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21 September 2007 4 th Southwest Hydrometeorology Symposium, Tucson, AZ Future QPE: Dual-Pol and Gap-Filler Radars Kevin Scharfenberg University of Oklahoma/CIMMS.

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Presentation on theme: "21 September 2007 4 th Southwest Hydrometeorology Symposium, Tucson, AZ Future QPE: Dual-Pol and Gap-Filler Radars Kevin Scharfenberg University of Oklahoma/CIMMS."— Presentation transcript:

1 21 September 2007 4 th Southwest Hydrometeorology Symposium, Tucson, AZ Future QPE: Dual-Pol and Gap-Filler Radars Kevin Scharfenberg University of Oklahoma/CIMMS and NOAA National Severe Storms Laboratory Kevin Scharfenberg University of Oklahoma/CIMMS and NOAA National Severe Storms Laboratory

2 21 September 2007 4 th Southwest Hydrometeorology Symposium, Tucson, AZ WSR-88D RAINFALL RATE COMPARISON [in/hr] Z [dBZ] Marshall-Palmer Z=200R 1.6 East-Cool Stratiform Z=130R 2.0 West-Cool Stratiform Z=75R 2.0 88D Convective Z=300R 1.4 Rosenfeld Tropical Z=250R 1.2 150.01 in/hr 0.02 in/hr 0.03 in/hr <0.01 in/hr 200.03 in/hr 0.04 in/hr 0.05 in/hr 0.02 in/hr 250.05 in/hr 0.06 in/hr 0.08 in/hr 0.04 in/hr 0.05 in/hr 300.11 in/hr 0.14 in/hr 0.09 in/hr 0.13 in/hr 350.22 in/hr 0.19 in/hr 0.26 in/hr 0.21 in/hr 0.33 in/hr 400.45 in/hr 0.35 in/hr 0.46 in/hr 0.48 in/hr 0.85 in/hr 450.93 in/hr 0.61 in/hr 0.81 in/hr 1.10 in/hr 2.22 in/hr 501.91 in/hr 1.09 in/hr 1.44 in/hr 2.50 in/hr 5.80 in/hr 553.93 in/hr 1.94 in/hr 2.56 in/hr 5.68 in/hr 15.14 in/hr 608.07 in/hr 3.45 in/hr 4.55 in/hr 12.93 in/hr 39.53 in/hr Quantitative Precipitation Estimation

3 21 September 2007 4 th Southwest Hydrometeorology Symposium, Tucson, AZ Dual-polarization in one slide Current state: linear horizontal E pulses: — — — … Original WSR-88D contract specified capability for later upgrade to dual-pol After upgrade, WSR-88D will transmit simultaneous horizontal/vertical pulse (“slant 45º”): ∕ ∕ ∕ ∕ … Separate receivers will listen for horizontal and vertical backscatter Current state: linear horizontal E pulses: — — — … Original WSR-88D contract specified capability for later upgrade to dual-pol After upgrade, WSR-88D will transmit simultaneous horizontal/vertical pulse (“slant 45º”): ∕ ∕ ∕ ∕ … Separate receivers will listen for horizontal and vertical backscatter

4 21 September 2007 4 th Southwest Hydrometeorology Symposium, Tucson, AZ Early dual-pol QPE results Point Estimates Areal (basin) Estimates

5 21 September 2007 4 th Southwest Hydrometeorology Symposium, Tucson, AZ Spring hail cases Cold season stratiform rain Bias of radar areal rainfall estimates Early dual-pol QPE results

6 21 September 2007 4 th Southwest Hydrometeorology Symposium, Tucson, AZ Reflectivity (Z h )Differential reflectivity (Z dr ) Similar reflectivity – very different differential reflectivity! Northeast – Mostly large rain drops Southwest – Mostly hail

7 21 September 2007 4 th Southwest Hydrometeorology Symposium, Tucson, AZ Reflectivity (Z h )Differential reflectivity (Z dr ) Similar reflectivity – very different differential reflectivity! Northwest – relatively large number of relatively small drops Southeast – relatively small number of relatively large drops

8 21 September 2007 4 th Southwest Hydrometeorology Symposium, Tucson, AZ Quantitative Precipitation Estimation Warm rain case – A very unusual DSD! Warm rain case – A very unusual DSD!

9 21 September 2007 4 th Southwest Hydrometeorology Symposium, Tucson, AZ Quantitative Precipitation Estimation Hail case – Z-R relations break down! Hail case – Z-R relations break down!

10 21 September 2007 4 th Southwest Hydrometeorology Symposium, Tucson, AZ ZZ DR K DP  hv RHI in stratiform rainfall RHI in stratiform rainfall Hydrometeor Classification

11 21 September 2007 4 th Southwest Hydrometeorology Symposium, Tucson, AZ Hydrometeor classification algorithm No Echo Lgt/mod rain Heavy rain Hail “Big drops” Graupel Ice crystals Dry snow Wet snow Unknown AP or Clutter Biological

12 21 September 2007 4 th Southwest Hydrometeorology Symposium, Tucson, AZ Operational strategy Where HCA detectsUse R= Ground clutter / AP / biologicals0 RainR(Z, Z dr ) Possible hail below melting layerR(K DP ) Wet snow0.6R(Z) Graupel/hail above melting layer0.8R(Z) Dry snow / ice crystals2.8R(Z) R(Z) is from standard WSR-88D R(Z) equations. Operational strategy Where HCA detectsUse R= Ground clutter / AP / biologicals0 RainR(Z, Z dr ) Possible hail below melting layerR(K DP ) Wet snow0.6R(Z) Graupel/hail above melting layer0.8R(Z) Dry snow / ice crystals2.8R(Z) R(Z) is from standard WSR-88D R(Z) equations. Dual-pol QPE Algorithm

13 21 September 2007 4 th Southwest Hydrometeorology Symposium, Tucson, AZ NCAR SPOL radar ; From Vivekanandan et al. 1999, JTech 16, 837-845 Dual-pol and partial attenuation Partial terrain blockage

14 21 September 2007 4 th Southwest Hydrometeorology Symposium, Tucson, AZ WSR-88D coverage at 3 km AGL

15 21 September 2007 4 th Southwest Hydrometeorology Symposium, Tucson, AZ “Gap-Filler” Boundary Layer Radars Courtesy CASA project Courtesy CASA project

16 21 September 2007 4 th Southwest Hydrometeorology Symposium, Tucson, AZ “Gap-Filler” Boundary Layer Radars Nearest WSR-88D CASA radars

17 21 September 2007 4 th Southwest Hydrometeorology Symposium, Tucson, AZ - Dual-pol WSR-88D upgrade - Dual-pol, low-power “gap-filler” radars - Multiple-radar data mergers incorporating NWP - Corrections for dual-pol radar QPE using rain gages - Incorporation of dual-pol base data vertical profiles - Incorporate corrections for partial beam attenuation (including partial terrain blockage!) - Dual-pol WSR-88D upgrade - Dual-pol, low-power “gap-filler” radars - Multiple-radar data mergers incorporating NWP - Corrections for dual-pol radar QPE using rain gages - Incorporation of dual-pol base data vertical profiles - Incorporate corrections for partial beam attenuation (including partial terrain blockage!) Radar-based QPE: The Future

18 21 September 2007 4 th Southwest Hydrometeorology Symposium, Tucson, AZ Questions? Kevin.Scharfenberg@noaa.gov

19 21 September 2007 4 th Southwest Hydrometeorology Symposium, Tucson, AZ Quantitative Precipitation Estimation R(Z) on a 2 km x 2 km grid

20 21 September 2007 4 th Southwest Hydrometeorology Symposium, Tucson, AZ Quantitative Precipitation Estimation Dual-pol QPE on a 2 km x 2 km grid

21 21 September 2007 4 th Southwest Hydrometeorology Symposium, Tucson, AZ Increasing value  Height  * * * Hydrometeor Classification

22 21 September 2007 4 th Southwest Hydrometeorology Symposium, Tucson, AZ Operational QPE algorithm - Significant improvement over R(Z), particularly inside 150 km and in heavy rain (and possible hail) - Measurable improvement 150-230 km - Measurable improvement over adjusted R(Z) using vertical Z h profiles/mean-field bias (MFB) corrections - Later work to incorporate multiple radars, corrections using MFB, vertical dual-pol profiles, beam attenuation Operational QPE algorithm - Significant improvement over R(Z), particularly inside 150 km and in heavy rain (and possible hail) - Measurable improvement 150-230 km - Measurable improvement over adjusted R(Z) using vertical Z h profiles/mean-field bias (MFB) corrections - Later work to incorporate multiple radars, corrections using MFB, vertical dual-pol profiles, beam attenuation Quantitative Precipitation Estimation

23 21 September 2007 4 th Southwest Hydrometeorology Symposium, Tucson, AZ Differential Reflectivity (Z dr )

24 21 September 2007 4 th Southwest Hydrometeorology Symposium, Tucson, AZ Indicates the presence of larger liquid drops Hail shafts without a lot of liquid water Differential Reflectivity (Z dr )

25 21 September 2007 4 th Southwest Hydrometeorology Symposium, Tucson, AZ Differential reflectivity Z dr = 10 log (E h /E v ) = Z h - Z v [dB] The reflectivity-weighted mean axis ratio of scatterers in a sample volume Z dr > 0  Horizontally-oriented mean profile Z dr < 0  Vertically-oriented mean profile Z dr ~ 0  Near-spherical mean profile Differential reflectivity Z dr = 10 log (E h /E v ) = Z h - Z v [dB] The reflectivity-weighted mean axis ratio of scatterers in a sample volume Z dr > 0  Horizontally-oriented mean profile Z dr < 0  Vertically-oriented mean profile Z dr ~ 0  Near-spherical mean profile EhEh EvEv Differential Reflectivity (Z dr )

26 21 September 2007 4 th Southwest Hydrometeorology Symposium, Tucson, AZ Differential Phase Shift  DP =  h –  v (  h,  v ≥ 0) [deg] The difference in phase between the horizontally- and vertically-polarized pulses at a given range along the propagation path. - Two-way process - Independent of partial beam blockage, attenuation - Independent of absolute radar calibration - Immune to propagation effects on calibration - Independent of system noise Differential Phase Shift  DP =  h –  v (  h,  v ≥ 0) [deg] The difference in phase between the horizontally- and vertically-polarized pulses at a given range along the propagation path. - Two-way process - Independent of partial beam blockage, attenuation - Independent of absolute radar calibration - Immune to propagation effects on calibration - Independent of system noise Differential Phase Shift (  DP )

27 21 September 2007 4 th Southwest Hydrometeorology Symposium, Tucson, AZ Specific Differential Phase Shift  DP(r2) –  DP(r1) K DP = [deg/km] 2 (r 2 – r 1 ) The range derivative of differential phase shift - Identify areas with significantly non-spherical scatterers (usually, rain) - Can estimate rain amount in rain/hail mixture Specific Differential Phase Shift  DP(r2) –  DP(r1) K DP = [deg/km] 2 (r 2 – r 1 ) The range derivative of differential phase shift - Identify areas with significantly non-spherical scatterers (usually, rain) - Can estimate rain amount in rain/hail mixture Specific Differential Phase Shift (K DP )

28 21 September 2007 4 th Southwest Hydrometeorology Symposium, Tucson, AZ Specific Differential Phase Shift (K DP )

29 21 September 2007 4 th Southwest Hydrometeorology Symposium, Tucson, AZ Result: The K DP dilemma - Using a long-distance derivative for calculating K DP can oversmooth heavy rain features but reduces noise - Using a short-distance derivative for calculating K DP retains features in heavy rain but is also noisy Result: The K DP dilemma - Using a long-distance derivative for calculating K DP can oversmooth heavy rain features but reduces noise - Using a short-distance derivative for calculating K DP retains features in heavy rain but is also noisy Specific Differential Phase Shift (K DP )

30 21 September 2007 4 th Southwest Hydrometeorology Symposium, Tucson, AZ Calculating K DP : current practice - If Z > 40 dBZ, use a K DP calculation range of 9 gates (2 km). - Otherwise, use a range derivative of 25 gates (6 km) - Filter the final K DP product at 0.9  hv Calculating K DP : current practice - If Z > 40 dBZ, use a K DP calculation range of 9 gates (2 km). - Otherwise, use a range derivative of 25 gates (6 km) - Filter the final K DP product at 0.9  hv Specific Differential Phase Shift (K DP )

31 21 September 2007 4 th Southwest Hydrometeorology Symposium, Tucson, AZ Outline Differential phase shift (  DP )

32 21 September 2007 4 th Southwest Hydrometeorology Symposium, Tucson, AZ Outline Specific differential phase shift (K DP )

33 21 September 2007 4 th Southwest Hydrometeorology Symposium, Tucson, AZ Rainfall estimation using polarimetric variables R(Z, Z DR ) = 0.0142 Z 0.77 Z DR -1.67 [mm/h] R(K DP ) = 44|K DP | 0.822 sign(K DP ) [mm/h] Rainfall estimation using polarimetric variables R(Z, Z DR ) = 0.0142 Z 0.77 Z DR -1.67 [mm/h] R(K DP ) = 44|K DP | 0.822 sign(K DP ) [mm/h] Quantitative Precipitation Estimation


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