Z-R Law for Quantitative Rainfall Estimation Using a C-band Radar and a Network of Ground-Based Disdrometers

9 pages•Published: September 20, 2018

Roberta Karinne Mocva-Kurek and Adrián Pedrozo-Acuña

Abstract

It is acknowledged that spatial variations in the DSD and type of rainfall are important for an adequate rainfall estimation using operational weather radars. However, due to a lack of instrumentation, the Z-R relationship is rarely considered spatially variable. This relationship is usually applied unawarely of the scale, which is questionable since the nonlinearity of this relation could lead to undesirable discrepancies when combined with scale aggregation. This paper investigates different methods to define an adequate Z–R law relation for a study region, where a spatial variation of coefficients and rain type may be considered. For this, we utilize data from a disdrometers network and a C-band radar located in Mexico City. Coefficients of the Z-R law are obtained through: the definition of the Z-R relationship at each disdrometer and the use of three methods (dBZ, R and Do/R) for the data classification by rain type (ST, T, C). Results show that the coefficients for the Z-R law are very diverse and strongly dependent on the rain type. Regarding radar data, the evaluation indicates that the values do not correspond quantitatively to those recorded on the earth’s surface, but it can represent the variances in most of the period.

Keyphrases: c band radar, disdrometer, megalopolis, mexico city, urban, z r relationship

In: Goffredo La Loggia, Gabriele Freni, Valeria Puleo and Mauro De Marchis (editors). HIC 2018. 13th International Conference on Hydroinformatics, vol 3, pages 1415-1423.

Links:	https://easychair.org/publications/paper/VhvR
	https://doi.org/10.29007/6n1m

BibTeX entry

@inproceedings{HIC2018:Z_R_Law_Quantitative,
  author    = {Roberta Karinne Mocva-Kurek and Adrián Pedrozo-Acuña},
  title     = {Z-R Law for Quantitative Rainfall Estimation Using a C-band Radar and a Network of Ground-Based Disdrometers},
  booktitle = {HIC 2018. 13th International Conference on Hydroinformatics},
  editor    = {Goffredo La Loggia and Gabriele Freni and Valeria Puleo and Mauro De Marchis},
  series    = {EPiC Series in Engineering},
  volume    = {3},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2516-2330},
  url       = {/publications/paper/VhvR},
  doi       = {10.29007/6n1m},
  pages     = {1415-1423},
  year      = {2018}}

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