The Italian radar QPE: description, performance analysis and perspectives

Transcription

1 The Italian radar QPE: description, performance analysis and perspectives 15th Plinius Conference on Mediterranean Risks Giardini Naxos, Sicily, Italy Vulpiani 1, G., E. Guerriero 2, P. Giordano 1, M. Negri 1 and P. Pagliara 1 (1) Department of Civil Protection, Rome, Italy (2) Leonardo (formerly Finmeccanica), Rome, Italy

2 Overview The Italian radar QPE - 15th Plinius Conference on Mediterranean Risks Ø The operational contest Ø Rationale/advantages of radar polarimetry Ø QPE processing chain Ø Performance analysis Ø Conclusions

3 The contest National Radar network (June 2016) Ø Federated network Ø Situation at June 2016: 21 radar systems managed by 11 administrations. (The Italian «OPERA») Ø DPC is responsible for the generation and dissemination of products at national level Ø Radar DPC: 6 C-band + 2 X-band, all with dual-pol capability Ø About 65% of the network is composed by polarimetric systems (11 at C-band and 2 at X-band). Ø With the new radars in Sardinia the percentage should increase up to 75%

4 The partners Operational community Scientific community ARPA EMR ARPA PIEMONTE CETEMPS CNR-ISAC Regione Liguria SAR Sardegna ARPA Piemonte CFC ENAV A.M. ARPA-SIMC EmR Radar DPC Monte Crocione (LU) Monte Pettinascura (CS) Monte Serano (PG) Monte Il Monte (CH) Monte Zoufplan (UD) Monte Lauro (SR) Aeroporto dello Stretto (RC) Aeroporto di Fontanarossa (CT) Radar regionali Bric della Croce (TO) Settepani (SV) Gattatico (RE) S. Pietro Capofiume (BO) Monte Grande (PD) Concordia Sagittaria (VE) Monte Macaion (BZ) Fossalon (GO) Monte Rasu (SS) Monte Midia (AQ) Regione Abruzzo PR. Auton. Trento e BZ Regione FVG Regione Veneto Radar A.M (manut. straordinaria) Brindisi San Giusto (PI) Grazzanise (CE) Decimomannu (CA) Radar dell Enav Linate (MI) Fiumicino (RM)

5 Scan Reception Processing Centralization

6 Scan Reception Processing Centralization Composition Dissemination

7 Polarimetric Weather Radar Polarimetric Radar

8 The Italian radar QPE - 15th Plinius Conference on Mediterranean Risks Polarimetric Weather Radar Raindrops are oblate spheroids è Horizontal Returns greater than ver8cal returns è Phase shi9 in horizontal is more than in ver8cal à ΦDP increases with range through rain

9 Rationale of radar polarimetry Carey et al. (2000) ud et al., (2000) Vulpiani et al., (2008) Bringi and Chandrasekar (2001) Vulpiani et al., (2012) Vulpiani et al., (2015)

10 Inversion problem Rain rate estimation (mm/h) from radar observables R = 6π 10 D 4 D max min v( D) D 3 N( D) dd ( m/s ) v(d): fall speed v(d)=a D b R m 3+b Z m 6 a, b, N w are variable with space Z hh = a N 1 b w R b and time polarimetric algorithms reduce uncertainty related to DSD variability Bringi and Chandrasekar (2001)

11 QPE processing chain Rainfall es*ma*on q Data quality retrieval; q Differen8al phase processing; q AAenua8on correc8on; q Polarimetric rainfall es8ma8on; q Quality-based mosaiking of singlesite rainfall maps

12 Data Quality Quality Source Beam Blocking Ground Clutter WLAN Quality Height Attenuation Distance (beam broadening)

13 Data quality Quality Source Data Beam Visibility DEM Blocking VisbilityMa p Occurren ce Map Ground Clutter Clutter Map Clutter Map Occurren cemap Quality WLAN Spike Declutter Z Clutter Map Height FL Freezing Level Distance Attenuation Attenuation Z Φdp

14 Data quality Quality Source Data Correction Beam Visibility DEM Visibility : Bech et al., (2003) Quality Blocking Clutter WLAN Height VisbilityMap ClutterMap Spike Declutter FL Occurrence Map Clutter Map Occurrence Map Z Clutter Map Freezing Level Z FL : Friedrich et al. (2006) Attenuation : Rinollo et al., (2013) Attenuation Correction: Vulpiani et al., (2012) Attenuation Attenuation Z Φdp Z Distance

15 STEP 1 STEP 2 The Italian radar QPE - 15th Plinius Conference on Mediterranean Risks Data processing chain: Φ dp filtering and K dp estimation Vulpiani et al., (2012) Notes: STEP 1 - K dp retrieval (first guess). K Ø dp it can is retrieved be demonstrated from Ψ dp through that: a finitedifference scheme over a ( moving ) window ( of ) length 1L; σ Ψdp σ Kdp = STEP 2: K dp check. 2A Nspecial Lcare is taken σ(k to treat the K dp values that are not dp ) is about 0.05 deg km 1 manifestly for σ(φ physical dp ) = 3 deg and L=3 km STEP 3 STEP 4 ITERATION STEP 3 - Φ dp reconstruction. The filtered differential phase is estimated as σ(k Ø dp ) can be further ' reduced Φ dp by = iterating 2 K dp ( steps s) ds STEP : K dp retrieval (final guess). The final estimation of the specific differential ( ) ( I ) phase 1K dp is σ ( then Ψdp ) obtained as σ range Kdp derivative = of the reconstructed I L Φ dp. 2N

16 Rainfall algorithms Algorithms 1 R(Z)=R(f(Z,Q))) with f(z,q)= (Q Z)/ Q Z-R: Marshall and Palmer (1948) 2 R DUAL (Z, K DP )=(1-w)R(Z)+w R(K DP ) Vertical section of radar volume Z or K dp profiles w: weight depending on K DP (Vulpiani et al., 2015) Radar-Gauge Comparison 1 km 2 resolu*on 90th percen8le of the radar pixels within 10 x 10 km 2 around the gauge Posi8on 150 m R R Range distance [km] Performance analysis BIAS: 10 log(r G /R) ME=<R-R G >

17 Performance Analysis Peaks are related to convective storms R(mm) RG R(Z) R(Z,KDP) Results shown in terms of monthly average of hourly precipitation R for R>1 mm 2 0 g f m a m g l a s o n d g f m a m g l a s o n d g f m 7 RG: Rain Gauge obs. R: Radar estimate 10*log(RG/R) Low Precip regimes-> low Kdp impact g f m a m g l a s o n d g f m a m g l a s o n d g f m R(Z) R(Z,Kdp) target

18 Performance Analysis: spatial distribution of Ratio Bias (aggregated per warning area) 133 Warning Areas Single-polarization rainfall algorithm R(Z) Polarimetric rainfall algorithm R(Z, KDP)

19 Performance Analysis: sensitivity with respect to data quality 7 (Static) Data Quality (2015) R(Z) - Mean Error (mm) R(Z,Kdp) - Mean Error (mm) Mean Quality (%) Mean Quality (%)

20 Performance Analysis: sensitivity with respect to data quality 7 (Static) Data Quality (2015) R(Z) - Mean Ra8o Bias (10*log(P/R)) R(Z,Kdp) - Mean Ra8o Bias (10*log(P/R)) Mean Quality (%) Mean Quality (%)

21 Conclusions Ø The Italian radar network is composed by 21 operational radars, mostly with dual-polarization capability; Ø The processing chain deals with the main error sources through a quality-based scheme Ø The quality is used to derive SRI from the volumetric single-radar observations and to generate the composite products; Ø The use of specific differential phase (KDP) has remarkably improved the QPE Ø Orography represents the main error source Ø Additional system installations are expected to improve the performance

22 Acknowledgments Ø The Authors are grateful to operational and scientific Italian radar community, partner of the national civil protection service. Ø The Authors are also grateful to the industrial partners (Gematronik, Leonardo (formerly Finmeccanica), Eldes for the effective support.

23 References Bech, J., B. Codina, J. Lorente, and D. Bebbington, 2003: The sensitivity of single polarization weather radar beam blockage correction to variability in the vertical refractivity gradient. J. Atmos. Oceanic Technol., 20, Bringi, V. N. and V. Chandrasekar, 2001: Polarimetric doppler weather radar. Cambridge University Press, 636 pp. Carey, L. D., S. A. Rutledge, and D. A. Ahijevych, 2000: Correcting propagation eects in C-band polarimetric radar observations of tropical convection using dierential propagation phase. J. Appl. Meteor., 39, Friedrich, K., Hagen, M., and Einfalt, T.: A quality control concept for radar reflectivity, polarimetric parameters, and Doppler velocity, J. Atmos. Ocean. Tech., 23, , Marshall, J. S., and W. M. Palmer, 1948: The distribution of raindrops with size. J. Meteor., 5, Rinollo, A., Vulpiani, G., Puca, S., Pagliara, P., Kaňák, J., Lábó, E., Okon, L'., Roulin, E., Baguis, P., Cattani, E., Laviola, S., and Levizzani, V., 2013: Definition and impact of a quality index for radar-based reference measurements in the H-SAF precipitation product validation, Nat. Hazards Earth Syst. Sci., 13, , doi: /nhess ud, J., E. L. Bouar, E. Obligis, and M. Ali-Mehenni, 2000: The rain profiling algorithm applied to polarimetric weather radar. J. Atmos. Oceanic Technol., 17, Vulpiani, G., P. Tabary, J. P. D. Chatelet, and F. S. Marzano, 2008: Comparison of advanced radar polarimetric techniques for operational attenuation correction at c band. J. Atmos. Oceanic Technol., 25, Vulpiani, G., M. Montopoli, L. Delli Passeri, A. G. Gioia, P. Giordano, and F. S. Marzano (2012), On the Use of Dual- Polarized C-Band Radar for Operational Rainfall Retrieval in Mountainous Areas, J. Appl. Meteor. Climatol., 51, Vulpiani, G., L. Baldini, and N. Roberto (2015), Characterization of Mediterranean hail-bearing storms using an operational polarimetric X-band radar, Atmos. Meas. Tech., 8,