dual polarization technology: the kict upgrade paul schlatter warning decision training branch paul...
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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
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