radar-derived rainfall estimation

Radar-Derived Rainfall Estimation

Presented byD.-J. Seo1

Hydrologic Science and Modeling BranchHydrology Laboratory

National Weather ServicePresented at the NWSRFS International

Workshop, Kansas City, MO, Oct 21, 20031 dongjun.seo@noaa.gov

In this presentation

• Introduction to weather radar

• Principles of radar rainfall estimation

• Major sources of error

• Radar-based Quantitative Precipitation Estimation (QPE) in NWS

• Ongoing improvements

• Summary

Weather radar

From Wood and Brown (2001)

Range=230 km

Reflectivity field (1x1km)

Reflectivity field

Doppler velocity field

Oklahoma City, May 3, 1999

Radar Rainfall Estimation

Z drop size6

R drop size3 fall velocity

Z = A Rb

whereZ is the reflectivity factor (mm6/m3)R is the rain rate (mm/hr)

R = A-1/b Z1/b

Major Sources of Error

• Hardware– lack of calibration– clutter– attenuation

• Microphysics– variability in raindrop size– variability in phase of hydrometeor

• Sampling Geometry– beam blockage– vertical profile of reflectivity

From Kelsh 1999

From Kelsh 1999

From Kelsh 1999

From Kelsh 1999

Bright Band

From Kelsh 1999

Radar QPE in NWS

Weather Surveillance Radar - 1988 Doppler version (WSR-88D)

WSR-88D Precipitation Processing Subsystem (PPS)

• Preprocessing– Constructs the reflectivity field from the lowest unobstructed and

uncontaminated measurements from multiple elevation angles– Removes clutter (including that from anomalous propagation

(AP)) and outliers• Rate

– Converts reflectivity to rain rate– Five Z-R relationships– Quality control checks– Capped for hail mitigation

PPS (cont.)

• Accumulation– Accumulates rainfall

• Adjustment– Applies mean field bias (based on real-time rain

gauge data)• Products

– Graphical– Digital

• For further details on PPS, see Fulton et al. (1998)

PPS Products

– Graphical (1x2 km)• 1-H Precipitation (OHP) -

every volume scan• 3-H Precipitation (THP) -

every hour• Storm Total Precipitation

(STP) - every volume scan• User Selectable storm-

total Precipitation (USP) - between 2~30 hrs, every hour

– Digital• Digital Precipitation Array

(DPA) - hourly, 4x4km2, every volume scan

• Digital Hybrid-Scan Reflectivity (DHR) - 1x1km, every volume scan

• Digital Storm-Total Precipitation (DSP) - 2x2km2, every volume scan

From Kessinger et al. 2000

Ground Clutter Removal

Radar Echo Classifier (REC)

Sep 16, 1999: Storm Total Radar-derived Accumulation from KRAX (Raleigh, NC)

From Kelsh 1999

Sep 16, 1999: Storm Total Radar-derived Accumulation from KAKQ (Wakefield, VA)

From Kelsh 1999

Accounting for Beam Blockage

Digital Terrain Model used for KFTG (Denver, CO)

Elevation angle selection map used for KFTG (Denver, CO)

From Kelsh 1999

Accounting for vertical profile of reflectivity (VPR)

Range-dependent bias Correction Algorithm (RCA)

Slant Range vs Adjustment Factor (Tilts 1 thru 3)

Vertical Profiles of Reflectivity

From Seo et al. 1999

Storm Total Rainfall - KATX (Seattle, WA), Unadjusted

From Seo et al. 1999

Storm Total Rainfall - KATX (Seattle, WA), Adjusted

From Seo et al. 1999

Before Adjustment After Adjustment

Radar-Gauge Comparison

From Vignal et al. (2000)

Accounting for VPR variability

Convective-Stratiform Separation Algorithm (CSSA)

Convective-stratiform separation

From Seo et al. (2003)

SAA snow depth estimated from Reno NV (KRGX) radar data for a heavy 12 hour Sierra Nevada snow event ending ~07UTC, 4 December 1998.

Snow Accumulation Algorithm (SAA) Developed for the ROC by the US Bureau of Reclamation, the SAA uses logic similar to the PPS to estimate snow depth and snow water equivalent.

From O’Bannon and Ding (2003)

Summary

• Radar is a critical part of the hydrologic and hydrometeorological observing and prediction system in NWS

• Radar rainfall estimates are subject to a number of significant sources of error

• Thorough understanding and systematic and explicit correction of the errors are essential to operational success

• With ongoing improvements and dual polarization in the near future, radar is expected to play an even more important role in operational hydrology and hydrometeorology

For more information, see http://www.nws.noaa.gov/oh/hrl/papers/papers.htm

Thank you!