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What can Dual-Polarization Doppler Radar Do for You? Neil Fox Department of Atmospheric Science University of Missouri - Columbia.

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Presentation on theme: "What can Dual-Polarization Doppler Radar Do for You? Neil Fox Department of Atmospheric Science University of Missouri - Columbia."— Presentation transcript:

1 What can Dual-Polarization Doppler Radar Do for You? Neil Fox Department of Atmospheric Science University of Missouri - Columbia

2 The NSSL Joint Polarization Experiment  The Nexrad radar at Norman, OK has been retrofitted for dual-polarization capability  The project will determine the benefits of a network wide upgrade  This talk will present (some of) the expected benefits  http://cimms.ou.edu/~schuur/jpole/

3 Presentation Contents  Principles of polarization diversity  What can be measured  Benefits of dual polarization –Precipitation estimation –Error reduction –Hydrometeor classification

4 Polarized electric fields of radiation are scattered differently by oblate hydrometeors

5 Z DR  Differential reflectivity  The ratio of returned power in the horizontal and vertical polarized channels  Information on axial ratio of precipitation particles

6 Axial ratio of airborne particles e.g. an elephant Axial ratio ~ 1 Z DR = 0

7 Real rain: this will not fly

8 Or Disney rain? Has even less chance of being in the air Z DR < 0 Tells us something is wrong!

9 Something this shape may be found in the air Z DR > 0

10 K DP  Differential phase  Measures the difference in phase of the horizontal and vertical polarized return signals  Affected by particle axial ratio as it impacts on forward propagating signal phase

11 Rain rate estimation  Z-R relationships: very sensitive to drop size distribution  Z DR -R relationships: inherent drop size information  K DP -R relationships: Much less sensitive to drop size distribution  K DP, Z DR, Z – R relationships: Use all the available information on DSD

12 Sample relationships  Z = 200R 1.6 or 300R 1.5 –Reflectivity related to D 6  R = 43 K DP 0.8 –Many relationships close to linearity  R = 54 K DP 0.91 Z DR -0.42 –Combined relationship –Can have other combinations R(Z,Z DR,K DP )  From Schuur et al. (2001)

13 Parameter sensitivity Independent of Calibration Immune to Propagation Effects Immune to Noise Bias Used for QuantitativeEstimation Independent of Concentration ZHZHZHZHNoNoNoYesNo Z DR YesNoNoYesYes K DP YesYesYesYesNo CorrelationYesYesNoNoYes DeltaYesNoYesNoYes LDRYesNoNoNoYes From Zrnic and Ryzhkov, 1999

14 Error reduction (ρ HV )  Cross-correlation of horizontal and vertical polarized return signals  For most precipitation ρ HV is close to 1  For melting snowflakes (e.g. in the bright band) it is lower  For non-meteorological targets it is even lower

15 Bright band detection  Bright band is characterized by the presence of axially asymmetric melting snow particles  These produce large values of Z DR not seen elsewhere in radar data  This provides a means of detecting areas of overestimation of rainfall and correcting them  Also provides a means of finding the 0  C isotherm

16 Z DR Brightband detection

17 Differentiating Brightband from embedded convection

18 Hydrometeor Classification Species Z HH (dB) Z DR (dB) ρ HV K DP (deg km -1 ) L DR (dB) Temp (C ) Drizzle 10 to 25 -0.2 to 0.2 > 0.99 0 to 0.05 < -34 -15 to 40 Rain 25 to 60 0.5 to 4 > 0.97 0 to 20 -27 to 34 -15 to 40 Snow (Dry, low density) -10 to 35 0 to 0.5 > 0.99 0 to 1 < -34 -90 to 0 Snow (dry high density) -10 to 25 -0.5 to 1 > 0.95 0.1 to 2 -25 to -34 -90 to 0 Snow (wet melting) 20 to 45 -0.5 to 3 0.8 to 0.95 0.2 to 4 -13 -18 0 to 5 Graupel, dry 20 to 50 -0.5 to 1.0 > 0.99 -1 to 1 < -30 -90 to 0 Graupel, wet 40 to 55 -0.5 to 3 > 0.99 -1 to 4 -20 to -25 0 to 5 Hail, small wet < 2cm 50 to 60 -0.5 to 0.5 > 0.95 -1 to 1 < -20 -7 to 5 Hail, large wet> 2cm 55 to 70 -4 to –0.5 >0.96 -2 to 2 -10 to -15 -7 to 5 Rain& hail 55 to 70 -1 to 1 >0.99 0 to 20 -20 to -10 -7 to 5

19 Graupel?

20 Hail and hail size  Combining Z and Z DR gives information on this  Also knowledge of freezing layer height helps (see next talk!)

21 Lightning detection / prediction K DP is negative: Vertically aligned ice crystals K DP is positive: Horizontally aligned ice crystals

22 If it’s so great, why test it?  Theory is great, but how does it work operationally?  How does the processing work  Where are the real benefits and how do these compare to costs?  Testing different scan strategies  Application in other areas

23 WAFICUS 2: December 2003


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