atmospheric instrumentationm. d. eastin dual-polarization radars
TRANSCRIPT
Atmospheric Instrumentation M. D. Eastin
Dual-Polarization Radars
Atmospheric Instrumentation M. D. Eastin
Outline
Dual-Polarization Radars
• 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
Single vs. Dual Polarization Radars
Atmospheric Instrumentation
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
Single vs. Dual Polarization Radars
Atmospheric Instrumentation
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
Atmospheric Instrumentation
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
Atmospheric Instrumentation
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
Atmospheric Instrumentation
M. D. Eastin
Dual-Polarimetric ParametersDifferential Reflectivity (ZDR):
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
Atmospheric Instrumentation
M. D. Eastin
Dual-Polarimetric ParametersDifferential Reflectivity (ZDR):
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)
Atmospheric Instrumentation
M. D. Eastin
Dual-Polarimetric ParametersDifferential Reflectivity (ZDR):
Atmospheric Instrumentation
M. D. Eastin
Dual-Polarimetric ParametersDifferential Reflectivity (ZDR):
Atmospheric Instrumentation
Heavy rainfall(small drops)ZE = 50 dBZZDR < 2 dB
Hail-rain mix(large drops)ZE = 50 dBZZDR = 3-5 dB
M. D. Eastin
Dual-Polarimetric ParametersDifferential Reflectivity (ZDR):
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
Atmospheric Instrumentation
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
Atmospheric Instrumentation
M. D. Eastin
Dual-Polarimetric ParametersLinear Depolarization Ratio (LDR):
Atmospheric Instrumentation
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
Dual-Polarimetric ParametersLinear Depolarization Ratio (LDR):
Advantages
• Independent of radar calibration• Independent of hydrometeor concentration• Can help identify hydrometeor type
Limitations
• Susceptible to the same data quality effects as traditional radar reflectivity
1. Attenuation2. Second-trip echoes3. Side lobes
• Susceptible to “noise” since cross-polar signals are 2-3 orders of magnitude smaller than co-polar signals
Atmospheric Instrumentation
Large HailZ > 45 dBZZDR < 1 dB
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
Atmospheric Instrumentation
M. D. Eastin
Dual-Polarimetric ParametersCo-Polar Correlation (ρHV):
Atmospheric Instrumentation
M. D. Eastin
Dual-Polarimetric Parameters
Insects(Low ρHV)
Co-Polar Correlation (ρHV):
Atmospheric Instrumentation
M. D. Eastin
Dual-Polarimetric Parameters
All Snow(High ρHV)Mixed Phase
(Low ρHV)
Co-Polar Correlation (ρHV):
Atmospheric Instrumentation
M. D. Eastin
Dual-Polarimetric ParametersCo-Polar Correlation (ρHV):
Atmospheric Instrumentation
Tornado Debris
Signature(TDS)
(Very low ρHV)
ZEZDR
ρHV
M. D. Eastin
Dual-Polarimetric ParametersCo-Polar Correlation (ρHV):
Advantages
• Independent of radar calibration• Independent of hydrometeor concentration
Limitations
• Susceptible to the same data quality effects as traditional radar reflectivity
1. Attenuation2. Second-trip echoes3. Side lobes
• Affected by low signal to noise ratios
Large HailZ > 45 dBZZDR < 1 dB
LDR > -20 dB1.00 > ρHV > 0.85
Atmospheric Instrumentation
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
Atmospheric Instrumentation
M. D. Eastin
Dual-Polarimetric ParametersSpecific Differential Phase Shift (KDP):
Atmospheric Instrumentation
M. D. Eastin
Dual-Polarimetric ParametersSpecific Differential Phase Shift (KDP):
Atmospheric Instrumentation
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
Atmospheric Instrumentation
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
Atmospheric Instrumentation
M. D. Eastin
Hydrometeor ClassificationHydrometeor Classification Algorithm (HCA):
Atmospheric Instrumentation
M. D. Eastin
Hydrometeor ClassificationHydrometeor Classification Algorithm (HCA):
Atmospheric Instrumentation
M. D. Eastin
Hydrometeor ClassificationHydrometeor Classification Algorithm (HCA):
Atmospheric Instrumentation
M. D. Eastin
Hydrometeor ClassificationHydrometeor Classification Algorithm (HCA):
Atmospheric Instrumentation
Atmospheric Instrumentation M. D. Eastin
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
Atmospheric Instrumentation M. D. Eastin
Summary
Dual-Polarization Radars
• 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
Atmospheric Instrumentation M. D. Eastin
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.