1. STEPS Severe Thunderstorm Electrification and Precipitation Study May-July 2000 Prof. Steven Rutledge Department of Atmospheric Science Colorado State University

2. Radar Network Dual-Doppler and Triple Dopplerconfigurations

3. STEPS Ops Center CSU-CHILL National Radar Facility; 10 cm polarimetric/Doppler www.chill.colostate.edu

4. STEPS Fixed Instrumentation: Triple- Doppler Network and LMA (VHF TOA) At KGLD: -NWS -T-28 -NSSL -Electric field balloon -Mobile mesonet -MGLASS

5. Storm swath of base reflectivities (2100-0251 UTC) with NLDN lightning data overlaid. 2130 UTC 2328 UTC 0110 UTC 0110 UTC 0251 UTC KGLD Tessendorf et al., JAS, 2005

6. 29 June Supercell Inverted tripole +CGs 3 June storm Inverted dipole No CGs 23 June storm Early: normal tripole, -CGs Later, collapse: inverted tripole, +CGs

7. 29 June 3 June 23 June Q: Why did charge structures differ? A: Supercooled liquid water content. + +

8. Switching gears now, lets talk about polarimetric radar……

9. NWS Polarimetric upgrade!! A really exciting opportunity for the science community as well! The STSR architecture first developed on the CSU-CHILL radar in 1995. Proof of concept. In STSR, H-V polarizations transmitted at the same time. Previously, alternate transmission of H,V used. Needed method to switch polarizations with so called “ferrite” switch—very unreliable.

10. The polarization variables..  In addition to Z and Doppler velocity..  Z dr, differential reflectivity  Sensitive to particle shape and phase  Power based measurement  Φ dp, differential phase (K dp )  Sensitive to particle shape and phase  Phase based measurement  ρ hv, correlation coefficient  Sensitive to particle shape and phase  Power based measurement  In addition to Z and Doppler velocity..  Z dr, differential reflectivity  Sensitive to particle shape and phase  Power based measurement  Φ dp, differential phase (K dp )  Sensitive to particle shape and phase  Phase based measurement  ρ hv, correlation coefficient  Sensitive to particle shape and phase  Power based measurement

11. hail rain H V Z dr = 10 log 10 (Z hh /Z vv )

12. Single particle Z dr expressed as dB Plot from Herzegh and Jameson (1992) Illustrates dependence on both shape and phase, water vs. ice (dielectric)

13. see Lang et al. 2004 J. Atmos. Ocean. Tech. Non-precipitation echo: insects (preferred flight direction) Zdr values reach CHILL data system limit (+9 dB) Large Z and Z dr when looking at long axis of insects, oriented with mean wind.

14. Propagation Differential Phase, φ dp  φ dp is a phase based measurement, independent of power  Since the H wave encounters more dielectric compared to the V wave, the H wave moves more slowly than the V wave. H wave lags the V wave therefore in phase.  Φ dp is then the phase difference (in degrees) between the H and V wave as these waves propagate out and back to the radar. This difference (degrees) will be > 0 for oblate particles (rain), zero for isotropic media (hail), and < 0 for prolate particles (e.g., oriented ice particles).  φ dp is a phase based measurement, independent of power  Since the H wave encounters more dielectric compared to the V wave, the H wave moves more slowly than the V wave. H wave lags the V wave therefore in phase.  Φ dp is then the phase difference (in degrees) between the H and V wave as these waves propagate out and back to the radar. This difference (degrees) will be > 0 for oblate particles (rain), zero for isotropic media (hail), and < 0 for prolate particles (e.g., oriented ice particles). H V

15. From A. Illingworth, Chapter 5, in Weather Radar (2003) P. Meischner, Editor (Springer) Illustration of H and V waves propagating through oblate raindrops. A phase lag between H and V waves results since the H wave moves slightly more slowly than the V wave, in oblate media. For prolate media, the V wave lags the H wave. Phi dp (propagation differential phase) is a measure of this phase difference between H and V waves.

16. PPI display presentation of differential propagation phase -20 o diff. phase at near point +15 o ~8 km farther range 35 o phase change in 8 km Basic concept: H, V return signal phase difference changes most rapidly in beam path segments where net differential forward scattering effects are large

17. Conversion to customary K dp units: (Bringi and Chandra (2001) Eq 7.17) K dp is product of rainwater content and deviation of mass-weighted mean axis ratio from one. (Alternatively, particles with mean axis ratio of one (tumbling hailstones) do not contribute to Kdp). K dp is phase measurement, not dependent on accurate radar reflectivity calibration (including partial beam blockage effects), Z dr offsets / drifts, etc. From a physical perspective…. K dp is only arrived at after “filtering” the range profile of φ dp Too little filtering introduces noise in rain estimates, too much filtering removes fine scale estimates of rain rate and rain rate local peaks.

18. Based on best fit of S-band K dp – rain rate scatter plots for typical range of rain DSD ’ s gives these estimators for rain rate R in mm hr -1 (Bringi and Chandra 2001 eq 8.14): R(K dp )=50.7(K dp ) 0.85 (using Beard and Chuang drop shapes) R(K dp )=40.5(K dp ) 0.85 (using Pruppacher-Beard drop shapes) Note: NSSL results are R(K dp )=44.8(K dp ) 0.822 (Ryzhkov et al., 2005 JAM) (In all of the above K dp is one-way value expressed in o km -1 ) Summary of rain rate estimation with S-band polarimetric radar: Best estimator needs to be selected based on rain regime: Light rain (quasi-spherical drops) : conventional R(Z) Moderate “ pure ” (no ice contamination) rain: Z dr modified R(Z) Heavy rain or confirmed ice contamination: R(K dp ) more useful Details of how to optimally select / combine various rain rate estimators is topic of current research. (Also more to come on this in later sections of this course.)

19. Increasing rain rate Rain rate estimation…

20. CHILL: Rainfall Accumulation Optimization Algorithm CHILL: Rainfall Accumulation NEXRAD Z-R Algorithm Ice contamination!

21. 30 July 2010 DZ Zdr Kdp Strong rainfall event -34 mm of rain in 30 minutes Zdr Z

22. Engineering Parking Lot at Colorado State University: Flash Flood of 28 July 1997 CHILL observations of the Ft. Collins flood led to research that caused the NWS in Denver to modify their algorithms used to derive rainfall rates from NWS radar measurements

23. An Example from the Ft. Collins Flash Flood of 28 July 1997: Cumulative Rainfall Gauge Survey Z = AR b

24. Vertical structure of microphysical classification Hydrometeor type classification results for 5 July storm from STEPS (data from CSU-CHILL)—Model Intercomparison

25. Squall line and HID using polarimetric variables

26. Co-polar H,V Correlation (ρ hv ) The correlation coefficient is a measure of the shape variations or irregularities in the radar resolution volume…… The correlation coefficient decreases when diverse particles types are present. This diversity can be in phase of water, shape and size.

27. ρ hv reduction to ~0.91 in a hail shaft: 7 June 1995 near Gilcrest, CO CSU-CHILL data Negative Zdr; these values also modeled for larger, wet hail. Mie effects operate to reduce Z H relative to Z V, leading to negative Zdr. For axis ratios in range of 0.6 to 0.8.

28.  hv reduced in hail area: Mixed precip types; ρ hv especially reduced when Z rain =Z ice Diverse shapes

29. Ryzhkov et al. (2005) REMOVING NON-MET ECHO: FUZZY LOGIC CLASSIFICATION (FHC) Clutter/AP Rain Insects/Birds Example from JPOLE of rain embedded in clutter/AP and biological scatterers

30.  : Primarily useful to characterize variability of scatterer characteristics within the pulse volume. Drizzle / light rain > ~0.98 Convective (but no ice) rain > ~0.96 Hail / rain mixtures ~0.90 Bright band mixed rain and snow ~0.75 Tornado debris ~0.50 or less Ground clutter ~0.6-0.8

31. Some winter storm applications…….

33. Bright band descending to surface in rain/snow transition

34. Vertical profile in a snowstorm.

35. Dual offset antenna: 2008 Prof. Bringi leads a successful >$1M MRI proposal to acquire a new antenna Offset feed design, first time be used on an S-band weather radar Unprecedented performance has now been demonstrated Advances the Facility to a new level of performance The new antenna set the stage for another major development…..

36. Dual-wavelength project  No other radar like this in the world  Will allow CHILL to make impact on NWS gap-filling radar concept  Takes advantage of CASA second generation radar  Unique dual- frequency combination enables new science  CSU cost share dollars used to acquire critical components  Will be tested later in the spring….  No other radar like this in the world  Will allow CHILL to make impact on NWS gap-filling radar concept  Takes advantage of CASA second generation radar  Unique dual- frequency combination enables new science  CSU cost share dollars used to acquire critical components  Will be tested later in the spring…. 12/9/2010 Main Reflector Sub-Reflector Feed Horn CASA Magnetron T/R Pkg Dual-frequency Feed Horn CSU-CHILL Update 36