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Weather Radar Polarimetry [Pehme köide]

(University of Oklahoma, Norman, USA)
  • Formaat: Paperback / softback, 304 pages, kõrgus x laius: 234x156 mm, kaal: 480 g
  • Ilmumisaeg: 10-Dec-2019
  • Kirjastus: CRC Press
  • ISBN-10: 0367866536
  • ISBN-13: 9780367866532
Teised raamatud teemal:
Weather Radar PolarimetrySuurem pilt
  • Formaat: Paperback / softback, 304 pages, kõrgus x laius: 234x156 mm, kaal: 480 g
  • Ilmumisaeg: 10-Dec-2019
  • Kirjastus: CRC Press
  • ISBN-10: 0367866536
  • ISBN-13: 9780367866532
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9780367866532.html
Märksõnad:

This book presents the fundamentals of polarimetric radar remote sensing through understanding wave scattering and propagation in geophysical media filled with hydrometers and other objects. The text characterizes the physical, statistical, and electromagnetic properties of hydrometers and establishes the relations between radar observables and physical state parameters. It introduces advanced remote sensing techniques (such as polarimetric phased array radar) and retrieval methods for physical parameters. The book also illustrates applications of polarimetric radar measurements in hydrometer classification, particle size distribution retrievals, microphysical parameterization, and weather quantification and forecast.

Arvustused

"Zhangs text is an outstanding, up-to date account of polarimetric radar measurements as applied to hydrometeor classification, retrieval of microphysical properties through the use of data- assimilation techniques, and the measurement of polarimetric variables by phased-array radars. This text will be invaluable to students and researchers who are applying cutting-edge radar sensing technology and numerical forecast techniques to improve forecasts of precipitation and severe weather." Howard B. Bluestein, University of Oklahoma, USA

"This is a unified treatment of weather radar and polarimetric radar. These two areas are closely related, but often treated separately. This book treats these two areas from a unified point of view and, in addition, it has some new ideas such as array radar polarimetry. The book will be useful and give some new ideas and insights for future weather research." Akira Ishimaru, University of Washington, USA

"Tremendous progress has been achieved during the recent decade in operational implementation of the weather radar polarimetry, and dual-polarization radar is becoming a standard for operational weather radar networks around the world. This book perfectly fits the needs of the radar and meteorological communities which have to be better educated about the advantages and potential of this new technology." Alexander Ryzhkov, National Severe Storms Laboratory, Norman, Oklahoma, USA

"Dr. Zhangs wide range of expertise in formulating and developing focused research to solve cutting edge problems in radar meteorology has made this book attractive to academic, research, and operational communities. The author interweaves science and engineering aspects of weather radar polrimetry seamlessly. This approach has made the book valuable course material as well as a great resource for practicing radar meteorologists." Jothiram Vivekanandan, National Center for Atmospheric Research, Boulder, Colorado, USA

"This is a valuable reference book on weather radars and their associated algorithms, and it is written by a vital member of the University of Oklahoma Advanced Radar Research Center. As someone who originally studied physics for his B.S. degree and then, apparently, became an enthusiast of the physical interactions occurring around hydrometeorological targets, Prof. Zhang has poured all of the necessary physical explanations, relevant equations, and measurement techniques involving modern polarimetric weather radar into this book. The work is impressively organized in the ascending complexity of the topics it covers. An engineer or scientist who is new to the subject will find it very easy to read, since it covers almost all of the necessary preliminary information in a highly descriptive manneramazingly, without forcing the reader to check many of the previous references." IEEE Antennas and Propagation Magazine, April 2018 Issue

"The text summarizes weather radar theory and design, incorporating many in-service weather radars as examples. It extensively uses mathematics and statistics as tools to establish the theory and includes high-quality photos of weather radar outputs. This textbook is an excellent resource for graduate-level courses as well as for weather radar researchers."

IEEE Microwave Magazine, May 2019 Issue

Foreword xi
Preface xiii
Acknowledgments xv
About the Author xvii
Chapter 1 Introduction
1(6)
1.1 Historical Development
1(3)
1.2 Objectives and Organization of the Book
4(3)
Chapter 2 Characterization of Hydrometeors
7(44)
2.1 Physical and Statistical Properties
7(23)
2.1.1 Rain
9(1)
2.1.1.1 Drop Size Distribution
10(6)
2.1.1.2 Drop Shape
16(2)
2.1.1.3 Terminal Velocity
18(2)
2.1.2 Snow
20(1)
2.1.2.1 Snow Particle Size Distribution
21(1)
2.1.2.2 Snow Bulk Density
21(4)
2.1.2.3 Melting Models
25(4)
2.1.3 Hail and Graupel
29(1)
2.1.4 Cloud Water and Ice
30(1)
2.2 Electromagnetic Properties
30(17)
2.2.1 Dielectric Constant
31(3)
2.2.2 Dielectric Constant for a Lossy Medium
34(1)
2.2.3 Debye Formula
35(3)
2.2.4 Dielectric Constant for a Mixture of Two and Three Materials
38(9)
Appendix 2A Fitting Procedures for DSD Models: Marshall--Palmer Distribution
47(1)
Appendix 2B Fitting Procedures for DSD Models: Exponential Distribution
47(1)
Appendix 2C Fitting Procedures for DSD Models: Gamma Distribution
47(4)
Chapter 3 Wave Scattering by a Single Particle
51(44)
3.1 Wave and Electromagnetic Wave
51(8)
3.1.1 Vibration and Wave
51(2)
3.1.2 Phasor Representation of Time-Harmonic Waves
53(1)
3.1.3 EM Wave
53(2)
3.1.4 Wave Polarization and Representation
55(2)
3.1.4.1 Linear Polarization
57(1)
3.1.4.2 Circular Polarization
57(1)
3.1.4.3 Elliptical Polarization
57(2)
3.2 Scattering Fundamentals
59(5)
3.2.1 Scattering Amplitude, Scattering Matrix, and Scattering Cross Sections
59(5)
3.3 Rayleigh Scattering
64(5)
3.3.1 Original Statement
64(1)
3.3.2 Scattering as Dipole Radiation
65(4)
3.4 Mie Scattering Theory
69(4)
3.4.1 Conceptual Description
69(1)
3.4.2 Mathematical Expression and Sample Results
69(4)
3.5 Scattering Calculations for a Nonspherical Particle
73(9)
3.5.1 Basic Nonspherical Shape: Spheroid
74(1)
3.5.2 Rayleigh Scattering Approximation for Spheroids
75(2)
3.5.3 T-Matrix Method
77(5)
3.5.4 Other Numerical Methods for Scattering Calculations
82(1)
3.6 Scattering for Arbitrary Orientations
82(7)
3.6.1 Scattering Formulation through Coordinate Transformation
82(2)
3.6.2 General Expression for Rayleigh Scattering
84(1)
3.6.3 Backscattering Matrix for a Spheroid
85(1)
3.6.4 Forward Scattering Alignment versus Backscattering Alignment
86(2)
3.6.5 Scattering Matrix by a Spheroid with Any Orientation
88(1)
Appendix 3A Derivation of Optical Theorem (Forward Scattering Theorem)
89(2)
Appendix 3B Vector Spherical Wave Harmonics
91(4)
Chapter 4 Scattering and Propagation in Clouds and Precipitation
95(42)
4.1 Scattering Models
95(2)
4.2 Single Scattering Model
97(17)
4.2.1 Coherent Addition Approximation
97(1)
4.2.2 Mean Wave Field
98(1)
4.2.3 Wave Intensity and Independent Scattering
99(2)
4.2.4 Time-Correlated Scattering
101(1)
4.2.5 PDF of Scattered Wave Fields
102(1)
4.2.5.1 Single-Polarization Wave Field
102(3)
4.2.5.2 Dual-Polarization Wave Fields
105(4)
4.2.6 Polarimetric Radar Variables
109(5)
4.3 Coherent Wave Propagation
114(7)
4.3.1 Concept of Effective Medium
114(1)
4.3.2 Scalar Wave Propagation
114(3)
4.3.3 Polarized Wave Propagation
117(1)
4.3.3.1 No Canting Angle
117(1)
4.3.3.2 Random Orientation with Zero Means
118(1)
4.3.3.3 General Formulation for Coherent Wave Propagation
119(2)
4.4 Propagation-Included Scattering
121(7)
4.4.1 Transmission-Included Scattering Matrix
122(2)
4.4.2 Propagation-Included Radar Variables
124(4)
Appendix 4A Monte Carlo Simulation
128(1)
Appendix 4B Statistics of Random Orientation Angle Terms
129(8)
Chapter 5 Radar Measurements and Improvement of Data Quality
137(42)
5.1 The Polarimetric Weather Radar System and Equation
137(4)
5.1.1 Fundamentals and the Polarimetric Radar Equation
137(3)
5.1.2 Polarization Modes of Radar Operation
140(1)
5.2 Regular Estimation of Polarimetric Radar Variables
141(6)
5.2.1 Reflectivity Estimation
143(1)
5.2.2 Differential Reflectivity
144(1)
5.2.3 Co-Polar Correlation Coefficient
145(1)
5.2.4 Differential Phase
146(1)
5.2.5 Radial Velocity and Spectrum Width
146(1)
5.3 Multilag Correlation Estimators
147(10)
5.3.1 Concept of Multilag Correlation Estimation
148(1)
5.3.2 General Expressions
149(2)
5.3.3 Specific Estimators
151(1)
5.3.3.1 Two-Lag Estimator
151(1)
5.3.3.2 Three-Lag Estimator
152(2)
5.3.3.3 Four-Lag Estimator
154(1)
5.3.4 Performance of the Estimators
154(3)
5.4 Clutter Detection
157(13)
5.4.1 Background of Clutter Detection
159(1)
5.4.2 Definition and Property of Discriminants
159(1)
5.4.2.1 Power Ratio Discriminant
159(1)
5.4.2.2 Dual-Polarization Discriminants
160(3)
5.4.2.3 Dual-Scan Discriminant
163(1)
5.4.2.4 Dual-Pol Dual-Scan Discriminants (DPDS)
164(2)
5.4.3 Implementation and Evaluation of SBC Dual-Pol Clutter Detection
166(4)
5.5 Clutter Mitigation
170(2)
5.5.1 Bi-Gaussian Spectrum Model and Cost Functions
170(1)
5.5.2 Examples of BGMAP Fitting to Separate Weather and Clutter Spectra
171(1)
5.6 Spectrum-Time Estimation and Processing
172(4)
Appendix 5A Derivation of Cost Function for Optimal Spectral Parameter Estimation
176(1)
Appendix 5B NEXRAD Radar Data Access
177(2)
Chapter 6 Applications in Weather Observation and Quantification
179(46)
6.1 Observation of Polarimetric Radar Signatures
179(5)
6.1.1 Stratiform Precipitation
179(2)
6.1.2 Mesoscale Convection
181(1)
6.1.3 Storm Complex
181(1)
6.1.4 Severe Storms
181(3)
6.2 Hydrometeor Classification
184(8)
6.2.1 Classification Background
185(2)
6.2.2 Fuzzy Logic Approach
187(2)
6.2.3 Classification Results from PRD
189(3)
6.3 Quantitative Precipitation Estimation
192(8)
6.3.1 Radar Rain Estimators
193(1)
6.3.2 Polarimetric Radar Rain Estimators
194(4)
6.3.3 Rain Estimation Results
198(1)
6.3.4 Estimation Errors and Practical Issues
199(1)
6.4 DSD Retrieval
200(11)
6.4.1 Selection of Measurements and DSD Model
201(2)
6.4.2 Retrieval Procedure
203(2)
6.4.3 Application of DSD Retrieval in Parameterization of Rain Microphysics
205(6)
6.5 Attenuation Correction
211(6)
6.5.1 Correction Methods
212(1)
6.5.1.1 DP Method
212(2)
6.5.1.2 Z-PHI Method
214(1)
6.5.1.3 Self-Consistent with Constraint Method
215(1)
6.5.1.4 Dual-Frequency Method
216(1)
6.5.2 Example Results
217(1)
Appendix 6A Rain Estimation Based on Bayes' Theorem
217(4)
Appendix 6B Equivalence among Constrained Gamma DSD Models
221(4)
Chapter 7 Advanced Methods and Optimal Retrievals
225(28)
7.1 Simultaneous Attenuation Correction and DSD Retrieval
225(4)
7.1.1 Analogy between Dual-Polarization and Dual-Frequency Radar Techniques
225(1)
7.1.2 Formulation: Integral Equation Method
226(2)
7.1.3 Example of a Simultaneous Retrieval
228(1)
7.2 Statistical Retrieval of Rain DSDs
229(7)
7.2.1 Statistical Retrieval Method: Bayesian Approach
229(1)
7.2.2 Prior Distribution of DSD Parameters
230(1)
7.2.3 The Forward Conditional Distribution
230(2)
7.2.4 Results and Evaluation
232(4)
7.3 Variational Retrieval
236(8)
7.3.1 Formulation of Variational Retrieval
236(1)
7.3.1.1 General Formulation
236(1)
7.3.1.2 Formulation for DSD Retrieval fromPRD
237(1)
7.3.2 Forward Observation Operator and Iteration Procedure
238(2)
7.3.3 Application to PRD
240(4)
7.4 Optimal Retrieval through DA
244(9)
7.4.1 General Challenges
244(1)
7.4.2 Observation Operators and Errors
245(1)
7.4.3 Model Microphysics Uncertainty
246(4)
7.4.4 Expectation for Future PRD DA
250(3)
Chapter 8 Phased Array Radar Polarimetry
253(30)
8.1 Background and Challenges
253(6)
8.2 Formulation for Planar Polarimetric Phased Array Radar
259(11)
8.2.1 Dipole Radiation
259(3)
8.2.2 Backscattering Matrix
262(1)
8.2.3 Scattering Matrix Corrections
263(1)
8.2.3.1 Alternate Transmission
263(1)
8.2.3.2 Simultaneous Transmission
264(1)
8.2.4 Correction to Polarimetric Variables
264(1)
8.2.4.1 Reflectivity Factor
265(1)
8.2.4.2 Differential Reflectivity
265(3)
8.2.4.3 Correlation Coefficient
268(1)
8.2.4.4 Linear Depolarization Ratio
269(1)
8.3 Cylindrical Polarimetric Phased Array Radar
270(8)
8.3.1 CPPAR Concept and Formulation
271(4)
8.3.2 Sample Calculation of CPPAR Patterns
275(2)
8.3.3 CPPAR Development
277(1)
Appendix 8A PPAR Formulation for Aperture and Patch Elements
278(5)
References 283(14)
Index 297
Guifu Zhang is Professor of Meteorology at University of Oklahoma School of Meteorology.