1. Dual Polarization Technology: The KICT Upgrade Paul Schlatter Warning Decision Training Branch Paul Schlatter Warning Decision Training Branch AMS/NWA Meeting Wichita November 10, 2009

2. Outline Explain dual-pol and the new productsExplain dual-pol and the new products What dual-pol can/can’t doWhat dual-pol can/can’t do Current training and deployment plansCurrent training and deployment plans

3. 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

4. WSR-88D with the Upgrade to Dual-Pol Transmitted at 45 o, received at both horizontal and verticalTransmitted at 45 o, received at both horizontal and vertical

5. Compare to Current WSR-88D Retrofit on existing dish, tower, etc.Retrofit on existing dish, tower, etc. Same VCPs, wavelength, beamwidthSame VCPs, wavelength, beamwidth Velocity, SW, Reflectivity, Algorithms: UnchangedVelocity, SW, Reflectivity, Algorithms: Unchanged Policy of “Do no harm”

6. List of New Products via Dual-Pol Correlation Coefficient (CC)Correlation Coefficient (CC) Differential Reflectivity (ZDR)Differential Reflectivity (ZDR) Specific Differential Phase (KDP)Specific Differential Phase (KDP) 2 Algorithms2 Algorithms –Melting Layer –Hydrometeor Classification 9 NEW Precipitation Estimation Products9 NEW Precipitation Estimation Products

7. The Dual-Pol Base Products

8. New Base Product #1 Correlation Coefficient (CC) DefinitionPossible Range of Values UnitsAbbreviated Name Measure of how similarly of the horizontally and vertically polarized pulses are behaving within a pulse volume 0 to 1NoneCC (AWIPS) ρ HV (Literature) 

9. 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)

10. Correlation Coefficient (CC) Typical Values

11. What is CC Used for? Not-weather targets (LOW CC < 0.80)Not-weather targets (LOW CC < 0.80) –Best discriminator Melting layer detection (Ring of reduced CC ~ 0.80 – 0.95)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)Giant hail or tornadic debris (LOW CC < 0.70 in the midst of high Z/Low ZDR)

12. Marginally Severe Supercell What about the rest? All > 0.97 What about the rest? All > 0.97 Insects Precip Rain

13. 3. Melting Layer Detection Frozen Liquid Melting Layer Example 2.4 deg CC Mixed Phase

14. New Base Product #2: Differential Reflectivity (ZDR) DefinitionPossible Range of Values UnitsAbbreviated Name Measure of the log of the ratio of the horizontal to vertical power returns -4 to 10Decibels (dB) ZDR Horizontal Reflectivity Vertical Reflectivity

15. Physical Interpretation Spherical (drizzle, small hail, etc.) Horizontally Oriented (rain, melting hail, etc.) Vertically Oriented (i.e. vertically oriented ice crystals) ZDR ~ 0 dBZDR > 0 dBZDR < 0 dB PvPv PhPh PvPv PhPh PvPv PhPh Z h ~ Z v Z h > Z v Z h < Z v

16. Why Would You Examine ZDR? Indicates the presence of liquid dropsIndicates the presence of liquid drops Severe-sized hail or hail shafts without a lot of liquid waterSevere-sized hail or hail shafts without a lot of liquid water

17. Typical ZDR Values for Various Targets

18. Marginally Severe Supercell

19. Definition: gradient of the difference between phase shift in the horizontal and vertical directionsDefinition: gradient of the difference between phase shift in the horizontal and vertical directions Units: degrees per kilometer ( o /km)Units: degrees per kilometer ( o /km) New Base Product #3: Specific Differential Phase Shift (KDP) Differential phase shift

20. Differential Phase Ilustrated blahblah

21. Forward Propagation has its Advantages Immune to partial (< 40%) beam blockage, attenuation, radar calibration, presence of hailImmune to partial (< 40%) beam blockage, attenuation, radar calibration, presence of hail Used primarily for rainfall estimationUsed primarily for rainfall estimation Gradients Most Important = KDP!!!

22. Typical Values of Specific Differential Phase Shift (KDP)

23. Marginally Severe Supercell

24. Base Data Summary Need to integrate at a minimum Z, ZDR, and CC to analyze the situationNeed to integrate at a minimum Z, ZDR, and CC to analyze the situation AWIPS is readyAWIPS is ready Are humans???Are humans???

25. The Dual-Pol Algorithms QPE, Hydrometeor Classification, and Melting Layer

26. 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

27. 9 new products9 new products –Match Legacy PPS –Instantaneous Rate –User Selectable (Up to 10 durations) for the NWS –Difference products Dual-Pol QPE Output

28. Algorithm makes best guess of dominant radar echo typeAlgorithm makes best guess of dominant radar echo type –For every radar elevation angle Hydrometeor Classification Algorithm Lgt/mod rain Heavy rain Hail “Big drops” Graupel Ice crystals Dry snow Wet snow Unknown AP or Clutter Biological Current Classification Options

29. SOO-DOH Images\kcri_0.5_HC_20080408_0638.pngSOO-DOH Images\kcri_0.5_HC_20080408_0638.pngSOO-DOH Images\kcri_0.5_HC_20080408_0638.pngSOO-DOH Images\kcri_0.5_HC_20080408_0638.png 20000 ft MSL

30. VerificationVerification “Fuzzy” Logic and ambiguity between types“Fuzzy” Logic and ambiguity between types Typical Radar sampling limitations (snow at 2000 ft AGL may not be snow at the surface)Typical Radar sampling limitations (snow at 2000 ft AGL may not be snow at the surface) Hydrometeor Classification Algorithm Challenges

31. Mixed phase hydrometeors: Easy detection for dual-pol!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 layerAlgorithm overlay product for top and bottom of melting layer Melting Layer Detection Algorithm

32. ML Product in AWIPS

33. Part 2: What Dual-Pol Can/Can’t Do

34. 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    

35. Hail Detection Horizontal ReflectivityDifferential Reflectivity HAILHAIL

36. Thunderstorm Updraft Example “ZDR Columns” Horizontal ReflectivityDifferential Reflectivity2.4° tilt Melting layer Updrafts

37. Thunderstorm Updraft Example KDP Horizontal ReflectivitySpecific Differential Phase Shift2.4° tilt Melting layer Updrafts

38. Thunderstorm updraft example CC Horizontal ReflectivityCorrelation Coefficient2.4° tilt Melting layer Updrafts

39. Dry environmentsDry environments –Cloud base near 0 o C –Shallow warm cloud depths Depth above in cloud 0 o C could be proxy for relative updraft strengthDepth above in cloud 0 o C could be proxy for relative updraft strength If exists, then good chance of lead time on hail production and thus storm severityIf exists, then good chance of lead time on hail production and thus storm severity ZDR Column Issues

40. Reflectivity Lowest Cut Storm-Relative Velocity 0.5 deg CC Tornadic Debris Signature

41. Reflectivity 0.5 deg CC

42. What Dual-Pol Can do Vastly improve precip estimationVastly improve precip estimation Detect hail aloft, infer presence of giant hailDetect hail aloft, infer presence of giant hail Detect melting layer and improve winter weather nowcastingDetect melting layer and improve winter weather nowcasting Improve identification of non-weather echoesImprove identification of non-weather echoes Offer best guess at P-type aloftOffer best guess at P-type aloft Improve confidence in damaging tornado close to the radarImprove confidence in damaging tornado close to the radar

43. What Dual-pol Can’t do Overcome the laws of physicsOvercome the laws of physics Perfect rainfall estimation at each gatePerfect rainfall estimation at each gate Exact hail sizesExact hail sizes Identify surface precipitation typeIdentify surface precipitation type Detect every tornadoDetect every tornado Predict any tornadoPredict any tornado

44. Part 3: Deployment and Training Plans

45. When/What is the Impact? All WSR-88Ds upgraded 2010- 2012All WSR-88Ds upgraded 2010- 2012 10-14 days radar downtime during upgrade10-14 days radar downtime during upgrade

46. Target Two Critical Stakeholders Course WSR-88D Dual Pol Operations Course Dual-Pol Education and Outreach Audience All NWS Forecasters - Meteorologists - Hydrologists - CWSUs - 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

47. Training/Deployment High-level Schedule KICT upgraded Mid-July 2010*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 2013 AMJ 2013 JAS Beta Test 1 st WSR- 88Ds upgraded Deployment 10-14 days downtime each radar WDTB’s Dual-Pol Outreach Course Targeted audience: EMs, first responders, media, general public Beta DPOC WDTB’s Dual-Pol Operations Course Part 1 Topics: Background and Theory Topics: Background and Theory End Goal: Develop Expertise End Goal: Develop Expertise WDTB’s Dual-Pol Operations Course Part 2 Topics: Advanced Applications and Simulations End Goal: Fully Integrated into Operations

48. Questions? Tel: 405-325-1091 Email: Paul.T.Schlatter@noaa.gov