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Radar-Derived Precipitation

Radar-Derived Precipitation. Deriving Precipitation Rates Radar Sampling Issues Validating: Comparing Radar Estimates with Gauge Reports. COMAP Symposium 00-3 (Heavy Precip/Flash Flood) Matt Kelsch Tuesday, 12 September 2000 kelsch@comet.ucar.edu. Radar Representation of Rainfall.

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Radar-Derived Precipitation

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  1. Radar-Derived Precipitation Deriving Precipitation Rates Radar Sampling Issues Validating: Comparing Radar Estimates with Gauge Reports COMAP Symposium 00-3 (Heavy Precip/Flash Flood) Matt Kelsch Tuesday, 12 September 2000 kelsch@comet.ucar.edu

  2. Radar Representation of Rainfall • Deriving rainfall (the Z-R conversion) • Rainfall rates (R) are directly related to the drop size distribution of precipitation (based on the diameter cubed). • Reflectivity (Z) is directly related to the drop size distribution of precipitation (based on the diameter to the sixth power). • If the drop size distribution were known, the relationship between Z and R could be calculated. It is not known, so no unique relationship between Z and R can be defined. Instead empirical relationships have been developed.

  3. Z-R RelationshipsWSR-88D, Marshall-Palmer (general), and Tropical

  4. Radar Representation of Rainfall • Sampling Issues • Radar domain cannot be sampled at consistent elevations, with consistent bin volumes, or for precipitation with similar stage of development or phase. • Range degradation • Low-level beam blocking • Changes in precip phase have inconsistent effects--bright band, hail contamination

  5. 16 sep99: Storm Total Radar-derived Accumulation from KRAX (Raleigh NC)

  6. 16 sep99: Storm Total Radar-derived Accumulation from KAKQ (Wakefield VA)

  7. Bright Band 

  8. Radar-Rain Gauge Comparisons • Radar samples a volume of the atmosphere • At discrete intervals • Up to several thousands feet AGL • Over a surface area which may exceed 1 mi2 • Rain gauges sample • Continuously • At the surface • Over an area less than 1 ft2 • Accumulations are measurements with the error factors associated with the gauge type

  9. 0500 UTC 7 Aug 1999 0700 UTC 7 Aug 1999

  10. 1215 UTC 27 June 1995 1815 UTC 27 June 1995

  11. 1402 UTC 27 June 1995 1658 UTC 27 June 1995

  12. Virginia Topography Radar-derived accumulation 27 June 1995

  13. Changing Z-R Will help when: • Consistently different average DSD (climate) • Tropical versus mid-latitude (warm vs. cold process) • Maritime versus continental • Consistently different average DSD (season) • Convective versus stratiform Is not the solution when: • Range degradation, overshooting low-levels • Phase change: hail, melting snow • Snowfall

  14. KRAX Storm Total 1159 UTC 6 Sep 96: Z=300R1.4

  15. KRAX Storm Total 1159 UTC 6 Sep 96: Z=250R1.2

  16. Radar-derived Precipitation:A Summary Of Major Points • Radar provides excellent storm-scale information about the spatial and temporal evolution of precipitation systems. • Radar provides very valuable input as part of a comprehensive, multi-sensor precipitation system. • Quantitative reliability issues are related to the fact that radar samples some volume at some elevation to estimate precipitation at the ground. • Radar-derived precipitation is most reliably modeled for liquid hydrometeors; hail and snow add complexity. • The above two points are not effectively corrected by changing Z-R coefficients; Z-R changes should be related to Drop Size Distribution knowledge. • Radars and rain gauges do not measure equal samples • Rain gauges do not provide a good representation of precipitation distribution, especially convective precip. • The PPS algorithm has the versatility to evolve into a more comprehensive system, taking into account the ambient environment.

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