.1.1 Model Classesp. 129
7.1.2 Model Parametersp. 134
7.1.3 Model State Variables and Data Assimilationp. 135
7.1.4 Hydrological Model Evaluationp. 142
7.2 Hydrological Evaluation of Radar QPEp. 145
7.2.1 Case Study in Ft. Cobb Basin, Oklahomap. 146
7.2.2 Evaluation with a Hydrologic Model Calibrated to a Reference QPEp. 149
7.2.3 Evaluation with Monte Carlo Simulations from a Hydrologic Modelp. 151
7.2.4 Evaluation with a Hydrologic Model Calibrated to Individual QPEsp. 153
Referencesp. 154
8 Flash Flood Forecastingp. 157
8.1 Flash Flood Guidancep. 158
8.2 Flash Flood Guidance: Historyp. 162
8.3 Lumped Flash Flood Guidancep. 164
8.4 Flash Flood Potential Indexp. 165
8.5 Gridded Flash Flood Guidancep. 166
8.6 Comments on the Use of Flash Flood Guidancep. 168
8.7 Threshold Frequency Approachp. 169
Referencesp. 172
Indexp. 175
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