Quantitative precipitation estimation of the epic 2013 Colorado flood event: Polarization radar-based variational scheme

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Title:	Quantitative precipitation estimation of the epic 2013 Colorado flood event: Polarization radar-based variational scheme
Authors:	張偉裕;Chang, Wei-Yu;Vivekanandan, Jothiram;Ikeda, Kyoko;Lin, Pay-Liam
Contributors:	地球科學學院大氣科學學系
Keywords:	Accuracy;Algorithms;Atmospheric precipitations;Decision trees;Dual polarization radar;Floods;Light;Meteorological radar;Microphysics;Performance degradation;Polarimetric radar;Polarimetry;Polarization;Power law;Precipitation;Precipitation estimation;Quality;Radar;Radar measurement;Rain;Rainfall;Rainfall estimation;Reflectance;Storms;Weather forecasting;Weather radar
Date:	2016-01-01
Issue Date:	2026-04-21 14:10:39 (UTC+8)
Publisher:	American Meteorological Society;Boston: American Meteorological Society
Abstract:	摘要： The accuracy of rain-rate estimation using polarimetric radar measurements has been improved as a result of better characterization of radar measurement quality and rain microphysics. In the literature, a variety of power-law relations between polarimetric radar measurements and rain rate are described because of the dynamic or varying nature of rain microphysics. A variational technique that concurrently takes into account radar observational error and dynamically varying rain microphysics is proposed in this study. Rain-rate estimation using the variational algorithm that uses event-based observational error and background rain climatological values is evaluated using observing system simulation experiments (OSSE), and its performance is demonstrated in the case of an epic Colorado flood event. The rain event occurred between 11 and 12 September 2013. The results from OSSE show that the variational algorithm with event-based observational error consistently estimates more accurate rain rate than does the "R(Z HH, Z DR)" power-law algorithm. On the contrary, the usage of ad hoc or improper observational error degrades the performance of the variational method. Furthermore, the variational algorithm is less sensitive to the observational error of differential reflectivity Z DR than is the R(Z HH, Z DR) algorithm. The variational quantitative precipitation estimation (QPE) retrieved more accurate rainfall estimation than did the power-law dual-polarization QPE in this particular event, despite the fact that both algorithms used the same dual-polarization radar measurements from the Next Generation Weather Radar (NEXRAD). 出版者： Boston: American Meteorological Society 出版日期： 2016-07-01 出處： Journal of applied meteorology and climatology, 2016-07, Vol.55 (7), p.1477-1495 資源來源： EBSCOhost OmniFile Full Text Select 版權： 2016 American Meteorological Society 版權： Copyright American Meteorological Society Jul 2016 版權： Copyright American Meteorological Society 2016 識別號： ISSN: 1558-8424 識別號： EISSN: 1558-8432 識別號： DOI: 10.1175/JAMC-D-15-0222.1 識別號： CODEN: JOAMEZ
Appears in Collections:	[Department of Atmospheric Sciences] journal & Dissertation

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