Preprints
https://doi.org/10.5194/amt-2016-388
https://doi.org/10.5194/amt-2016-388

  12 Dec 2016

12 Dec 2016

Review status: this preprint was under review for the journal AMT. A revision for further review has not been submitted.

Exploring the potential of utilizing high resolution X-band radar for urban rainfall estimation

Wen-Yu Yang1, Guang-Heng Ni1, You-Cun Qi2,3, Yang Hong1,4, and Ting Sun1 Wen-Yu Yang et al.
  • 1State Key Laboratory of Hydro - Science and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China
  • 2Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma
  • 3NOAA/OAR/National Severe Storms Laboratory, Norman, Oklahoma
  • 4Department of Civil Engineering and Environmental Science, University of Oklahoma, Norman, Oklahoma

Abstract. X-band-radar-based quantitative precipitation estimation (QPE) system is increasingly gaining interest thanks to its strength in providing high spatial resolution rainfall information for urban hydrological applications. However, prior to such applications, a variety of errors associated with X-band radars are mandatory to be corrected. In general, X-band radar QPE systems are affected by two types of errors: 1) common errors (e.g. mis-calibration, beam blockage, attenuation, non-precipitation clutter, variations in the raindrop size distribution) and 2) “wind drift” errors resulting from non-vertical falling of raindrops. In this study, we first assess the impacts of different corrections of common error using a dataset consisting of one-year reflectivity observations collected at an X-band radar site and a distrometer along with rainfall observations in Beijing urban area. The common error corrections demonstrate promising improvements in the rainfall estimates, even though an underestimate of 24.6% by the radar QPE system in the total accumulated rainfall still exists as compared with gauge observations. The most significant improvement is realized by beam integration correction. The DSD-related corrections (i.e., convective–stratiform classification and local Z-R relationship) also lead to remarkable improvement and highlight the necessity of deriving the localized Z-R relationships for specific rainfall systems. The effectiveness of wind drift correction is then evaluated for a fast-moving case, whose results indicate both the total accumulation and the temporal characteristics of the rainfall estimates can be improved. In conclusion, considerable potential of X-band radar in high-resolution rainfall estimation can be realized by necessary error corrections.

Wen-Yu Yang et al.

 
Status: closed (peer review stopped)
Status: closed (peer review stopped)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Status: closed (peer review stopped)
Status: closed (peer review stopped)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Wen-Yu Yang et al.

Wen-Yu Yang et al.

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Latest update: 02 Mar 2021
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Short summary
Using a dataset consisting of one-year measurements by an X-band radar and distrometer, we found that error corrections greatly improve X-band-radar-based rainfall estimation. Specifically, the greatest improvement is realized by the beam integration. Derivation of localized Z-R relationships for specific rainfall systems is also of great importance. Moreover, wind drift correction improves quantitative estimates and temporal consistency.