Atmospheric InstrumentationM. D. Eastin Dual-Polarization Radars.

Atmospheric Instrumentation M. D. Eastin

Dual-Polarization Radars


Outline


• Comparison (Single vs. Double)• Definitions and Notation

• Parameters based on dual-polarimetric data• Differential reflectivity (ZDR)• Linear depolarization ratio (LDR)• Co-polar correlation (ρHV)• Differential phase shift (KDP)

• Hydrometeor Classification Algorithm (HCA)• Improved Rainfall Estimation

M. D. Eastin

Single-polarization radars:

• Transmits and observes echoes using only horizontal polarization• Assumes ALL hydrometeors are spherical liquid drops• Estimates rain rates and storm total precipitation under these assumptions and constraints

HOWEVER

• Large hydrometeors are NOT spherical• Upper-level hydrometeors are NOT liquid and are NOT spherical

Single vs. Dual Polarization Radars

Atmospheric Instrumentation

M. D. Eastin

Dual-polarization radars:

• Transmits and observes echo with both horizontal and vertical polarization• Unique hydrometer shapes and sizes more accurately determined from the two views• Can distinguish between large/small liquid drops, hail, graupel, and the ice crystal spectrum

Provides: More detailed information about storm structure and evolutionMore accurate rain rate estimates → improved flash flood warnings



M. D. Eastin

Backscatter Considerations:

Single Polarization

• Radar transmits horizontal polarization• Radar receives only backscatter at horizontal polarization• Assumes all hydrometeors are spherical water drops• Radar cross section is “simple” and unique

Dual Polarization

• Radar transmits horizontal and vertical polarization• Radar receives backscatter across all combinations:

Transmits Backscattered PowerHorizontal ↔ Horizontal or VerticalVertical ↔ Horizontal or Vertical

• Radar cross-sections are not unique and are dependent on particle shape• Can only develop a unique radar equation for one polarization (horizontal → as before)

Otherwise: Dual-polarization parameters must be defined as “ratios” or “correlations” between the returned horizontal power and returned vertical power



4

625

DK

M. D. Eastin

Observed Quantities:

• Since dual-polarized radars can transmit and receive signals in both horizontal (H)and vertical (V) polarization, the number of uniquely observed quantities increasesfrom two (single polarization) to eight (dual polarization)

Single: P HH / φ HH

Dual: P HH / P HV / P VV / P VH P H H

φ HH / φ HV / φ VV / φ VH

where: P = power of the signal (Watts) often converted to ZE (dBZ)

φ = phase of the signal (radians) often converted to VR (m s-1)

Co-polar: Signals transmitted and received at the same polarization (PHH)

Cross-polar: Signals transmitted at onepolarization and received at another (PHV)

Transmitted at horizontal polarization

Received at horizontal polarization

Definitions and Notation


M. D. Eastin

Derived Parameters:

• As a result of such additional information, a number of useful parameters have beendeveloped from combinations of these eight observations that can help distinguishbetween hydrometeor type, shape, and size

1. Radar reflectivity (ZE) from PHH

2. Radial velocity (VR) from φHH

3. Spectral width (σ) from φHH

4. Differential reflectivity (ZDR) from PHH and PVV 5. Linear depolarization ratio (LDR) from PHH and PVH

6. Differential phase shift (KDP) from φHH and φVV

7. Co-polar correlation (ρHV) from PHH and PVV

•Many more additional parameters have been developed (see Section 6.2.5 in your textand Cifelli and Chandrasekar 2010) but have not received as much attention due to theirnarrow / limited use

Definitions and Notation


Same as singlepolarized radars

Unique to dualpolarized radars

M. D. Eastin

Dual-Polarimetric ParametersDifferential Reflectivity (ZDR):

• Used to identify hydrometeor shape / type

• Depends on axis ratio:

Oblate particles ZDR > 0

Prolate particles ZDR < 0

Spherical particles ZDR ~ 0

Why use ZDR?

• Hydrometeor shape can be easily inferred • Presence of hail and/or super-cooled drops can be easily inferred

10log10dBZDR

ZVV

ZHH

4.0 mm 3.7 mm 2.9 mm

2.7 mm 1.8 mm 1.4 mm


M. D. Eastin


Liquid water drops

• Shape ranges from spherical (small drops)to oblate (large drops)

• Drops fall with their major axis horizontal

ZDR = 0 to +5 dB

Ice Crystals

• Shapes are highly variable• Typically fall with major axis horizontal

ZDR = +2 to +4 dB (columns)ZDR = +3 to +6 dB (dendrites / plates)ZDR = 0 to +1 dB (aggregates)

4.0 mm 3.7 mm 2.9 mm

2.7 mm 1.8 mm 1.4 mm


M. D. Eastin


Graupel and Hail

• Graupel often has a “classic raindrop” shape and falls with the major axis vertical

ZDR = –0.5 to +1 dB (graupel)

• Hail is often spherical, but irregular, and it tends to tumble while with falls but with its major axis aligned vertically

ZDR = –1 to +0.5 dB (hail)


M. D. Eastin



M. D. Eastin



Heavy rainfall(small drops)ZE = 50 dBZZDR < 2 dB

Hail-rain mix(large drops)ZE = 50 dBZZDR = 3-5 dB

M. D. Eastin


Advantages:

• Independent of radar calibration• Independent of hydrometeor concentration• Can easily identify hail/graupel• Can help identify melting layer• Easier to identify ground clutter

Limitations:

• Susceptible to the same data quality effects as traditional radar reflectivity

1. Attenuation2. Second-trip echoes3. Side lobes


Large HailZ > 45 dBZZDR < 1 dB

M. D. Eastin

Dual-Polarimetric ParametersLinear Depolarization Ratio (LDR):

• Used to identify hydrometeor shape / type

• Detects tumbling, wobbling, canting angles, phase, and irregular shaped hydrometeors

Small raindrops LDR < -30 dBLarge raindrops -30 < LDR < -20 dBHail / raindrop mixture -20 < LDR < -10 dB

Wet snow -18 < LDR < -13 dB

Why look at LDR?

• Hydrometeor shape can better inferred when combined with ZDR measurements

10log10dBLDR

ZHH

ZHV


M. D. Eastin



Hail-rain mix(large drops)ZE = 50 dBZZDR = 3-5 dB

LDR > -25 dB

Heavy rainfall(small drops)ZE = 50 dBZZDR < 2 dB

LDR < -25 dB

M. D. Eastin


Advantages

• Independent of radar calibration• Independent of hydrometeor concentration• Can help identify hydrometeor type

Limitations



• Susceptible to “noise” since cross-polar signals are 2-3 orders of magnitude smaller than co-polar signals



LDR > -20 dB

M. D. Eastin

Dual-Polarimetric ParametersCo-Polar Correlation (ρHV):

• A measure of the linear correlation betweenthe co-polar horizontal backscatter (PHH) and co-polar vertical backscatter (PVV)within a pulse volume

• Influenced by wobbling, canting angles, phase, and irregular hydrometeors

• Used to identify hydrometeor type, mixed-phase precipitation, and non-meteorological targets

Small diversity in hydrometeor type: 0.96 < ρHV < 1.00Large diversity in hydrometeor type: 0.85 < ρHV < 0.95Non-meteorological targets: ρHV < 0.85

Why use ρHV?

• Clarify hydrometeor type when combined with ZDR and LDR• Identify other targets (insects, birds, debris, etc.)

PHH

PVV


M. D. Eastin



M. D. Eastin

Dual-Polarimetric Parameters

Insects(Low ρHV)

Co-Polar Correlation (ρHV):


M. D. Eastin

Dual-Polarimetric Parameters

All Snow(High ρHV)Mixed Phase

(Low ρHV)

Co-Polar Correlation (ρHV):


M. D. Eastin



Tornado Debris

Signature(TDS)

(Very low ρHV)

ZEZDR

ρHV

M. D. Eastin


Advantages

• Independent of radar calibration• Independent of hydrometeor concentration

Limitations



• Affected by low signal to noise ratios


LDR > -20 dB1.00 > ρHV > 0.85


M. D. Eastin

Dual-Polarimetric ParametersDifferential Phase Shift (KDP):

• Measure of the phase shift difference between the co-polar horizontal (φHH) and the co-polar

vertical (φVV) returns due to both backscatter and forward propagation

where:

• Used to distinguish large drops from hail, identify super-cooled drops above the

freezing layer, and estimate rain rate

Spherical hydrometeors KDP < 1.0 Oblate hydrometeors KDP > 1.0

• Horizontal phase shift is often larger than the vertical phase shift since large raindrops are oblate → horizontal propagates slower

122/deg 12

rrkmK DPDP

DP

VVHHDP φDP = 0° φDP = 10° φDP = 10°

No phaseshift

Phaseshift

No additionalphase shift

ΦDP = 0° ΦDP = 25° ΦDP = 25°

No phaseshift

Phaseshift

No additionalphase shift


M. D. Eastin

Dual-Polarimetric ParametersSpecific Differential Phase Shift (KDP):


M. D. Eastin

Dual-Polarimetric ParametersSpecific Differential Phase Shift (KDP):

Advantages

• Independent of radar calibration• Independent of drop concentration• Independent of attenuation• Can be used to distinguish large rain

rates (flash floods) from shafts oflarge hail (severe hail)

Limitations

• Noisy product → interpretation difficult • Less reliable at greater ranges


Large Hail (middle)Large Drops (left edge)

Z > 45 dBZZDR < 1 dB

LDR > -20 dB1.00 > ρHV > 0.85

M. D. Eastin

Hydrometeor ClassificationHydrometeor Classification Algorithm (HCA):

• Algorithm runs in real-time on WSR-88D• Based on fuzzy logic technique• Total of 17 classification types

Five observedpolarimetric variables

[ ZHH ZDR LDR ρHV KDP ]

Temperature profile

Hydrometeor type at

each volume element

FuzzyLogicBox


M. D. Eastin

Hydrometeor ClassificationHydrometeor Classification Algorithm (HCA):



Improved Rainfall EstimationDual-Polarization Rain Rate Algorithms:

•There are three dual-polarization quantities that can be related to rain rate

ZHH over-sensitive to large drops

ZDR sensitive to the shape of mediumto large drops

KDP sensitive to both drop shape andnumber concentration

WSR-88D Radars:

•Uses the hydrometeor classification algorithmto first identify the basic target type

•Then applies the following three equations

Rain:

Mixed:

Snow:

43.3927.00067.0 DRHH ZZR

714.0102.0 HHZR

822.044 DPKR


Summary


• Comparison (Single vs. Double)• Definitions and Notation

• Parameters based on dual-polarimetric data• Differential reflectivity (ZDR)• Linear depolarization ratio (LDR)• Co-polar correlation (ρHV)• Differential phase shift (KDP)

• Hydrometeor Classification Algorithm (HCA)• Improved Rainfall Estimation


References

Atlas , D., 1990: Radar in Meteorology, American Meteorological Society, 806 pp.

Cifelli, R. and Chandrasekar, V. , 2010: Dual-Polarization Radar Rainfall Estimation, American Geophysical Union, Washington, D. C.. doi: 10.1029/2010GM000930

Crum, T. D., R. L. Alberty, and D. W. Burgess, 1993: Recording, archiving, and using WSR-88D data. Bulletin of the American Meteorological Society, 74, 645-653.

Doviak, R. J., and D. S. Zrnic, 1993: Doppler Radar and Weather Observations, Academic Press, 320 pp.

Fabry, F., 2015: Radar Meteorology Principles and Practice, Cambridge University Press, 256 pp.

Joregensen, D. P., T. Matejka, and J. D. DuGranrut, 1996: Multi-beam techniques for deriving wind fields from airborne Doppler radars. Meteorology and Atmospheric Physics, 59, 83-104.

Park, H. S., A. V. Ryzhkov, D. S. Zrnic, and K. E. Kim, 2009: The hydrometeor classification algorithm for the polarimetric WSR-88D: Description and application to an MCS. Weather and Forecasting, 24, 730-748.

Reinhart, R. E., 2004: Radar for Meteorologists, Wiley- Blackwell Publishing, 250 pp.

Ryzhkov, A. V., T. J. Schuur, D. W. Burgess, et al., 2005: The joint polarization experiment: Polarimetric rainfall measurement and hydrometeor classification. Bulletin of the American Meteorological Society, 74, 645-653.

Atmospheric InstrumentationM. D. Eastin Dual-Polarization Radars.

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