Cargando…

Improving Radar Rainfall Estimations with Scaled Raindrop Size Spectra in Mei-Yu Frontal Rainstorms

Hydrological calibration of raw weather radar rainfall estimation relies on in situ rainfall measurements. Raindrop size distribution (DSD) was collected during three typical Mei-Yu rainstorms in July 2014 using three particle size velocity (Parsivel) DSD sensors along the Mei-Yu front in Nanjing, C...

Descripción completa

Detalles Bibliográficos
Autores principales: Zheng, Hepeng, Wu, Zuhang, Zhang, Lifeng, Xie, Yanqiong, Lei, Hengchi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7570947/
https://www.ncbi.nlm.nih.gov/pubmed/32937991
http://dx.doi.org/10.3390/s20185257
_version_ 1783597064827961344
author Zheng, Hepeng
Wu, Zuhang
Zhang, Lifeng
Xie, Yanqiong
Lei, Hengchi
author_facet Zheng, Hepeng
Wu, Zuhang
Zhang, Lifeng
Xie, Yanqiong
Lei, Hengchi
author_sort Zheng, Hepeng
collection PubMed
description Hydrological calibration of raw weather radar rainfall estimation relies on in situ rainfall measurements. Raindrop size distribution (DSD) was collected during three typical Mei-Yu rainstorms in July 2014 using three particle size velocity (Parsivel) DSD sensors along the Mei-Yu front in Nanjing, Chuzhou, and the western Pacific, respectively. To improve the radar precipitation estimation in different parts of the Mei-Yu front, a scaling method was adopted to formulate the DSD model and further derive the Z–R relations. The results suggest a distinct variation of DSDs in different parts of the Mei-Yu front. Compared with statistical radar Z–AR(b) relations obtained by mathematical fitting techniques, the use of a DSD model fitting based on a scaling law formulation theoretically shows a significant improvement in both stratiform (33.9%) and convective (2.8%) rainfall estimations of the Mei-Yu frontal system, which indicates that using a scaling law can better reflect the DSD variations in different parts of the Mei-Yu front. Polarimetric radar has indisputable advantages with multiparameter detection ability. Several dual-polarization radar estimators are also established by DSD sensor data, and the R(Z(H), Z(DR)) estimator is proven to be more accurate than traditional Z–R relations in Mei-Yu frontal rainfall, with potential applications for operational C-band polarimetric radar.
format Online
Article
Text
id pubmed-7570947
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-75709472020-10-28 Improving Radar Rainfall Estimations with Scaled Raindrop Size Spectra in Mei-Yu Frontal Rainstorms Zheng, Hepeng Wu, Zuhang Zhang, Lifeng Xie, Yanqiong Lei, Hengchi Sensors (Basel) Article Hydrological calibration of raw weather radar rainfall estimation relies on in situ rainfall measurements. Raindrop size distribution (DSD) was collected during three typical Mei-Yu rainstorms in July 2014 using three particle size velocity (Parsivel) DSD sensors along the Mei-Yu front in Nanjing, Chuzhou, and the western Pacific, respectively. To improve the radar precipitation estimation in different parts of the Mei-Yu front, a scaling method was adopted to formulate the DSD model and further derive the Z–R relations. The results suggest a distinct variation of DSDs in different parts of the Mei-Yu front. Compared with statistical radar Z–AR(b) relations obtained by mathematical fitting techniques, the use of a DSD model fitting based on a scaling law formulation theoretically shows a significant improvement in both stratiform (33.9%) and convective (2.8%) rainfall estimations of the Mei-Yu frontal system, which indicates that using a scaling law can better reflect the DSD variations in different parts of the Mei-Yu front. Polarimetric radar has indisputable advantages with multiparameter detection ability. Several dual-polarization radar estimators are also established by DSD sensor data, and the R(Z(H), Z(DR)) estimator is proven to be more accurate than traditional Z–R relations in Mei-Yu frontal rainfall, with potential applications for operational C-band polarimetric radar. MDPI 2020-09-14 /pmc/articles/PMC7570947/ /pubmed/32937991 http://dx.doi.org/10.3390/s20185257 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zheng, Hepeng
Wu, Zuhang
Zhang, Lifeng
Xie, Yanqiong
Lei, Hengchi
Improving Radar Rainfall Estimations with Scaled Raindrop Size Spectra in Mei-Yu Frontal Rainstorms
title Improving Radar Rainfall Estimations with Scaled Raindrop Size Spectra in Mei-Yu Frontal Rainstorms
title_full Improving Radar Rainfall Estimations with Scaled Raindrop Size Spectra in Mei-Yu Frontal Rainstorms
title_fullStr Improving Radar Rainfall Estimations with Scaled Raindrop Size Spectra in Mei-Yu Frontal Rainstorms
title_full_unstemmed Improving Radar Rainfall Estimations with Scaled Raindrop Size Spectra in Mei-Yu Frontal Rainstorms
title_short Improving Radar Rainfall Estimations with Scaled Raindrop Size Spectra in Mei-Yu Frontal Rainstorms
title_sort improving radar rainfall estimations with scaled raindrop size spectra in mei-yu frontal rainstorms
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7570947/
https://www.ncbi.nlm.nih.gov/pubmed/32937991
http://dx.doi.org/10.3390/s20185257
work_keys_str_mv AT zhenghepeng improvingradarrainfallestimationswithscaledraindropsizespectrainmeiyufrontalrainstorms
AT wuzuhang improvingradarrainfallestimationswithscaledraindropsizespectrainmeiyufrontalrainstorms
AT zhanglifeng improvingradarrainfallestimationswithscaledraindropsizespectrainmeiyufrontalrainstorms
AT xieyanqiong improvingradarrainfallestimationswithscaledraindropsizespectrainmeiyufrontalrainstorms
AT leihengchi improvingradarrainfallestimationswithscaledraindropsizespectrainmeiyufrontalrainstorms