Relating ocean-atmospheric climate indices with Australian river streamflow

The relationship between climate indices with Australian river streamflow (ASF) may provide valuable information for long-lead streamflow forecasting for Australian rivers. The current study examines the correlations between three climate indices (SST, 500 mb meridional wind -U500 and 500 mb geopote...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Shams, Md Shamim [verfasserIn] Faisal Anwar, A.H.M. [verfasserIn] Lamb, Kenneth W. [verfasserIn] Bari, Mohammed [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2017

Schlagwörter:	Climate indices Australian streamflow (ASF) Singular Value Decomposition (SVD) Teleconnection Correlation

Übergeordnetes Werk:	Enthalten in: Journal of hydrology - Amsterdam [u.a.] : Elsevier, 1963, 556, Seite 294-309
Übergeordnetes Werk:	volume:556 ; pages:294-309

DOI / URN:	10.1016/j.jhydrol.2017.11.017

Katalog-ID:	ELV000649279

Internformat


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100	1		\|a Shams, Md Shamim \|e verfasserin \|0 (orcid)0000-0002-0681-1467 \|4 aut
245	1	0	\|a Relating ocean-atmospheric climate indices with Australian river streamflow
264		1	\|c 2017
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520			\|a The relationship between climate indices with Australian river streamflow (ASF) may provide valuable information for long-lead streamflow forecasting for Australian rivers. The current study examines the correlations between three climate indices (SST, 500 mb meridional wind -U500 and 500 mb geopotential height-Z500) and 135 unimpaired ASF gauges for 1971–2011 using the singular value decomposition (SVD) method. First, SVD method was applied to check the SST-ASF correlated regions of influence and then extended SST-ASF variabilities were used to determine the correlated regions within Z500 and U500 fields. Based on the teleconnection, the most correlated region (150°E to 105°W and 35°S to 5°N) was identified and its persistency was checked by lag analysis up to 2 years from seasonal to yearly time-scale. The results displayed positive correlation for the south and south-eastern part of Australia while negative correlation prevails in the north-eastern region (at 95% significance level). The most correlated region was found situated along the South Pacific Convergence Zone (SPCZ) axis which may be considered as a probable climate driver for ASF. The persistency of this region was checked by a separate climate indicator (mean vertical velocity-500 mb) and found prominent in dry period than the wet period. This persistent teleconnected region may be potentially useful for long-lead forecasting of ASF.
650		4	\|a Climate indices
650		4	\|a Australian streamflow (ASF)
650		4	\|a Singular Value Decomposition (SVD)
650		4	\|a Teleconnection
650		4	\|a Correlation
700	1		\|a Faisal Anwar, A.H.M. \|e verfasserin \|4 aut
700	1		\|a Lamb, Kenneth W. \|e verfasserin \|4 aut
700	1		\|a Bari, Mohammed \|e verfasserin \|4 aut
773	0	8	\|i Enthalten in \|t Journal of hydrology \|d Amsterdam [u.a.] : Elsevier, 1963 \|g 556, Seite 294-309 \|h Online-Ressource \|w (DE-627)268761817 \|w (DE-600)1473173-3 \|w (DE-576)077610628 \|x 1879-2707 \|7 nnns
773	1	8	\|g volume:556 \|g pages:294-309
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912			\|a GBV_ILN_65
912			\|a GBV_ILN_69
912			\|a GBV_ILN_70
912			\|a GBV_ILN_73
912			\|a GBV_ILN_74
912			\|a GBV_ILN_90
912			\|a GBV_ILN_95
912			\|a GBV_ILN_100
912			\|a GBV_ILN_105
912			\|a GBV_ILN_110
912			\|a GBV_ILN_150
912			\|a GBV_ILN_151
912			\|a GBV_ILN_187
912			\|a GBV_ILN_224
912			\|a GBV_ILN_370
912			\|a GBV_ILN_381
912			\|a GBV_ILN_602
912			\|a GBV_ILN_702
912			\|a GBV_ILN_2001
912			\|a GBV_ILN_2003
912			\|a GBV_ILN_2004
912			\|a GBV_ILN_2005
912			\|a GBV_ILN_2007
912			\|a GBV_ILN_2009
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912			\|a GBV_ILN_2014
912			\|a GBV_ILN_2015
912			\|a GBV_ILN_2020
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912			\|a GBV_ILN_2038
912			\|a GBV_ILN_2039
912			\|a GBV_ILN_2044
912			\|a GBV_ILN_2048
912			\|a GBV_ILN_2049
912			\|a GBV_ILN_2050
912			\|a GBV_ILN_2055
912			\|a GBV_ILN_2056
912			\|a GBV_ILN_2059
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912			\|a GBV_ILN_2152
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912			\|a GBV_ILN_2232
912			\|a GBV_ILN_2336
912			\|a GBV_ILN_2360
912			\|a GBV_ILN_2507
912			\|a GBV_ILN_2522
912			\|a GBV_ILN_4035
912			\|a GBV_ILN_4037
912			\|a GBV_ILN_4112
912			\|a GBV_ILN_4125
912			\|a GBV_ILN_4126
912			\|a GBV_ILN_4242
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912			\|a GBV_ILN_4313
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912			\|a GBV_ILN_4333
912			\|a GBV_ILN_4334
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936	b	k	\|a 38.85 \|j Hydrologie: Allgemeines
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952			\|d 556 \|h 294-309

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matchkey_str	article:18792707:2017----::eaigcaamshrclmtidcsihuta
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publishDate	2017
allfields	10.1016/j.jhydrol.2017.11.017 doi (DE-627)ELV000649279 (ELSEVIER)S0022-1694(17)30771-0 DE-627 ger DE-627 rda eng 690 DE-600 38.85 bkl Shams, Md Shamim verfasserin (orcid)0000-0002-0681-1467 aut Relating ocean-atmospheric climate indices with Australian river streamflow 2017 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The relationship between climate indices with Australian river streamflow (ASF) may provide valuable information for long-lead streamflow forecasting for Australian rivers. The current study examines the correlations between three climate indices (SST, 500 mb meridional wind -U500 and 500 mb geopotential height-Z500) and 135 unimpaired ASF gauges for 1971–2011 using the singular value decomposition (SVD) method. First, SVD method was applied to check the SST-ASF correlated regions of influence and then extended SST-ASF variabilities were used to determine the correlated regions within Z500 and U500 fields. Based on the teleconnection, the most correlated region (150°E to 105°W and 35°S to 5°N) was identified and its persistency was checked by lag analysis up to 2 years from seasonal to yearly time-scale. The results displayed positive correlation for the south and south-eastern part of Australia while negative correlation prevails in the north-eastern region (at 95% significance level). The most correlated region was found situated along the South Pacific Convergence Zone (SPCZ) axis which may be considered as a probable climate driver for ASF. The persistency of this region was checked by a separate climate indicator (mean vertical velocity-500 mb) and found prominent in dry period than the wet period. This persistent teleconnected region may be potentially useful for long-lead forecasting of ASF. Climate indices Australian streamflow (ASF) Singular Value Decomposition (SVD) Teleconnection Correlation Faisal Anwar, A.H.M. verfasserin aut Lamb, Kenneth W. verfasserin aut Bari, Mohammed verfasserin aut Enthalten in Journal of hydrology Amsterdam [u.a.] : Elsevier, 1963 556, Seite 294-309 Online-Ressource (DE-627)268761817 (DE-600)1473173-3 (DE-576)077610628 1879-2707 nnns volume:556 pages:294-309 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_224 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2009 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_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2098 GBV_ILN_2106 GBV_ILN_2108 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_2360 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 38.85 Hydrologie: Allgemeines AR 556 294-309
spelling	10.1016/j.jhydrol.2017.11.017 doi (DE-627)ELV000649279 (ELSEVIER)S0022-1694(17)30771-0 DE-627 ger DE-627 rda eng 690 DE-600 38.85 bkl Shams, Md Shamim verfasserin (orcid)0000-0002-0681-1467 aut Relating ocean-atmospheric climate indices with Australian river streamflow 2017 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The relationship between climate indices with Australian river streamflow (ASF) may provide valuable information for long-lead streamflow forecasting for Australian rivers. The current study examines the correlations between three climate indices (SST, 500 mb meridional wind -U500 and 500 mb geopotential height-Z500) and 135 unimpaired ASF gauges for 1971–2011 using the singular value decomposition (SVD) method. First, SVD method was applied to check the SST-ASF correlated regions of influence and then extended SST-ASF variabilities were used to determine the correlated regions within Z500 and U500 fields. Based on the teleconnection, the most correlated region (150°E to 105°W and 35°S to 5°N) was identified and its persistency was checked by lag analysis up to 2 years from seasonal to yearly time-scale. The results displayed positive correlation for the south and south-eastern part of Australia while negative correlation prevails in the north-eastern region (at 95% significance level). The most correlated region was found situated along the South Pacific Convergence Zone (SPCZ) axis which may be considered as a probable climate driver for ASF. The persistency of this region was checked by a separate climate indicator (mean vertical velocity-500 mb) and found prominent in dry period than the wet period. This persistent teleconnected region may be potentially useful for long-lead forecasting of ASF. Climate indices Australian streamflow (ASF) Singular Value Decomposition (SVD) Teleconnection Correlation Faisal Anwar, A.H.M. verfasserin aut Lamb, Kenneth W. verfasserin aut Bari, Mohammed verfasserin aut Enthalten in Journal of hydrology Amsterdam [u.a.] : Elsevier, 1963 556, Seite 294-309 Online-Ressource (DE-627)268761817 (DE-600)1473173-3 (DE-576)077610628 1879-2707 nnns volume:556 pages:294-309 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_224 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2009 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_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2098 GBV_ILN_2106 GBV_ILN_2108 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_2360 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 38.85 Hydrologie: Allgemeines AR 556 294-309
allfields_unstemmed	10.1016/j.jhydrol.2017.11.017 doi (DE-627)ELV000649279 (ELSEVIER)S0022-1694(17)30771-0 DE-627 ger DE-627 rda eng 690 DE-600 38.85 bkl Shams, Md Shamim verfasserin (orcid)0000-0002-0681-1467 aut Relating ocean-atmospheric climate indices with Australian river streamflow 2017 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The relationship between climate indices with Australian river streamflow (ASF) may provide valuable information for long-lead streamflow forecasting for Australian rivers. The current study examines the correlations between three climate indices (SST, 500 mb meridional wind -U500 and 500 mb geopotential height-Z500) and 135 unimpaired ASF gauges for 1971–2011 using the singular value decomposition (SVD) method. First, SVD method was applied to check the SST-ASF correlated regions of influence and then extended SST-ASF variabilities were used to determine the correlated regions within Z500 and U500 fields. Based on the teleconnection, the most correlated region (150°E to 105°W and 35°S to 5°N) was identified and its persistency was checked by lag analysis up to 2 years from seasonal to yearly time-scale. The results displayed positive correlation for the south and south-eastern part of Australia while negative correlation prevails in the north-eastern region (at 95% significance level). The most correlated region was found situated along the South Pacific Convergence Zone (SPCZ) axis which may be considered as a probable climate driver for ASF. The persistency of this region was checked by a separate climate indicator (mean vertical velocity-500 mb) and found prominent in dry period than the wet period. This persistent teleconnected region may be potentially useful for long-lead forecasting of ASF. Climate indices Australian streamflow (ASF) Singular Value Decomposition (SVD) Teleconnection Correlation Faisal Anwar, A.H.M. verfasserin aut Lamb, Kenneth W. verfasserin aut Bari, Mohammed verfasserin aut Enthalten in Journal of hydrology Amsterdam [u.a.] : Elsevier, 1963 556, Seite 294-309 Online-Ressource (DE-627)268761817 (DE-600)1473173-3 (DE-576)077610628 1879-2707 nnns volume:556 pages:294-309 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_224 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2009 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_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2098 GBV_ILN_2106 GBV_ILN_2108 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_2360 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 38.85 Hydrologie: Allgemeines AR 556 294-309
allfieldsGer	10.1016/j.jhydrol.2017.11.017 doi (DE-627)ELV000649279 (ELSEVIER)S0022-1694(17)30771-0 DE-627 ger DE-627 rda eng 690 DE-600 38.85 bkl Shams, Md Shamim verfasserin (orcid)0000-0002-0681-1467 aut Relating ocean-atmospheric climate indices with Australian river streamflow 2017 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The relationship between climate indices with Australian river streamflow (ASF) may provide valuable information for long-lead streamflow forecasting for Australian rivers. The current study examines the correlations between three climate indices (SST, 500 mb meridional wind -U500 and 500 mb geopotential height-Z500) and 135 unimpaired ASF gauges for 1971–2011 using the singular value decomposition (SVD) method. First, SVD method was applied to check the SST-ASF correlated regions of influence and then extended SST-ASF variabilities were used to determine the correlated regions within Z500 and U500 fields. Based on the teleconnection, the most correlated region (150°E to 105°W and 35°S to 5°N) was identified and its persistency was checked by lag analysis up to 2 years from seasonal to yearly time-scale. The results displayed positive correlation for the south and south-eastern part of Australia while negative correlation prevails in the north-eastern region (at 95% significance level). The most correlated region was found situated along the South Pacific Convergence Zone (SPCZ) axis which may be considered as a probable climate driver for ASF. The persistency of this region was checked by a separate climate indicator (mean vertical velocity-500 mb) and found prominent in dry period than the wet period. This persistent teleconnected region may be potentially useful for long-lead forecasting of ASF. Climate indices Australian streamflow (ASF) Singular Value Decomposition (SVD) Teleconnection Correlation Faisal Anwar, A.H.M. verfasserin aut Lamb, Kenneth W. verfasserin aut Bari, Mohammed verfasserin aut Enthalten in Journal of hydrology Amsterdam [u.a.] : Elsevier, 1963 556, Seite 294-309 Online-Ressource (DE-627)268761817 (DE-600)1473173-3 (DE-576)077610628 1879-2707 nnns volume:556 pages:294-309 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_224 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2009 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_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2098 GBV_ILN_2106 GBV_ILN_2108 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_2360 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 38.85 Hydrologie: Allgemeines AR 556 294-309
allfieldsSound	10.1016/j.jhydrol.2017.11.017 doi (DE-627)ELV000649279 (ELSEVIER)S0022-1694(17)30771-0 DE-627 ger DE-627 rda eng 690 DE-600 38.85 bkl Shams, Md Shamim verfasserin (orcid)0000-0002-0681-1467 aut Relating ocean-atmospheric climate indices with Australian river streamflow 2017 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The relationship between climate indices with Australian river streamflow (ASF) may provide valuable information for long-lead streamflow forecasting for Australian rivers. The current study examines the correlations between three climate indices (SST, 500 mb meridional wind -U500 and 500 mb geopotential height-Z500) and 135 unimpaired ASF gauges for 1971–2011 using the singular value decomposition (SVD) method. First, SVD method was applied to check the SST-ASF correlated regions of influence and then extended SST-ASF variabilities were used to determine the correlated regions within Z500 and U500 fields. Based on the teleconnection, the most correlated region (150°E to 105°W and 35°S to 5°N) was identified and its persistency was checked by lag analysis up to 2 years from seasonal to yearly time-scale. The results displayed positive correlation for the south and south-eastern part of Australia while negative correlation prevails in the north-eastern region (at 95% significance level). The most correlated region was found situated along the South Pacific Convergence Zone (SPCZ) axis which may be considered as a probable climate driver for ASF. The persistency of this region was checked by a separate climate indicator (mean vertical velocity-500 mb) and found prominent in dry period than the wet period. This persistent teleconnected region may be potentially useful for long-lead forecasting of ASF. Climate indices Australian streamflow (ASF) Singular Value Decomposition (SVD) Teleconnection Correlation Faisal Anwar, A.H.M. verfasserin aut Lamb, Kenneth W. verfasserin aut Bari, Mohammed verfasserin aut Enthalten in Journal of hydrology Amsterdam [u.a.] : Elsevier, 1963 556, Seite 294-309 Online-Ressource (DE-627)268761817 (DE-600)1473173-3 (DE-576)077610628 1879-2707 nnns volume:556 pages:294-309 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_224 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2009 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_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2098 GBV_ILN_2106 GBV_ILN_2108 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_2360 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 38.85 Hydrologie: Allgemeines AR 556 294-309
language	English
source	Enthalten in Journal of hydrology 556, Seite 294-309 volume:556 pages:294-309
sourceStr	Enthalten in Journal of hydrology 556, Seite 294-309 volume:556 pages:294-309
format_phy_str_mv	Article
bklname	Hydrologie: Allgemeines
institution	findex.gbv.de
topic_facet	Climate indices Australian streamflow (ASF) Singular Value Decomposition (SVD) Teleconnection Correlation
dewey-raw	690
isfreeaccess_bool	false
container_title	Journal of hydrology
authorswithroles_txt_mv	Shams, Md Shamim @@aut@@ Faisal Anwar, A.H.M. @@aut@@ Lamb, Kenneth W. @@aut@@ Bari, Mohammed @@aut@@
publishDateDaySort_date	2017-01-01T00:00:00Z
hierarchy_top_id	268761817
dewey-sort	3690
id	ELV000649279
language_de	englisch
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author	Shams, Md Shamim
spellingShingle	Shams, Md Shamim ddc 690 bkl 38.85 misc Climate indices misc Australian streamflow (ASF) misc Singular Value Decomposition (SVD) misc Teleconnection misc Correlation Relating ocean-atmospheric climate indices with Australian river streamflow
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topic_title	690 DE-600 38.85 bkl Relating ocean-atmospheric climate indices with Australian river streamflow Climate indices Australian streamflow (ASF) Singular Value Decomposition (SVD) Teleconnection Correlation
topic	ddc 690 bkl 38.85 misc Climate indices misc Australian streamflow (ASF) misc Singular Value Decomposition (SVD) misc Teleconnection misc Correlation
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title	Relating ocean-atmospheric climate indices with Australian river streamflow
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title_full	Relating ocean-atmospheric climate indices with Australian river streamflow
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title_sort	relating ocean-atmospheric climate indices with australian river streamflow
title_auth	Relating ocean-atmospheric climate indices with Australian river streamflow
abstract	The relationship between climate indices with Australian river streamflow (ASF) may provide valuable information for long-lead streamflow forecasting for Australian rivers. The current study examines the correlations between three climate indices (SST, 500 mb meridional wind -U500 and 500 mb geopotential height-Z500) and 135 unimpaired ASF gauges for 1971–2011 using the singular value decomposition (SVD) method. First, SVD method was applied to check the SST-ASF correlated regions of influence and then extended SST-ASF variabilities were used to determine the correlated regions within Z500 and U500 fields. Based on the teleconnection, the most correlated region (150°E to 105°W and 35°S to 5°N) was identified and its persistency was checked by lag analysis up to 2 years from seasonal to yearly time-scale. The results displayed positive correlation for the south and south-eastern part of Australia while negative correlation prevails in the north-eastern region (at 95% significance level). The most correlated region was found situated along the South Pacific Convergence Zone (SPCZ) axis which may be considered as a probable climate driver for ASF. The persistency of this region was checked by a separate climate indicator (mean vertical velocity-500 mb) and found prominent in dry period than the wet period. This persistent teleconnected region may be potentially useful for long-lead forecasting of ASF.
abstractGer	The relationship between climate indices with Australian river streamflow (ASF) may provide valuable information for long-lead streamflow forecasting for Australian rivers. The current study examines the correlations between three climate indices (SST, 500 mb meridional wind -U500 and 500 mb geopotential height-Z500) and 135 unimpaired ASF gauges for 1971–2011 using the singular value decomposition (SVD) method. First, SVD method was applied to check the SST-ASF correlated regions of influence and then extended SST-ASF variabilities were used to determine the correlated regions within Z500 and U500 fields. Based on the teleconnection, the most correlated region (150°E to 105°W and 35°S to 5°N) was identified and its persistency was checked by lag analysis up to 2 years from seasonal to yearly time-scale. The results displayed positive correlation for the south and south-eastern part of Australia while negative correlation prevails in the north-eastern region (at 95% significance level). The most correlated region was found situated along the South Pacific Convergence Zone (SPCZ) axis which may be considered as a probable climate driver for ASF. The persistency of this region was checked by a separate climate indicator (mean vertical velocity-500 mb) and found prominent in dry period than the wet period. This persistent teleconnected region may be potentially useful for long-lead forecasting of ASF.
abstract_unstemmed	The relationship between climate indices with Australian river streamflow (ASF) may provide valuable information for long-lead streamflow forecasting for Australian rivers. The current study examines the correlations between three climate indices (SST, 500 mb meridional wind -U500 and 500 mb geopotential height-Z500) and 135 unimpaired ASF gauges for 1971–2011 using the singular value decomposition (SVD) method. First, SVD method was applied to check the SST-ASF correlated regions of influence and then extended SST-ASF variabilities were used to determine the correlated regions within Z500 and U500 fields. Based on the teleconnection, the most correlated region (150°E to 105°W and 35°S to 5°N) was identified and its persistency was checked by lag analysis up to 2 years from seasonal to yearly time-scale. The results displayed positive correlation for the south and south-eastern part of Australia while negative correlation prevails in the north-eastern region (at 95% significance level). The most correlated region was found situated along the South Pacific Convergence Zone (SPCZ) axis which may be considered as a probable climate driver for ASF. The persistency of this region was checked by a separate climate indicator (mean vertical velocity-500 mb) and found prominent in dry period than the wet period. This persistent teleconnected region may be potentially useful for long-lead forecasting of ASF.
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title_short	Relating ocean-atmospheric climate indices with Australian river streamflow
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up_date	2024-07-06T18:41:40.689Z
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The current study examines the correlations between three climate indices (SST, 500 mb meridional wind -U500 and 500 mb geopotential height-Z500) and 135 unimpaired ASF gauges for 1971–2011 using the singular value decomposition (SVD) method. First, SVD method was applied to check the SST-ASF correlated regions of influence and then extended SST-ASF variabilities were used to determine the correlated regions within Z500 and U500 fields. Based on the teleconnection, the most correlated region (150°E to 105°W and 35°S to 5°N) was identified and its persistency was checked by lag analysis up to 2 years from seasonal to yearly time-scale. The results displayed positive correlation for the south and south-eastern part of Australia while negative correlation prevails in the north-eastern region (at 95% significance level). The most correlated region was found situated along the South Pacific Convergence Zone (SPCZ) axis which may be considered as a probable climate driver for ASF. The persistency of this region was checked by a separate climate indicator (mean vertical velocity-500 mb) and found prominent in dry period than the wet period. 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Relating ocean-atmospheric climate indices with Australian river streamflow

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