1. Radar-Derived Rainfall Estimation Presented by D.-J. Seo 1 Hydrologic Science and Modeling Branch Hydrology Laboratory National Weather Service Presented at the NWSRFS International Workshop, Kansas City, MO, Oct 21, 2003 1 dongjun.seo@noaa.gov

2. 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

3. Weather radar

5. From Wood and Brown (2001)

6. Range=230 km Reflectivity field (1  x1km)

7. Reflectivity field

8. Doppler velocity field

9. Oklahoma City, May 3, 1999

10. Radar Rainfall Estimation Z  drop size 6 R  drop size 3  fall velocity Z = A R b where Z is the reflectivity factor (mm 6 /m 3 ) R is the rain rate (mm/hr) R = A -1/b Z 1/b

11. 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

12. From Kelsh 1999

17. Bright Band  From Kelsh 1999

18. Radar QPE in NWS Weather Surveillance Radar - 1988 Doppler version (WSR-88D)

19. 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

20. 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)

21. PPS Products –Graphical (1  x2 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, 4x4km 2, every volume scan Digital Hybrid-Scan Reflectivity (DHR) - 1  x1km, every volume scan Digital Storm-Total Precipitation (DSP) - 2x2km 2, every volume scan

22. From Kessinger et al. 2000 Ground Clutter Removal Radar Echo Classifier (REC)

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

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

25. Accounting for Beam Blockage

26. Digital Terrain Model used for KFTG (Denver, CO)

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

28. From Kelsh 1999 Accounting for vertical profile of reflectivity (VPR) Range-dependent bias Correction Algorithm (RCA)

29. Slant Range vs Adjustment Factor (Tilts 1 thru 3) Vertical Profiles of Reflectivity From Seo et al. 1999

30. Storm Total Rainfall - KATX (Seattle, WA), Unadjusted From Seo et al. 1999

31. Storm Total Rainfall - KATX (Seattle, WA), Adjusted From Seo et al. 1999

32. Before Adjustment After Adjustment Radar-Gauge Comparison

33. From Vignal et al. (2000) Accounting for VPR variability Convective-Stratiform Separation Algorithm (CSSA)

34. Convective-stratiform separation From Seo et al. (2003)

35. 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)

36. 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

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