Geospatial QPE Accuracy Dependence on Weather Radar Network Configurations

Details

• Journal Title:
  Journal of Applied Meteorology and Climatology
• Personal Author:
  Kurdzo, James M. ; Joback, Emily F. ; Kirstetter, Pierre-Emmanuel ; Cho, John Y. N.
• NOAA Program & Office:
  OAR (Oceanic and Atmospheric Research) ; NSSL (National Severe Storms Laboratory)
• Description:
  The relatively low density of weather radar networks can lead to low-altitude coverage gaps. As existing networks are evaluated for gap fillers and new networks are designed, the benefits of low-altitude coverage must be assessed quantitatively. This study takes a regression approach to modeling quantitative precipitation estimation (QPE) differences based on network density, antenna aperture, and polarimetric bias. Thousands of cases from the warm-season months of May–August 2015–17 are processed using both the specific attenuation [R(A)] and reflectivity–differential reflectivity [R(Z, ZDR)] QPE methods and are compared with Automated Surface Observing System (ASOS) rain gauge data. QPE errors are quantified on the basis of beam height, cross-radial resolution, added polarimetric bias, and observed rainfall rate. The collected data are used to construct a support vector machine regression model that is applied to the current WSR-88D network for holistic error quantification. An analysis of the effects of polarimetric bias on flash-flood rainfall rates is presented. Rainfall rates that are based on 2-yr/1-h return rates are used for a contiguous-U.S.-wide analysis of QPE errors in extreme rainfall situations. These errors are then requantified using previously proposed network design scenarios with additional radars that provide enhanced estimate capabilities. Last, a gap-filling scenario utilizing the QPE error model, flash-flood rainfall rates, population density, and potential additional WSR-88D sites is presented, exposing the highest-benefit coverage holes in augmenting the WSR-88D network (or a future network) relative to QPE performance.
• Keywords:
  Atmospheric Science
• Source:
  Journal of Applied Meteorology and Climatology, 59(11), 1773-1792
• DOI:
  https://doi.org/10.1175/jamc-d-19-0164.1
• ISSN:
  1558-8424 ; 1558-8432
• Format:
  PDF
• Publisher:
  American Meteorological Society
• Document Type:
  Journal Article
• Rights Information:
  Other
• Compliance:
  Library
• Main Document Checksum:
  urn:sha256:ff2d6a89e95a4ead7cde0e173e2b24aeae218c8260025db3fc0e6ed8b4fa55c6
• Download URL:
  https://repository.library.noaa.gov/view/noaa/53728/noaa_53728_DS1.pdf
• File Type:
  [PDF - 3.86 MB ]