DOI: 10.1002/jgrd.50726
论文题名: Identification and uncertainty estimation of vertical reflectivity profiles using a Lagrangian approach to support quantitative precipitation measurements by weather radar
作者: Hazenberg P. ; Torfs P.J.J.F. ; Leijnse H. ; Delrieu G. ; Uijlenhoet R.
刊名: Journal of Geophysical Research Atmospheres
ISSN: 21698996
出版年: 2013
卷: 118, 期: 18 起始页码: 10243
结束页码: 10261
语种: 英语
英文关键词: precipitation
; radar hydrology
; radar rainfall estimation
; vertical profile of reflectivity
; weather radar
Scopus关键词: Estimation
; Lagrange multipliers
; Piecewise linear techniques
; Precipitation (chemical)
; Rain
; Rain gages
; Reflection
; Uncertainty analysis
; Estimation procedures
; La-grangian approaches
; Precipitation measurement
; Radar rainfall
; Rainfall uncertainties
; Uncertainty estimation
; Vertical profile of reflectivities
; Vertical reflectivity profile
; Meteorological radar
; algorithm
; climate modeling
; estimation method
; Lagrangian analysis
; precipitation (climatology)
; radar imagery
; rainfall
; raingauge
; uncertainty analysis
; vertical profile
; weather station
英文摘要: This paper presents a novel approach to estimate the vertical profile of reflectivity (VPR) from volumetric weather radar data using both a traditional Eulerian as well as a newly proposed Lagrangian implementation. For this latter implementation, the recently developed Rotational Carpenter Square Cluster Algorithm (RoCaSCA) is used to delineate precipitation regions at different reflectivity levels. A piecewise linear VPR is estimated for either stratiform or neither stratiform/convective precipitation. As a second aspect of this paper, a novel approach is presented which is able to account for the impact of VPR uncertainty on the estimated radar rainfall variability. Results show that implementation of the VPR identification and correction procedure has a positive impact on quantitative precipitation estimates from radar. Unfortunately, visibility problems severely limit the impact of the Lagrangian implementation beyond distances of 100 km. However, by combining this procedure with the global Eulerian VPR estimation procedure for a given rainfall type (stratiform and neither stratiform/convective), the quality of the quantitative precipitation estimates increases up to a distance of 150 km. Analyses of the impact of VPR uncertainty shows that this aspect accounts for a large fraction of the differences between weather radar rainfall estimates and rain gauge measurements. Key Points A new Lagrangian based VPR identification methodRadar rainfall uncertainty estimation from spatial precipitation variabilityImproved weather radar based surface rainfall estimation ©2013. American Geophysical Union. All Rights Reserved. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/63318
Appears in Collections: 影响、适应和脆弱性 气候减缓与适应
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作者单位: Department of Atmospheric Sciences, University of Arizona, 1118 E. 4th St., Tucson, AZ 85721, United States; Hydrology and Quantitative Water Management Group, Wageningen University, Wageningen, Netherlands; Royal Netherlands Meteorological Institute, De Bilt, Netherlands; Laboratoire d'Étude des Transferts en Hydrologie et Environnement, Grenoble, France
Recommended Citation:
Hazenberg P.,Torfs P.J.J.F.,Leijnse H.,et al. Identification and uncertainty estimation of vertical reflectivity profiles using a Lagrangian approach to support quantitative precipitation measurements by weather radar[J]. Journal of Geophysical Research Atmospheres,2013-01-01,118(18)