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Analysis & Diagnosis 1Radar Palette Home Dual Polarized

Dual Polarized Radar

• What is polarimetric radar• Polarimetric products• Uses of these ‘raw’ outputs in forecasting• Winter precipitation field study• Particle ID algorithms• Etc – other topics• Dual Polarized Analysis and Diagnosis

(Important Material – linked to page 80)


Dual Polarization Radar

Courtesy: http://cimms.ou.edu/~schuur/radar.html

- Particles have different shapes and orientations

-Horizontally and vertically polarized signals encounter different amounts of water mass and return different signals

- From these differences, you can infer some properties of the hydrometeors


Polarization Products

• Radar Reflectivity Zh

• Differential Reflectivity ZDR

• Correlation coefficient ρHV

• Differential Phase φDP

• Specific differential phase KDP


Radar Reflectivity Zh

• Conventional radar product• Depends on size (D6) and number density• Sensitive to calibration and partial beam

blocking• Prone to attenuation for shorter microwaves C-

band (5 cm)


Differential Reflectivity (ZDR)

• Ratio of scattered H and V power returns (PHH/PVV)

• Function of the particle shape and orientation• Independent of absolute calibration and particle

concentration• Affected by differential attenuation


Differential Reflectivity (ZDR)Drop shape as a function of size:


Differential Reflectivity (ZDR

) H/V

•Good discriminator between heavy rain and hail.

•For hail ZDR~1 (hail is round and tumbling)

•For heavy rain ZDR is large since ZHH>>ZVV (big drops are Big Macs – large horizontally & smaller in the vertical)

•Low values for ground clutter (< 0) (buildings tend to be vertical…)•High values for biological scatters (> 3) (birds and bugs have winds – horizontally larger than vertical dimension…)•Intermediate values meteorological• ZDR > 0 H dim greater• ZDR < 0 V dim greater• ZDR ~ 0 spherical or randomly oriented


Differential Reflectivity (ZDR

)

•Light rain (0.5 -1.0 dB)

•Moderate rain (1.5 - 2.0 dB)

•Heavy rain (2.5 - 3.0 dB)

•Rain/Hail (0.0 - 1.0 dB)

•Dry snow (0.0 - 0.3 dB)

•Wet snow (1.0 - 2.0 dB)

•Ice crystals (2.0 - 3.0 dB)


Correlation Coefficient – ρHV

Correlation of the time series of H and V returns

Not quantitative measurement

Independent of calibration, attenuation and particle concentration

A measure of the variety of particle shapes and fall modes



For radar bins with single particle shape Zh/Zv is constant in series of pulses. No variance equals 1 on “rhoHV” display

Mixed particles.. Zh/Zv not constant and variance recorded as less than 1.Mixed particles.. Zh/Zv not constant and variance recorded as less than 1.



• ~ 1 for single type of hydrometeors in a preferred orientation (rain or snow)

• Decreases with increasing diversity of hydrometeor shapes and orientation

• More significant if particles wet or large and irregular


First Application of Dual Polarized Radar in Canada

Doppler Radar


Rain with moderate northeast winds

It is OK to look out the window!


Polarized Radar


Sphereical

Flat

Flat

Sphereical

ZDR


New PolarizedRadar

Old DopplerRadar

These are not Stereo Radars


Sphereical

More Blockage


SNOWSpherical

RAINFlat

Flat

Some ice pellets… snow and even rain at the office

Differential Phase is caused by compression of the microwaves in the hyrdometeor medium and the different horizontal and vertical presented by non spherical hydrometeors.


SNOWSpherical

RAINFlat


Rain-Snow Boundary Case

Ground clutterGround clutter

Radome interference

snow

rain

Wet snow and

rain


Bright band Case

Differential Reflectivity

Differential Phase

Reflectivity

Correlation Coefficient

Bright Band


Icing Aloft

Differential Reflectivity

Differential Phase

Reflectivity

Correlation Coefficient

LGT-MDT MXD ICG @ 14KFT


Another Day

December 23, 2004


ρHV

Unifo

rm S

now

Chang

e to

Fre

ezin

g Rai

n

Rain


Particle Characteristics

In Cross-Section

ρρHVHV

Uniform Snow

Less Uniform Melting Snow-Liquid Mix

More Uniform Liquid

High Correlation

Uniform ParticlesLower Correlation

Mixed Particles

High Correlation

Uniform Particles

Infer

Infer

Infe

r

FRLVL

Melting

Melted

Snow

Snow-ZR-

ZR-


Precipitation Transition CaseJanuary 21, 2006


Rain-snow transition at CAREVertiX radar:

• at ~0800Z, fall velocities show change from rain

• after 1030Z, light falling snow only

rain mix /melting / aggregation snow


0700-0710Z:Rain

Rain-snow transition at CARE

0730-0740Z:Rain/Snow

HVSD 10-minute analysis


Rain-snow transition at CARE

1307-1317Z:Dry snow

HVSD 10-minute analysis

0800-0810Z:Wet Snow/ Dry Snow


Z ZDR

ρHV

Round/tumblingH and V are similar

Sig Reflectivity

Correlated in Time

Dry Snow


Heavy Wet Snow


Uncorrelated RhoHV in a sea of correlationsSuggests a phase change line.


Significant Reflectivity but not the sameAlong the entire length of the band


Differential Reflectivity ZDR show a changeAlong the entire length of the band

ZDR > 0 H dim greaterZDR < 0 V dim greaterZDR ~ 0 spherical or randomly oriented

SNOW

RAIN

Wet SNOW

Wet SNOW – shaped like flatten badminton shuttlecocks


1120Z

ZDR

Vr

2006-01-21: Radome attenuation

• ZDR anomaly in northern sector of radar picture; > 3dB high• Rain-snow transition zone approaches and passes radar origin

• Note low level wind direction affects attenuated sector

1030Z

ZDR

50 minutes


Snow Squall CaseFebruary 24, 2006


Z ZDR

ρHV


Polarimetric Radar and Snowsqualls

• Snowfall rates of 5-10 cm an hour are not uncommon in squalls although water equivalents may be only 20 or 30 to 1.

• Do these “big squalls” look any different with polarimetric radar?

• Feb 6 2006 a very strong snowsquall went though the Toronto area.

• 30 cm accumulation east of city.


Differential Reflectivity ZDR is negative so the snow flake tend to be vertically larger

ZDR > 0 H dim greaterZDR < 0 V dim greaterZDR ~ 0 spherical or randomly oriented


RhoHV is nearly perfectly correlatedThe flakes are all the same


Doppler shows a northwesterly flow at an angle to the long axis of the snowsquall.Is the snowsquall going to remain stationary?Is the snowsquall going to drift southward?


Fuzzy Logic to Radar Interpretation

• Inputs (radar variables)

• Decision process (membership functions)

• Output classification (hydrometeor type)


Types of Membership Functions

• Typical one-dimensional Trapezoid Membership Function


2D Trapezoid Membership Function

2-D TMF for Moderate Rain


“Simple” Membership Functions


King HCA (iParCA)

• IDL code emulating the NSSL algorithm• Three schemes of particle classification:

– Simple– Summer– Winter


Radar and snow accumulation

• The Z-S relationship often produces poor results.• Can polarimetric parameters improve this situation


6 hour snowfall accumulation mapDecember 08, 2006

YXU London airport Exeter radar estimated 2-3 cm YXU observed 12 cm with water equivalent of 11 mm


Radar and snow accumulation

• The Z-S relationship often produces poor results.• Can polarimetric parameters improve this situation• Yes… but the work isn’t completed yet…


Dual Polarized Radar

• Doppler was started in Canada in research mode at King City in 1985

• It took 10 years to understand the power of the outputs

• It took 15 years to dopplerize the Canadian radar network

• Dual Polarized radar was started at King City in 2004…


Dual Polarized Radar Analysis and Diagnosis Strategies

An operational guide to getting the most information from Dual Polarized radar:

• Under construction

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