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- Herausgeber: John Wiley & Sons
- Kategorie: Wissenschaft und neue Technologien
- Serie: Advancing Weather and Climate Science
- Sprache: Englisch
A comprehensive introduction to the current technology and application of radar in meteorology and atmospheric sciences
Written by leading experts in the field, Radar Meteorology, A first Course offers an introduction to meteorological radar systems and applications, with emphasis on observation and interpretation of physical processes in clouds and weather systems. This comprehensive introduction to the subject offers an overview of the quantities essential to radar meteorology including the radar reflectivity factor, and Doppler, dual-polarization, and multi-wavelength radar variables. The authors highlight wind retrieval from single and multiple Doppler radars, precipitation estimation and hydrometeorological applications, with chapters dedicated to interpretation of radar data from warm season mid-latitude severe weather, winter storms, tropical cyclones and more.
In addition, Radar Meteorology highlights research applications of this burgeoning technology, exploring dynamic applications such as space-borne and ground-based vertically pointing radar systems, and cloud, airborne and mobile radars. As meteorological radars are increasingly used professionally for weather observation, forecasting and warning, this much-needed text:
- Presents an introduction to the technical aspects and current application of radar as used in the meteorology and atmospheric sciences
- Contains full-colour illustrations that enhance the understanding of the material presented
- Examines the wide-range of meteorological applications of radar
- Includes problems at the end of each chapter as a helpful review of the contents
- Provides full instructor support with all illustrations and answers to problems available via the book’s instructor website.
Radar Meteorology offers a much-needed introductory text to the study of radar as applied to meteorology. The text was designed for a one semester course based on the authors' own course in Radar Meteorology at the University of Illinois at Urbana-Champaign.
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Table of Contents
Cover
Title Page
Copyright
Dedication
Preface
Acknowledgments
About the Companion Website
Chapter 1: Properties of Electromagnetic Waves
1.1 Introduction
1.2 Electric and magnetic fields
1.3 The nature of electromagnetic radiation
1.4 Interactions of electromagnetic waves with matter
1.5 Polarization of electromagnetic waves
Important terms
Review questions
Challenge problems
Chapter 2: Radar Hardware
2.1 Introduction
2.2 Frequency and wavelength
2.3 Components of a weather radar system
2.4 Specialized radar systems
Important terms
Review questions
Challenge problems
Chapter 3: Radar Characteristics
3.1 Introduction
3.2 Range and range ambiguity
3.3 The transmitted and received signal
3.4 Radar geometry and types of displays
Important terms
Review questions
Challenge problems
Chapter 4: The Path of a Radar Ray
4.1 Introduction
4.2 Ray propagation in an idealized atmosphere
4.3 Anomalous propagation
Important terms
Review questions
Challenge problems
Chapter 5: Power and the Radar Reflectivity Factor
5.1 Introduction
5.2 Radar equation for a solitary target
5.3 Radar equation for a distributed target
5.4 The weather radar equation
5.5 Summary
Important terms
Review questions
Challenge problems
Chapter 6: Radial Velocity—The Doppler Effect
6.1 Introduction
6.2 Measurement of radial velocity
6.3 Doppler spectra
6.4 Measurement of the Doppler moments
6.5 Summary
Important terms
Review questions
Challenge problems
Chapter 7: Dual-Polarization Radar
7.1 Introduction
7.2 The physical bases for radar polarimetry
7.3 Measuring polarimetric quantities
7.4 Reflectivity, differential reflectivity, and linear depolarization ratio
7.5 Polarization and phase
Important terms
Review questions
Challenge problems
Chapter 8: Clear Air Echoes
8.1 Introduction
8.2 Ground clutter
8.3 Echoes from biological sources
8.4 Debris, dust, and smoke
8.5 Aircraft echoes and chaff
8.6 Other non-meteorological echo sources
8.7 Bragg scattering
Important terms
Review questions
Challenge problems
Chapter 9: Propagation Effects: Attenuation and Refractivity
9.1 Introduction
9.2 Attenuation
9.3 Refractivity
Important terms
Review questions
Challenge problems
Chapter 10: Operational Radar Networks
10.1 Introduction
10.2 The WSR-88D radar network
10.3 Terminal Doppler weather radars
10.4 International operational radar networks
Important terms
Review questions
Challenge problems
Chapter 11: Doppler Velocity Patterns and Single-Radar Wind Retrieval
11.1 Introduction
11.2 Kinematic properties of the wind field
11.3 Doppler radial velocity patterns and the wind field
11.4 Wind retrieval with profiling radars
11.5 Velocity–azimuth display wind retrieval
Important terms
Review questions
Challenge problems
Chapter 12: Multiple Doppler Wind Retrieval
12.1 Introduction
12.2 Network design and deployment
12.3 Characteristics of single Doppler data
12.4 Procedures for multiple Doppler syntheses
12.5 Summary
Important terms
Review questions
Chapter 13: Precipitation Estimation with Radar
13.1 Introduction
13.2 Measurement of precipitation rate, total precipitation, and particle size distributions
13.3 Nature of particle size distributions
13.4 Radar remote sensing of precipitation
13.5 Precipitation estimation using dual polarization
13.6 Winter precipitation
13.7 Measuring precipitation from space
Important terms
Review questions
Challenge problems
Chapter 14: Warm Season Convection
14.1 Introduction
14.2 Mesoscale convective systems
14.3 Supercell thunderstorms
14.4 Downbursts and wind shear
Important terms
Review questions
Challenge problems
Chapter 15: Extratropical Cyclones
15.1 Introduction
15.2 Radar approaches to monitor cyclone mesostructure
15.3 Mesoscale structures observable with radar
Important terms
Review questions
Challenge problems
Chapter 16: Tropical Cyclones
16.1 Introduction
16.2 Airborne and satellite radar systems for tropical cyclone research and operations
16.3 Tropical cyclone structure and kinematics
16.4 Operational use of radar to detect tropical cyclone hazards
Important terms
Review questions
Challenge problems
Chapter 17: Clouds and Vertical Motions
17.1 Introduction
17.2 Cloud radars
17.3 Application of cloud radars
Important terms
Review questions
Challenge problems
Appendix A: List of Variables (and Chapters)
Appendix B: Derivation of the Exact Equation for a Ray Path through a Spherically Stratified Atmosphere
Index
End User License Agreement
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Guide
Cover
Table of Contents
Preface
Begin Reading
List of Illustrations
Chapter 1: Properties of Electromagnetic Waves
Figure 1.1 The electric field (black arrows) and lines of constant voltage (green lines) between two infinite, parallel, oppositely-charged plates
Figure 1.2 The electric field of a simple dipole
Figure 1.3 The magnetic field induction field (red arrows,
B
) associated with a current (
I
) and the force associated with the field (blue arrows). The right hand rule (force =
I
×
B
) can be used to determine the relationship between the vectors
Figure 1.4 Oscillation of the charge, voltage, and current in a simple dipole antenna.
Figure 1.5 Oscillation of the electric and magnetic fields in a propagating electromagnetic wave
Figure 1.6 The effect of propagation and absorption on the amplitude of a propagating wave
Figure 1.7 The electromagnetic spectrum and the opacity of the atmosphere to electromagnetic waves propagating through the depth of the atmosphere. Meteorological radars operate in the microwave part of the spectrum
Figure 1.8 An example of destructive and constructive interference on two waves with the same amplitude and frequency
Figure 1.9 An example of refraction of light at an optical wavelength. The straw appears to be bent to the observer because the light undergoes refraction at the water/air interface
Figure 1.10 A radar ray crossing an interface marked by a change in the index of refraction will bend according to Snell's law
Figure 1.11 Specular reflection
Figure 1.12 The blue sky above the three Doppler on Wheels radar trucks results from scattering of sunlight by molecules in the atmosphere
Figure 1.13 The radar cross section of a sphere as a function of the ratio of the sphere circumference to the radar wavelength
Figure 1.14 Phase lines (red) of a plane wave passing a particle. In the top panel the particle diameter is much smaller than the wavelength, in the middle, the diameter is comparable to the wavelength, and in the bottom, the diameter significantly exceeds the wavelength, leading to different types of scattering
Figure 1.15 Scattered radiation pattern for progressively larger spherical particles. The distance is proportional to the amplitude of the scattered radiation
Figure 1.16 Bragg scattering occurs when electromagnetic waves impinge on regularly-spaced objects or regions of air with different indices of refraction leading to constructive interference between the scattered waves and a coherent wave front
Figure 1.17 Oscillation and propagation of the electric field vector in a (a) horizontally polarized, (b) vertical polarized, and (c) right hand circularly polarized wave
Chapter 2: Radar Hardware
Figure 2.1 Block diagram of the components of the S-Pol S-band radar system, which has a klystron transmitter
Figure 2.2 The S-Pol S-band antenna and trailer
Figure 2.3 The STALO and COHO component housing in the S-Pol radar
Figure 2.4 (a) Diagram of the key components of a klystron transmitter. (b) The klystron transmitter in the S-Pol radar (Note the tape measure is extended 6 in. to give an idea of scale.)
Figure 2.5 Waveguides for S, C, X, K
a
, and W-band radars
Figure 2.6 Close up of the S-Pol antenna system showing the waveguides for both polarizations, the feedhorn, and the reflector
Figure 2.7 S-band and X-band rotary joints
Figure 2.8 Waveguide polarization switches and dummy loads to prevent reflection at waveguide junctions
Figure 2.9 Circulators and transmit–receive limiters in the S-Pol radar system.
Figure 2.10 The radome covering the KILX WSR-88D radar antenna. The building on the left is for rawinsonde launches
Figure 2.11 The 2-D gain function of an antenna showing the main lobe and side lobes
Figure 2.12 A “three-dimensional” image of the gain function for an antenna with very narrow beamwidth (about 0.33°). The height of the contour above the base plane is proportional to the power gain in decibels. Numerous sidelobes are evident
Figure 2.13 The effect of sidelobes on the horizontal appearance of a radar echo
Figure 2.14 The receiver system in the S-Pol radar
Figure 2.15 Box diagram showing the retrieval of the
I
and
Q
signals from the input Doppler frequency
Figure 2.16 A K
a
-band magnetron
Figure 2.17 Internal structure of a magnetron transmitter
Figure 2.18 Block diagram of the components of the S-PolKa K
a
-band radar system, which has a magnetron transmitter system
Figure 2.19 A phased-array antenna on a mobile Doppler radar
Figure 2.20 A wind profiler phased-array antenna. The devices on the corners are part of a radio-acoustic sounding system and are not part of the radar itself
Figure 2.21 A beam can be steered with a phased-array radar by staggering the length of the transmission lines between the transmitter and the radiators
Figure 2.22 Scanning procedure for the NOAA P-3 aircraft tail radar system
Figure 2.23 The beam pattern produced by the P-3 radar scanning as the aircraft moves along a weather system. The cross beam pattern permits dual-Doppler retrieval of the wind field
Figure 2.24 The dual-frequency precipitation radar antenna on the Global Precipitation Mission satellite, shown here in its testing phase before launch
Chapter 3: Radar Characteristics
Figure 3.1 The relationship between the pulse duration and the pulse period
Figure 3.2 The relationship between the maximum unambiguous range of a radar and the pulse repetition frequency
Figure 3.3 Ambiguity in the position of a target arises when the echo from an earlier pulse arrives at the radar after the next pulse has been transmitted
Figure 3.4 The long, narrow shape of a second-trip echo arises because the echo is constrained into the solid angle of the beam, but much closer to the radar
Figure 3.5 Second-trip echoes appearing in the radar reflectivity field (left) and the radial velocity field (right)
Figure 3.6 The red area denotes a radar pulse. The along-beam resolution is equal to half the pulse length
Figure 3.7 A cathode ray tube display from an early radar system showing the first thunderstorm hook echo reported in history
Figure 3.8 A plan position indicator (PPI) display from the WSR-88D showing a group of supercell thunderstorms
Figure 3.9 A schematic of the range–height indicator (RHI) scanning strategy
Figure 3.10 An RHI display of a stratiform winter storm. The bright red line is the melting level where snowflakes are melting into raindrops
Figure 3.11 An A-scope display of data along a single beam
Figure 3.12 A time–height display from a vertically pointing airborne radar. The black line is the flight track
Figure 3.13 A PPI at 0.5° elevation of a winter storm over Indiana. The white line shows the location of the flight track of a research aircraft flying a vertically pointing radar
Figure 3.14 (a) A vertical cross section along the white line in Figure 3.13 taken by a high-resolution W-band radar on board an aircraft. (b) The same cloud system, but shown as a reconstructed RHI from the WSR-88D located in Indianapolis, IN
Figure 3.15 Strategy for constructing a Constant Altitude Plan Position Indicator (CAPPI) display
Figure 3.16 (a) Horizontal cross section through a squall line at 2 km elevation. (b) Vertical cross section through the same squall line along the black line on the horizontal cross section
Figure 3.17 Reflectivity factor and radial velocity measured by the ELDORA radar on board the Navy Research Laboratory P-3 aircraft as the aircraft flew along a squall line
Chapter 4: The Path of a Radar Ray
Figure 4.1 A ray launched at the horizon, because of earth's curvature, will rise higher above the earth's surface and eventually into space
Figure 4.2 The water molecule is a polar molecule because the average distribution of electrons creates a dipole with a positive charged side at the location of the hydrogen atoms
Figure 4.3 Standard atmosphere profile of temperature (a) and vapor pressure (b). The relative contribution of density and humidity to radio refractivity (c) in the standard atmosphere of (a, b)
Figure 4.4 A radar ray (blue) follows a curved path through the atmosphere due to the combined effects of earth's curvature and atmospheric refraction
Figure 4.5 Geometry used to calculate the distance across the earth's surface and the height of a point along a ray as a function of slant range and radar elevation angle
Figure 4.6 Ray paths in an atmosphere characterized by standard atmospheric refraction
Figure 4.7 Three soundings used to calculate the ray paths in Figure 4.8
Figure 4.8 Ray paths for each of the three soundings in Figure 4.7. The red, blue, and green soundings are for the soundings in panels a, b, and c, respectively. The elevation angle of the radar is noted at the end of each ray path
Figure 4.9 Radar image from the KILX radar in Lincoln, Illinois, on August 27, 2010 at 12:00 UTC showing effects of anomalous propagation
Figure 4.10 Temperature and relative humidity profile from the 12:00 UTC August 27, 2010 Lincoln, IL, rawinsonde that was taken at the time the radar data in Figure 4.9 was collected
Chapter 5: Power and the Radar Reflectivity Factor
Figure 5.1 An isotropic antenna radiates energy equally in all directions
Figure 5.2 The angular coordinates
θ
and
φ
are measured in the azimuthal and elevation directions, respectively, relative to the beam axis, which itself is defined as the direction the antenna has maximum gain
Figure 5.3 The Northrop Grumman B-2 Spirit is an American strategic bomber, designed to avoid radar detection and be able to penetrate dense anti-aircraft defenses
Figure 5.4 Distortion of a raindrop as a function of diameter (mm) for a raindrop falling in still air.
Figure 5.5 Ice crystal shapes as a function of temperature and ice supersaturation
Figure 5.6 Conical and spherical hailstones
Figure 5.7 The radiation pattern of a directional antenna and the 3 dB beamwidth
Figure 5.8 The contributing volume of a conical beam
Figure 5.9 A dipole induced in a small spherical drop as a polarized plane wave propagates past the drop
Figure 5.10 Data from the 0.5° scan of the KTWX radar showing the radar reflectivity factor during an outbreak of supercell thunderstorms
Chapter 6: Radial Velocity—The Doppler Effect
Figure 6.1 A Doppler radar can only measure the component of the target's motion along the direction of the beam
Figure 6.2 Illustration of recovery of the Doppler frequency from a sequence of phase measurements. The blue dots denote the measurements. The red line is a fit to the measurements
Figure 6.3 Illustration of ambiguity in recovery of the Doppler frequency from phase measurements. The blue dots denote the measurements. The red and green lines are equally valid fits to the measurements
Figure 6.4 The true versus measured radial velocity of a target for a radar with a Nyquist velocity of 10 m s
−1
. Note that all true radial velocities beyond the range −10 to 10 m s
−1
are folded back into that range
Figure 6.5 The relationship between maximum unambiguous range and velocity for common radar wavelengths
Figure 6.6 Radar reflectivity (a) and radial velocity (b) from the Norman, OK, WSR-88D (KTLX) 5.2° elevation scan at 23 : 18 : 55 UTC on May 3, 1999. Velocity folds are indicated on the radial velocity image
Figure 6.7 Radar reflectivity (a) and radial velocity (b) from the Norman, OK, WSR-88D (KTLX) 5.2° elevation scan at 00 : 19 : 44 UTC on May 4, 1999. Note the complicated structures in the radial velocity field near the hook echo of the supercell near the radar
Figure 6.8 RHI through the core of the severe thunderstorm observed at Newcastle showing the reflectivity factor (a) and measured radial velocity (b). The radial velocities are folded in many locations. Turbulence in the top half of the storm is severe enough that the velocity pattern lacks coherence
Figure 6.9 Same RHI through the core of a severe thunderstorm updraft as Figure 6.8, except that the radial velocities have been unfolded. The velocities in the turbulent region were too complicated to recover and were removed
Figure 6.10 A Doppler spectrum measured by a vertically pointing radar in a light rain shower. Note the logarithmic scale for power
Figure 6.11 Doppler spectra measured in a vertical column as ice particles form near cloud top, grow as they fall, melt to become rain, and approach the ground
Figure 6.12 An idealized Doppler spectrum showing the relationship of the spectrum to the spectral moments
Figure 6.13 Examples of Doppler spectra that produce biased estimates of the mean radial velocity
Figure 6.14 Simple phase diagram showing the amplitude vector rotating at an angular frequency
ω
d
. The phase at a particular time is
φ
Figure 6.15 Determination of the mean phase change (green) from the components of the autocorrelation function (red)
Chapter 7: Dual-Polarization Radar
Figure 7.1 Three-dimensional visualization of a horizontally (blue) and vertically (green) linearly polarized electromagnetic wave
Figure 7.2 Block diagram of a switched polarization-agile Doppler radar (a), dual-transmitter polarization-agile Doppler radar (b), polarization-diverse Doppler radar (c). Polarimetric variables measured by each system are shown at the right. Asterisks denote variables measured when transmission is made at 45° slant polarization
Figure 7.3 (a) Photograph of a two-dimensional video distrometer.
Figure 7.4 (a) Axis ratio as a function of drop diameter (mm) for a raindrop falling in still air. (b) Axis ratio versus maximum diameter from two laboratory studies
Figure 7.5 Illustration of canting angle of four raindrops observed with a two-dimensional video disdrometer
Figure 7.6 Histogram of raindrop canting angle from two-dimensional video disdrometer observations
Figure 7.7 Fall trajectories of 1.4–1.9 mm raindrops (a) at equilibrium and (b), (c) displaying multimode oscillations. These images are obtained by digitally combining the instantaneous raindrop images taken 1 ms apart. White arrow indicates the direction of gravity vector and the horizontal size of an image frame (43 mm) gives the scale
Figure 7.8 Two-dimensional video disdrometer images of a large droplet observed on April 23, 2011 in north-central Oklahoma. The equivalent diameter of the droplet was observed to be 8.7 mm
Figure 7.9 T-matrix simulations of a raindrop (a) reflectivity at horizontal polarization and (b) differential reflectivity versus drop equivalent diameter at S-band (green), C-band (blue), and X-band (red). The dashed and solid lines denote different axis ratio parameterizations. Droplet canting was modeled with a Gaussian distribution with a 7° standard deviation
Figure 7.10 Comparison of nearly time-matched 0.7° PPI scans from the NASA NPOL S-band radar, sited near Marland, Oklahoma (panels a and b), and the Department of Energy Atmospheric Radiation Measurement Climate Research Facility CSAPR C-band radar near Nardin, Oklahoma (panels c and d). Panels a and c are reflectivity at horizontal polarization, whereas panels b and d are differential reflectivity. The NPOL sweep began at May 23, 2011 at 22:21 UTC, whereas the CSAPR sweep began at 22:16 UTC. Regions of attenuation and differential attenuation are noted with hatching in the CSAPR images
Figure 7.11 As in Figure 7.9, but for (a) specific attenuation at horizontal polarization and (b) specific differential attenuation
Figure 7.12 Vertical wind tunnel observations of the time evolution of a melting hail particle
Figure 7.13 KFTG NEXRAD (Front Range, Colorado) 0.5° elevation PPI S-band observations from 8 May 2017 at 21:24 UTC of a severe hailstorm. (a) Reflectivity at horizontal polarization, (b) differential reflectivity, (c) co-polar correlation coefficient, and (d) specific differential phase
Figure 7.14 KFTG NEXRAD (Front Range, Colorado) 0.5° elevation ray plot at 265.2° azimuth from the severe hailstorm shown in Figure 7.13. (a) Reflectivity at horizontal polarization (dBZ), (b) differential reflectivity (dB), (c) co-polar correlation coefficient, and (d) differential phase (deg)
Figure 7.15 Time–height quasi-vertical profiles (QVPs) of (a) reflectivity at horizontal polarization (dBZ) and (b) differential reflectivity (dB) observed from February 15, 2014 to February 16, 2014, taken by the KBOX NEXRAD (Boston, Massachusetts) at 10° elevation. Contours of RAP model-analyzed temperature starting at −15 °C (magenta) in 3 °C increments (black) and pressure vertical velocity starting at −1 Pa s
−1
in −1 Pa s
−1
increments (heavy dotted) are overlaid
Figure 7.16 CSU-CHILL (Greeley, Colorado) 160° azimuth RHI S-band observations from June 21, 2010 at 22:20 UTC of a hail-producing deep convective system. (a) Reflectivity at horizontal polarization, (b) Doppler radial velocity, (c) linear depolarization ratio, (d) differential reflectivity, (e) specific differential phase, and (f) correlation coefficient
Figure 7.17 CSU-CHILL (Greeley, Colorado) 1.25° elevation 160° azimuth ray plot from the convective system shown in Figure 7.16. (a) Reflectivity at horizontal polarization, (b) differential reflectivity, (c) correlation coefficient, (d) differential phase, (e) specific differential phase, and (f) linear depolarization ratio
Figure 7.18 Illustration of the differential phase shift (Δ
φ
) and attenuation (Δ
A
) effects of passing through matter of different complex indices of refraction
Figure 7.19 As in Figure 7.9, but for (a) specific differential phase and (b) backscatter differential phase
Figure 7.20 Illustration of microphysical factors that, in practice, lead to positive differential phase (left panel) and small to zero differential phase (right panel)
Figure 7.21 KTLX NEXRAD (Twin Lakes, Oklahoma) 0.5° elevation PPI S-band observations from April 21, 2017 at 14:31 UTC of a leading line-trailing stratiform convective system. (a) Differential phase (deg), (b) 11-gate moving window standard deviation of differential phase (deg), and (c) specific differential phase (deg km
−1
)
Figure 7.22 KVNX NEXRAD (Vance Air Force Base, Oklahoma) 0.5° elevation 165.3° azimuth ray plot from May 20, 2011 at 09:44 UTC through a leading line-trailing stratiform convective system. (a) Reflectivity at horizontal polarization (dBZ), (b) differential reflectivity (dB), (c) 11-gate moving window standard deviation of differential phase (deg), and (d) retrieved specific differential phase (deg km
−1
)
Figure 7.23 KINX NEXRAD (Tulsa, Oklahoma) 0.5° elevation PPI S-band observations from April 17, 2017 at 04:19 UTC of a mesoscale convective system. (a) Reflectivity at horizontal polarization, (b) differential reflectivity, (c) co-polar correlation coefficient, and (d) specific differential phase
Figure 7.24 Department of Energy Atmospheric Radiation Measurement Climate Research Facility CSAPR C-band radar 0.7° elevation 220.7° azimuth ray plot of the convective system shown in Figure 7.10, panels b and d. (a) Reflectivity at horizontal polarization, (b) differential reflectivity, (c) co-polar correlation coefficient, and (d) specific differential phase
Figure 7.25 As in Figure 7.15, except showing data from the KOKX NEXRAD (Upton, New York) from February 8, 2013 to February 9, 2013. Plotted are (a) reflectivity at horizontal polarization, (b) differential phase, and (c) specific differential phase
Figure 7.26 KVNX NEXRAD (Vance Air Force Base, Oklahoma) images of (a,c) reflectivity at horizontal polarization at approximately the melting level, (b,d) specific differential phase integrated in a slab above the melting level. The panels a and b are from May 20, 2011 at 09:48 UTC, whereas the panels (c) and (d) are from May 23, 2011 at 21:53 UTC
Figure 7.27 Analysis of polarimetric observations from the S-band Vance WSR-88D on May 23, 2011. (a) Area with specific differential phase >0.75 deg km
−1
at each level (filled colors), volume with specific differential phase >0.75 deg km
−1
above the melting level (gray line), and the melting level (dotted line). (b) As in (panel a), but for differential reflectivity >1 dB. (c) Number of specific differential phase columns detected (black) and area of each column (red)
Figure 7.28 Doppler on Wheels (DOW) complex pulse pair time series measurements observed at the University of Illinois at Urbana-Champaign campus from March 3, 2016 at 16:37 UTC. Data from (a) range = 500 m within the bright band and (b) range = 1500 m within snow. The red and blue points show the H*V and V*H points. The angle depicted is an illustration of the estimate differential phase. Thirty-two pulses are shown from each sample
Figure 7.29 Simulation of complex pulse pair measurements in (a) rain only with 32 samples and an inherent co-polar correlation coefficient of 0.95 and (b) in rain mixed with melting hail, each with a co-polar correlation coefficient of 0.95, but with an intrinsic differential phase shift of 45° and 50°, respectively
Figure 7.30 KBOX NEXRAD (Boston, Massachusetts) 0.5° elevation PPI S-band observations from February 5, 2016 at 13:15 UTC of an east coast cyclone with a clear rain–snow transition extending southwest–northeast across Cape Cod. (a) Reflectivity at horizontal polarization, (b) differential reflectivity, (c) co-polar correlation coefficient, and (d) specific differential phase
Figure 7.31 Relationships between S-band and C-band polarimetric variables. (a and c) Reflectivity at horizontal polarization versus differential reflectivity and (b and d) reflectivity at horizontal polarization and specific differential phase. From May 23, 2011, S-band observations (panels a and c) are from a 0.9° elevation PPI observed by the KVNX NEXRAD (Vance Air Force Base, Oklahoma) at 22:15 UTC, whereas C-band observations are from a 0.7° elevation PPI from the Department of Energy Atmospheric Radiation Measurement Climate Research Facility CSAPR C-band radar near Nardin, Oklahoma at 22:16 UTC. The shaded panels in each Figure give the joint probability distribution of the data, whereas the traces on the edges of each Figure display the probability distribution on one axis only
Figure 7.32 KMLB NEXRAD (Melbourne, Florida) 0.5° elevation PPI S-band observations from October 17, 2016 at 10:52 UTC of Hurricane Matthew (2016). (a) Reflectivity at horizontal polarization, (b) differential reflectivity, (c) co-polar correlation coefficient, and (d) specific differential phase
Figure 7.33 KTLX NEXRAD (Twin Lakes, Oklahoma) 0.5° elevation PPI S-band observations from October 17, 2016 at 10:52 UTC of the squall line shown in Figure 7.21. (a) Reflectivity at horizontal polarization, (b) differential reflectivity, (c) co-polar correlation coefficient, and (d) specific differential phase
Figure 7.34 KVNX NEXRAD (Vance Air Force Base, Oklahoma) 2.4° elevation PPI S-band observations from May 23, 2011 at 22:15 UTC showing (a) radar reflectivity at horizontal polarization and (b) hydrometeor classification algorithm results (hydrometeor type indicated by the legend)
Figure 7.35 Illustration of a fuzzy logic hydrometeor classification algorithm
Figure 7.36 Membership functions for polarimetric variables for rain, drizzle, and big drops from the Colorado State University hydrometeor classification algorithm at S-band (green), C-band (blue), and X-band (red) data. These values were obtained from the CSU RadarTools software package available at https://github.com/CSU-Radarmet/CSU_RadarTools
Figure 7.38 Membership functions for polarimetric variables for aggregates and wet snow from the Colorado State University hydrometeor classification algorithm at S-band (green), C-band (blue), and X-band (red) data. These values were obtained from the CSU RadarTools software package available at https://github.com/CSU-Radarmet/CSU_RadarTools
Figure 7.39 Membership functions for polarimetric variables for hail, low-density graupel, and high-density graupel from the Colorado State University hydrometeor classification algorithm at S-band (green), C-band (blue), and X-band (red) data. These values were obtained from the CSU RadarTools software package available at https://github.com/CSU-Radarmet/CSU_RadarTools
Chapter 8: Clear Air Echoes
Figure 8.1 Ground clutter in the vicinity of convective echoes as it appears in the reflectivity (a) and radial velocity (b) fields of a Doppler on Wheels X-band radar. Note the grid pattern within the 10 km range ring where targets have zero radial velocity
Figure 8.2 Ground clutter echo on an RHI caused by radar sidelobe energy striking the Vehicle Assembly Building at Cape Canaveral, Florida (see Figure 8.3)
Figure 8.3 The Vehicle Assembly Building at Cape Canaveral
Figure 8.4 Example of sea clutter echo in the (a) reflectivity, (b) radial velocity, and (c) correlation coefficient fields. The data were collected in the vicinity of a lake effect snowband over the east end of Lake Ontario
Figure 8.5 Example of anomalous propagation due to a nocturnal inversion. The larger echoes in panel a are from wind farms, whereas the thin lines are from cell phone towers along interstates. In panel b, most of these echoes have disappeared after daytime heating destroys the inversion. The larger echoes at the top of panel b are from precipitation that moved in during the intervening time between a and b
Figure 8.6 Graphic depiction of removal of ground clutter contamination. The Doppler spectra in (a) has a secondary peak near zero velocity associated with ground clutter. A clutter filter removes this echo (b), resulting in a radial velocity closer to the true value (c)
Figure 8.7 An insect echo bloom in the reflectivity field (a, b) and the radial velocity field (c, d) occurring at sunset at the KILX radar on a summer evening
Figure 8.8 The gust front echoes in this reflectivity image from the KAMA radar are the result of insects being lofted by updrafts along the gust fronts
Figure 8.9 Radar echoes from birds, bats, and insects at sunset from the KGRK radar near Austin, TX
Figure 8.10 The echo at the end of the hook on the southwest side of the supercell is caused by debris from a tornado
Figure 8.11 The line of radar echoes passing the KLBB radar was associated with the advance of a wall of dust called a
haboob
Figure 8.12 The radar return is associated with a plume of smoke originating from two fires near the southwest end of the echoes
Figure 8.13 An example of an RHI scan with an aircraft echo embedded within the stratiform echo of a winter storm
Figure 8.14 The radar echoes over south Florida are caused by chaff released from a military aircraft during training exercises
Figure 8.15 The echo labeled “sun spike” on the KOKX radar is caused by microwaves emitted from the sun. Sun spikes are most common near sunrise and sunset when the radar antenna points directly at the sun
Figure 8.16 Receiver noise appears as an increase in the reflectivity factor with range and as random velocities (the speckled values) in the radial velocity field
Figure 8.17 Bragg scattering associated with layers of humidity and turbulence in the tropical trade wind layer leads to a reduction in spectral width (green/blue) from noise values (yellow) in panel a and an enhancement in the radar reflectivity factor (b)
Figure 8.18 The time evolution of moisture layers (green) and the trade wind transition and mixed layers (blue) over a day, as mapped out by the Bragg scattering layers appearing in Figure 8.17. Each red and blue dot denotes the top and bottom of a layer, respectively, on one PPI scan. The data were obtained with the S-Pol 10 cm radar, which was located on the Island of Barbuda in the Caribbean
Chapter 9: Propagation Effects: Attenuation and Refractivity
Figure 9.1 Atmospheric absorption by the 1.35 cm line of water vapor for a mean absolute humidity of 7.75 g m
−3
(blue line) and by the 0.5 cm line of oxygen at a temperature of 20 °C and a pressure of 1 atm
Figure 9.2 Gaseous two-way attenuation in similar atmospheric conditions at S-band and X-band for beams at 0° and 5° elevation
Figure 9.3 PPI plots of (a) K
a
-band and (b) S-band reflectivity values. The arrows are meant to illustrate two methods of creating secondary rays for attenuation estimation as described in the text
Figure 9.4 One-way attenuation due to water vapor (dB km
−1
) for conditions characteristic of air over the Caribbean Sea in winter and over the High Plains of Colorado just east of the Rockies in summer
Figure 9.5 An example of radar-retrieved water vapor density (red) from the S-Pol radar when it was located on an island in the Caribbean. The black line is the water vapor density from a nearby sounding and the blue line is the same sounding averaged to match the radar resolution
Figure 9.6 Trade wind cumulus clouds sampled using a 4.5° sector scan of the S-Pol radar. The cross sections in Figure 9.7 are along the red line
Figure 9.7 Vertical cross sections of (a) reflectivity (dBZ) and (b) liquid water content (g m
−3
) within clouds along the cross section in Figure 9.6
Figure 9.8 The rain attenuation coefficient for three wavelengths as a function of rainfall rate
Figure 9.9 Reflectivity factor at C-band (a) and S-band (b) and corresponding
Z
DR
fields at C- and S-band (c,d) for a thunderstorm complex. Areas of negative bias in reflectivity caused by attenuation at C-band are marked as A and B in panel (a). In panels (a) and (c), a line indicates the azimuthal direction for the RHI plot in Figure 9.10
Figure 9.10 Composite RHI of the reflectivity factor at C-band (a) and S-band (b) and corresponding
Z
DR
fields at C- and S-band (c,d) along the line in Figure 9.9a,c
Figure 9.11 Scatterplots of (a,b)
A
h
and (c,d)
A
DP
vs
K
DP
in pure rain at C-band for (a), (c) all Z
DR
and (b), (d) Z
DR
< 3 dB. Radar variables are computed from 25,920 drop size distributions measured in Oklahoma
Figure 9.12 The same data as in Figure 9.9, but corrected for the effects of attenuation
Figure 9.13 PPI images from an X-band radar of the reflectivity factor (a,c) and differential reflectivity (b,d) during a heavy rain event, uncorrected (a,b) and corrected (c,d) for attenuation. The delta symbols denote the locations of disdrometers
Figure 9.14 Normalized specific attenuation (a,b) and normalized specific differential attenuation (c,d) of dry (a,c) and melting (b,d) hail as a function of size at three radar wavelengths: 11.0 cm (S-band; black curves), 5.45 cm (C-band; dashed dark gray curves), and 3.2 cm (X-band; light gray curves). For the melting hailstones, the vertical dotted line at particle size 0.8 cm represents the cutoff between fully melted raindrops and melting hailstones
Figure 9.15 Relative contributions of different parts of particle size spectrum to S-band (a,c,e,g) and C-band (b,d,f,h)
A
h
at four height levels for large, high-density hail
Figure 9.16 Relative contributions of different parts of particle size spectrum to S-band (a,c,e,g) and C-band (b,d,f,h)
A
DP
at four height levels for large, high-density hail
Figure 9.17 W-band reflectivity (a) and vertical radial velocity (b) obtained by the Wyoming cloud radar flying over a mid-lake lake-effect snowband over Lake Ontario. Note the strong attenuation coincident with the stronger convective updrafts, which likely contain supercooled water
Figure 9.18 Radar refractivity retrievals from the S-Pol radar located in the vicinity of the western Oklahoma dryline. (a) 15:03 UTC: a relatively uniform field before dryline formation; (b) 20:30 UTC: after the dryline had formed, (running through the radar); (c) 22:57 UTC: when the dryline was 15 km east of S-Pol and a secondary dryline had formed running through the radar; and (d) with the dryline through the radar site at 00:01 UTC. Range rings are at every 20 km. Surface station names are shown with temperature (°C) plotted in the upper left and dew point temperatures (°C) in the lower left. Half barbs indicate wind speeds of 5 m s
−1
and full barbs are 10 m s
−1
. Red and blue lines denote research aircraft tracks
Figure 9.19 Surface station refractivity (blue) and corresponding S-Pol radar refractivity (black) comparisons from the same event as in Figure 9.18. Temperature (red; °C) and mixing ratio (green; g kg
−1
) traces for each surface station are also shown
Chapter 10: Operational Radar Networks
Figure 10.1 Coverage of the WSR-88D network at 4000, 6000, and 10,000 ft altitude above ground level across the continental USA
Figure 10.2 Locations of WSR-88D radars in Hawaii, Alaska, US Territories, and overseas US military bases
Figure 10.3 The components of a WSR-88D radar system
Figure 10.5 Characteristics of the WSR-88D resolution and scan strategies
Figure 10.4 Volume coverage patterns used by the WSR-88D radar network
Figure 10.6 Illustration of legacy resolution reflectivity and super resolution reflectivity and radial velocity data
Figure 10.7 TDWR radar locations in the continental USA
Figure 10.8 Example of elevation cuts used by the Baltimore − Washington Airport TDWR for VCP-90 and VCP-80
Figure 10.9 Comparison of reflectivity in a tornadic supercell from a WSR-88D and a TDWR radar where the TDWR was favorably located relative to the hook echo
Figure 10.10 The Canadian operational radar network
Figure 10.11 The Australian meteorological radar network
Figure 10.12 Locations of radars used in the European OPERA cooperative
Chapter 11: Doppler Velocity Patterns and Single-Radar Wind Retrieval
Figure 11.1 Wind components in a Cartesian coordinate system
Figure 11.2 Kinematic properties of the wind field. The black square is the fluid element at the initial time and the white shape is the fluid element at a later time
Figure 11.3 Winds as a function of altitude displayed as wind barbs (a), plots of wind direction and speed (b), and as appearing on the radial velocity display of a Doppler radar (c)
Figure 11.4 Radar display of radial velocity for winds that have constant speed but are backing (turning counterclockwise) with height
Figure 11.5 Radar display of radial velocity for winds that are increasing in speed and are veering (turning clockwise) with height. Note that radial velocities on the edge of the display are folded
Figure 11.6 Radar beams passing through a front for radars positioned at two locations (see Figure 11.7 and 11.8)
Figure 11.7 Radial velocity patterns for a front northwest of a radar (top) and southeast of a radar (bottom) (see Figure 11.6)
Figure 11.8 Radial velocity pattern for a radar beneath a warm front (see Figure 11.6)
Figure 11.9 Radial velocity pattern associated with small-scale rotation similar to what would occur in a supercell thunderstorm. Here, the rotation is located 100 km north of the radar
Figure 11.10 Radial velocity pattern associated with small-scale divergence similar to what would occur in a microburst. Here, the center of divergence is located 100 km north of the radar
Figure 11.11 An example wind profiler. The phased-array antenna is the grid in the middle. The cylindrical devices with crowns are a part of a radio acoustic system used with the wind profiler to measure temperature profiles
Figure 11.12 A three-beam profiling radar system
Figure 11.13 Winds recovered from a boundary layer wind profiler as a function of time and altitude
Figure 11.14 Geometry used for VAD scans
Figure 11.15 Relationship between the kinematic wind fields and the Fourier components derived from VAD analysis
Figure 11.16 (b) Radial velocity data from a ring at constant elevation and the best-fit curve to the data. (a) The zeroth, first, and second harmonic components of the best-fit curve
Figure 11.17 (a) The zeroth, first, and second harmonic components of the best-fit curve. (b) Radial velocity data from a ring at constant elevation and the best-fit curve to the data
Figure 11.18 Profiles of (a) wind speed and direction, and (b) deformation and the axis of dilatation from a radar performing VAD scans in the vicinity of a warm front during an ice storm in Illinois
Figure 11.19 Wind profiles from the KIND WSR-88D radar recovered up to 25,000 ft. every 6 min, while the radar was routinely scanning during a rain event. In the figure, ND means no data are available at that level and time
Figure 11.20 Extended VAD analysis is performed by analyzing data from many rings within a layer using scans at a large number of elevation angles. The technique allows recovery of particle fall velocity and divergence
Figure 11.21 Profiles of divergence, vertical air velocity, and hydrometeor terminal velocity recovered from a radar scanning in EVAD mode during a winter ice storm in Illinois
Chapter 12: Multiple Doppler Wind Retrieval
Figure 12.1 Winds (arrows), vertical air motion (a, colors), and horizontal air flow (b, colors) in a squall line that occurred on June 29, 2003 during the Bow Echo and Mesoscale Convective Vortex Experiment (BAMEX)
Figure 12.2 Sine wave (black) and a reconstruction of the sine wave using two samples per wavelength (blue), five samples per wavelength (orange), and ten samples per wavelength (red)
Figure 12.3 Two thunderstorms located at different distances from a radar. The black lines denote elevations required for the radar to sample the nearby storm within a 100 s time period
Figure 12.4 Radar beam and range gate spacing at 10 km height and 20 km slant range for a typical Doppler radar attempting to scan a thunderstorm over an elapsed time of 100 s. The angular separation between beams is 4° and the range gate spacing is 0.2 km
Figure 12.5 Reflectivity and radial velocity measurements from a single beam of data from a Doppler radar viewing rain cells over the ocean
Figure 12.6 Reflectivity and radial velocity measurements from a second beam of data from the same Doppler radar as in Figure 12.5, but at a different location
Figure 12.7 Unfiltered (a) and filtered (b) Doppler radial velocity data from a single beam in a rain cell using a three-point, top-hat filter. Panel (c) shows the residual obtained by subtracting the filtered data from the unfiltered data
Figure 12.8 Reflectivity (a) and radial velocity (b) from the NCAR CP-4 radar located along the north Florida coast during the Convection and Precipitation/Electrification Experiment (CaPE) illustrating ground clutter, blocked beams, and noise
Figure 12.9 Reflectivity (a) and radial velocity (b) from the NCAR CP-4 radar located along the north Florida coast during the Convection and Precipitation/Electrification Experiment (CaPE) illustrating range folding effects
Figure 12.10 Reflectivity from the NCAR CP-4 radar illustrating a sidelobe echo above a high-reflectivity core within a rainband observed during the Hawaiian Rainband Project
Figure 12.11 Reflectivity from the Greer, South Carolina KGSP WSR-88D radar illustrating a three-body scatter spike
Figure 12.12 Illustration of bilinear interpolation, where eight points in a spherical coordinate system are used to calculate a value at a point in a Cartesian coordinate system
Figure 12.13 The pulse volumes from radars viewing the same point in space from different locations will have different size and orientation, leading to differences in the solutions for the Cartesian wind components
Figure 12.14 Geometry for four radars viewing a thunderstorm
Figure 12.15 The normalized standard deviation of the
u
wind component. The colors on the diagram represent the increase in error in the
u
wind component relative to any error that may be present in the measured radial velocities
Figure 12.16 The normalized standard deviation of the
v
wind component. The colors on the diagram represent the increase in error in the
v
wind component relative to any error that may be present in the measured radial velocities
Figure 12.17 The normalized standard deviation of the horizontal wind vector from the two-radar solution. The colors on the diagram represent the increase in error in the wind relative to any error that may have been present in the measured radial velocities
Figure 12.18 Method to draw the 30° dual-Doppler lobes for two Doppler radars
Figure 12.19 The term
ϵ
u
in Eq. (12.25) for the radar geometry in Figure 12.15–12.17
Figure 12.20 Standard deviation of
w
for a large number of vertical integrations of a field of random velocities characteristic of noise
Chapter 13: Precipitation Estimation with Radar
Figure 13.1 A standard 4-in. orifice manual rain gauge used by the Community Collaborative Rain, Hail and Snow Network (CoCoRaHS)
Figure 13.2 A tipping bucket rain gauge. The inset shows the seesaw tipping mechanism
Figure 13.3 A Joss–Waldvogel impact disdrometer
Figure 13.4 A two-dimensional video disdrometer
Figure 13.5 A Parsivel optical disdrometer
Figure 13.6 Two-dimensional cloud (right) and precipitation (left) optical array probes mounted under the wing of the National Science Foundation/National Center for Atmospheric Research C-130 Hercules Aircraft
Figure 13.7 Raindrop images from a two-dimensional cloud optical array probe
Figure 13.8 Composite raindrop spectra for Hurricanes Alex, Charley, Gaston, and Tropical Storm Matthew, all which occurred in 2004. The number of 1 min spectra comprising the composite are listed. All spectra correspond to a radar reflectivity factor of 40 dBZ
Figure 13.9 Comparison of an exponential raindrop size distribution with a gamma distribution where both correspond approximately to the same radar reflectivity factor and rainfall rate
Figure 13.10 A
Z
–
R
relationship calculated using the indirect method from measurements of raindrop size distributions measured over the western Atlantic Ocean beneath precipitating trade wind clouds
Figure 13.11 The relationship between the reflectivity factor and rainfall rate for the five legacy WSR-88D
Z
–
R
relationships (solid lines). The shading denotes the range of relationships for 69 other
Z
–
R
relationships in the published literature
Figure 13.12 A example of effects of the radar bright band on estimates of precipitation using
Z
–
R
relationships. The actual total storm precipitation was closer to 1 in. across the domain of the radar
Figure 13.13 Scatterplot of gauge vs radar rainfall accumulation for three rainfall events (denoted by red, green, and blue dots) for single polarization retrieval (SPR) using the WSR-88D default
Z
–
R
relationship (a,b), the dual-polarization retrieval (DPR, c,d) for the KEAX (a,c), and KTWX (b,d) WSR-88D radars
Figure 13.14
Z
e
–
S
scatterplot with the equivalent radar reflectivity factor measured using a 0.5° ray path and the precipitation measured with a hotplate (see Figure 13.15)
Figure 13.15 A hotplate precipitation gauge for measurement of snow water equivalent precipitation rate
Figure 13.16 Annual average precipitation across the tropics between 1998 and 2013 as measured by the Tropical Rainfall Measuring Mission
Figure 13.17 Image of the Global Precipitation Mission Core Observatory
Chapter 14: Warm Season Convection
Figure 14.1 The life cycle of a mesoscale convective system. Over a period of 7 h, initial convection intensifies, grows upscale as a cold pool develops, forms a convective line with a bowing segment, and a trailing stratiform region
Figure 14.2 (a) Schematic cross section of the structure and storm-relative flow within a mature MCS with a trailing stratiform precipitation region. (b) Radar reflectivity factor and (c) radial velocity measured by the NOAA P-3 aircraft within a mature MCS
Figure 14.3 Reflectivity factor and radial velocity from the KLCH WSR-88D showing an MCS convective line with strong outbound radial velocities associated with a descending rear-inflow jet. The white line is the Gulf Coastline
Figure 14.4 Quad-Doppler analysis normal to the convective line of a mature MCS showing the cross section parallel storm-relative wind component (colors) and two-dimensional flow vectors in the plane of the cross section. Hot (cold) colors denote flow to the right (left). The descending rear-inflow jet, divergent flow at the top of the updraft, and front-to-rear flow above the rear-inflow jet are all evident
Figure 14.5 Radar fine line associated with a spreading cold pool generated by convection near the KFFC WSR-88D radar
Figure 14.6 Radar reflectivity factor and radial velocity measured in the vicinity of a severe wind producing bow echo squall line by the KSLX WSR-88D
Figure 14.7 Radial velocity fields measured by the KSLX radar at two times 10 min apart during which weak tornadoes were reported along the line. The circles denote regions of local rotation and are marked by cusps in the line
Figure 14.8 A frontal squall line stretching across several states
Figure 14.9 A squall line with leading stratiform precipitation
Figure 14.10 Structure of a supercell thunderstorm as viewed from southwest
Figure 14.11 Evolving flows within a supercell thunderstorm. Updrafts are noted in yellow color and downdrafts in blue color. Green arrows denote the mid-level flow and tan arrows denote the upper-level flow. Gust fronts are noted by the blue lines with barbs. Time progresses from (a) to (d)
Figure 14.12 Relationship of radar echoes in a supercell to key structural features including the forward flank downdraft (FFD), rear flank downdraft (RFD), updraft (UD), and forward and rear flank gust fronts
Figure 14.13 Tornado signatures (circled area) from Arkansas supercell: (a) debris signature in the reflectivity factor field; (b) velocity couplet in the radial velocity field; (c) low or negative values of differential reflectivity; (d) low values of the correlation coefficient
Figure 14.14 A large outbreak of tornadic supercell thunderstorms over northern Alabama and nearby states on April 27, 2011
Figure 14.15 A tornado viewed by the Rapid Scan X-Band dual-Polarization Radar (RAXPOL). The panels show (a) the radar reflectivity factor, (b) the differential reflectivity, (c) radial velocity, and (d) correlation coefficient
Figure 14.16 Reflectivity factor (a) and differential reflectivity (b) within a severe hailstorm over the Dallas–Fort Worth area as observed by the KFWS WSR-88D. The circle and oval areas are described in the text
Figure 14.17 Microburst outflow as observed by the Phoenix, Arizona WSR-88D (KIWA) in the reflectivity factor (a,c,e) and radial velocity (b,d,f) fields at three times, each separated by 10 min. The maximum wind gust was 67 miles h
−1
Chapter 15: Extratropical Cyclones
Figure 15.1 Composite radar image of an extratropical cyclone over the central USA. The yellow line refers to the location of cross sections in Figure 15.4
Figure 15.4 Radar reflectivity factor measured by (a) the KARX WSR-88D and (b) by the W-band Wyoming Cloud Radar flown aboard the NSF/NCAR C-130 aircraft at approximately the same time and in the same location. The features labeled with letters correspond to the features in Figure 15.3
Figure 15.2 Common tracks of the surface low-pressure centers associated with major winter cyclones impacting the North American Continent
Figure 15.3 Radar reflectivity factor from the KARX WSR-88D in the same storm as shown in Figure 15.1. The white dashed line corresponds to the yellow line in Figure 15.1. The features labeled with letters correspond to the features in the cross sections shown in Figure 15.4
Figure 15.5 WSR-88D composite of a weak cyclone over the Ohio Valley. The yellow square in Indiana shows the location of the University of Alabama-Huntsville's vertically pointing X-band Polarization Radar (XPR) that collected the data shown in Figure 15.6
Figure 15.6 (a) Radar reflectivity factor and (b) vertical radial velocity measured by the University of Alabama-Huntsville's X-band vertically pointing radar (XPR) in the cyclone depicted in Figure 15.5
Figure 15.7 Schematic cross sections through an anafront (a) and katafront (b). Frontal zones are indicated in blue, clouds in gray, circulations with arrows, and precipitation as rain (short lines) and snow (stars)
Figure 15.8 An example of a narrow cold-frontal rainband and a wide cold-frontal rainband along the tail of a cyclone that passed over eastern Ohio and Pennsylvania. The larger panel shows the radar reflectivity factor, whereas the left inset shows the radial velocity and the right inset the cloud cover from a visible satellite image
Figure 15.9 Rainbands along an upper level front and a surface cold front. The narrow cold-frontal rainband along the surface front exhibits core and gap structure
Figure 15.10 Cross section from the Wyoming Cloud Radar W-band radar showing the radar reflectivity factor (a) and vertical radial velocity (b) in an elevated convective cell within the southern comma head of the cyclone depicted in Figure 15.1. The dashed line is the aircraft flight track
Figure 15.11 Wyoming Cloud Radar observations of vertical radial velocity depicted in a contour frequency by altitude diagram. The diagram shows the percentage of observations at each altitude falling into each 0.2 m s
−1
velocity bin. The break in the diagram below 7 km is the aircraft altitude. The numbers on the contours denote the percentage of observations with values to the left of the contour
Figure 15.12 Precipitation bands within a winter cyclone over the US East Coast
Figure 15.13 Wyoming Cloud Radar (a) reflectivity factor and (b) vertical radial velocity shown at a one-to-one aspect ratio depicting cloud-top generating cells at the top of a stratiform cloud layer. The aircraft track is the dotted line
Figure 15.14 Wyoming Cloud Radar observations of vertical radial velocity depicted in a contour frequency by altitude diagram. The diagram shows the percentage of observations at each altitude falling into each 0.2 m s
−1
velocity bin. The break in the diagram below 7 km is the aircraft altitude. The numbers on the contours denote the percentage of observations with values to the left of the contour
Figure 15.15 Precipitation fall streaks emanating from generating cells atop the comma-head clouds within an extratropical cyclone
Figure 15.16 Radar signature of the radar bright band, with strong echoes associated with very large wet snowflakes. The inner and outer yellow circles denote the base and top of the bright band
Figure 15.17 Radar signature of “silver dollar”-sized snowflakes (Giant snowflakes were observed at the ground at the location of the highest reflectivity at the time of this image.) The insets show a reconstructed RHI from points A to B and a satellite image showing the location of the radar image
Figure 15.18 The radar reflectivity factor measured by the KLOT WSR-88D within the comma-head of a winter cyclone. The temperature field (°F) and the best estimate of the position of the rain–snow line based on surface observations are overlaid
Figure 15.19 The correlation coefficient (a) and differential reflectivity (b) corresponding to Figure 15.18. The rain–snow line, the temperature field (°F), and the best estimate of the position of the rain–snow line based on surface observations are overlaid
Chapter 16: Tropical Cyclones
Figure 16.1 Hurricane Alice imaged by a radar in 1954 showing the eye and eyewall structure
Figure 16.2 Hurricane tracks in the Atlantic and East Pacific basins with coastal and island radar locations superimposed
Figure 16.3 Hurricane Katrina (2005)
Figure 16.4 Hurricane Olivia (1994) as imaged by the lower fuselage radar of a NOAA WP-3D aircraft. The white lines indicate flight paths
Figure 16.5 Scanning procedure used with the tail Doppler radar on the NOAA WP-3D aircraft
Figure 16.6 (a) Radial velocity (corrected for aircraft motion and unfolded) and (b) radar reflectivity factor from a conical sweep of the tail Doppler radar in Hurricane Olivia (1994)
Figure 16.7 Schematic depiction of the beam locations for fore (blue) and aft (red) scanning of the tail Doppler radar on the NOAA WP-3D aircraft, as well as the ELDORA radar formerly deployed on the U.S. Navy W3-PD aircraft
Figure 16.8 Three-dimensional depiction of the radar reflectivity measured by the GPM precipitation radar overlaid on a GOES-West infrared image of the hurricane
Figure 16.9 Schematic illustration of the radar reflectivity in a northern hemisphere tropical cyclone exhibiting double-eyewall structure
Figure 16.10 Idealized vertical cross section through a hurricane with double-eyewall structure. The scalloped region represents the cloud boundary of the convective features. The shading represents radar reflectivity at intervals of 25, 30, 35, 37.5, 40, and 45 dBZ
Figure 16.11 Schematic representation of the stationary band complex in a hurricane, the flows in which they are embedded, and the core and outer regions of a hurricane
Figure 16.12 (a) Radar reflectivity factor and (b) radial velocity measured by the KHGX WSR-88D in Hurricane Ike (2008) at landfall on September 13, 2008 at 07:04 UTC illustrating the band features noted in the conceptual model in Figure 16.11. Note the folded radial velocities in the eyewall region
Figure 16.13 The eyewall of Hurricane Andrew (1992)
Figure 16.14 (a) Radar reflectivity factor, (b) radial velocity, (c) differential reflectivity, and (d) correlation coefficient measured by the KMHX radar on July 4, 2014 at 03:01 UTC as Hurricane Arthur made landfall on the outer banks of North Carolina
Figure 16.15 Vertical structure of the radar reflectivity factor in tropical cyclones with single and concentric (primary and secondary) eyewalls as measured by the TRMM precipitation radar
Figure 16.16 Radar reflectivity from ELDORA X-band radar at 3-km altitude during (a) 19:36–20:03 UTC September 21 and (b) 18:38–19:15 UTC September 22 and (c) axisymmetric reflectivity from NOAA C-band at ∼3 km at four consecutive times shown in inset
Figure 16.17 Plan view of Hurricane Rita's concentric eyewalls at 4-km altitude as observed by the ELDORA radar during 18:00–18:20 UTC September 22, 2005. The flight leg began and ended in the southwestern portion of the storm where there is a gap in the data. (a) Radar reflectivity. (b) Tangential velocity relative to the storm center. Positive values are cyclonic. (c) Vertical velocity perturbations, defined as velocity components from wavenumbers 2 and higher. (d) Vertical vorticity perturbations, defined as vorticity components from wavenumbers 2 and higher
Figure 16.18 (a) Radar reflectivity factor and 2D wind field and (b) vertical velocity from the NASA EDOP radar in Hurricane Dennis illustrating a hot tower in the storm's eastern eyewall
Figure 16.19 Plan view schematic of an organized rainband complex in a mature tropical cyclone. Reflectivity contours (20 and 35 dBZ) show embedded convective cells (red) that collapse (orange) and form stratiform precipitation traveling around the storm. The arrows represent tangential jets associated with each precipitation feature, with
V
T
indicating the jet within the stratiform sector
Figure 16.20
Figure 16.21 Plan view of ELDORA reflectivity data at 2-km altitude in Hurricane Rita (2005) observed on September 21, 2005. The boxes outline data sections from individual flight legs used to assemble the image. Flight tracks corresponding to each leg are drawn as dotted and/or dashed lines. Visible satellite imagery from the Geostationary Operational Environmental Satellite-East (GOES-E) is shown in the background
Figure 16.22 (a) Schematic of the convective motions associated with two mature convective cells at different radial distances from a storm center within the inner core (see line A and B in Figure 16.19). Reflectivity contours are drawn showing cell 1 at a smaller radius and cell 2 at a larger radius. The solid arrows represent the overturning secondary circulation within each cell, and the plus (minus) signs indicate regions of increasing (decreasing) tangential velocity;
V
1
and
V
2
represent the tangential velocity jets in each cell. (b) Schematic of the dynamics within a stratiform rainband (see line C and D in Figure 16.19). Reflectivity contours are drawn. The line arrows represent vortex-scale motions associated with the overall storm, and the broad arrows represent mesoscale motions associated with the stratiform rainband. The broad arrows of the descending inflow are driven by two regions of a radial buoyancy gradient (∂
B
/∂
R
). The plus signs indicate regions of increasing tangential velocity by the secondary circulation. The circled region indicates the tangential jet (
V
T
). Latent cooling and latent heating occur in the indicated regions
Figure 16.23 RHI through Hurricane Andrew (1992) near the time of landfall in Florida showing spiral rainbands
Figure 16.24 (a) Radar reflectivity factor and (b) radial velocity from the KLIX radar during Hurricane Katrina (2005) at landfall. (c) Radar reflectivity factor and (d) radial velocity from the KHGX radar during Hurricane Ike (2008)
Figure 16.25 Storm total precipitation from Hurricane Ike (2008) as it make landfall and passed over Galveston and Houston, TX
Figure 16.26 Storm total precipitation over southern New England and western New York state during the passage of the remnants of Hurricane Irene (2011)
Figure 16.27 (a) Radar reflectivity from the KMHX radar as Hurricane Irene approached the outer banks of North Carolina. (b) Close-up of the echoes in the box in (a) showing a group of shallow supercells. The box in (b) is further expanded in Figure 16.28
Figure 16.28 (a) Radar reflectivity factor, (b) storm-relative radial velocity, (c) differential reflectivity, and (d) correlation coefficient for echoes within the box in Figure 16.27b. A tornado occurred in the region marked by the black circle
Chapter 17: Clouds and Vertical Motions
Figure 17.1 The radar on the left is a K
a
-band vertically pointing radar. The radars on the right are scanning K
a
-band and W-band radars. These radars are located at the DOE Southern Great Plains ARM facility in Oklahoma
Figure 17.2 One-way attenuation versus wavelength for (a) a 1-km horizontal path at the surface with a pressure of 1010 mbar, a temperature of 294 K, and water vapor amounts varying from 0 to 26.6 g m
−3
Figure 17.3 The radar reflectivity as a function of spherical particle diameter for three different radar frequencies: 3 GHz (red line), 35 GHz (blue line), and 94 GHz (green line). The particle concentration is 1 m
−3
. Rayleigh backscattering is valid for all raindrop sizes at 3 GHz. At higher radar frequencies, deviation from the 3-GHz red line indicates the maximum raindrop size for which the Rayleigh approximation is valid. Note that as the raindrop size increases, there is a decrease in the radar reflectivities and mean Doppler velocities at higher frequencies
Figure 17.4 (a) Wyoming Cloud Radar (WCR) reflectivity (dBZ), for the 06:52–07:18 UTC, February 15, 2010 C-130 flight leg during a pass through the comma head region of an extratropical cyclone. The black box indicates the location for which data are shown in more detail in Figure 17.5. The thick gray line is the flight track. The thin line echo near 5.7 km is caused by ground reflection. (b) WCR vertical radial velocity for the same time period as in (a)
