Organizational Modes of Severe Wind-producing Convective Systems over North China

Abstract Severe weather reports and composite radar reflectivity data from 2010–14 over North China were used to analyze the distribution of severe convective wind (SCW) events and their organizational modes of radar reflectivity. The six organizational modes for SCW events (and their proportions) w...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Yang, Xinlin [verfasserIn] Sun, Jianhua [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2018

Schlagwörter:	severe convective wind organizational mode convective system topography

Übergeordnetes Werk:	Enthalten in: Advances in atmospheric sciences - Beijing : Science in China Press, 2006, 35(2018), 5 vom: 19. Feb., Seite 540-549
Übergeordnetes Werk:	volume:35 ; year:2018 ; number:5 ; day:19 ; month:02 ; pages:540-549

Links:	Volltext

DOI / URN:	10.1007/s00376-017-7114-2

Katalog-ID:	SPR004548418

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520			\|a Abstract Severe weather reports and composite radar reflectivity data from 2010–14 over North China were used to analyze the distribution of severe convective wind (SCW) events and their organizational modes of radar reflectivity. The six organizational modes for SCW events (and their proportions) were cluster cells (35.4%), squall lines (18.4%), nonlinear-shaped systems (17.8%), broken lines (11.6%), individual cells (1.2%), and bow echoes (0.5%). The peak month for both squall lines and broken lines was June, whereas it was July for the other four modes. The highest numbers of SCW events were over the mountains, which were generally associated with disorganized systems of cluster cells. In contrast, SCW associated with linear systems occurred mainly over the plains, where stations recorded an average of less than one SCW event per year. Regions with a high frequency of SCW associated with nonlinear-shaped systems also experienced many SCW events associated with squall lines. Values of convective available potential energy, precipitable water, 0–3-km shear, and 0–6-km shear, were demonstrably larger over the plains than over the mountains, which had an evident effect on the organizational modes of SCW events. Therefore, topography may be an important factor in the organizational modes for SCW events over North China.
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Indexfelder

author_variant	x y xy j s js
matchkey_str	article:18619533:2018----::raiainloeosvrwnpouigovcie
hierarchy_sort_str	2018
bklnumber	38.81
publishDate	2018
allfields	10.1007/s00376-017-7114-2 doi (DE-627)SPR004548418 (SPR)s00376-017-7114-2-e DE-627 ger DE-627 rakwb eng 550 ASE 38.81 bkl Yang, Xinlin verfasserin aut Organizational Modes of Severe Wind-producing Convective Systems over North China 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Severe weather reports and composite radar reflectivity data from 2010–14 over North China were used to analyze the distribution of severe convective wind (SCW) events and their organizational modes of radar reflectivity. The six organizational modes for SCW events (and their proportions) were cluster cells (35.4%), squall lines (18.4%), nonlinear-shaped systems (17.8%), broken lines (11.6%), individual cells (1.2%), and bow echoes (0.5%). The peak month for both squall lines and broken lines was June, whereas it was July for the other four modes. The highest numbers of SCW events were over the mountains, which were generally associated with disorganized systems of cluster cells. In contrast, SCW associated with linear systems occurred mainly over the plains, where stations recorded an average of less than one SCW event per year. Regions with a high frequency of SCW associated with nonlinear-shaped systems also experienced many SCW events associated with squall lines. Values of convective available potential energy, precipitable water, 0–3-km shear, and 0–6-km shear, were demonstrably larger over the plains than over the mountains, which had an evident effect on the organizational modes of SCW events. Therefore, topography may be an important factor in the organizational modes for SCW events over North China. severe convective wind (dpeaa)DE-He213 organizational mode (dpeaa)DE-He213 convective system (dpeaa)DE-He213 topography (dpeaa)DE-He213 Sun, Jianhua verfasserin aut Enthalten in Advances in atmospheric sciences Beijing : Science in China Press, 2006 35(2018), 5 vom: 19. Feb., Seite 540-549 (DE-627)509756603 (DE-600)2228064-9 1861-9533 nnns volume:35 year:2018 number:5 day:19 month:02 pages:540-549 https://dx.doi.org/10.1007/s00376-017-7114-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.81 ASE AR 35 2018 5 19 02 540-549
spelling	10.1007/s00376-017-7114-2 doi (DE-627)SPR004548418 (SPR)s00376-017-7114-2-e DE-627 ger DE-627 rakwb eng 550 ASE 38.81 bkl Yang, Xinlin verfasserin aut Organizational Modes of Severe Wind-producing Convective Systems over North China 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Severe weather reports and composite radar reflectivity data from 2010–14 over North China were used to analyze the distribution of severe convective wind (SCW) events and their organizational modes of radar reflectivity. The six organizational modes for SCW events (and their proportions) were cluster cells (35.4%), squall lines (18.4%), nonlinear-shaped systems (17.8%), broken lines (11.6%), individual cells (1.2%), and bow echoes (0.5%). The peak month for both squall lines and broken lines was June, whereas it was July for the other four modes. The highest numbers of SCW events were over the mountains, which were generally associated with disorganized systems of cluster cells. In contrast, SCW associated with linear systems occurred mainly over the plains, where stations recorded an average of less than one SCW event per year. Regions with a high frequency of SCW associated with nonlinear-shaped systems also experienced many SCW events associated with squall lines. Values of convective available potential energy, precipitable water, 0–3-km shear, and 0–6-km shear, were demonstrably larger over the plains than over the mountains, which had an evident effect on the organizational modes of SCW events. Therefore, topography may be an important factor in the organizational modes for SCW events over North China. severe convective wind (dpeaa)DE-He213 organizational mode (dpeaa)DE-He213 convective system (dpeaa)DE-He213 topography (dpeaa)DE-He213 Sun, Jianhua verfasserin aut Enthalten in Advances in atmospheric sciences Beijing : Science in China Press, 2006 35(2018), 5 vom: 19. Feb., Seite 540-549 (DE-627)509756603 (DE-600)2228064-9 1861-9533 nnns volume:35 year:2018 number:5 day:19 month:02 pages:540-549 https://dx.doi.org/10.1007/s00376-017-7114-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.81 ASE AR 35 2018 5 19 02 540-549
allfields_unstemmed	10.1007/s00376-017-7114-2 doi (DE-627)SPR004548418 (SPR)s00376-017-7114-2-e DE-627 ger DE-627 rakwb eng 550 ASE 38.81 bkl Yang, Xinlin verfasserin aut Organizational Modes of Severe Wind-producing Convective Systems over North China 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Severe weather reports and composite radar reflectivity data from 2010–14 over North China were used to analyze the distribution of severe convective wind (SCW) events and their organizational modes of radar reflectivity. The six organizational modes for SCW events (and their proportions) were cluster cells (35.4%), squall lines (18.4%), nonlinear-shaped systems (17.8%), broken lines (11.6%), individual cells (1.2%), and bow echoes (0.5%). The peak month for both squall lines and broken lines was June, whereas it was July for the other four modes. The highest numbers of SCW events were over the mountains, which were generally associated with disorganized systems of cluster cells. In contrast, SCW associated with linear systems occurred mainly over the plains, where stations recorded an average of less than one SCW event per year. Regions with a high frequency of SCW associated with nonlinear-shaped systems also experienced many SCW events associated with squall lines. Values of convective available potential energy, precipitable water, 0–3-km shear, and 0–6-km shear, were demonstrably larger over the plains than over the mountains, which had an evident effect on the organizational modes of SCW events. Therefore, topography may be an important factor in the organizational modes for SCW events over North China. severe convective wind (dpeaa)DE-He213 organizational mode (dpeaa)DE-He213 convective system (dpeaa)DE-He213 topography (dpeaa)DE-He213 Sun, Jianhua verfasserin aut Enthalten in Advances in atmospheric sciences Beijing : Science in China Press, 2006 35(2018), 5 vom: 19. Feb., Seite 540-549 (DE-627)509756603 (DE-600)2228064-9 1861-9533 nnns volume:35 year:2018 number:5 day:19 month:02 pages:540-549 https://dx.doi.org/10.1007/s00376-017-7114-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.81 ASE AR 35 2018 5 19 02 540-549
allfieldsGer	10.1007/s00376-017-7114-2 doi (DE-627)SPR004548418 (SPR)s00376-017-7114-2-e DE-627 ger DE-627 rakwb eng 550 ASE 38.81 bkl Yang, Xinlin verfasserin aut Organizational Modes of Severe Wind-producing Convective Systems over North China 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Severe weather reports and composite radar reflectivity data from 2010–14 over North China were used to analyze the distribution of severe convective wind (SCW) events and their organizational modes of radar reflectivity. The six organizational modes for SCW events (and their proportions) were cluster cells (35.4%), squall lines (18.4%), nonlinear-shaped systems (17.8%), broken lines (11.6%), individual cells (1.2%), and bow echoes (0.5%). The peak month for both squall lines and broken lines was June, whereas it was July for the other four modes. The highest numbers of SCW events were over the mountains, which were generally associated with disorganized systems of cluster cells. In contrast, SCW associated with linear systems occurred mainly over the plains, where stations recorded an average of less than one SCW event per year. Regions with a high frequency of SCW associated with nonlinear-shaped systems also experienced many SCW events associated with squall lines. Values of convective available potential energy, precipitable water, 0–3-km shear, and 0–6-km shear, were demonstrably larger over the plains than over the mountains, which had an evident effect on the organizational modes of SCW events. Therefore, topography may be an important factor in the organizational modes for SCW events over North China. severe convective wind (dpeaa)DE-He213 organizational mode (dpeaa)DE-He213 convective system (dpeaa)DE-He213 topography (dpeaa)DE-He213 Sun, Jianhua verfasserin aut Enthalten in Advances in atmospheric sciences Beijing : Science in China Press, 2006 35(2018), 5 vom: 19. Feb., Seite 540-549 (DE-627)509756603 (DE-600)2228064-9 1861-9533 nnns volume:35 year:2018 number:5 day:19 month:02 pages:540-549 https://dx.doi.org/10.1007/s00376-017-7114-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.81 ASE AR 35 2018 5 19 02 540-549
allfieldsSound	10.1007/s00376-017-7114-2 doi (DE-627)SPR004548418 (SPR)s00376-017-7114-2-e DE-627 ger DE-627 rakwb eng 550 ASE 38.81 bkl Yang, Xinlin verfasserin aut Organizational Modes of Severe Wind-producing Convective Systems over North China 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Severe weather reports and composite radar reflectivity data from 2010–14 over North China were used to analyze the distribution of severe convective wind (SCW) events and their organizational modes of radar reflectivity. The six organizational modes for SCW events (and their proportions) were cluster cells (35.4%), squall lines (18.4%), nonlinear-shaped systems (17.8%), broken lines (11.6%), individual cells (1.2%), and bow echoes (0.5%). The peak month for both squall lines and broken lines was June, whereas it was July for the other four modes. The highest numbers of SCW events were over the mountains, which were generally associated with disorganized systems of cluster cells. In contrast, SCW associated with linear systems occurred mainly over the plains, where stations recorded an average of less than one SCW event per year. Regions with a high frequency of SCW associated with nonlinear-shaped systems also experienced many SCW events associated with squall lines. Values of convective available potential energy, precipitable water, 0–3-km shear, and 0–6-km shear, were demonstrably larger over the plains than over the mountains, which had an evident effect on the organizational modes of SCW events. Therefore, topography may be an important factor in the organizational modes for SCW events over North China. severe convective wind (dpeaa)DE-He213 organizational mode (dpeaa)DE-He213 convective system (dpeaa)DE-He213 topography (dpeaa)DE-He213 Sun, Jianhua verfasserin aut Enthalten in Advances in atmospheric sciences Beijing : Science in China Press, 2006 35(2018), 5 vom: 19. Feb., Seite 540-549 (DE-627)509756603 (DE-600)2228064-9 1861-9533 nnns volume:35 year:2018 number:5 day:19 month:02 pages:540-549 https://dx.doi.org/10.1007/s00376-017-7114-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.81 ASE AR 35 2018 5 19 02 540-549
language	English
source	Enthalten in Advances in atmospheric sciences 35(2018), 5 vom: 19. Feb., Seite 540-549 volume:35 year:2018 number:5 day:19 month:02 pages:540-549
sourceStr	Enthalten in Advances in atmospheric sciences 35(2018), 5 vom: 19. Feb., Seite 540-549 volume:35 year:2018 number:5 day:19 month:02 pages:540-549
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	severe convective wind organizational mode convective system topography
dewey-raw	550
isfreeaccess_bool	false
container_title	Advances in atmospheric sciences
authorswithroles_txt_mv	Yang, Xinlin @@aut@@ Sun, Jianhua @@aut@@
publishDateDaySort_date	2018-02-19T00:00:00Z
hierarchy_top_id	509756603
dewey-sort	3550
id	SPR004548418
language_de	englisch
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The six organizational modes for SCW events (and their proportions) were cluster cells (35.4%), squall lines (18.4%), nonlinear-shaped systems (17.8%), broken lines (11.6%), individual cells (1.2%), and bow echoes (0.5%). The peak month for both squall lines and broken lines was June, whereas it was July for the other four modes. The highest numbers of SCW events were over the mountains, which were generally associated with disorganized systems of cluster cells. In contrast, SCW associated with linear systems occurred mainly over the plains, where stations recorded an average of less than one SCW event per year. Regions with a high frequency of SCW associated with nonlinear-shaped systems also experienced many SCW events associated with squall lines. Values of convective available potential energy, precipitable water, 0–3-km shear, and 0–6-km shear, were demonstrably larger over the plains than over the mountains, which had an evident effect on the organizational modes of SCW events. 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author	Yang, Xinlin
spellingShingle	Yang, Xinlin ddc 550 bkl 38.81 misc severe convective wind misc organizational mode misc convective system misc topography Organizational Modes of Severe Wind-producing Convective Systems over North China
authorStr	Yang, Xinlin
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topic_title	550 ASE 38.81 bkl Organizational Modes of Severe Wind-producing Convective Systems over North China severe convective wind (dpeaa)DE-He213 organizational mode (dpeaa)DE-He213 convective system (dpeaa)DE-He213 topography (dpeaa)DE-He213
topic	ddc 550 bkl 38.81 misc severe convective wind misc organizational mode misc convective system misc topography
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title	Organizational Modes of Severe Wind-producing Convective Systems over North China
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title_full	Organizational Modes of Severe Wind-producing Convective Systems over North China
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title_sort	organizational modes of severe wind-producing convective systems over north china
title_auth	Organizational Modes of Severe Wind-producing Convective Systems over North China
abstract	Abstract Severe weather reports and composite radar reflectivity data from 2010–14 over North China were used to analyze the distribution of severe convective wind (SCW) events and their organizational modes of radar reflectivity. The six organizational modes for SCW events (and their proportions) were cluster cells (35.4%), squall lines (18.4%), nonlinear-shaped systems (17.8%), broken lines (11.6%), individual cells (1.2%), and bow echoes (0.5%). The peak month for both squall lines and broken lines was June, whereas it was July for the other four modes. The highest numbers of SCW events were over the mountains, which were generally associated with disorganized systems of cluster cells. In contrast, SCW associated with linear systems occurred mainly over the plains, where stations recorded an average of less than one SCW event per year. Regions with a high frequency of SCW associated with nonlinear-shaped systems also experienced many SCW events associated with squall lines. Values of convective available potential energy, precipitable water, 0–3-km shear, and 0–6-km shear, were demonstrably larger over the plains than over the mountains, which had an evident effect on the organizational modes of SCW events. Therefore, topography may be an important factor in the organizational modes for SCW events over North China.
abstractGer	Abstract Severe weather reports and composite radar reflectivity data from 2010–14 over North China were used to analyze the distribution of severe convective wind (SCW) events and their organizational modes of radar reflectivity. The six organizational modes for SCW events (and their proportions) were cluster cells (35.4%), squall lines (18.4%), nonlinear-shaped systems (17.8%), broken lines (11.6%), individual cells (1.2%), and bow echoes (0.5%). The peak month for both squall lines and broken lines was June, whereas it was July for the other four modes. The highest numbers of SCW events were over the mountains, which were generally associated with disorganized systems of cluster cells. In contrast, SCW associated with linear systems occurred mainly over the plains, where stations recorded an average of less than one SCW event per year. Regions with a high frequency of SCW associated with nonlinear-shaped systems also experienced many SCW events associated with squall lines. Values of convective available potential energy, precipitable water, 0–3-km shear, and 0–6-km shear, were demonstrably larger over the plains than over the mountains, which had an evident effect on the organizational modes of SCW events. Therefore, topography may be an important factor in the organizational modes for SCW events over North China.
abstract_unstemmed	Abstract Severe weather reports and composite radar reflectivity data from 2010–14 over North China were used to analyze the distribution of severe convective wind (SCW) events and their organizational modes of radar reflectivity. The six organizational modes for SCW events (and their proportions) were cluster cells (35.4%), squall lines (18.4%), nonlinear-shaped systems (17.8%), broken lines (11.6%), individual cells (1.2%), and bow echoes (0.5%). The peak month for both squall lines and broken lines was June, whereas it was July for the other four modes. The highest numbers of SCW events were over the mountains, which were generally associated with disorganized systems of cluster cells. In contrast, SCW associated with linear systems occurred mainly over the plains, where stations recorded an average of less than one SCW event per year. Regions with a high frequency of SCW associated with nonlinear-shaped systems also experienced many SCW events associated with squall lines. Values of convective available potential energy, precipitable water, 0–3-km shear, and 0–6-km shear, were demonstrably larger over the plains than over the mountains, which had an evident effect on the organizational modes of SCW events. Therefore, topography may be an important factor in the organizational modes for SCW events over North China.
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container_issue	5
title_short	Organizational Modes of Severe Wind-producing Convective Systems over North China
url	https://dx.doi.org/10.1007/s00376-017-7114-2
remote_bool	true
author2	Sun, Jianhua
author2Str	Sun, Jianhua
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doi_str	10.1007/s00376-017-7114-2
up_date	2024-07-04T01:33:43.047Z
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Organizational Modes of Severe Wind-producing Convective Systems over North China

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