1 / 23

Analysis of Radar-Rain Rate Relations During the Southeast Texas Flood Event of 18 April 2009

Analysis of Radar-Rain Rate Relations During the Southeast Texas Flood Event of 18 April 2009. Steve Vasiloff, NOAA/National Severe Storms Laboratory Jeffrey Lindner, Harris County Flood Control District Lance Wood, NOAA/National Weather Service, Houston. Outline.

Download Presentation

Analysis of Radar-Rain Rate Relations During the Southeast Texas Flood Event of 18 April 2009

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Analysis of Radar-Rain Rate Relations During the Southeast Texas Flood Event of 18 April 2009 Steve Vasiloff, NOAA/National Severe Storms Laboratory Jeffrey Lindner, Harris County Flood Control District Lance Wood, NOAA/National Weather Service, Houston 2010 National Flood Workshop, Houston, TX

  2. Outline • Radar reflectivity rainrate (Z-R) relations • Radar resolution impacts • Heavy rain and wind impacts on gauges • 5 and 1-min radar and gauge comparisons • Examples of radar and gauge uncertainties • Concluding remarks

  3. Harris County Flood Control District gauges

  4. NSSL Q2 systemhttp://nmq.ou.edu • Next-generation quantitative precipitation estimation (QPE) system • 1 km resolution CONUS every 5 min • Multisensor products • Dynamic Z-R • Q2 radar-based used as base field for West Gulf RFC operations (with local gauge correction) • Other RFCs “cut and paste” Q2 into their systems

  5. Q2 main page

  6. TS Nicole exampleQ2 Z-Rs

  7. TS Nicole exampleQ2 reflectivity

  8. Radar reflectivity-rainrate relations

  9. Radar data resolution

  10. KHGX super-res

  11. Q2 1-km res 180 * * 130

  12. 5-min Q2 dBZ; gauge dataconvective & tropical Z-Rs Q2 5-min reflectivity Gauge Tropical QPE Convective QPE 5 min data are aggregated from 1st to 5th min past top of the hour

  13. 5-min Q2 dBZ & gauge dataconvective & tropical Z-Rs Q2 5-min reflectivity Hi-res reflectivity Gauge

  14. 1-min hi-res KHGX & gauge Hi-res reflectivity Gauge

  15. 5-min Q2 dBZ; gauge dataconvective & tropical Z-Rs Q2 5-min reflectivity Gauge Tropical QPE Convective QPE 5 min data are aggregated from 1st to 5th min past top of the hour

  16. 1-min hi-res KHGX & gauge Hi-res reflectivity Gauge

  17. Radar clutter filter “zero isodop” line

  18. Radar clutter filtering Radar echo minima due to filter?

  19. 5 min sampling – constant rainrate for QPE Echo motion

  20. Gauge networks

  21. Gauge networks

  22. Summary • Urban FF warnings require hi-res data • 1 –min data too noisy? • High rainrates and winds reduce confidence in gauge data – difficult to quantify undercatch • 15-30%???? • Clutter filter causes uncertainty in radar data • Need better gauge-radar metadata • Know which gauges are in clutter, zero isodop • Gauge QC is an ongoing issue

  23. Q2 future • Higher resolution • 2.5 min radar (NEXGEN) • 10-15 min gauge • MADIS/additional gauge networks (HCFCD) • Gauge quality control algorithm • Using temporal analysis of radar-gauge bias • Spatial checks • Gauge Quality Index

More Related