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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 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 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 D Convective Z=300R 1.4 Rosenfeld Tropical Z=250R in/hr 0.02 in/hr 0.03 in/hr <0.01 in/hr in/hr 0.04 in/hr 0.05 in/hr 0.02 in/hr in/hr 0.06 in/hr 0.08 in/hr 0.04 in/hr 0.05 in/hr in/hr 0.14 in/hr 0.09 in/hr 0.13 in/hr in/hr 0.19 in/hr 0.26 in/hr 0.21 in/hr 0.33 in/hr in/hr 0.35 in/hr 0.46 in/hr 0.48 in/hr 0.85 in/hr in/hr 0.61 in/hr 0.81 in/hr 1.10 in/hr 2.22 in/hr in/hr 1.09 in/hr 1.44 in/hr 2.50 in/hr 5.80 in/hr in/hr 1.94 in/hr 2.56 in/hr 5.68 in/hr in/hr in/hr 3.45 in/hr 4.55 in/hr in/hr in/hr Quantitative Precipitation Estimation

3 21 September 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 th Southwest Hydrometeorology Symposium, Tucson, AZ Early dual-pol QPE results Point Estimates Areal (basin) Estimates

5 21 September 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 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 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 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 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 th Southwest Hydrometeorology Symposium, Tucson, AZ ZZ DR K DP  hv RHI in stratiform rainfall RHI in stratiform rainfall Hydrometeor Classification

11 21 September 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 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 th Southwest Hydrometeorology Symposium, Tucson, AZ NCAR SPOL radar ; From Vivekanandan et al. 1999, JTech 16, Dual-pol and partial attenuation Partial terrain blockage

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

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

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

17 21 September 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 th Southwest Hydrometeorology Symposium, Tucson, AZ Questions?

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

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

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

22 21 September 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 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 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 th Southwest Hydrometeorology Symposium, Tucson, AZ Differential Reflectivity (Z dr )

24 21 September 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 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 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 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 th Southwest Hydrometeorology Symposium, Tucson, AZ Specific Differential Phase Shift (K DP )

29 21 September 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 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 th Southwest Hydrometeorology Symposium, Tucson, AZ Outline Differential phase shift (  DP )

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

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


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