Dual Polarization Technology:

The KICT UpgradePaul SchlatterWarning Decision Training

Branch

AMS/NWA Meeting WichitaNovember 10, 2009

Outline• Explain dual-pol and the new products• What dual-pol can/can’t do• Current training and deployment plans

Traditional radars transmit and receive each pulse with the E-field parallel to the local horizontal surface.

The WSR-88D Prior to Dual-pol Upgrade

_

88D

WSR-88D with the Upgrade to Dual-Pol

• Transmitted at 45o, received at both horizontal and vertical

Compare to Current WSR-88D

• Retrofit on existing dish, tower, etc.

• Same VCPs, wavelength, beamwidth

• Velocity, SW, Reflectivity, Algorithms: Unchanged

Policy of “Do no harm”Policy of “Do no harm”

List of New Products via Dual-Pol• Correlation Coefficient (CC)

• Differential Reflectivity (ZDR)

• Specific Differential Phase (KDP)

• 2 Algorithms – Melting Layer – Hydrometeor Classification

• 9 NEW Precipitation Estimation Products

The Dual-Pol Base Products

New Base Product #1 Correlation Coefficient (CC)

2/122/12

*

vvhh

hhvv

SS

SSCC

Definition Possible Range of

Values

Units Abbreviated Name

Measure of how similarly of the horizontally and vertically

polarized pulses are behaving within a pulse volume

0 to 1 None CC (AWIPS)ρHV (Literature)

N

Physical Interpretation

Non-Meteorological (birds, insects, etc.)

Metr (Uniform)(rain, snow, etc.)

Metr (Non-Uniform)(hail, melting snow, etc.)

Shapes are complex and highly variable. Horizontal and vertical pulses will behave very differently with these objects

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

Shapes can be complex and are mixed phase. Horizontal and vertical pulses behave somewhat differently with these objects

Low CC (< 0.85) High CC (> 0.97) Moderate CC (0.85 to 0.95)

Correlation Coefficient (CC) Typical Values

What is CC Used for?

• Not-weather targets (LOW CC < 0.80)

– Best discriminator

• Melting layer detection (Ring of reduced CC ~ 0.80 – 0.95)

• Giant hail or tornadic debris (LOW CC < 0.70 in the midst of high Z/Low ZDR)

Marginally Severe Supercell

What about the rest?All > 0.97

What about the rest?All > 0.97

InsectsPrecip

Rain

3. Melting Layer Detection

Frozen

Liquid

Melting Layer Example

2.4 deg CC

Mixed Phase

New Base Product #2: Differential Reflectivity (ZDR)

^

^

10log10

v

h

Z

ZZDR

Definition Possible Range of

Values

Units Abbreviated Name

Measure of the log of the ratio of the horizontal to vertical power

returns

-4 to 10 Decibels (dB)

ZDR

Horizontal Reflectivity

Vertical Reflectivity

Physical Interpretation

Spherical (drizzle, small hail, etc.)

Horizontally Oriented

(rain, melting hail, etc.)

Vertically Oriented

(i.e. vertically oriented ice crystals)

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

Pv

Ph

Pv

Ph

Pv

Ph

Zh ~ Zv Zh > Zv Zh < Zv

0log10 10

v

h

Z

Z0log10 10

v

h

Z

Z0log10 10

v

h

Z

Z

Why Would You Examine ZDR?

• Indicates the presence of liquid drops

• Severe-sized hail or hail shafts without a lot of liquid water

Typical ZDR Values for Various Targets

Marginally Severe Supercell

• Definition: gradient of the difference between phase shift in the horizontal and vertical directions

• Units: degrees per kilometer (o/km)

New Base Product #3: Specific Differential Phase Shift (KDP)

VHDP Differential phase shift

Differential Phase Ilustrated

• blah

Forward Propagation has its Advantages

• Immune to partial (< 40%) beam blockage, attenuation, radar calibration, presence of hail

• Used primarily for rainfall estimation

Gradients Most Important

= KDP!!!

Typical Values of Specific Differential Phase Shift (KDP)

Marginally Severe Supercell

Base Data Summary

• Need to integrate at a minimum Z, ZDR, and CC to analyze the situation

• AWIPS is ready• Are humans???

The Dual-Pol AlgorithmsQPE, Hydrometeor Classification, and Melting Layer

Precipitation Estimation Improvement with Dual-Pol

Based on 43 events (179 hrs) of radar rainfall data comparisons to a dense network of rain gauges in C. OK

• 9 new products–Match Legacy PPS–Instantaneous Rate–User Selectable (Up to 10 durations) for the NWS

–Difference products

Dual-Pol QPE Output

• 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 Unknown AP or

Clutter Biological

Current Classification Options

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

• Verification

• “Fuzzy” Logic and ambiguity between types

• Typical Radar sampling limitations (snow at 2000 ft AGL may not be snow at the surface)

Hydrometeor Classification Algorithm Challenges

• Mixed phase hydrometeors: Easy detection for dual-pol!– Z typically increases (bright band)– ZDR and KDP definitely increase

– Coexistence of ice and water will reduce the correlation coefficient (CC ~0.95-0.80)

• Algorithm overlay product for top and bottom of melting layer

Melting Layer Detection Algorithm

ML Product in AWIPS

Part 2: What Dual-Pol Can/Can’t Do

1. Better precipitation estimation

2. Improved detection and mitigation of

non-weather echoes

3. Melting layer identification

4. Hydrometeor classification

5. New/improved storm signatures (NEXT)

Highlights of How Dual-pol Data Will Aid Decision Makers

P

P

P

P

Hail Detection

Horizontal Reflectivity Differential Reflectivity

HAIL HAIL

Thunderstorm Updraft Example“ZDR Columns”

Horizontal Reflectivity Differential Reflectivity2.4° tilt

Melting layer Updrafts

Thunderstorm Updraft ExampleKDP

Horizontal Reflectivity Specific Differential Phase Shift2.4° tilt

Melting layer Updrafts

Thunderstorm updraft exampleCC

Horizontal Reflectivity Correlation Coefficient2.4° tilt

Melting layer Updrafts

• Dry environments– Cloud base near 0oC– Shallow warm cloud depths

• Depth above in cloud 0oC could be proxy for relative updraft strength

• If exists, then good chance of lead time on hail production and thus storm severity

ZDR Column Issues

Reflectivity Lowest CutStorm-Relative Velocity0.5 deg CC

Tornadic Debris Signature

Reflectivity0.5 deg CC

What Dual-Pol Can do

• Vastly improve precip estimation

• Detect hail aloft, infer presence of giant hail

• Detect melting layer and improve winter weather nowcasting

• Improve identification of non-weather echoes

• Offer best guess at P-type aloft

• Improve confidence in damaging tornado close to the radar

What Dual-pol Can’t do

• Overcome the laws of physics

• Perfect rainfall estimation at each gate

• Exact hail sizes

• Identify surface precipitation type

• Detect every tornado

• Predict any tornado

Part 3: Deployment and Training Plans

When/What is the Impact?

• All WSR-88Ds upgraded 2010-2012

• 10-14 days radar downtime during upgrade

Target Two Critical Stakeholders

Course WSR-88D Dual Pol Operations Course

Dual-PolEducation and Outreach

Audience All NWS Forecasters - Meteorologists - Hydrologists - CWSUs

- First Responders- Broadcast Mets- Emergency Managers- Other Public Stakeholders

Scope - 2000 Students- Two ~8 hour courses- Web-based & Simulations

-10,000 students- Two online modules- WCM support material

Training/Deployment High-level Schedule

• KICT upgraded Mid-July 2010*

2009 OND

2010 JFM

2010 AMJ

2010 JAS

2010 OND

2011 JFM

2011 AMJ

2011 JAS

2011 OND

2012 JFM

2012 AMJ

2012 JAS

2012 OND

2013 JFM

2013AMJ

2013 JAS

Beta Test 1st WSR-

88Ds upgraded

Deployment10-14 days downtime each radar

WDTB’s Dual-Pol Outreach CourseTargeted audience: EMs, first responders, media, general public

Beta DPOC

WDTB’s Dual-Pol Operations Course Part 1 Topics: Background and Theory

End Goal: Develop Expertise

WDTB’s Dual-Pol Operations Course Part 2Topics: Advanced Applications and Simulations

End Goal: Fully Integrated into Operations

Questions?

Tel: 405-325-1091

Email: Paul.T.Schlatter@noaa.gov