WSR-88D Radar Rainfall Estimation Present and Near Future Daniel S. Berkowitz Applications Branch NWS Radar Operations Center Norman, Oklahoma 1

Paradigms of the Past One R(Z) relationship (a.k.a. Z-R or Z/R) could be used for the entire coverage (currently a 230 km range) – Conventional radar (WSR-57 and WSR-74 radars) used “stratiform” (i.e., Marshall-Palmer Z=200R 1.6 derived in the late 1940s) or “convective” R(Z) (Z=55R 1.6 ) in the 1960s to the 1990s. – WSR-88D has used a default R(Z) (the “Miami Z-R relation” derived from studies in Florida in the mid- to late-1950s) from mid-1980s legacy Precipitation Processing Subsystem (PPS) development to the present. – WSR-88Ds were authorized additional relationships: “Rosenfeld Tropical” (Z=250R 1.2 ) in 1997 Relative to the Continental Divide, “East-Cool Stratiform” (Z=130R 2.0 ) and “West-Cool Stratiform” (Z=75R 2.0 ) in

Paradigms of the Past (continued) A “bias correction” (a.k.a. “multiplicative bias”) can be applied for the entire radar coverage. – The multiplicative bias ratio is computed from all available gauge-radar pairs as follows: Mean Field Bias = (∑G i )/(∑R i ). – Gauge data are ingested in an external system (e.g., Multisensor Precipitation Estimator, MPE), where this bias is calculated. – The spatial distribution of the gauge-radar pairs is considered irrelevant. – The computed bias table is sent from AWIPS to the relevant RPG, where, based on Hydromet Adjustment adaptable parameters (minimum number of pairs and whether or not to apply this “correction”), the appropriate correction factor is selected from the table. 3

Paradigms of the Past (continued) Hybrid scan construction can mitigate contamination from residual ground clutter (not already removed by the RDA) and can compensate for blockages. – Vertical resolution is dependent upon the VCP being used. Some legacy VCPs (especially 31, 32, 21, and 11) had rather poor vertical resolution at low elevation angles. – Blockages were estimated from surface elevation data based on (for sites <60° N. latitude) the February 2000 Shuttle Radar Topography Mission (SRTM) with 1 arc- second (about 30 m.) horizontal resolution & ≤16 m. vertical error. Tree growth and man-made construction since then has made the data for many sites out of date. – The time required to build the Hybrid Scan array may leave gaps when convective cells move quickly. 4

Elevation Angles in a “Precipitation Mode” Volume Coverage Pattern (VCP) 0.5° 1.5° 19.5° } several other elevation angles Mountains cause beam blockages (as do trees, buildings, etc.)

Hybrid Scan Illustration 6 0.5° 0.9° 1.3° 1.8° 2.4° Object being excluded from the hybrid scan

Terrain-based Hybrid Scan (NE cross-section at Eureka, CA) Note the height of the radar beam samples relative to the surface elevation.

Accumulation Period vs. Volume Scan Duration Volume scan Hybrid scan Accumulation period Top of clock hour during antenna retrace time Avg. time of hybrid scan 18:01 8 The accumulation period is measured between the average times of the hybrid scan (which may range from a single 0.5° elevation angle to >7° of elevation based on blockages).

9 Digital Terrain Elevation Data Radar Echo Classifier Anomalous Propagation Detection Algorithm (REC-APDA) Enhanced Precipitation Preprocessor (EPRE) Hybrid Scan (reflectivity) Reflectivity Radial Velocity Spectrum Width Beam Blockage Algorithm Clutter Likelihood Precipitation Rate Algorithm Precipitation Accumulation Algorithm Rain Gauge Reports Gauge/RadarBias Table Precipitation Adjustment (Rainfall) Precipitation Products (OHP, THP, STP, DPA, USP, etc.) Snow Accumulation Algorithm DHR for Flash Flood Monitoring & Prediction (FFMP) Components of the Precipitation Processing Subsystem Dissemination

Dual Polarization QPE Relationships Echo classification-based relationships (next slide) “Tropical” R(Z,Z DR ) from Bringi & Chandrasekar (2001) “Continental” R(Z,Z DR ) from Ryzhkov R(K DP ) from Ryzhkov R(Z) from “default convective” legacy PPS Hydromet Rate algorithm (the “Miami Z-R relation”) Melting layer determined from Z DR at 4°-10° elevation angles Hybrid Scan construction from Hydrometeor Classifications 10

Hydro Class, Melting Layer, & Dual Pol variables H ydrometeor C lassification A lgorithm Quantitative Precipitation Estimation and other dual pol products Super- resolution Products Melting Layer Detection Algorithm Super- resolution Data ( 0.5°x0.25 km) Legacy Algorithms Recombined (Legacy Resolution) Data (1.0°x1.00 km for reflectivity and 1.0°x0.25 km for Doppler) RDA (Radar Data Acquisition) RPG (Radar Product Generator) Recombined (Dual Polarization Resolution) Data (1.0°x0.25 km) Legacy Products Environmental data Blockage data

GC, BI, BD, RA, HR GC, BI, WS, GR, BD, RA, HR GC, BI, DS, WS, GR, BD GC, DS, GR, WS, IC, BD Note: HA can occur at all ranges/heights. DS, IC, GR Beam bottomBeam top BD = big drops BI = biological DS = dry snow GC = ground clutter GR = graupel HA = hail/rain mixture HR = heavy rain IC = ice crystals RA = light/moderate rain WS = wet snow (0° C.) Beam centerline

Conditions/Classifications R method (mm/hr) Ground Clutter (GC) or Unknown (UK) Not computed No Echo (ND) or Biological (BI)0 Light/Moderate Rain (RA) or Big Drops (BD)R(Z, Zdr) Heavy Rain (HR) and blockage < 20% and ≤ 45 dBZ R(Z, Zdr) Heavy Rain (HR) and blockage ≥ 20% or Z > 45 dBZ R(Kdp) Rain/Hail (HA) and blockage ≥ 5%R(Kdp) Rain/Hail (HA) and echo is at or below the top of the melting layer (ML) and blockage < 5% R(Kdp) Rain/Hail (HA) and echo is above the top of the ML and blockage < 5% 0.8*R(Z) Graupel (GR)0.8*R(Z) Wet Snow (WS)0.6*R(Z) Dry Snow (DS) and echo is at or below the top of the MLR(Z) Dry Snow (DS) and echo is above the top of the ML 2.8*R(Z) ! Ice Crystals (IC)2.8*R(Z)

Paradigms of the Past (continued) Single radar rainfall estimation is adequate for all hydrologic purposes. Ignore these uncertainties: – Beam propagation path (considered to be determined from “standard atmosphere”) varies. – Beam typically overshoots the ground at long ranges. – Wind shear displaces radar volume with surface location. – Echoing volume is often not filled with uniform drop size distribution (DSD) nor with same precip. type. – Evaporation may occur near the ground. – Rain gauge reports are “ground truth”! 14

Near Future Use of MetSignal to mitigate wind turbine clutter, ground traffic returns, and radar frequency interference Simplification of adaptable parameter selection Improved guidance for parameter selection from Multi- Radar Multi-Sensor (MRMS) and from 5 years of WSR-88D dual pol. experience, e.g., study to reduce multiplier for rainfall estimate from dry snow, currently having default of R=2.8*R(Z) using MRMS – NSSL DEV system. New VCPs with improved vertical resolution Improved ground clutter suppression of base data Continuous improvements of MRMS QPE by NSSL, including – blockage compensation based on recent history of data – mitigation of melting layer effects – use of vertical profile information and High Resolution Rapid Refresh model data to determine precip. type 15

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General Surveillance Same elevations as VCP 12/212 below 10° Same vertical coverage as VCP 11/211 above 10° Same data quality as VCP 21 Duration: ~6 mins AVSET & 1 SAILS cut VCP

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Clear-Air More angles than 31/32 Based on low-level elevations of VCP 12/212 Duration: ~7 mins May eventually replace VCP 32 1 SAILS cut VCP 35 19

“Distant” Future Better utilization of new VCPs and MESO-SAILS cuts Virtual volume scans - constant “voxel” (volume element) updating, preferably via MRMS mosaics Use of vertical profiles of radar variables Increased use of model data for improved microphysics (better hydrometeor classification and physical environment) Probabilistic (rather than deterministic) QPE More use of MRMS, where applicable, instead of RPG algorithms 20

21 Fig. 16 from Miller, D. A., S. Wu, and D. Kitzmiller, 2013: Spatial and temporal resolution considerations in evaluating and utilizing radar quantitative precipitation estimates. J. Operational Meteor., 1(15), 168–184.

Dealing With Uncertainty “As we know, there are known knowns. There are things we know we know. We also know there are known unknowns. That is to say, we know there are some things we do not know. But there are also unknown unknowns, the ones we don’t know we don’t know.” -- Donald Rumsfeld (2004)

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