National Weather Service Dual-Polarization Radar Technology Photo courtesy of NSSL

National Weather Service

Dual-Polarization Radar Technology

Dual-Polarization Radar Technology

Photo courtesy of NSSL


AcknowledgementsAcknowledgements

Paul Schlatter and Andrew Wood

@ NWS Warning Decision Training Branch Norman, OK

http://www.wdtb.noaa.gov/courses/dualpol/outreach/

Paul Schlatter and Andrew Wood

@ NWS Warning Decision Training Branch Norman, OK

http://www.wdtb.noaa.gov/courses/dualpol/outreach/


What Is Dual-Polarization Radar Technology Exactly?What Is Dual-Polarization Radar Technology Exactly?


Why Is Dual-Polarization Technology Important?

Why Is Dual-Polarization Technology Important?

Conventional RadarConventional Radar Dual-Polarization RadarDual-Polarization Radar

Conventional radar tells us about the size of objects

Dual-polarization radar tells us about the size, shape, & variety of objects

– = Size

– = Size(| + –) = Shape σ(| + –) = Variety


Highlights of How Dual-pol Data Will Aid Decision Makers

Highlights of How Dual-pol Data Will Aid Decision Makers

1. Improved detection and mitigation ofnon-weather echoes (insects, clutter, etc.)

2. Melting layer identification

3. Hydrometeor classification (precip type)

4. New severe storm signatures

5. Better precipitation estimation

1. Improved detection and mitigation ofnon-weather echoes (insects, clutter, etc.)

2. Melting layer identification

3. Hydrometeor classification (precip type)

4. New severe storm signatures

5. Better precipitation estimation


List of New Products via Dual-Pol

List of New Products via Dual-Pol

Differential Reflectivity (ZDR)

Correlation Coefficient (CC)

Hydrometeor Classification Algorithm (HCA)

Melting Layer Detection Algorithm (MLDA)

Specific Differential Phase (KDP)

9 NEW Precipitation Estimation Products


Correlation Coefficient (CC)


Melting Layer Detection Algorithm (MLDA)

Specific Differential Phase (KDP)

9 NEW Precipitation Estimation Products




• Simple definition:

• Ratio of Horizontally and Vertically Oriented Power Returns

• Size and shape dependent

• Values of -2 to +6 dB


• Ratio of Horizontally and Vertically Oriented Power Returns

• Size and shape dependent

• Values of -2 to +6 dB


Differential Reflectivity (ZDR)Differential Reflectivity (ZDR)

ZDR < 0 Indicates the presence of large liquid drops.

Most horizontal

ZDR < 0 Indicates the presence of large liquid drops.

Most horizontal

ZDR ~ 0 Indicates large hail or hail shafts without a lot of liquid water


Physical InterpretationPhysical Interpretation

Spherical (small rain drops and large hail)

Horizontal(large rain drops,

melting hail, insects, etc.)

Vertical(i.e. vertically oriented ice

crystals, sometimes large

hail)

ZDR ~ 0 dB ZDR > 0 dB ZDR < 0 dB

Pv

Ph

Pv

Ph

Pv

Ph

Zh ~ Zv Zh > Zv Zh < Zv


Reflectivity vs ZDR

Is there hail and if so where is it, exactly?

Area of ZDR ~ 0(blues)


Updraft DetectionUpdraft Detection

“ZDR columns”: regions of liquid water found above the environmental 0oC height (freezing level)

Water droplets “flattened” by intense updraft (ZDR > 0)

“ZDR columns”: regions of liquid water found above the environmental 0oC height (freezing level)

Water droplets “flattened” by intense updraft (ZDR > 0)





• Measures the relationship between the horizontal and vertical power returns

• ZDR is useful for:

• Detecting the presence of liquid drops (especially large drops)

• Detecting updrafts containing liquid water above the freezing layer

• Detecting severe-sized hail


• Measures the relationship between the horizontal and vertical power returns

• ZDR is useful for:

• Detecting the presence of liquid drops (especially large drops)

• Detecting updrafts containing liquid water above the freezing layer

• Detecting severe-sized hail


Correlation Coefficient (CC)Correlation Coefficient (CC)


The VARIETY or DIVERSITY of shapes reflected back to the radar

“Spectrum width” for reflectivity

Values range from 0 to 1


The VARIETY or DIVERSITY of shapes reflected back to the radar

“Spectrum width” for reflectivity

Values range from 0 to 1


What Do We Mean by Variety? Small Variety Example

What Do We Mean by Variety? Small Variety Example

When the radar detects objects similar in size and type, the correlation coefficient is high


What Do We Mean by Variety? Large Variety Example

What Do We Mean by Variety? Large Variety Example

When the radar detects a variety of object sizes and types, the correlation coefficient is lower


Physical InterpretationPhysical InterpretationNon-Meteorological (birds, insects, etc.)

Uniform Precip(rain, snow, etc.)

Non-Uniform or Mixed Precip

(hail, melting snow, etc.)

Shapes are complex and highly variable. Horizontal and vertical pulses will behave very differently with these objectsAlso GIANT hail, larger than golfballs, because so few of these stones among much smaller objects

Shapes are fairly simple and do not vary much. Horizontal and vertical pulses behave very similarly with these objects Precip vs NonPrecip

Shapes can be complex and are MIXED phase. Horizontal and vertical pulses behave somewhat differently with these objectsMelting Layer Detection

High Diversity

Low CC (< 0.85)

Low Diversity

High CC (> 0.97)

Diverse

Moderate CC (0.85 to 0.95)


Melting LayerMelting Layer

Helps both aviation & surface transportation better resolve precipitation type issues

Identifies areas of icing

Helps both aviation & surface transportation better resolve precipitation type issues

Identifies areas of icing

Liquid

Melting

Frozen


Winter PrecipWinter Precip

Are all these precip types the same?

Right is uniform (either all rain or all snow)

Center and left are mixed precip


Precip vs NonPrecipPrecip vs NonPrecip

Chaff, AP/Ground Clutter, Birds/Insects

Standard Reflectivity (Z) Correlation Coefficient(CC)

Chaff, AP/Ground Clutter, Birds/Insects

Standard Reflectivity (Z) Correlation Coefficient(CC)


Precip vs NonPrecipPrecip vs NonPrecip

0.5o Base Reflectivity 0.5o Correlation Coefficient

Biological Targets

Developing Showers


Very Large Hail Detection

Is there very large hail here?

Area of low CC


Correlation Coefficient (CC)Correlation Coefficient (CC)


• Measure of similarity between the horizontally and vertically oriented pulses in a volume

(VARIETY)

• Lower CC values useful for identifying:

• Non-weather targets

• Melting layer

• Very large hail


• Measure of similarity between the horizontally and vertically oriented pulses in a volume

(VARIETY)

• Lower CC values useful for identifying:

• Non-weather targets

• Melting layer

• Very large hail





• Uses “fuzzy logic” algorithm to make a best guess at radar echo classification on every elevation angle scan

• Combines ZDR, CC and other data

• HCA is useful for:

• Identifying precipitation type

• Hail detection

• Biological target detection

• Ground clutter removal


• Uses “fuzzy logic” algorithm to make a best guess at radar echo classification on every elevation angle scan

• Combines ZDR, CC and other data

• HCA is useful for:

• Identifying precipitation type

• Hail detection

• Biological target detection

• Ground clutter removal


Algorithm makes best guess of dominant radar echo type

–For every radar elevation angle

Algorithm makes best guess of dominant radar echo type

–For every radar elevation angle

Hydrometeor Classification Algorithm


Lgt/modrain

Heavyrain

Hail“Big

drops”Graupel

Ice crystals

Drysnow

Wetsnow

UnknownAP or

ClutterBiological

Currently 11 Classification Options




SOO-DOH Images\kcri_0.5_HC_20080408_0638.png

SOO-DOH Images\kcri_0.5_HC_20080408_0638.png20000 ft MSL


SummarySummary

Dual-Polarization Radar:

• Provides more information about observed targets (i.e., size, shape, & variety)

• Allows forecasters to make better decisions (hopefully) about issuing products

• Enables your local office to improve service during hazardous weather

Dual-Polarization Radar:

• Provides more information about observed targets (i.e., size, shape, & variety)

• Allows forecasters to make better decisions (hopefully) about issuing products

• Enables your local office to improve service during hazardous weather

Hail Mixedw/Rain

BigDrops

HeavyRain

Rain


Ken Drozd

NWS Tucson

520-670-5156 x 223

[email protected]

Ken Drozd

NWS Tucson

520-670-5156 x 223

[email protected]

Documents

National Weather Service Dual-Polarization Radar Technology Photo courtesy of NSSL