The origins of radar date back to World War II， when they provided a new and unique capability to detect enemy aircraft， submarines on the ocean surface， and ships.Radar not only changed the face of the war， but once it became adapted to observe the weather， it led to a revolution in meteorology. It has been instrumental in the study of severe thunderstorms， identification of rotation associated with meso cyclones and tornadoes， detection of severe hail and damaging winds， and estimation of heavy rainfall associated with flash floods.For these reasons， many countries throughout the world have invested in large radar networks for routine observations used to warn the public of these imminent weather hazards.
This book focuses on the use of radars in hydrology.Weather radars haveproven their value for remote sensing of precipitation， even at high enoughresolution to monitor and predict the onset of flash floods.But the processto arrive at an accurate estimate of precipitation from the raw radar signalis not a straightforward one.For this reason， five chapters of this book arededicated to radar-based precipitation estimation alone.Graduate students，operational forecasters， and researchers will acquire the theoretical frame-work and practical experience behind radar precipitation estimation.We present new radar technologies that will improve the accuracy andresolution of precipitation estimates.The description of these platforms， some of which are mobile or transportable， does not attempt to comprehensively cover all new radar technologies.Rather， we focus on platforms that are more familiar to the authors.Likewise， several of the studies we highlight reflect our own experiences with those observing platforms， basins， and method- ologies.We supply complete bibliographies and encourage the interested reader to explore those other studies to gain a more holistic understanding of the topics presented herein.
We believe the next revolution in hydrology will be initiated by radar remote sensing of additional variables going beyond precipitation.Space-based，airborne， and ground-based radars operating at multiple frequencies can be used to detect and measure surface water spatial extent and depth， stream dis- charge， near-surface soil moisture， subsurface water， and depth to the water table.Radars are now providing insights into water storage and fluxes in regions that have only scarcely been observed.These new observations will influence new hydrologic theories， formulations， and basic understanding. Moreover， accurate estimation of the freshwater storage on Earth will provide the pulse of the planet's climate state.

Preface ix

Acknowledgments xi

About the Authors xi

1 Introduction to Basic Radar Principles 1

1.1 Radar Components 1

1.2 The Radar Beam 3

1.3 The Radar Pulse 8

1.4 Signal Processing 11

References 16

2 Radar Quantitative Precipitation Estimation 17

2.1 Radar Calibration 17

2.2 Quality Control 19

      2.2.1 Signal Processing 19

      2.2.2 Fuzzy Logic 20

2.3 Precipitation Rate Estimation 24

2.4 Vertical Profile of Reflectivity 26

2.5 Rain Gauge Adjustment 28

2.6 Space-Time Aggregation 30

2.7 Remaining Challenges 32

2.8 Uncertainty Estimation 34

References 37

3 Polarimetric Radar Quantitative Precipitation Estimation 41

3.1 Polarimetric Radar Variables 41

3.2 Polarimetric Radar Data Quality Control 43

      3.2.1 Noise Effect and Reduction 44

      3.2.2 Clutter Detection and Removal 44

      3.2.3 Attenuation Correction 45

      3.2.4 Calibration 47

      3.2.5 Self-Consistency Check 47

3.3 Hydrometeor Classification 48

      3.3.1 Polarimetric Characteristics of Radar Echoes 49

      3.3.2 Classification Algorithms 49

3.4 Polarimetric Radar-Based QPE 51

3.5 Microphysical Retrievals 55

      3.5.1 Raindrop Size Distribution Model 55

      3.5.2 DSD Retrieval 56

      3.5.3 Snowfall and Hail Estimation 58

      3.5.4 Validation 59

      References 61

4 Multi-Radar Multi-Sensor (MRMS) Algorithm 67

4.1 Single-Radar Processing 69

      4.1.1 Dual-Polarization Quality Control 69

      4.1.2 Vertical Profile of Reflectivity Correction 70

      4.1.3 Product Generation 73

4..2 Precipitation Typology 75

4.3 Precipitation Estimation 77

4.4 Verification 80

4.5 Discussion 84

References 85

5 Advanced Radar Technologies for Quantitative Precipitation Estimation 87

5.1 Mobile and Gap-Filling Radars 88

      5.1.1 ARRC's Shared Mobile Atmospheric Research and Teaching Radar (SMART-R) 88

      5.1.2 NSSL's X-Band Polarimetric Mobile Radar (NOXP) 90

      5.1.3 ARRC's Atmospheric Imaging Radar (AIR) 91

      5.1.4 ARRC's Polarimetric X-Band 1000 (PX-1000) 93

      5.1.5 Collaborative Adaptive Sensing of the Atmosphere (CASA) 94

5.2 Spaceborne Radars 95

      5.2.1 Precipitation Radar aboard TRMM 95

      5.2.2 Dual-Frequency Precipitation Radar aboard NASA GPM 100

5.3 Phased-Array Radar 101

      5.3.1 Design Aspects and Product Resolution 101

      5.3.2 Dual Polarization 102

      5.3.3 Impact on Hydrology 104

      References 106

6 Radar Technologies for Observing the Water Cycle 109

6.1 The Hydrologic Cycle 109

6.2 Surface Water 112

      6.2.1 Streamflow Radar 112

      6.2.2 Surface Water Altimetry 114

      6.2.3 Synthetic Aperture Radar 116

6.3 Subsurface Water 117

      6.3.1 L-Band Radar 118

      6.3.2 C-Band Radar 118

      6.3.3 Ground-Penetrating Radar 119

6.4 Subsurface Water 124

References 126

7 Radar QPE for Hydrologic Modeling 129

7.1 Overview of Hydrological Models 129

      7.1.1 Model Classes 129

      7.1.2 Model Parameters 134

      7.1.3 Model State Variables and Data Assimilation 135

      7.1.4 Hydrological Model Evaluation 142

7.2 Hydrological Evaluation of Radar QPE 145

      7.2.1 Case Study in Ft. Cobb Basin, Oklahoma 146

      7.2.2 Evaluation with a Hydrologic Model Calibrated to a Reference QPE 149

      7.2.3 Evaluation with Monte Carlo Simulations from a Hydrologic Model 151

      7.2.4 Evaluation with a Hydrologic Model Calibrated to Individual QPEs 153

      References 154

8 Flash Flood Forecasting 157

8.1 Flash Flood Guidance 158

8.2 Flash Flood Guidance: History 162

8.3 Lumped Flash Flood Guidance 164

8.4 Flash Flood Potential Index 165

8.5 Gridded Flash Flood Guidance 166

8.6 Comments on the Use of Flash Flood Guidance 168

8.7 Threshold Frequency Approach 169

References 172

Index 175

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.

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