1. What to make of this new radar technology Luke Madaus, UW Atmospheric Sciences 11/2/2011

2. Outline Dual-Pol background New dual-pol variables and products A few examples from Pacific Northwest weather Further information

3. What is Dual-Pol?

4. Dual-Pol Variables Differential Reflectivity METEOR SIZE Correlation Coefficient HOMOGENEITY (Specific) Differential Phase METEOR CONCENTRATION

5. Differential Reflectivity (ZDR) ZDR = Z H -Z V Units of dB

6. Differential Reflectivity (ZDR) Rather good relation between major-axis rain drop diameter and ZDR (Large) hail tumbles  spherical (0 dB ZDR) Ice and snow poorly understood Other echoes—even worse

7. Dual-Pol Variables Differential Reflectivity METEOR SIZE Correlation Coefficient HOMOGENEITY (Specific) Differential Phase METEOR CONCENTRATION

8. Correlation Coefficient (CC or  hv ) “Measure of how similarly the horizontal and vertical pulses are behaving within a pulse volume” Unitless, should range from 0 to 1

9. Correlation Coefficient (CC or  hv )

10. Melting layer in Correlation Coefficient MeltingLayer All rain All snow/ice High CC Low CC High CC Melting Layer shows up as a (roughly) circular band of lower correlation coefficients around the radar

11. SNOW & ICE MELTING LAYER RAIN Melting Layer “Bright Band” in Correlation Coefficient

12. Dual-Pol Variables Differential Reflectivity METEOR SIZE Correlation Coefficient HOMOGENEITY (Specific) Differential Phase METEOR CONCENTRATION

13. Differential Phase (  DP )  DP =  H -  V Think of it as the difference in speed between the horizontal and vertical pulses The more dense the precipitation, the more the horizontal pulse tends to get slowed down Specific Differential Phase (KDP) Range derivative of Differential Phase

14. Differential Phase Both in phase Passing through lots of fat drops causes horizontal pulse to slow down more than vertical pulse; no longer in phase Phase difference preserved as pulses exit rain Encountering more fat drops causes phase difference to increase again.  DP 0 deg.45 deg. 0 deg.90 deg. Horizontal beam Vertical beam

17. Estimating rain in complex terrain Radar reflectivity biased by ground returns – it will be high KDP only affected by precipitation in the volume Partial beam blockage KDP-derived rainfall should give more numerous and accurate rainfall estimates in the mountains

19. Dual-Pol Derived Products Dual-Pol Rainfall ACCUMULATED RAIN Hydrometeor Class. Algorithm LIKELY TARGET TYPE Dual-Pol Rain Rate INSTANTANEOUS RAIN RATE

20. Hydrometeor Classification Algorithm Abbreviated HCA Represents a “best guess” of the type of object (hydrometeor or not) at a particular location on radar

21. RainSnow Corr. Coeff.ZDRReflectivity Sigma Of Ref KDP HYDROMETEOR CLASSIFICATION ALGORITHM

23. Pacific Northwest Examples Light Rain Case Frontal Passage Another, detailed frontal passage (GR2A) Bird Migration (GR2A)

24. More training NSSL Dual-Pol Info (Terry Schuur) – http://www.cimms.ou.edu/~schuur/dualpol/ http://www.cimms.ou.edu/~schuur/dualpol/ ROC Dual Pol Training for NWS Partners – http://www.wdtb.noaa.gov/courses/dualpol/outreach/ http://www.wdtb.noaa.gov/courses/dualpol/outreach/ Luke’s Animations of Dual-Pol Products from KLGX and KATX – http://www.atmos.washington.edu/~lmadaus/radars/ http://www.atmos.washington.edu/~lmadaus/radars/

25. Actual NWS KDP Algorithm Is 5-bin median CC > 0.90? Compute 5-bin median of PHI Is associated reflectivity < 40 dBZ? Compute 25-bin average of PHI Take 25-bin least- squares derivative Compute 9-bin average of PHI Take the 9-bin least-squares derivative No KDP Calculated Take Median Take Average Take large- range derivative Not so straight-forward!

26. Bird Migration CC

27. Bird Migration ZDR

28. Dual-Pol Upgrade Drawbacks Slow deployment Loss of clutter filtering until next build release Loss of clutter filtering --Dual-pol derived clutter filtering not for many years Loss of sensitivity – “3 dB down”