A comparison of statistical methods for benchmarking the threshold of daily precipitation extremes in the Shanghai metropolitan area during 1981–2010
Abstract The Shanghai metropolitan area is physically and socio-economically vulnerable to extreme precipitation events and associated flooding due to its location on the Yangtze estuary, low topography and high density of human activity. This paper presents a statistical analysis for the threshold...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Yin, Jie [verfasserIn] Zhang, Qi [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2014 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Theoretical and applied climatology - Wien [u.a.] : Springer, 1948, 120(2014), 3-4 vom: 18. Juni, Seite 601-607 |
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| Übergeordnetes Werk: |
volume:120 ; year:2014 ; number:3-4 ; day:18 ; month:06 ; pages:601-607 |
| Links: |
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| DOI / URN: |
10.1007/s00704-014-1199-7 |
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| Katalog-ID: |
SPR007335369 |
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| 245 | 1 | 2 | |a A comparison of statistical methods for benchmarking the threshold of daily precipitation extremes in the Shanghai metropolitan area during 1981–2010 |
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| 520 | |a Abstract The Shanghai metropolitan area is physically and socio-economically vulnerable to extreme precipitation events and associated flooding due to its location on the Yangtze estuary, low topography and high density of human activity. This paper presents a statistical analysis for the threshold of daily precipitation extremes at the city scale using percentile indices, probability distribution and detrended fluctuation analysis (DFA). A comparison of the statistical results with consideration of local impact factors suggests that the threshold of daily precipitation extremes over Shanghai increases from 70 mm in the western region to 80 mm in the city centre and then decreases to 75 mm in coastal areas. Finally, further suggestions are presented for decision makers, researchers and other concerned stakeholders to give a more complete picture of urban climatic extremes. | ||
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| 650 | 4 | |a Detrended Fluctuation Analysis |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Extreme Precipitation Event |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Zhang, Qi |e verfasserin |4 aut | |
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10.1007/s00704-014-1199-7 doi (DE-627)SPR007335369 (SPR)s00704-014-1199-7-e DE-627 ger DE-627 rakwb eng 550 ASE 38.82 bkl Yin, Jie verfasserin aut A comparison of statistical methods for benchmarking the threshold of daily precipitation extremes in the Shanghai metropolitan area during 1981–2010 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The Shanghai metropolitan area is physically and socio-economically vulnerable to extreme precipitation events and associated flooding due to its location on the Yangtze estuary, low topography and high density of human activity. This paper presents a statistical analysis for the threshold of daily precipitation extremes at the city scale using percentile indices, probability distribution and detrended fluctuation analysis (DFA). A comparison of the statistical results with consideration of local impact factors suggests that the threshold of daily precipitation extremes over Shanghai increases from 70 mm in the western region to 80 mm in the city centre and then decreases to 75 mm in coastal areas. Finally, further suggestions are presented for decision makers, researchers and other concerned stakeholders to give a more complete picture of urban climatic extremes. Return Period (dpeaa)DE-He213 Daily Precipitation (dpeaa)DE-He213 Precipitation Extreme (dpeaa)DE-He213 Detrended Fluctuation Analysis (dpeaa)DE-He213 Extreme Precipitation Event (dpeaa)DE-He213 Zhang, Qi verfasserin aut Enthalten in Theoretical and applied climatology Wien [u.a.] : Springer, 1948 120(2014), 3-4 vom: 18. Juni, Seite 601-607 (DE-627)25490968X (DE-600)1463177-5 1434-4483 nnns volume:120 year:2014 number:3-4 day:18 month:06 pages:601-607 https://dx.doi.org/10.1007/s00704-014-1199-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GEO 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_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_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 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_2056 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_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.82 ASE AR 120 2014 3-4 18 06 601-607 |
| spelling |
10.1007/s00704-014-1199-7 doi (DE-627)SPR007335369 (SPR)s00704-014-1199-7-e DE-627 ger DE-627 rakwb eng 550 ASE 38.82 bkl Yin, Jie verfasserin aut A comparison of statistical methods for benchmarking the threshold of daily precipitation extremes in the Shanghai metropolitan area during 1981–2010 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The Shanghai metropolitan area is physically and socio-economically vulnerable to extreme precipitation events and associated flooding due to its location on the Yangtze estuary, low topography and high density of human activity. This paper presents a statistical analysis for the threshold of daily precipitation extremes at the city scale using percentile indices, probability distribution and detrended fluctuation analysis (DFA). A comparison of the statistical results with consideration of local impact factors suggests that the threshold of daily precipitation extremes over Shanghai increases from 70 mm in the western region to 80 mm in the city centre and then decreases to 75 mm in coastal areas. Finally, further suggestions are presented for decision makers, researchers and other concerned stakeholders to give a more complete picture of urban climatic extremes. Return Period (dpeaa)DE-He213 Daily Precipitation (dpeaa)DE-He213 Precipitation Extreme (dpeaa)DE-He213 Detrended Fluctuation Analysis (dpeaa)DE-He213 Extreme Precipitation Event (dpeaa)DE-He213 Zhang, Qi verfasserin aut Enthalten in Theoretical and applied climatology Wien [u.a.] : Springer, 1948 120(2014), 3-4 vom: 18. Juni, Seite 601-607 (DE-627)25490968X (DE-600)1463177-5 1434-4483 nnns volume:120 year:2014 number:3-4 day:18 month:06 pages:601-607 https://dx.doi.org/10.1007/s00704-014-1199-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GEO 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_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_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 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_2056 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_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.82 ASE AR 120 2014 3-4 18 06 601-607 |
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10.1007/s00704-014-1199-7 doi (DE-627)SPR007335369 (SPR)s00704-014-1199-7-e DE-627 ger DE-627 rakwb eng 550 ASE 38.82 bkl Yin, Jie verfasserin aut A comparison of statistical methods for benchmarking the threshold of daily precipitation extremes in the Shanghai metropolitan area during 1981–2010 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The Shanghai metropolitan area is physically and socio-economically vulnerable to extreme precipitation events and associated flooding due to its location on the Yangtze estuary, low topography and high density of human activity. This paper presents a statistical analysis for the threshold of daily precipitation extremes at the city scale using percentile indices, probability distribution and detrended fluctuation analysis (DFA). A comparison of the statistical results with consideration of local impact factors suggests that the threshold of daily precipitation extremes over Shanghai increases from 70 mm in the western region to 80 mm in the city centre and then decreases to 75 mm in coastal areas. Finally, further suggestions are presented for decision makers, researchers and other concerned stakeholders to give a more complete picture of urban climatic extremes. Return Period (dpeaa)DE-He213 Daily Precipitation (dpeaa)DE-He213 Precipitation Extreme (dpeaa)DE-He213 Detrended Fluctuation Analysis (dpeaa)DE-He213 Extreme Precipitation Event (dpeaa)DE-He213 Zhang, Qi verfasserin aut Enthalten in Theoretical and applied climatology Wien [u.a.] : Springer, 1948 120(2014), 3-4 vom: 18. Juni, Seite 601-607 (DE-627)25490968X (DE-600)1463177-5 1434-4483 nnns volume:120 year:2014 number:3-4 day:18 month:06 pages:601-607 https://dx.doi.org/10.1007/s00704-014-1199-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GEO 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_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_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 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_2056 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_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.82 ASE AR 120 2014 3-4 18 06 601-607 |
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10.1007/s00704-014-1199-7 doi (DE-627)SPR007335369 (SPR)s00704-014-1199-7-e DE-627 ger DE-627 rakwb eng 550 ASE 38.82 bkl Yin, Jie verfasserin aut A comparison of statistical methods for benchmarking the threshold of daily precipitation extremes in the Shanghai metropolitan area during 1981–2010 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The Shanghai metropolitan area is physically and socio-economically vulnerable to extreme precipitation events and associated flooding due to its location on the Yangtze estuary, low topography and high density of human activity. This paper presents a statistical analysis for the threshold of daily precipitation extremes at the city scale using percentile indices, probability distribution and detrended fluctuation analysis (DFA). A comparison of the statistical results with consideration of local impact factors suggests that the threshold of daily precipitation extremes over Shanghai increases from 70 mm in the western region to 80 mm in the city centre and then decreases to 75 mm in coastal areas. Finally, further suggestions are presented for decision makers, researchers and other concerned stakeholders to give a more complete picture of urban climatic extremes. Return Period (dpeaa)DE-He213 Daily Precipitation (dpeaa)DE-He213 Precipitation Extreme (dpeaa)DE-He213 Detrended Fluctuation Analysis (dpeaa)DE-He213 Extreme Precipitation Event (dpeaa)DE-He213 Zhang, Qi verfasserin aut Enthalten in Theoretical and applied climatology Wien [u.a.] : Springer, 1948 120(2014), 3-4 vom: 18. Juni, Seite 601-607 (DE-627)25490968X (DE-600)1463177-5 1434-4483 nnns volume:120 year:2014 number:3-4 day:18 month:06 pages:601-607 https://dx.doi.org/10.1007/s00704-014-1199-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GEO 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_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_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 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_2056 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_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.82 ASE AR 120 2014 3-4 18 06 601-607 |
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10.1007/s00704-014-1199-7 doi (DE-627)SPR007335369 (SPR)s00704-014-1199-7-e DE-627 ger DE-627 rakwb eng 550 ASE 38.82 bkl Yin, Jie verfasserin aut A comparison of statistical methods for benchmarking the threshold of daily precipitation extremes in the Shanghai metropolitan area during 1981–2010 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The Shanghai metropolitan area is physically and socio-economically vulnerable to extreme precipitation events and associated flooding due to its location on the Yangtze estuary, low topography and high density of human activity. This paper presents a statistical analysis for the threshold of daily precipitation extremes at the city scale using percentile indices, probability distribution and detrended fluctuation analysis (DFA). A comparison of the statistical results with consideration of local impact factors suggests that the threshold of daily precipitation extremes over Shanghai increases from 70 mm in the western region to 80 mm in the city centre and then decreases to 75 mm in coastal areas. Finally, further suggestions are presented for decision makers, researchers and other concerned stakeholders to give a more complete picture of urban climatic extremes. Return Period (dpeaa)DE-He213 Daily Precipitation (dpeaa)DE-He213 Precipitation Extreme (dpeaa)DE-He213 Detrended Fluctuation Analysis (dpeaa)DE-He213 Extreme Precipitation Event (dpeaa)DE-He213 Zhang, Qi verfasserin aut Enthalten in Theoretical and applied climatology Wien [u.a.] : Springer, 1948 120(2014), 3-4 vom: 18. Juni, Seite 601-607 (DE-627)25490968X (DE-600)1463177-5 1434-4483 nnns volume:120 year:2014 number:3-4 day:18 month:06 pages:601-607 https://dx.doi.org/10.1007/s00704-014-1199-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GEO 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_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_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 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_2056 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_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.82 ASE AR 120 2014 3-4 18 06 601-607 |
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Enthalten in Theoretical and applied climatology 120(2014), 3-4 vom: 18. Juni, Seite 601-607 volume:120 year:2014 number:3-4 day:18 month:06 pages:601-607 |
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Theoretical and applied climatology |
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Yin, Jie @@aut@@ Zhang, Qi @@aut@@ |
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Yin, Jie |
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Yin, Jie ddc 550 bkl 38.82 misc Return Period misc Daily Precipitation misc Precipitation Extreme misc Detrended Fluctuation Analysis misc Extreme Precipitation Event A comparison of statistical methods for benchmarking the threshold of daily precipitation extremes in the Shanghai metropolitan area during 1981–2010 |
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550 ASE 38.82 bkl A comparison of statistical methods for benchmarking the threshold of daily precipitation extremes in the Shanghai metropolitan area during 1981–2010 Return Period (dpeaa)DE-He213 Daily Precipitation (dpeaa)DE-He213 Precipitation Extreme (dpeaa)DE-He213 Detrended Fluctuation Analysis (dpeaa)DE-He213 Extreme Precipitation Event (dpeaa)DE-He213 |
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A comparison of statistical methods for benchmarking the threshold of daily precipitation extremes in the Shanghai metropolitan area during 1981–2010 |
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comparison of statistical methods for benchmarking the threshold of daily precipitation extremes in the shanghai metropolitan area during 1981–2010 |
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A comparison of statistical methods for benchmarking the threshold of daily precipitation extremes in the Shanghai metropolitan area during 1981–2010 |
| abstract |
Abstract The Shanghai metropolitan area is physically and socio-economically vulnerable to extreme precipitation events and associated flooding due to its location on the Yangtze estuary, low topography and high density of human activity. This paper presents a statistical analysis for the threshold of daily precipitation extremes at the city scale using percentile indices, probability distribution and detrended fluctuation analysis (DFA). A comparison of the statistical results with consideration of local impact factors suggests that the threshold of daily precipitation extremes over Shanghai increases from 70 mm in the western region to 80 mm in the city centre and then decreases to 75 mm in coastal areas. Finally, further suggestions are presented for decision makers, researchers and other concerned stakeholders to give a more complete picture of urban climatic extremes. |
| abstractGer |
Abstract The Shanghai metropolitan area is physically and socio-economically vulnerable to extreme precipitation events and associated flooding due to its location on the Yangtze estuary, low topography and high density of human activity. This paper presents a statistical analysis for the threshold of daily precipitation extremes at the city scale using percentile indices, probability distribution and detrended fluctuation analysis (DFA). A comparison of the statistical results with consideration of local impact factors suggests that the threshold of daily precipitation extremes over Shanghai increases from 70 mm in the western region to 80 mm in the city centre and then decreases to 75 mm in coastal areas. Finally, further suggestions are presented for decision makers, researchers and other concerned stakeholders to give a more complete picture of urban climatic extremes. |
| abstract_unstemmed |
Abstract The Shanghai metropolitan area is physically and socio-economically vulnerable to extreme precipitation events and associated flooding due to its location on the Yangtze estuary, low topography and high density of human activity. This paper presents a statistical analysis for the threshold of daily precipitation extremes at the city scale using percentile indices, probability distribution and detrended fluctuation analysis (DFA). A comparison of the statistical results with consideration of local impact factors suggests that the threshold of daily precipitation extremes over Shanghai increases from 70 mm in the western region to 80 mm in the city centre and then decreases to 75 mm in coastal areas. Finally, further suggestions are presented for decision makers, researchers and other concerned stakeholders to give a more complete picture of urban climatic extremes. |
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3-4 |
| title_short |
A comparison of statistical methods for benchmarking the threshold of daily precipitation extremes in the Shanghai metropolitan area during 1981–2010 |
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https://dx.doi.org/10.1007/s00704-014-1199-7 |
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| author2 |
Zhang, Qi |
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Zhang, Qi |
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| doi_str |
10.1007/s00704-014-1199-7 |
| up_date |
2024-07-04T02:52:26.681Z |
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| score |
7.3992023 |