Seasonal predictable signals of east Asian summer monsoon rainfall in existing monsoon indices
Abstract East Asian summer monsoon indices (EASMIs) have been widely used to investigate the variability and predictability of the East Asian summer monsoon rainfall (EASMR). However, the ability of existing EASMIs remains unclear to represent the interannual variability of the EASMR in predictable...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Ying, Kairan [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2023 |
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| Anmerkung: |
© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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| Übergeordnetes Werk: |
Enthalten in: Climate dynamics - Berlin : Springer, 1986, 61(2023), 11-12 vom: 16. Juni, Seite 4927-4947 |
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| Übergeordnetes Werk: |
volume:61 ; year:2023 ; number:11-12 ; day:16 ; month:06 ; pages:4927-4947 |
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| DOI / URN: |
10.1007/s00382-023-06827-2 |
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SPR053650360 |
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| 520 | |a Abstract East Asian summer monsoon indices (EASMIs) have been widely used to investigate the variability and predictability of the East Asian summer monsoon rainfall (EASMR). However, the ability of existing EASMIs remains unclear to represent the interannual variability of the EASMR in predictable (P-) and unpredictable (U-) components. Based on a (co-)variance decomposition method, the fractional variance explained by a single EASMI has the highest value of 22% in both P- and U-components. A set of the best three EASMIs, together with the linear trend, is linearly independent of each other and can explain a large percentage of EASMR variance in P-component (54%). This set of EASMIs captures the main predictive circulation features in the corresponding EASMR P-modes, i.e., a low-level Philippine Sea (anti-)cyclone and an upper-level zonal wind tripole pattern for P-mode1, an East China Sea (anti-)cyclone for P-mode2, and a west–east pressure dipole pattern for P-mode3. In addition, they also have the major predictable sources from the predictors of their corresponding P-modes, i.e., the decaying and developing El Niño–Southern Oscillation, the spring Arctic Oscillation, the spring sea surface temperatures over the western North Pacific, tropical and southern Atlantic, southern Indian and Arctic oceans. By considering the predictable and unpredictable components, this work not only improves our knowledge of the physical meanings and the potential limitations of the existing EASMIs, but also helps us in selecting the most appropriate EASMIs when focusing on the issue of seasonal forecasting. | ||
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10.1007/s00382-023-06827-2 doi (DE-627)SPR053650360 (SPR)s00382-023-06827-2-e DE-627 ger DE-627 rakwb eng Ying, Kairan verfasserin aut Seasonal predictable signals of east Asian summer monsoon rainfall in existing monsoon indices 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract East Asian summer monsoon indices (EASMIs) have been widely used to investigate the variability and predictability of the East Asian summer monsoon rainfall (EASMR). However, the ability of existing EASMIs remains unclear to represent the interannual variability of the EASMR in predictable (P-) and unpredictable (U-) components. Based on a (co-)variance decomposition method, the fractional variance explained by a single EASMI has the highest value of 22% in both P- and U-components. A set of the best three EASMIs, together with the linear trend, is linearly independent of each other and can explain a large percentage of EASMR variance in P-component (54%). This set of EASMIs captures the main predictive circulation features in the corresponding EASMR P-modes, i.e., a low-level Philippine Sea (anti-)cyclone and an upper-level zonal wind tripole pattern for P-mode1, an East China Sea (anti-)cyclone for P-mode2, and a west–east pressure dipole pattern for P-mode3. In addition, they also have the major predictable sources from the predictors of their corresponding P-modes, i.e., the decaying and developing El Niño–Southern Oscillation, the spring Arctic Oscillation, the spring sea surface temperatures over the western North Pacific, tropical and southern Atlantic, southern Indian and Arctic oceans. By considering the predictable and unpredictable components, this work not only improves our knowledge of the physical meanings and the potential limitations of the existing EASMIs, but also helps us in selecting the most appropriate EASMIs when focusing on the issue of seasonal forecasting. East Asian summer monsoon rainfall (dpeaa)DE-He213 Monsoon index (dpeaa)DE-He213 Predictable (dpeaa)DE-He213 Unpredictable (dpeaa)DE-He213 Jiang, Dabang aut Zheng, Xiaogu aut Frederiksen, Carsten S. aut Deng, Difei aut Enthalten in Climate dynamics Berlin : Springer, 1986 61(2023), 11-12 vom: 16. Juni, Seite 4927-4947 (DE-627)268128561 (DE-600)1471747-5 1432-0894 nnns volume:61 year:2023 number:11-12 day:16 month:06 pages:4927-4947 https://dx.doi.org/10.1007/s00382-023-06827-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_612 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_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_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_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 AR 61 2023 11-12 16 06 4927-4947 |
| spelling |
10.1007/s00382-023-06827-2 doi (DE-627)SPR053650360 (SPR)s00382-023-06827-2-e DE-627 ger DE-627 rakwb eng Ying, Kairan verfasserin aut Seasonal predictable signals of east Asian summer monsoon rainfall in existing monsoon indices 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract East Asian summer monsoon indices (EASMIs) have been widely used to investigate the variability and predictability of the East Asian summer monsoon rainfall (EASMR). However, the ability of existing EASMIs remains unclear to represent the interannual variability of the EASMR in predictable (P-) and unpredictable (U-) components. Based on a (co-)variance decomposition method, the fractional variance explained by a single EASMI has the highest value of 22% in both P- and U-components. A set of the best three EASMIs, together with the linear trend, is linearly independent of each other and can explain a large percentage of EASMR variance in P-component (54%). This set of EASMIs captures the main predictive circulation features in the corresponding EASMR P-modes, i.e., a low-level Philippine Sea (anti-)cyclone and an upper-level zonal wind tripole pattern for P-mode1, an East China Sea (anti-)cyclone for P-mode2, and a west–east pressure dipole pattern for P-mode3. In addition, they also have the major predictable sources from the predictors of their corresponding P-modes, i.e., the decaying and developing El Niño–Southern Oscillation, the spring Arctic Oscillation, the spring sea surface temperatures over the western North Pacific, tropical and southern Atlantic, southern Indian and Arctic oceans. By considering the predictable and unpredictable components, this work not only improves our knowledge of the physical meanings and the potential limitations of the existing EASMIs, but also helps us in selecting the most appropriate EASMIs when focusing on the issue of seasonal forecasting. East Asian summer monsoon rainfall (dpeaa)DE-He213 Monsoon index (dpeaa)DE-He213 Predictable (dpeaa)DE-He213 Unpredictable (dpeaa)DE-He213 Jiang, Dabang aut Zheng, Xiaogu aut Frederiksen, Carsten S. aut Deng, Difei aut Enthalten in Climate dynamics Berlin : Springer, 1986 61(2023), 11-12 vom: 16. Juni, Seite 4927-4947 (DE-627)268128561 (DE-600)1471747-5 1432-0894 nnns volume:61 year:2023 number:11-12 day:16 month:06 pages:4927-4947 https://dx.doi.org/10.1007/s00382-023-06827-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_612 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_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_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_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 AR 61 2023 11-12 16 06 4927-4947 |
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10.1007/s00382-023-06827-2 doi (DE-627)SPR053650360 (SPR)s00382-023-06827-2-e DE-627 ger DE-627 rakwb eng Ying, Kairan verfasserin aut Seasonal predictable signals of east Asian summer monsoon rainfall in existing monsoon indices 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract East Asian summer monsoon indices (EASMIs) have been widely used to investigate the variability and predictability of the East Asian summer monsoon rainfall (EASMR). However, the ability of existing EASMIs remains unclear to represent the interannual variability of the EASMR in predictable (P-) and unpredictable (U-) components. Based on a (co-)variance decomposition method, the fractional variance explained by a single EASMI has the highest value of 22% in both P- and U-components. A set of the best three EASMIs, together with the linear trend, is linearly independent of each other and can explain a large percentage of EASMR variance in P-component (54%). This set of EASMIs captures the main predictive circulation features in the corresponding EASMR P-modes, i.e., a low-level Philippine Sea (anti-)cyclone and an upper-level zonal wind tripole pattern for P-mode1, an East China Sea (anti-)cyclone for P-mode2, and a west–east pressure dipole pattern for P-mode3. In addition, they also have the major predictable sources from the predictors of their corresponding P-modes, i.e., the decaying and developing El Niño–Southern Oscillation, the spring Arctic Oscillation, the spring sea surface temperatures over the western North Pacific, tropical and southern Atlantic, southern Indian and Arctic oceans. By considering the predictable and unpredictable components, this work not only improves our knowledge of the physical meanings and the potential limitations of the existing EASMIs, but also helps us in selecting the most appropriate EASMIs when focusing on the issue of seasonal forecasting. East Asian summer monsoon rainfall (dpeaa)DE-He213 Monsoon index (dpeaa)DE-He213 Predictable (dpeaa)DE-He213 Unpredictable (dpeaa)DE-He213 Jiang, Dabang aut Zheng, Xiaogu aut Frederiksen, Carsten S. aut Deng, Difei aut Enthalten in Climate dynamics Berlin : Springer, 1986 61(2023), 11-12 vom: 16. Juni, Seite 4927-4947 (DE-627)268128561 (DE-600)1471747-5 1432-0894 nnns volume:61 year:2023 number:11-12 day:16 month:06 pages:4927-4947 https://dx.doi.org/10.1007/s00382-023-06827-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_612 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_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_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_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 AR 61 2023 11-12 16 06 4927-4947 |
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10.1007/s00382-023-06827-2 doi (DE-627)SPR053650360 (SPR)s00382-023-06827-2-e DE-627 ger DE-627 rakwb eng Ying, Kairan verfasserin aut Seasonal predictable signals of east Asian summer monsoon rainfall in existing monsoon indices 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract East Asian summer monsoon indices (EASMIs) have been widely used to investigate the variability and predictability of the East Asian summer monsoon rainfall (EASMR). However, the ability of existing EASMIs remains unclear to represent the interannual variability of the EASMR in predictable (P-) and unpredictable (U-) components. Based on a (co-)variance decomposition method, the fractional variance explained by a single EASMI has the highest value of 22% in both P- and U-components. A set of the best three EASMIs, together with the linear trend, is linearly independent of each other and can explain a large percentage of EASMR variance in P-component (54%). This set of EASMIs captures the main predictive circulation features in the corresponding EASMR P-modes, i.e., a low-level Philippine Sea (anti-)cyclone and an upper-level zonal wind tripole pattern for P-mode1, an East China Sea (anti-)cyclone for P-mode2, and a west–east pressure dipole pattern for P-mode3. In addition, they also have the major predictable sources from the predictors of their corresponding P-modes, i.e., the decaying and developing El Niño–Southern Oscillation, the spring Arctic Oscillation, the spring sea surface temperatures over the western North Pacific, tropical and southern Atlantic, southern Indian and Arctic oceans. By considering the predictable and unpredictable components, this work not only improves our knowledge of the physical meanings and the potential limitations of the existing EASMIs, but also helps us in selecting the most appropriate EASMIs when focusing on the issue of seasonal forecasting. East Asian summer monsoon rainfall (dpeaa)DE-He213 Monsoon index (dpeaa)DE-He213 Predictable (dpeaa)DE-He213 Unpredictable (dpeaa)DE-He213 Jiang, Dabang aut Zheng, Xiaogu aut Frederiksen, Carsten S. aut Deng, Difei aut Enthalten in Climate dynamics Berlin : Springer, 1986 61(2023), 11-12 vom: 16. Juni, Seite 4927-4947 (DE-627)268128561 (DE-600)1471747-5 1432-0894 nnns volume:61 year:2023 number:11-12 day:16 month:06 pages:4927-4947 https://dx.doi.org/10.1007/s00382-023-06827-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_612 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_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_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_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 AR 61 2023 11-12 16 06 4927-4947 |
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10.1007/s00382-023-06827-2 doi (DE-627)SPR053650360 (SPR)s00382-023-06827-2-e DE-627 ger DE-627 rakwb eng Ying, Kairan verfasserin aut Seasonal predictable signals of east Asian summer monsoon rainfall in existing monsoon indices 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract East Asian summer monsoon indices (EASMIs) have been widely used to investigate the variability and predictability of the East Asian summer monsoon rainfall (EASMR). However, the ability of existing EASMIs remains unclear to represent the interannual variability of the EASMR in predictable (P-) and unpredictable (U-) components. Based on a (co-)variance decomposition method, the fractional variance explained by a single EASMI has the highest value of 22% in both P- and U-components. A set of the best three EASMIs, together with the linear trend, is linearly independent of each other and can explain a large percentage of EASMR variance in P-component (54%). This set of EASMIs captures the main predictive circulation features in the corresponding EASMR P-modes, i.e., a low-level Philippine Sea (anti-)cyclone and an upper-level zonal wind tripole pattern for P-mode1, an East China Sea (anti-)cyclone for P-mode2, and a west–east pressure dipole pattern for P-mode3. In addition, they also have the major predictable sources from the predictors of their corresponding P-modes, i.e., the decaying and developing El Niño–Southern Oscillation, the spring Arctic Oscillation, the spring sea surface temperatures over the western North Pacific, tropical and southern Atlantic, southern Indian and Arctic oceans. By considering the predictable and unpredictable components, this work not only improves our knowledge of the physical meanings and the potential limitations of the existing EASMIs, but also helps us in selecting the most appropriate EASMIs when focusing on the issue of seasonal forecasting. East Asian summer monsoon rainfall (dpeaa)DE-He213 Monsoon index (dpeaa)DE-He213 Predictable (dpeaa)DE-He213 Unpredictable (dpeaa)DE-He213 Jiang, Dabang aut Zheng, Xiaogu aut Frederiksen, Carsten S. aut Deng, Difei aut Enthalten in Climate dynamics Berlin : Springer, 1986 61(2023), 11-12 vom: 16. Juni, Seite 4927-4947 (DE-627)268128561 (DE-600)1471747-5 1432-0894 nnns volume:61 year:2023 number:11-12 day:16 month:06 pages:4927-4947 https://dx.doi.org/10.1007/s00382-023-06827-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_612 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_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_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_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 AR 61 2023 11-12 16 06 4927-4947 |
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Enthalten in Climate dynamics 61(2023), 11-12 vom: 16. Juni, Seite 4927-4947 volume:61 year:2023 number:11-12 day:16 month:06 pages:4927-4947 |
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Enthalten in Climate dynamics 61(2023), 11-12 vom: 16. Juni, Seite 4927-4947 volume:61 year:2023 number:11-12 day:16 month:06 pages:4927-4947 |
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Ying, Kairan @@aut@@ Jiang, Dabang @@aut@@ Zheng, Xiaogu @@aut@@ Frederiksen, Carsten S. @@aut@@ Deng, Difei @@aut@@ |
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Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract East Asian summer monsoon indices (EASMIs) have been widely used to investigate the variability and predictability of the East Asian summer monsoon rainfall (EASMR). However, the ability of existing EASMIs remains unclear to represent the interannual variability of the EASMR in predictable (P-) and unpredictable (U-) components. Based on a (co-)variance decomposition method, the fractional variance explained by a single EASMI has the highest value of 22% in both P- and U-components. A set of the best three EASMIs, together with the linear trend, is linearly independent of each other and can explain a large percentage of EASMR variance in P-component (54%). This set of EASMIs captures the main predictive circulation features in the corresponding EASMR P-modes, i.e., a low-level Philippine Sea (anti-)cyclone and an upper-level zonal wind tripole pattern for P-mode1, an East China Sea (anti-)cyclone for P-mode2, and a west–east pressure dipole pattern for P-mode3. In addition, they also have the major predictable sources from the predictors of their corresponding P-modes, i.e., the decaying and developing El Niño–Southern Oscillation, the spring Arctic Oscillation, the spring sea surface temperatures over the western North Pacific, tropical and southern Atlantic, southern Indian and Arctic oceans. By considering the predictable and unpredictable components, this work not only improves our knowledge of the physical meanings and the potential limitations of the existing EASMIs, but also helps us in selecting the most appropriate EASMIs when focusing on the issue of seasonal forecasting.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">East Asian summer monsoon rainfall</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Monsoon index</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Predictable</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Unpredictable</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Jiang, Dabang</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Zheng, Xiaogu</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Frederiksen, Carsten S.</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Deng, Difei</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Climate dynamics</subfield><subfield code="d">Berlin : Springer, 1986</subfield><subfield code="g">61(2023), 11-12 vom: 16. 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Ying, Kairan |
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Seasonal predictable signals of east Asian summer monsoon rainfall in existing monsoon indices East Asian summer monsoon rainfall (dpeaa)DE-He213 Monsoon index (dpeaa)DE-He213 Predictable (dpeaa)DE-He213 Unpredictable (dpeaa)DE-He213 |
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Seasonal predictable signals of east Asian summer monsoon rainfall in existing monsoon indices |
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Seasonal predictable signals of east Asian summer monsoon rainfall in existing monsoon indices |
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Ying, Kairan Jiang, Dabang Zheng, Xiaogu Frederiksen, Carsten S. Deng, Difei |
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seasonal predictable signals of east asian summer monsoon rainfall in existing monsoon indices |
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Seasonal predictable signals of east Asian summer monsoon rainfall in existing monsoon indices |
| abstract |
Abstract East Asian summer monsoon indices (EASMIs) have been widely used to investigate the variability and predictability of the East Asian summer monsoon rainfall (EASMR). However, the ability of existing EASMIs remains unclear to represent the interannual variability of the EASMR in predictable (P-) and unpredictable (U-) components. Based on a (co-)variance decomposition method, the fractional variance explained by a single EASMI has the highest value of 22% in both P- and U-components. A set of the best three EASMIs, together with the linear trend, is linearly independent of each other and can explain a large percentage of EASMR variance in P-component (54%). This set of EASMIs captures the main predictive circulation features in the corresponding EASMR P-modes, i.e., a low-level Philippine Sea (anti-)cyclone and an upper-level zonal wind tripole pattern for P-mode1, an East China Sea (anti-)cyclone for P-mode2, and a west–east pressure dipole pattern for P-mode3. In addition, they also have the major predictable sources from the predictors of their corresponding P-modes, i.e., the decaying and developing El Niño–Southern Oscillation, the spring Arctic Oscillation, the spring sea surface temperatures over the western North Pacific, tropical and southern Atlantic, southern Indian and Arctic oceans. By considering the predictable and unpredictable components, this work not only improves our knowledge of the physical meanings and the potential limitations of the existing EASMIs, but also helps us in selecting the most appropriate EASMIs when focusing on the issue of seasonal forecasting. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
| abstractGer |
Abstract East Asian summer monsoon indices (EASMIs) have been widely used to investigate the variability and predictability of the East Asian summer monsoon rainfall (EASMR). However, the ability of existing EASMIs remains unclear to represent the interannual variability of the EASMR in predictable (P-) and unpredictable (U-) components. Based on a (co-)variance decomposition method, the fractional variance explained by a single EASMI has the highest value of 22% in both P- and U-components. A set of the best three EASMIs, together with the linear trend, is linearly independent of each other and can explain a large percentage of EASMR variance in P-component (54%). This set of EASMIs captures the main predictive circulation features in the corresponding EASMR P-modes, i.e., a low-level Philippine Sea (anti-)cyclone and an upper-level zonal wind tripole pattern for P-mode1, an East China Sea (anti-)cyclone for P-mode2, and a west–east pressure dipole pattern for P-mode3. In addition, they also have the major predictable sources from the predictors of their corresponding P-modes, i.e., the decaying and developing El Niño–Southern Oscillation, the spring Arctic Oscillation, the spring sea surface temperatures over the western North Pacific, tropical and southern Atlantic, southern Indian and Arctic oceans. By considering the predictable and unpredictable components, this work not only improves our knowledge of the physical meanings and the potential limitations of the existing EASMIs, but also helps us in selecting the most appropriate EASMIs when focusing on the issue of seasonal forecasting. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
| abstract_unstemmed |
Abstract East Asian summer monsoon indices (EASMIs) have been widely used to investigate the variability and predictability of the East Asian summer monsoon rainfall (EASMR). However, the ability of existing EASMIs remains unclear to represent the interannual variability of the EASMR in predictable (P-) and unpredictable (U-) components. Based on a (co-)variance decomposition method, the fractional variance explained by a single EASMI has the highest value of 22% in both P- and U-components. A set of the best three EASMIs, together with the linear trend, is linearly independent of each other and can explain a large percentage of EASMR variance in P-component (54%). This set of EASMIs captures the main predictive circulation features in the corresponding EASMR P-modes, i.e., a low-level Philippine Sea (anti-)cyclone and an upper-level zonal wind tripole pattern for P-mode1, an East China Sea (anti-)cyclone for P-mode2, and a west–east pressure dipole pattern for P-mode3. In addition, they also have the major predictable sources from the predictors of their corresponding P-modes, i.e., the decaying and developing El Niño–Southern Oscillation, the spring Arctic Oscillation, the spring sea surface temperatures over the western North Pacific, tropical and southern Atlantic, southern Indian and Arctic oceans. By considering the predictable and unpredictable components, this work not only improves our knowledge of the physical meanings and the potential limitations of the existing EASMIs, but also helps us in selecting the most appropriate EASMIs when focusing on the issue of seasonal forecasting. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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| container_issue |
11-12 |
| title_short |
Seasonal predictable signals of east Asian summer monsoon rainfall in existing monsoon indices |
| url |
https://dx.doi.org/10.1007/s00382-023-06827-2 |
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| author2 |
Jiang, Dabang Zheng, Xiaogu Frederiksen, Carsten S. Deng, Difei |
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Jiang, Dabang Zheng, Xiaogu Frederiksen, Carsten S. Deng, Difei |
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| doi_str |
10.1007/s00382-023-06827-2 |
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2024-07-03T21:03:04.979Z |
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| score |
7.399684 |