An early performance evaluation of the nexrad dual-polarization radar rainfall estimates for urban flood applications

Luciana K. Cunha, James A. Smith, Mary Lynn Baeck, Witold F. Krajewski

Research output: Contribution to journalArticle

19 Scopus citations

Abstract

Dual-polarization radars are expected to provide better rainfall estimates than single-polarization radars because of their ability to characterize hydrometeor type. The goal of this study is to evaluate single- and dualpolarization radar rainfall fields based on two overlapping radars (Kansas City, Missouri, and Topeka, Kansas) and a dense rain gauge network in Kansas City. The study area is located at different distances from the two radars (23-72km for Kansas City and 104-157km for Topeka), allowing for the investigation of radar range effects. The temporal and spatial scales of radar rainfall uncertainty based on three significant rainfall events are also examined. It is concluded that the improvements in rainfall estimation achieved by polarimetric radars are not consistent for all events or radars. The nature of the improvement depends fundamentally on range-dependent sampling of the vertical structure of the storms and hydrometeor types. While polarimetric algorithms reduce range effects, they are not able to completely resolve issues associated with range-dependent sampling. Radar rainfall error is demonstrated to decrease as temporal and spatial scales increase. However, errors in the estimation of total storm accumulations based on polarimetric radars remain significant (up to 25%) for scales of approximately 650km2.

Original languageEnglish (US)
Pages (from-to)1478-1497
Number of pages20
JournalWeather and Forecasting
Volume28
Issue number6
DOIs
StatePublished - Dec 2013

All Science Journal Classification (ASJC) codes

  • Atmospheric Science

Keywords

  • Hydrology
  • Radars/Radar observations
  • Rainfall
  • Urban meteorology

Fingerprint Dive into the research topics of 'An early performance evaluation of the nexrad dual-polarization radar rainfall estimates for urban flood applications'. Together they form a unique fingerprint.

  • Cite this