Future QPE: Dual-Pol and Gap-Filler Radars

21 September 2007 4th Southwest Hydrometeorology Symposium, Tucson, AZ

Kevin Scharfenberg

University of Oklahoma/CIMMS and

NOAA National Severe Storms Laboratory

Kevin Scharfenberg

University of Oklahoma/CIMMS and

NOAA National Severe Storms Laboratory

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

Quantitative Precipitation Estimation

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

Early dual-pol QPE resultsEarly dual-pol QPE results

Point Estimates

Areal (basin) Estimates

Spring hail cases

Cold season stratiform rain

Bias of radar areal rainfall estimates

Early dual-pol QPE resultsEarly dual-pol QPE results

Reflectivity (Zh)Differential reflectivity (Zdr)

Similar reflectivity – very different differential reflectivity!Northeast – Mostly large rain dropsSouthwest – Mostly hail

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

Warm raincase – A very unusual DSD!

Hail case –Z-R relationsbreak down!

RHI instratiformrainfall

Hydrometeor ClassificationHydrometeor Classification

Hydrometeor classification algorithm

No EchoLgt/mod

rainHeavy

rainHail

“Big drops”

GraupelIce

crystalsDry

snowWet

snowUnknown

AP orClutter

Biological

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

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

WSR-88D coverage at 3 km AGLWSR-88D coverage at 3 km AGL

“Gap-Filler” Boundary Layer Radars

CourtesyCASA projectCourtesyCASA project

“Gap-Filler” Boundary Layer Radars

Nearest WSR-88D CASA radars

- 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

Questions?Questions?

Kevin.Scharfenberg@noaa.govKevin.Scharfenberg@noaa.gov

R(Z) on a 2 km x 2 km gridR(Z) on a 2 km x 2 km grid

Dual-pol QPE on a 2 km x 2 km gridDual-pol QPE on a 2 km x 2 km grid

Increasing value

ght * * *

Hydrometeor ClassificationHydrometeor Classification

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

Differential Reflectivity (Zdr)

• Indicates the presence of larger liquid drops• Indicates the presence of larger liquid drops

• Hail shafts without a lot of liquid water

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

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)

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)

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

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

OutlineOutlineDifferential phase shift (DP)

Differential phase shift (DP)

OutlineOutlineSpecific differential phase shift (KDP)

Specific differential phase shift (KDP)

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]

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