21 september 2007 4 th southwest hydrometeorology symposium, tucson, az future qpe: dual-pol and...
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![Page 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](https://reader036.vdocuments.mx/reader036/viewer/2022062423/56649cc45503460f9498d635/html5/thumbnails/1.jpg)
21 September 2007 4th Southwest Hydrometeorology Symposium, Tucson, AZ
Future QPE: Dual-Pol and Gap-Filler Radars
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
![Page 2: 21 September 2007 4 th Southwest Hydrometeorology Symposium, Tucson, AZ Future QPE: Dual-Pol and Gap-Filler Radars Kevin Scharfenberg University of Oklahoma/CIMMS](https://reader036.vdocuments.mx/reader036/viewer/2022062423/56649cc45503460f9498d635/html5/thumbnails/2.jpg)
21 September 2007 4th Southwest Hydrometeorology Symposium, Tucson, AZ
WSR-88D RAINFALL RATE COMPARISON [in/hr]
Z [dBZ]Marshall-Palmer
Z=200R1.6
East-Cool Stratiform
Z=130R2.0
West-Cool Stratiform
Z=75R2.0
88D Convective
Z=300R1.4
Rosenfeld Tropical
Z=250R1.2
15 0.01 in/hr 0.02 in/hr 0.03 in/hr <0.01 in/hr <0.01 in/hr
20 0.03 in/hr 0.04 in/hr 0.05 in/hr 0.02 in/hr 0.02 in/hr
25 0.05 in/hr 0.06 in/hr 0.08 in/hr 0.04 in/hr 0.05 in/hr
30 0.11 in/hr 0.11 in/hr 0.14 in/hr 0.09 in/hr 0.13 in/hr
35 0.22 in/hr 0.19 in/hr 0.26 in/hr 0.21 in/hr 0.33 in/hr
40 0.45 in/hr 0.35 in/hr 0.46 in/hr 0.48 in/hr 0.85 in/hr
45 0.93 in/hr 0.61 in/hr 0.81 in/hr 1.10 in/hr 2.22 in/hr
50 1.91 in/hr 1.09 in/hr 1.44 in/hr 2.50 in/hr 5.80 in/hr
55 3.93 in/hr 1.94 in/hr 2.56 in/hr 5.68 in/hr 15.14 in/hr
60 8.07 in/hr 3.45 in/hr 4.55 in/hr 12.93 in/hr 39.53 in/hr
Quantitative Precipitation Estimation
Quantitative Precipitation Estimation
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21 September 2007 4th Southwest Hydrometeorology Symposium, Tucson, AZ
Dual-polarization in one slide
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
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21 September 2007 4th Southwest Hydrometeorology Symposium, Tucson, AZ
Early dual-pol QPE resultsEarly dual-pol QPE results
Point Estimates
Areal (basin) Estimates
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21 September 2007 4th Southwest Hydrometeorology Symposium, Tucson, AZ
Spring hail cases
Cold season stratiform rain
Bias of radar areal rainfall estimates
Early dual-pol QPE resultsEarly dual-pol QPE results
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21 September 2007 4th Southwest Hydrometeorology Symposium, Tucson, AZ
Reflectivity (Zh)Differential reflectivity (Zdr)
Similar reflectivity – very different differential reflectivity!Northeast – Mostly large rain dropsSouthwest – Mostly hail
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21 September 2007 4th Southwest Hydrometeorology Symposium, Tucson, AZ
Reflectivity (Zh)Differential reflectivity (Zdr)
Similar reflectivity – very different differential reflectivity!Northwest – relatively large number of relatively small dropsSoutheast – relatively small number of relatively large drops
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21 September 2007 4th Southwest Hydrometeorology Symposium, Tucson, AZ
Quantitative Precipitation Estimation
Quantitative Precipitation Estimation
Warm raincase – A very unusual DSD!
Warm raincase – A very unusual DSD!
![Page 9: 21 September 2007 4 th Southwest Hydrometeorology Symposium, Tucson, AZ Future QPE: Dual-Pol and Gap-Filler Radars Kevin Scharfenberg University of Oklahoma/CIMMS](https://reader036.vdocuments.mx/reader036/viewer/2022062423/56649cc45503460f9498d635/html5/thumbnails/9.jpg)
21 September 2007 4th Southwest Hydrometeorology Symposium, Tucson, AZ
Quantitative Precipitation Estimation
Quantitative Precipitation Estimation
Hail case –Z-R relationsbreak down!
Hail case –Z-R relationsbreak down!
![Page 10: 21 September 2007 4 th Southwest Hydrometeorology Symposium, Tucson, AZ Future QPE: Dual-Pol and Gap-Filler Radars Kevin Scharfenberg University of Oklahoma/CIMMS](https://reader036.vdocuments.mx/reader036/viewer/2022062423/56649cc45503460f9498d635/html5/thumbnails/10.jpg)
21 September 2007 4th Southwest Hydrometeorology Symposium, Tucson, AZ
Z ZDR
KDPhv
RHI instratiformrainfall
RHI instratiformrainfall
Hydrometeor ClassificationHydrometeor Classification
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21 September 2007 4th Southwest Hydrometeorology Symposium, Tucson, AZ
Hydrometeor classification algorithm
No EchoLgt/mod
rainHeavy
rainHail
“Big drops”
GraupelIce
crystalsDry
snowWet
snowUnknown
AP orClutter
Biological
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21 September 2007 4th Southwest Hydrometeorology Symposium, Tucson, AZ
Operational strategy
Where HCA detects Use R=Ground clutter / AP / biologicals 0Rain R(Z, Zdr)Possible hail below melting layer R(KDP)Wet snow 0.6R(Z)Graupel/hail above melting layer 0.8R(Z)Dry snow / ice crystals 2.8R(Z)
R(Z) is from standard WSR-88D R(Z) equations.
Operational strategy
Where HCA detects Use R=Ground clutter / AP / biologicals 0Rain R(Z, Zdr)Possible hail below melting layer R(KDP)Wet snow 0.6R(Z)Graupel/hail above melting layer 0.8R(Z)Dry snow / ice crystals 2.8R(Z)
R(Z) is from standard WSR-88D R(Z) equations.
Dual-pol QPE AlgorithmDual-pol QPE Algorithm
![Page 13: 21 September 2007 4 th Southwest Hydrometeorology Symposium, Tucson, AZ Future QPE: Dual-Pol and Gap-Filler Radars Kevin Scharfenberg University of Oklahoma/CIMMS](https://reader036.vdocuments.mx/reader036/viewer/2022062423/56649cc45503460f9498d635/html5/thumbnails/13.jpg)
21 September 2007 4th Southwest Hydrometeorology Symposium, Tucson, AZ
NCAR SPOL radar ; From Vivekanandan et al. 1999, JTech 16, 837-845
Dual-pol and partial attenuationDual-pol and partial attenuation
Partial terrain blockagePartial terrain blockage
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21 September 2007 4th Southwest Hydrometeorology Symposium, Tucson, AZ
WSR-88D coverage at 3 km AGLWSR-88D coverage at 3 km AGL
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21 September 2007 4th Southwest Hydrometeorology Symposium, Tucson, AZ
“Gap-Filler” Boundary Layer Radars
“Gap-Filler” Boundary Layer Radars
CourtesyCASA projectCourtesyCASA project
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21 September 2007 4th Southwest Hydrometeorology Symposium, Tucson, AZ
“Gap-Filler” Boundary Layer Radars
“Gap-Filler” Boundary Layer Radars
Nearest WSR-88D CASA radars
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21 September 2007 4th 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 FutureRadar-based QPE: The Future
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21 September 2007 4th Southwest Hydrometeorology Symposium, Tucson, AZ
Questions?Questions?
[email protected]@noaa.gov
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21 September 2007 4th Southwest Hydrometeorology Symposium, Tucson, AZ
Quantitative Precipitation Estimation
Quantitative Precipitation Estimation
R(Z) on a 2 km x 2 km gridR(Z) on a 2 km x 2 km grid
![Page 20: 21 September 2007 4 th Southwest Hydrometeorology Symposium, Tucson, AZ Future QPE: Dual-Pol and Gap-Filler Radars Kevin Scharfenberg University of Oklahoma/CIMMS](https://reader036.vdocuments.mx/reader036/viewer/2022062423/56649cc45503460f9498d635/html5/thumbnails/20.jpg)
21 September 2007 4th Southwest Hydrometeorology Symposium, Tucson, AZ
Quantitative Precipitation Estimation
Quantitative Precipitation Estimation
Dual-pol QPE on a 2 km x 2 km gridDual-pol QPE on a 2 km x 2 km grid
![Page 21: 21 September 2007 4 th Southwest Hydrometeorology Symposium, Tucson, AZ Future QPE: Dual-Pol and Gap-Filler Radars Kevin Scharfenberg University of Oklahoma/CIMMS](https://reader036.vdocuments.mx/reader036/viewer/2022062423/56649cc45503460f9498d635/html5/thumbnails/21.jpg)
21 September 2007 4th Southwest Hydrometeorology Symposium, Tucson, AZ
Increasing value
Hei
ght * * *
Hydrometeor ClassificationHydrometeor Classification
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21 September 2007 4th 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 Zh 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 Zh profiles/mean-field bias (MFB) corrections
- Later work to incorporate multiple radars, corrections using MFB, vertical dual-pol profiles, beam attenuation
Quantitative Precipitation Estimation
Quantitative Precipitation Estimation
![Page 23: 21 September 2007 4 th Southwest Hydrometeorology Symposium, Tucson, AZ Future QPE: Dual-Pol and Gap-Filler Radars Kevin Scharfenberg University of Oklahoma/CIMMS](https://reader036.vdocuments.mx/reader036/viewer/2022062423/56649cc45503460f9498d635/html5/thumbnails/23.jpg)
21 September 2007 4th Southwest Hydrometeorology Symposium, Tucson, AZ
Differential Reflectivity (Zdr)
Differential Reflectivity (Zdr)
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21 September 2007 4th Southwest Hydrometeorology Symposium, Tucson, AZ
• Indicates the presence of larger liquid drops• Indicates the presence of larger liquid drops
• Hail shafts without a lot of liquid water
Differential Reflectivity (Zdr)
Differential Reflectivity (Zdr)
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21 September 2007 4th Southwest Hydrometeorology Symposium, Tucson, AZ
Differential reflectivityZdr = 10 log (Eh/Ev)
= Zh - Zv [dB]
The reflectivity-weighted mean axis ratio of scatterers in a sample volume
Zdr > 0 Horizontally-oriented mean profile
Zdr < 0 Vertically-oriented mean profile
Zdr ~ 0 Near-spherical mean profile
Differential reflectivityZdr = 10 log (Eh/Ev)
= Zh - Zv [dB]
The reflectivity-weighted mean axis ratio of scatterers in a sample volume
Zdr > 0 Horizontally-oriented mean profile
Zdr < 0 Vertically-oriented mean profile
Zdr ~ 0 Near-spherical mean profile
Eh
Ev
Differential Reflectivity (Zdr)
Differential Reflectivity (Zdr)
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21 September 2007 4th 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)
Differential Phase Shift (DP)
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21 September 2007 4th Southwest Hydrometeorology Symposium, Tucson, AZ
Specific Differential Phase Shift DP(r2) – DP(r1)
KDP = [deg/km] 2 (r2 – r1)
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)
KDP = [deg/km] 2 (r2 – r1)
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 (KDP)
Specific Differential Phase Shift (KDP)
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21 September 2007 4th Southwest Hydrometeorology Symposium, Tucson, AZ
Specific Differential Phase Shift (KDP)
Specific Differential Phase Shift (KDP)
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21 September 2007 4th Southwest Hydrometeorology Symposium, Tucson, AZ
Result: The KDP dilemma
- Using a long-distance derivative for calculating KDP can oversmooth heavy rain features but reduces noise
- Using a short-distance derivative for calculating KDP retains features in heavy rain but is also noisy
Result: The KDP dilemma
- Using a long-distance derivative for calculating KDP can oversmooth heavy rain features but reduces noise
- Using a short-distance derivative for calculating KDP retains features in heavy rain but is also noisy
Specific Differential Phase Shift (KDP)
Specific Differential Phase Shift (KDP)
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21 September 2007 4th Southwest Hydrometeorology Symposium, Tucson, AZ
Calculating KDP: current practice
- If Z > 40 dBZ, use a KDP calculation range of 9 gates (2 km).
- Otherwise, use a range derivative of 25 gates (6 km)
- Filter the final KDP product at 0.9 hv
Calculating KDP: current practice
- If Z > 40 dBZ, use a KDP calculation range of 9 gates (2 km).
- Otherwise, use a range derivative of 25 gates (6 km)
- Filter the final KDP product at 0.9 hv
Specific Differential Phase Shift (KDP)
Specific Differential Phase Shift (KDP)
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21 September 2007 4th Southwest Hydrometeorology Symposium, Tucson, AZ
OutlineOutlineDifferential phase shift (DP)
Differential phase shift (DP)
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21 September 2007 4th Southwest Hydrometeorology Symposium, Tucson, AZ
OutlineOutlineSpecific differential phase shift (KDP)
Specific differential phase shift (KDP)
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21 September 2007 4th Southwest Hydrometeorology Symposium, Tucson, AZ
Rainfall estimation using polarimetric variables
R(Z, ZDR) = 0.0142 Z0.77 ZDR-1.67
[mm/h]
R(KDP) = 44|KDP|0.822 sign(KDP) [mm/h]
Rainfall estimation using polarimetric variables
R(Z, ZDR) = 0.0142 Z0.77 ZDR-1.67
[mm/h]
R(KDP) = 44|KDP|0.822 sign(KDP) [mm/h]
Quantitative Precipitation Estimation
Quantitative Precipitation Estimation