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Dual Polarization Martin Hagen, Elena Saltikoff Deutsches Zentrum für Luft- und Raumfahrt (DLR) Oberpfaffenhofen, Germany Finnish Meteorological Institute.

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Presentation on theme: "Dual Polarization Martin Hagen, Elena Saltikoff Deutsches Zentrum für Luft- und Raumfahrt (DLR) Oberpfaffenhofen, Germany Finnish Meteorological Institute."— Presentation transcript:

1 Dual Polarization Martin Hagen, Elena Saltikoff Deutsches Zentrum für Luft- und Raumfahrt (DLR) Oberpfaffenhofen, Germany Finnish Meteorological Institute (FMI) Helsinki, Finland

2 Radar course 2010/11, Class room phase2 Precipitation is directly related to atmospheric motion.  Hydrometeors are displaced  Doppler shift of radar waves Cloud and precipitation particles have different shape, phase, size, and falling behaviour  scattering properties  Polarization Why Doppler and Polarization? Dynamics and Microphysics of precipitation

3 Radar course 2010/11, Class room phase3 Dual Polarization Who did work through the pre-reading material? Are you ready for a short test?

4 Radar course 2010/11, Class room phase4 Usage of dual-polarization Survey by Elena January 2010 What is your answer? What do you think dual-polarization will do for you (one ore more options)? Better quality of data Better rainfall estimations Better hail detection Identificat. non-met. echoes Rain-snow bounda. detect. Particle classification All of above I do not know 31.4% 33.3% 37.3% 15.7% 31.4% 23.5% 31.4% 35.2%

5 Radar course 2010/11, Class room phase5 Usage of dual-polarization Survey by Elena January 2010 What is your answer? Does your institute use or plan to use dual-polarization for operational forecasting? Which dual-polarization parameters you measure or will measure (one or more options)? We already do Yes, before 2012 Yes, after 2012 No confirmed plans yet I do not know ZDR rhoHV KDP phiDP LDR None I do not know 25.5% 13.7% 9.8% 11.8% 39.2% 20.4% 18.4% 12.2% 16.3% 4.1% 75.5%

6 Radar course 2010/11, Class room phase6 1960198519952002 Doppler RadarDoppler Radarbistataticdual-Doppler+Lidar (research) (operational Doppler RadarAssimilation in NWP in Europe) 19761986 1990 2004 polarimetric Radar polarimetric Radar polarimetric Radar (research) (operational, without (operational, (R-Z-ZDR) (R-KDP) substantial success) MeteoFrance) Polarization and Doppler Radar History DLR Poldirad

7 Radar course 2010/11, Class room phase7 Weather Radars in Europe 194 weather radars 166 have Doppler 34 have dual- polarization http://www.knmi.nl/opera

8 Radar course 2010/11, Class room phase8 Shape of Falling Raindrops Raindrops falling with their terminal velocity are oblate due to the air flow from below. Drops can be described as rotational ellipsoids with the axis a and b Observations in a vertical wind tunnel (Pruppacher & Klett) 2.70 mm3.45 mm5.30 mm 5.80 mm7.35 mm8.00 mm

9 Radar course 2010/11, Class room phase9 Internal Motion of Raindrops Raindrops do oscillate and tumble during fall 5 mm raindrop in a vertical wind tunnel (Univ. Mainz) Oscillation 60 Hz for a 5 mm drop tumbling

10 Radar course 2010/11, Class room phase10 Rain Drop Shapes Various studies in wind tunnels or observations in free atmosphere. Parameterization by Pruppacher and Beard (1970): a/b = 1.03 – 0.062 D eq with D eq in mm D eq equivalent volumetric diameter

11 Radar course 2010/11, Class room phase11 Polarimetric Radar Observations The polarization of an electromagnetic wave is defined by the orientation of the electrical field vector E Conventional Doppler radars use horizontal linear polarization only The orientation of the wave guide at the feed defines the polarization

12 Radar course 2010/11, Class room phase12 Polarimetric Radar Observations Mode simultaneous H and V transmit and receive - simple technical realization - possible contamination by strong depolarization in melting layer Rain Graupel Hail

13 Radar course 2010/11, Class room phase13 Polarimetric Radar Observations Mode alternating H and V transmit (pulse to pulse), simultaneous H and V receive - expensive and sensitive switch required - can measure full scattering matrix (research radars) Rain Graupel Hail

14 Radar course 2010/11, Class room phase14 Dual-Polarization Modes polarization transmit receive simultaneous transmit and receive STAR-mode, hybrid H V H  co-polar V  co-polar alternating from pulse to pulse 1. pulse: H 2. pulse: V H  co-polar V  cross-polar V  co-polar H  cross-polar fixed (“LDR-mode”) HH  co-polar V  cross-polar = 45° weather services use the STAR mode, some additionally LDR mode

15 Dual-Polarization Radar Products - Differential Reflectivity (ZDR) - Copolar Correlation Coefficient (ρ HV (0)) - Differential Phase, specific Differential Phase - Linear Depolarization Ratio

16 Radar course 2010/11, Class room phase16 Differential Reflectivity (ZDR) Differential reflectivity is the ratio between horizontal and vertical reflectivity factor using z H, z V in mm 6 m 3, or Z H, Z V in dBZ. positives ZDR is caused by oblate particles falling orientated parallel to the polarization basis. ZDR is weighted with reflectivity. ZDR depends on particle shape, orientation and falling behaviour. Z H Z V V H

17 Radar course 2010/11, Class room phase17 Differential Reflectivity (ZDR) Indication for oblate particles falling horizontally orientated

18 Radar course 2010/11, Class room phase18 Differential Reflectivity (ZDR) ZDR can be used to identify insects and birds in clear air echoes –Rain: ZDR 0 – 5 dB –Insects ZDR 5 – 10 dB ZZDR POLDIRAD at Waltenheim-sur-Zorn

19 Radar course 2010/11, Class room phase19 Differential Reflectivity (ZDR) ZDR should be zero or positive negative ZDR is an indication for a failure  differential attenuation in C-band by strong rain ZZDR

20 Radar course 2010/11, Class room phase20 Differential Reflectivity (ZDR) ZDR should be zero or positive negative ZDR is an indication for a failure  “monster snow flakes” Mie-scatter, large particles Z ZDR

21 Radar course 2010/11, Class room phase21 Co-polar Correlation Coefficient (ρ HV (0)) The correlation coefficient ρ HV (0) describes the correlation of the scattering signal between horizontal and vertical polarization. –a high correlation is expected if the orientation of particles does not change between pulses –a low correlation is expected if the orientation of particles changes irregular between pulses high correlation between H and V low correlation between H and V V-Pol. H-Pol. V-Pol. H-Pol. pulses log. power

22 Radar course 2010/11, Class room phase22 Co-polar Correlation Coefficient (ρ HV (0)) ρ HV (0) it almost 1 in rain, in strong rain 0.98 to 0.97. ρ HV (0) below 0.90 indicates particles with irregular shapes, ice/water mixtures and strong tumbling during fall. Used for the identification of irregular shaped particles.

23 Radar course 2010/11, Class room phase23 Co-polar Correlation Coefficient (ρ HV (0)) ρ HV (0) ZDR ZHZH Poldirad 13 Jan. 2011 09:15 towards 52° (-1 dB offset)

24 Radar course 2010/11, Class room phase24 Differential Propagation Phase Measurements of the differential phase describe properties of the propagation path, it is not a property of the backscattering media. Different propagation speed of waves (  phase shift) in rain and air. Refractive index n = 1.0003 (air), n = 1.33 (water). Non-spherical particles will have different phase shift depending on polarisation plane.

25 Radar course 2010/11, Class room phase25 The differential propagation phase shift on forward scatter  DP occurs on the way towards the scattering particle. The backscatter for particles with D << λ is without phase shift. The backscattered wave will receive again a differential phase shift. The specific differential propagation phase KDP describes the phase shift between horizontal and vertical polarized wave. Differential Propagation Phase  DP (r 1 )  DP (r 2 ) r1r1 r2r2

26 Radar course 2010/11, Class room phase26 Differential Phase

27 Radar course 2010/11, Class room phase27 Differential Propagation Phase POLDIRAD

28 Radar course 2010/11, Class room phase28 Summary Differential Propagation Phase K DP is a measure for the mass of the particles. Phase measurements are absolute measurements. They are independent of the calibration of the radar. Phase measurements are not affected by attenuation. K DP and  DP is used for the estimation of rain rate and the correction of attenuation.

29 Radar course 2010/11, Class room phase29 Linear Depolarization Ratio (LDR) The linear depolarization ratio LDR describes the ratio of cross- polar reflectivity to co-polar reflectivity using z VH, z H in mm 6 m -3 or Z VH, Z H in dBZ. LDR is caused by particles which are rotated to the polarization plane. LDR is weighted by reflectivity. LDR depends on the shape of the particles, their orientation and their falling behaviour.

30 Radar course 2010/11, Class room phase30 Linear Depolarization Ratio (LDR) Indication for oblate particles falling irregular or canted

31 Radar course 2010/11, Class room phase31 Melting Layer Stratiform Precipitation

32 Radar course 2010/11, Class room phase32 Melting Layer Convective Precipitation

33 Application of Dual-Polarization - Rain rate estimation - Hydrometeor classification - Quality control

34 Radar course 2010/11, Class room phase34 Rain rate and radar reflectivity Empirical relation between rain rate R and reflectivity z z in mm -6 m -3 R in mm/h Coefficients a and b depend on drop size distribution. 7000 1-minute drop size distribution, Oberpfaffenhofen, 1996

35 Radar course 2010/11, Class room phase35 Rain rate and polarimetric radar measurements Additional information about raindrop size distribution by differential reflectivity: sensitive to large drops. 7000 1-minute drop size distribution, Oberpfaffenhofen, 1996 Small errors in polarimetric quantities can give large errors in rain rate estimation.

36 Radar course 2010/11, Class room phase36 Summary Rain Rate Estimation Polarimetric quantities are only available for rainfall rates above a certain value, since small raindrops are spherical. As a first step a quality control is necessary Polarimetric estimates are only valid in the rain layer An optimized procedure would use different methods depending on rain intensity (numbers are approximate C- band) –rain rates below 2 mm/huse z-R relation –rain rates 2 – 10 mm/huse z-ZDR-R relation –rain rates above 10 mm/huse KDP-ZDR-R relation

37 Radar course 2010/11, Class room phase37 Classification of Hydrometeors Forecasters want to see this and not that

38 Radar course 2010/11, Class room phase38 Classification of Hydrometeors From observations and theoretical or practical considerations we know: Z (dBZ) ZDR (dB) KDP (°/km) ρ HV (0)LDR (dB) Rain10 – 550 – 50 – 10≈ 1.0< -30 Ice crystals< 150 – 20≈ 0.99< -30 Snow aggregates < 250 – 20≈ 0.99< -30 Graupelup to 40 ≈ 0 > 0.95 < 0.95 melting < -30 < -25 melting Hailup to 70 ≈ 0 0.9 – 0.95 < 0.9 melting > -25 -25 – -15 melting

39 Radar course 2010/11, Class room phase39 Classification of Hydrometeors From observations and theoretical or practical considerations we know: Z (dBZ) ZDR (dB) KDP (°/km) ρ HV (0)LDR (dB) Insects< 55 – 10?0.9 – 1.0 ?< -30 ? Birds< 53 – 6?0.9 – 1.0 ?< -30 ? Chaff< 50 – 6?< 0.3> -20 Ground clutter anynoisy 1 stopped < 0.6 rotating antenna > -20

40 Radar course 2010/11, Class room phase40 Classification of Hydrometeors Based on thresholds (Höller et al., 1994) Based on fuzzy logic (Vivekanandan et el., 1999) Each manufacturer (researcher) has her/his own algorithm, display, hydrometeor classes, parameters to adjust

41 Radar course 2010/11, Class room phase41 Classification of Hydrometeors

42 Radar course 2010/11, Class room phase42 Example of Fuzzy Logic: Rain – Snow A. Dalphinet, MeteoFrance - DLR snow at ground rain at ground Verification using MRR precipitation fall velocities snow rain 13 14 UTC 2500 AGL 0 m Reflectivity 21 Nov. 2008 13:30 UTC

43 Radar course 2010/11, Class room phase43 Quality control for polarimetric radar products Quality control for rain rate estimation: rain only, good beam filling, low beam blockage, low attenuation,... bad good

44 Radar course 2010/11, Class room phase44 Dual-Polarization Conclusion Additional information available –useful for hydrometeor classification –improved rain rate estimation –improved quality control –attenuation correction possible Dual-polarization –makes attenuation visible (at C- and X-band) –requires very high data quality (calibration issue) –many algorithms are only available for rain


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