A New Shape Matching-Based Verification Approach for QPFs

In this paper, a novel systematic method on the evaluation of quantitative precipitation forecast (QPF) errors from the perspective of rain-area shape verification is proposed. The method aims to improve the accuracy and efficiency of conventional station-based verifications (i.e., standard skill sc...
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Gespeichert in:

Autor*in:	Kai Chen [verfasserIn] Jun Liu [verfasserIn] Jinsong Chen [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2018

Schlagwörter:	Quantitative precipitation forecast (QPF) rainfall shape verification shape matching QPF error

Übergeordnetes Werk:	In: IEEE Access - IEEE, 2014, 6(2018), Seite 29013-29025
Übergeordnetes Werk:	volume:6 ; year:2018 ; pages:29013-29025

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1109/ACCESS.2018.2835440

Katalog-ID:	DOAJ049810022

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520			\|a In this paper, a novel systematic method on the evaluation of quantitative precipitation forecast (QPF) errors from the perspective of rain-area shape verification is proposed. The method aims to improve the accuracy and efficiency of conventional station-based verifications (i.e., standard skill scores), which are insensitive to the biases of station location and rain-area shape and tend to ignore the continuity of precipitation in time and space. The method develops and combines the shape verification indexes, which include the overlap ratio of a forecasted rain-area (Ratio<sub<f</sub<), the overlap ratio of the ground rainarea (Ratio<sub<t</sub<), the Jaccard similarity coefficient between the shape of the QPF area, the shape of the ground rain-area (Jaccard<sub<shape</sub<), the critical success index (CSI) for the rain-area shape (CSI<sub<shape</sub<), the probability of detection (POD) for the rain-area shape (POD<sub<shape</sub<), and the false alarm ratio (FAR) for the rain-area shape (FAR<sub<shape</sub<). This definition of QPF verification is applied to a rain event from 2016/08/02 00:30 to 2016/08/02 03:24 in the Guangdong Province. The decomposition of QPF errors into station-based errors and shape error components provides powerful insight into the effects of overall forecasting performance. The experimental results of this investigation show that the proposed method provides an opportunity to assess QPFs objectively and further promote advanced forecasting technologies from this perspective.
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spelling	10.1109/ACCESS.2018.2835440 doi (DE-627)DOAJ049810022 (DE-599)DOAJ3f795262f4a94affae094f7542f9f5a9 DE-627 ger DE-627 rakwb eng TK1-9971 Kai Chen verfasserin aut A New Shape Matching-Based Verification Approach for QPFs 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper, a novel systematic method on the evaluation of quantitative precipitation forecast (QPF) errors from the perspective of rain-area shape verification is proposed. The method aims to improve the accuracy and efficiency of conventional station-based verifications (i.e., standard skill scores), which are insensitive to the biases of station location and rain-area shape and tend to ignore the continuity of precipitation in time and space. The method develops and combines the shape verification indexes, which include the overlap ratio of a forecasted rain-area (Ratio<sub<f</sub<), the overlap ratio of the ground rainarea (Ratio<sub<t</sub<), the Jaccard similarity coefficient between the shape of the QPF area, the shape of the ground rain-area (Jaccard<sub<shape</sub<), the critical success index (CSI) for the rain-area shape (CSI<sub<shape</sub<), the probability of detection (POD) for the rain-area shape (POD<sub<shape</sub<), and the false alarm ratio (FAR) for the rain-area shape (FAR<sub<shape</sub<). This definition of QPF verification is applied to a rain event from 2016/08/02 00:30 to 2016/08/02 03:24 in the Guangdong Province. The decomposition of QPF errors into station-based errors and shape error components provides powerful insight into the effects of overall forecasting performance. The experimental results of this investigation show that the proposed method provides an opportunity to assess QPFs objectively and further promote advanced forecasting technologies from this perspective. Quantitative precipitation forecast (QPF) rainfall shape verification shape matching QPF error Electrical engineering. Electronics. Nuclear engineering Jun Liu verfasserin aut Jinsong Chen verfasserin aut In IEEE Access IEEE, 2014 6(2018), Seite 29013-29025 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:6 year:2018 pages:29013-29025 https://doi.org/10.1109/ACCESS.2018.2835440 kostenfrei https://doaj.org/article/3f795262f4a94affae094f7542f9f5a9 kostenfrei https://ieeexplore.ieee.org/document/8357764/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 6 2018 29013-29025
allfields_unstemmed	10.1109/ACCESS.2018.2835440 doi (DE-627)DOAJ049810022 (DE-599)DOAJ3f795262f4a94affae094f7542f9f5a9 DE-627 ger DE-627 rakwb eng TK1-9971 Kai Chen verfasserin aut A New Shape Matching-Based Verification Approach for QPFs 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper, a novel systematic method on the evaluation of quantitative precipitation forecast (QPF) errors from the perspective of rain-area shape verification is proposed. The method aims to improve the accuracy and efficiency of conventional station-based verifications (i.e., standard skill scores), which are insensitive to the biases of station location and rain-area shape and tend to ignore the continuity of precipitation in time and space. The method develops and combines the shape verification indexes, which include the overlap ratio of a forecasted rain-area (Ratio<sub<f</sub<), the overlap ratio of the ground rainarea (Ratio<sub<t</sub<), the Jaccard similarity coefficient between the shape of the QPF area, the shape of the ground rain-area (Jaccard<sub<shape</sub<), the critical success index (CSI) for the rain-area shape (CSI<sub<shape</sub<), the probability of detection (POD) for the rain-area shape (POD<sub<shape</sub<), and the false alarm ratio (FAR) for the rain-area shape (FAR<sub<shape</sub<). This definition of QPF verification is applied to a rain event from 2016/08/02 00:30 to 2016/08/02 03:24 in the Guangdong Province. The decomposition of QPF errors into station-based errors and shape error components provides powerful insight into the effects of overall forecasting performance. The experimental results of this investigation show that the proposed method provides an opportunity to assess QPFs objectively and further promote advanced forecasting technologies from this perspective. Quantitative precipitation forecast (QPF) rainfall shape verification shape matching QPF error Electrical engineering. Electronics. Nuclear engineering Jun Liu verfasserin aut Jinsong Chen verfasserin aut In IEEE Access IEEE, 2014 6(2018), Seite 29013-29025 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:6 year:2018 pages:29013-29025 https://doi.org/10.1109/ACCESS.2018.2835440 kostenfrei https://doaj.org/article/3f795262f4a94affae094f7542f9f5a9 kostenfrei https://ieeexplore.ieee.org/document/8357764/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 6 2018 29013-29025
allfieldsGer	10.1109/ACCESS.2018.2835440 doi (DE-627)DOAJ049810022 (DE-599)DOAJ3f795262f4a94affae094f7542f9f5a9 DE-627 ger DE-627 rakwb eng TK1-9971 Kai Chen verfasserin aut A New Shape Matching-Based Verification Approach for QPFs 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper, a novel systematic method on the evaluation of quantitative precipitation forecast (QPF) errors from the perspective of rain-area shape verification is proposed. The method aims to improve the accuracy and efficiency of conventional station-based verifications (i.e., standard skill scores), which are insensitive to the biases of station location and rain-area shape and tend to ignore the continuity of precipitation in time and space. The method develops and combines the shape verification indexes, which include the overlap ratio of a forecasted rain-area (Ratio<sub<f</sub<), the overlap ratio of the ground rainarea (Ratio<sub<t</sub<), the Jaccard similarity coefficient between the shape of the QPF area, the shape of the ground rain-area (Jaccard<sub<shape</sub<), the critical success index (CSI) for the rain-area shape (CSI<sub<shape</sub<), the probability of detection (POD) for the rain-area shape (POD<sub<shape</sub<), and the false alarm ratio (FAR) for the rain-area shape (FAR<sub<shape</sub<). This definition of QPF verification is applied to a rain event from 2016/08/02 00:30 to 2016/08/02 03:24 in the Guangdong Province. The decomposition of QPF errors into station-based errors and shape error components provides powerful insight into the effects of overall forecasting performance. The experimental results of this investigation show that the proposed method provides an opportunity to assess QPFs objectively and further promote advanced forecasting technologies from this perspective. Quantitative precipitation forecast (QPF) rainfall shape verification shape matching QPF error Electrical engineering. Electronics. Nuclear engineering Jun Liu verfasserin aut Jinsong Chen verfasserin aut In IEEE Access IEEE, 2014 6(2018), Seite 29013-29025 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:6 year:2018 pages:29013-29025 https://doi.org/10.1109/ACCESS.2018.2835440 kostenfrei https://doaj.org/article/3f795262f4a94affae094f7542f9f5a9 kostenfrei https://ieeexplore.ieee.org/document/8357764/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 6 2018 29013-29025
allfieldsSound	10.1109/ACCESS.2018.2835440 doi (DE-627)DOAJ049810022 (DE-599)DOAJ3f795262f4a94affae094f7542f9f5a9 DE-627 ger DE-627 rakwb eng TK1-9971 Kai Chen verfasserin aut A New Shape Matching-Based Verification Approach for QPFs 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper, a novel systematic method on the evaluation of quantitative precipitation forecast (QPF) errors from the perspective of rain-area shape verification is proposed. The method aims to improve the accuracy and efficiency of conventional station-based verifications (i.e., standard skill scores), which are insensitive to the biases of station location and rain-area shape and tend to ignore the continuity of precipitation in time and space. The method develops and combines the shape verification indexes, which include the overlap ratio of a forecasted rain-area (Ratio<sub<f</sub<), the overlap ratio of the ground rainarea (Ratio<sub<t</sub<), the Jaccard similarity coefficient between the shape of the QPF area, the shape of the ground rain-area (Jaccard<sub<shape</sub<), the critical success index (CSI) for the rain-area shape (CSI<sub<shape</sub<), the probability of detection (POD) for the rain-area shape (POD<sub<shape</sub<), and the false alarm ratio (FAR) for the rain-area shape (FAR<sub<shape</sub<). This definition of QPF verification is applied to a rain event from 2016/08/02 00:30 to 2016/08/02 03:24 in the Guangdong Province. The decomposition of QPF errors into station-based errors and shape error components provides powerful insight into the effects of overall forecasting performance. The experimental results of this investigation show that the proposed method provides an opportunity to assess QPFs objectively and further promote advanced forecasting technologies from this perspective. Quantitative precipitation forecast (QPF) rainfall shape verification shape matching QPF error Electrical engineering. Electronics. Nuclear engineering Jun Liu verfasserin aut Jinsong Chen verfasserin aut In IEEE Access IEEE, 2014 6(2018), Seite 29013-29025 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:6 year:2018 pages:29013-29025 https://doi.org/10.1109/ACCESS.2018.2835440 kostenfrei https://doaj.org/article/3f795262f4a94affae094f7542f9f5a9 kostenfrei https://ieeexplore.ieee.org/document/8357764/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 6 2018 29013-29025
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source	In IEEE Access 6(2018), Seite 29013-29025 volume:6 year:2018 pages:29013-29025
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topic_facet	Quantitative precipitation forecast (QPF) rainfall shape verification shape matching QPF error Electrical engineering. Electronics. Nuclear engineering
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container_title	IEEE Access
authorswithroles_txt_mv	Kai Chen @@aut@@ Jun Liu @@aut@@ Jinsong Chen @@aut@@
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callnumber-first	T - Technology
author	Kai Chen
spellingShingle	Kai Chen misc TK1-9971 misc Quantitative precipitation forecast (QPF) misc rainfall shape verification misc shape matching misc QPF error misc Electrical engineering. Electronics. Nuclear engineering A New Shape Matching-Based Verification Approach for QPFs
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topic_title	TK1-9971 A New Shape Matching-Based Verification Approach for QPFs Quantitative precipitation forecast (QPF) rainfall shape verification shape matching QPF error
topic	misc TK1-9971 misc Quantitative precipitation forecast (QPF) misc rainfall shape verification misc shape matching misc QPF error misc Electrical engineering. Electronics. Nuclear engineering
topic_unstemmed	misc TK1-9971 misc Quantitative precipitation forecast (QPF) misc rainfall shape verification misc shape matching misc QPF error misc Electrical engineering. Electronics. Nuclear engineering
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title	A New Shape Matching-Based Verification Approach for QPFs
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title_full	A New Shape Matching-Based Verification Approach for QPFs
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title_sort	new shape matching-based verification approach for qpfs
callnumber	TK1-9971
title_auth	A New Shape Matching-Based Verification Approach for QPFs
abstract	In this paper, a novel systematic method on the evaluation of quantitative precipitation forecast (QPF) errors from the perspective of rain-area shape verification is proposed. The method aims to improve the accuracy and efficiency of conventional station-based verifications (i.e., standard skill scores), which are insensitive to the biases of station location and rain-area shape and tend to ignore the continuity of precipitation in time and space. The method develops and combines the shape verification indexes, which include the overlap ratio of a forecasted rain-area (Ratio<sub<f</sub<), the overlap ratio of the ground rainarea (Ratio<sub<t</sub<), the Jaccard similarity coefficient between the shape of the QPF area, the shape of the ground rain-area (Jaccard<sub<shape</sub<), the critical success index (CSI) for the rain-area shape (CSI<sub<shape</sub<), the probability of detection (POD) for the rain-area shape (POD<sub<shape</sub<), and the false alarm ratio (FAR) for the rain-area shape (FAR<sub<shape</sub<). This definition of QPF verification is applied to a rain event from 2016/08/02 00:30 to 2016/08/02 03:24 in the Guangdong Province. The decomposition of QPF errors into station-based errors and shape error components provides powerful insight into the effects of overall forecasting performance. The experimental results of this investigation show that the proposed method provides an opportunity to assess QPFs objectively and further promote advanced forecasting technologies from this perspective.
abstractGer	In this paper, a novel systematic method on the evaluation of quantitative precipitation forecast (QPF) errors from the perspective of rain-area shape verification is proposed. The method aims to improve the accuracy and efficiency of conventional station-based verifications (i.e., standard skill scores), which are insensitive to the biases of station location and rain-area shape and tend to ignore the continuity of precipitation in time and space. The method develops and combines the shape verification indexes, which include the overlap ratio of a forecasted rain-area (Ratio<sub<f</sub<), the overlap ratio of the ground rainarea (Ratio<sub<t</sub<), the Jaccard similarity coefficient between the shape of the QPF area, the shape of the ground rain-area (Jaccard<sub<shape</sub<), the critical success index (CSI) for the rain-area shape (CSI<sub<shape</sub<), the probability of detection (POD) for the rain-area shape (POD<sub<shape</sub<), and the false alarm ratio (FAR) for the rain-area shape (FAR<sub<shape</sub<). This definition of QPF verification is applied to a rain event from 2016/08/02 00:30 to 2016/08/02 03:24 in the Guangdong Province. The decomposition of QPF errors into station-based errors and shape error components provides powerful insight into the effects of overall forecasting performance. The experimental results of this investigation show that the proposed method provides an opportunity to assess QPFs objectively and further promote advanced forecasting technologies from this perspective.
abstract_unstemmed	In this paper, a novel systematic method on the evaluation of quantitative precipitation forecast (QPF) errors from the perspective of rain-area shape verification is proposed. The method aims to improve the accuracy and efficiency of conventional station-based verifications (i.e., standard skill scores), which are insensitive to the biases of station location and rain-area shape and tend to ignore the continuity of precipitation in time and space. The method develops and combines the shape verification indexes, which include the overlap ratio of a forecasted rain-area (Ratio<sub<f</sub<), the overlap ratio of the ground rainarea (Ratio<sub<t</sub<), the Jaccard similarity coefficient between the shape of the QPF area, the shape of the ground rain-area (Jaccard<sub<shape</sub<), the critical success index (CSI) for the rain-area shape (CSI<sub<shape</sub<), the probability of detection (POD) for the rain-area shape (POD<sub<shape</sub<), and the false alarm ratio (FAR) for the rain-area shape (FAR<sub<shape</sub<). This definition of QPF verification is applied to a rain event from 2016/08/02 00:30 to 2016/08/02 03:24 in the Guangdong Province. The decomposition of QPF errors into station-based errors and shape error components provides powerful insight into the effects of overall forecasting performance. The experimental results of this investigation show that the proposed method provides an opportunity to assess QPFs objectively and further promote advanced forecasting technologies from this perspective.
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title_short	A New Shape Matching-Based Verification Approach for QPFs
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up_date	2024-07-04T00:54:10.758Z
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