Future of Weather Radar

8/6/2019 Future of Weather Radar

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Surveillance Weather Radar 2000 AD





Technology Developments

� Digital receivers ± Easy to achieve sampling rate higher than reciprocal

of pulse (oversampling)

� Versatile circuits for transmitter control ± Easy to phase code, to interleave PRTs (staggered

and other), to compress pulse

� Signal processing on general purposecomputers (PCs) ± Easy to program algorithms and analyze Doppler

spectra



Capability of the NSSL¶s R&D

weather surveillance radar � Doppler and Dual Polarization� Phase coding of transmitted pulses

� Transmission of arbitrary non uniform pulsesequence including staggered PRT� Oversampling

± by a factor of 5 in Dual Polarization Mode ± By a factor of 10 in Single Polarization Mode

� Arbitrary scanning strategy (including RHI)� Recording of time series data



Oversampling

� To increase speed of volume coverage� To decrease errors in estimates of

reflectivity, velocity, spectrum width, andpolarimetric variables



Z , Standard Processing, Aug 04



Z , from Decorrelated Samples



Mitigation of range velocity

ambiguities� Phase coding at lower elevations� Staggered PRT at higher elevations

� Demonstration of clutter filtering for bothschemes� Integration into volume coverage patterns� Inclusion of oversampling� Adaptive automatic choice of PRTs based

on obscurations in immediately precedingscans



ReflectivityLong PRT

EL = 0.5 deg10/08/02 15:11 GMT

Phase Coding



Doppler VelocityPhase coding, medium PRT EL = 0.5 deg

10/08/02 15:11 GMTDoppler Velocity

Processing as on WSR-88D

v a = 23.7 m s -1, r

a = 175 kmv a = 23.7 m s -1, r

a = 175 km

Phase Coding



Staggered PRT

ReflectivityStaggered PRT

EL = 2.5 deg04/06/03 4:42 GMT



Staggered PRT

v a = 25.4 m s -1 v

a = 45.2 m s -1

148 km

184 km

KTLX Doppler VelocityVCP 11 ± Batch Mode

KOUN Doppler VelocityStaggered PRT (184 km/276 km)EL = 2.5 deg

04/06/03 4:42 GMT



Dual Polarization at NSSL

� 1983: Upgrade of Cimarron radar to dual polarization; switching betweenhorizontal and vertical polarization

� 1984: Collection of first (anywhere) dual polarization time series data� 1985 to 1989: Definition of the complete set of polarimetric variables.

Development of schemes to obtain these variables together with spectralmoments

� 1992: First (anywhere) collection of polarimetric variables at all rangelocations

� 1992 to present: Development of schemes to classify hydrometeor type.

Improvement of rainfall estimation. Design of a system functionallycompatible with the WSR-88D; simultaneous transmission and receptionof horizontally and vertically polarized waves

� 2002: Upgrade of KOUN radar to dual polarization� 2002-2003: Joint POLarization Experiment (JPOLE)



Fields of polarimetric variables



Dual Polarization - Benefits� Vastly superior data quality: calibration, mitigation

of attenuation and beam blockage effects� Discrimination between insects, birds, ground

echoes, and precipitation� Superior measurement of rainfall� Detection of hail� Classification of precipitation ± rain vs freezing rain

vs snow� Determination of hail size� Measurement of snowfall� Icing detection



Stratiform Rain vs Snow



Imminent Goals

� Combining techniques to mitigate rangeand velocity ambiguities with optimum(pseudo whitening) procedure to increasespeed of volume coverage and decreaseerrors of estimates

� Incorporating the above combined

technique into dual polarization radar � Developing adaptive scanning strategy for agile beam phased array radar



Three Challenges

� Direct estimation of wind transverse to theradar beam

� Determination of the alias interval of Doppler velocity from a single pulse� Estimation of the forward propagation

coefficient using returns fromhydrometeors or biological scatterers



Major Endeavor

� Explaining bulk hydrometeor properties that causedistinct polarimetric signatures in convective storms



Major Endeavor

� Assimilation of radar data into local NWP(short term ~ 3 h, fine resolution ~ 1 km)model ± coupled to distributed hydrological model for

use over small watersheds (~ 1000s km 2) ± capable of predicting tornadoes, strong winds,

hail, and other hazards



END

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Future of Weather Radar