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Atmosphere 2015, 6(10), 1559-1577; doi:10.3390/atmos6101559

Radar Estimation of Intense Rainfall Rates through Adaptive Calibration of the Z-R Relation

1
Dipartimento di Ingegneria dell’Ambiente, del Territorio e delle Infrastrutture, Politecnico di Torino, Corso Duca degli Abruzzi, 24, 10129 Torino, Italy
2
Dipartimento Sistemi Previsionali, ARPA Piemonte, Via Pio VII, 9, 10135 Torino, Italy
*
Author to whom correspondence should be addressed.
Academic Editor: Guifu Zhang
Received: 15 July 2015 / Revised: 29 September 2015 / Accepted: 14 October 2015 / Published: 22 October 2015
(This article belongs to the Special Issue Radar Meteorology)
View Full-Text   |   Download PDF [2795 KB, uploaded 22 October 2015]   |  

Abstract

Rainfall intensity estimation from weather radar is still significantly uncertain, due to local anomalies, radar beam attenuation, inappropriate calibration of the radar reflectivity factor (Z) to rainfall rate (R) relationship, and sampling errors. The aim of this work is to revise the use of the power-law equation commonly adopted to relate radar reflectivity and rainfall rate to increase the estimation quality in the presence of intense rainfall rates. We introduce a quasi real-time procedure for an adaptive in space and time estimation of the Z-R relation. The procedure is applied in a comprehensive case study, which includes 16 severe rainfall events in the north-west of Italy. The study demonstrates that the technique outperforms the classical estimation methods for most of the analysed events. The determination coefficient improves by up to 30% and the bias values for stratiform events decreases by up to 80% of the values obtained with the classical, non-adaptive, Z-R relations. The proposed procedure therefore shows significant potential for operational uses. View Full-Text
Keywords: weather radar; areal rainfall estimation; adaptive calibration; Z-R relation weather radar; areal rainfall estimation; adaptive calibration; Z-R relation
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Libertino, A.; Allamano, P.; Claps, P.; Cremonini, R.; Laio, F. Radar Estimation of Intense Rainfall Rates through Adaptive Calibration of the Z-R Relation. Atmosphere 2015, 6, 1559-1577.

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