Page 1 Operational use of dual- polarisation: lessons learned at Météo France after 8 years of experience at all wavelengths (S / C / X) P. Tabary Météo.

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Page 1 Operational use of dual- polarisation: lessons learned at Météo France after 8 years of experience at all wavelengths (S / C / X) P. Tabary Météo France Head of Weather Radar Centre TECO October 2012 Brussels

Page 2 The French metropolitan radar network Demonstrated benefits of polarimetry at X / C / S bands Challenges / Open issues Outline of the presentation

Page 3 In 1991 : 11 radars In 2012  26 radars  All Doppler (Triple-PRT)  18 C band (13 DPOL)  6 S band (2 DPOL)  2 X band (2 DPOL) DP DP : DPOL Radar Purple = S Green = C Brown = X DP The French metropolitan radar network in 2012

Page : First polarimetric radar installed in Trappes

Page 5 Polarimetry Roadmap : First C-band dual-pol radar installed in Trappes 2004 – 2008: Demonstration of the benefits for: Non Precipitation Echo ID Attenuation Correction Self-consistency calibration Rainfall rate retrieval Hydrometeor Classification 2012: 1 ST version of DPOL processing chain operational Non Precipitation Echo ID Basic  DP -based Attenuation Correction 2014 (plan): 2 ND version of DPOL processing chain operational Hydrometeor ID (Rain, Hail, Wet Snow, Dry Snow, …) Improved Rain Rate Estimation : Hybrid “Z-K DP ” estimator Data Quality Calibration Monitoring

Page 6 Histograms of dual-polarisation variables (  HV and texture of Z DR ) in precipitation, ground-clutter and clear-air.  HV Texture of Z DR no precipitation Gourley, JJ, P. Tabary, J. Parent-du-Chatelet, 2007: A fuzzy logic algorithm for the separation of precipitating from non-precipitating echoes using polarimetric radar, J. Atmos. Oceanic Technol. Vol. 24, No. 8, 1439–1451. Automatic Non Precipitation Echo ID

Page 7 Echo Type Yellow = Precipitation Green = clear air Blue = ground-clutter Reflectivity (dBZ) Gourley, JJ, P. Tabary, J. Parent-du-Chatelet, 2007: A fuzzy logic algorithm for the separation of precipitating from non-precipitating echoes using polarimetric radar, J. Atmos. Oceanic Technol. Vol. 24, No. 8, 1439– km Automatic Non Precipitation Echo ID

Page 8 Quantitative Precipitation Estimation Evaluation at hourly time step against rain gauges in rain Comparison restricted to within 60 km of the radar Evaluation at the 3 wavelengths : X / C / S Comparison of 3 different rain rate estimators QPE algorithm is adapted from Tabary (2007) and includes : VPR and beam blocking correction, advection correction, …. No real-time gauge adjustment is applied  “radar only” QPE Tabary P The New French Operational Radar Rainfall Product. Part I: Methodology. Wea. Forecasting. 22:

Page 9 Results at S-band - Summer radar - 4 Events Evaluation at hourly time step against rain gauges RRNB corr ≥ RR NB corr ≥ RR NB corr ≥ “Z-K DP ” - If K DP < 1°/km  Use of Z-R (Marshall-Palmer) with attenuation correction - If K DP > 1°/km  Use of R(K DP ) Z-R (Marshall-Palmer) with attenuation correction PIA (dB) = 0.04 *  DP (°) Z-R (Marshall-Palmer) without attenuation correction RR= Hourly Rain Gauge Accumulation (in mm) NB = Normalized Bias (Radar vs. Gauge) Corr = Correlation coefficient

Page 10 Results at C-band - Summer radars - 26 Events Evaluation at hourly time step against rain gauges DBP2 No RGAdj RRNB corr ≥ RR NB corr ≥ RR NB corr ≥ “Z-K DP ” - If K DP < 1°/km  Use of Z-R (Marshall-Palmer) with attenuation correction - If K DP > 1°/km  Use of R(K DP ) Z-R (Marshall-Palmer) with attenuation correction PIA (dB) = 0.08 *  DP (°) Z-R (Marshall-Palmer) without attenuation correction RR= Hourly Rain Gauge Accumulation (in mm) NB = Normalized Bias (Radar vs. Gauge) Corr = Correlation coefficient

Page 11 Results at X-band – radar - 4 Events Evaluation at hourly time step against rain gauges RRNB corr ≥ RR NB corr ≥ RR NB corr ≥ “Z-K DP ” - If K DP < 0,5°/km  Use of Z-R (Marshall-Palmer) with attenuation correction - If K DP > 0,5°/km  Use of R(K DP ) Z-R (Marshall-Palmer) with attenuation correction PIA (dB) = 0.28 *  DP (°) Z-R (Marshall-Palmer) without attenuation correction RR= Hourly Rain Gauge Accumulation (in mm) NB = Normalized Bias (Radar vs. Gauge) Corr = Correlation coefficient

Page Data Quality: Polarimetric monitoring indicators If well calibrated / processed ( DP & Z DR ), polarimetric variables improve the quality of all conventional radar products; If not well calibrated / processed, polarimetric variables may lower the quality of all conventional radar products; Examples : 1) Large biases on Z DR may strongly impact rain rate estimation (0.2 dB ~ 15%) 2) Remaining ground-clutter may corrupt entire range profiles because of errors in  DP offset computation  Need to have very robust calibration, monitoing & correction procedures

Page & Maintenance on the radar & Maintenance on the radar Long-term monitoring of polarimetric indicators Blaisy (C-band) – August 2010  April 2011  DP offset 9 months Z DR for Z H =20-22 dBZ Z DR at 90°  HV Typical scatter ~  0.3 dB (Required:  0.2 dB) Slight positive bias (+0.2 dB)

Page & Maintenance on the radar & Maintenance on the radar Long-term monitoring of polarimetric indicators Blaisy  DP offset 9 months Z DR for Z H =20-22 dBZ Z DR at 90°  HV Typical scatter ~  0.3 dB (Required:  0.2 dB) Slight positive bias (+0.2 dB) Stability of Z DR is close to – but still slightly below - requirements (0.3 dB vs. 0.2 dB required) Temperature & electronic calibration procedures are thought to be responsible for the observed scatter Work under progress … The quantitative use of Z DR remains a challenge …

Page Conclusions Polarimetry has become the new standard in operational radar networks Polarimetry improves the quality of all radar products (e.g. rain rate estimation) especially at high frequency (X) New products can be proposed with polarimetry (e.g. hydrometeor classification) Phase-based parameters ( DP and K DP ) are very valuable for attenuation correction and rain rate estimation The quantitative use of Z DR is still a challenge (calibration / stability issues vs. 0.2 dB precision required) The benefits for Quantitative Precipitation Estimation have been demonstrated in rain. Solid precipitation estimation is still an open area of research Rain gauges are still needed !

Page 16 Questions