Predicting extreme rainfall over eastern Asia by using complex networks
A climate network of extreme rainfall over eastern Asia is constructed for the period of 1971-2000, employing the tools of complex networks and a measure of nonlinear correlation called event synchronization （ES）. Using this network, we predict the extreme rainfall for several cases without delay an...
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| Published in | Chinese physics B Vol. 23; no. 5; pp. 665 - 670 |
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| Main Author | |
| Format | Journal Article |
| Language | English |
| Published |
01.05.2014
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1674-1056 2058-3834 1741-4199 |
| DOI | 10.1088/1674-1056/23/5/059202 |
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| Abstract | A climate network of extreme rainfall over eastern Asia is constructed for the period of 1971-2000, employing the tools of complex networks and a measure of nonlinear correlation called event synchronization （ES）. Using this network, we predict the extreme rainfall for several cases without delay and with n-day delay （1 ≤ n ≤ 10）. The prediction accuracy can reach 58% without delay, 21% with 1-day delay, and 12% with n-day delay （2 ≤ n ≤ 10）. The results reveal that the prediction accuracy is low in years of a weak east Asia summer monsoon （EASM） or 1 year later and high in years of a strong EASM or 1 year later. Furthermore, the prediction accuracy is higher due to the many more links that represent correlations between different grid points and a higher extreme rainfall rate during strong EASM years. |
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| AbstractList | A climate network of extreme rainfall over eastern Asia is constructed for the period of 1971-2000, employing the tools of complex networks and a measure of nonlinear correlation called event synchronization （ES）. Using this network, we predict the extreme rainfall for several cases without delay and with n-day delay （1 ≤ n ≤ 10）. The prediction accuracy can reach 58% without delay, 21% with 1-day delay, and 12% with n-day delay （2 ≤ n ≤ 10）. The results reveal that the prediction accuracy is low in years of a weak east Asia summer monsoon （EASM） or 1 year later and high in years of a strong EASM or 1 year later. Furthermore, the prediction accuracy is higher due to the many more links that represent correlations between different grid points and a higher extreme rainfall rate during strong EASM years. A climate network of extreme rainfall over eastern Asia is constructed for the period of 1971-2000, employing the tools of complex networks and a measure of nonlinear correlation called event synchronization (ES). Using this network, we predict the extreme rainfall for several cases without delay and with n-day delay (1 [< or =] n [< or =] 10). The prediction accuracy can reach 58% without delay, 21% with 1-day delay, and 12% with n-day delay (2 [< or =] n [< or =] 10). The results reveal that the prediction accuracy is low in years of a weak east Asia summer monsoon (EASM) or 1 year later and high in years of a strong EASM or 1 year later. Furthermore, the prediction accuracy is higher due to the many more links that represent correlations between different grid points and a higher extreme rainfall rate during strong EASM years. |
| Author | 何苏红 封泰晨 龚艳春 黄雁华 吴成国 龚志强 |
| AuthorAffiliation | Institute of Science, PLA University of Science, Nanjing 211101, China Atmosphere and Science College, Lanzhou University, Lanzhou 730000, China Laboratory for Climate Monitoring and Diagnosing, National Climate Center, China Meteorological Administration, Beijing 100081, China Laboratory for Climate Diagnosis of National Climate Center, China Meteorological Administration, Beijing 100081, China |
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| CitedBy_id | crossref_primary_10_5194_esd_12_295_2021 crossref_primary_10_7498_aps_63_239202 crossref_primary_10_7498_aps_63_239201 crossref_primary_10_1016_j_atmosres_2024_107363 crossref_primary_10_1088_1674_1056_ad84c2 crossref_primary_10_1103_PhysRevE_101_052213 crossref_primary_10_1140_epjs_s11734_021_00166_1 crossref_primary_10_1007_s10584_025_03882_y crossref_primary_10_7498_aps_63_209202 crossref_primary_10_1016_j_jhydrol_2017_10_033 crossref_primary_10_1016_j_jhydrol_2024_132604 |
| Cites_doi | 10.1088/1674-1056/20/7/079201 10.1016/j.chaos.2006.09.036 10.1007/s00382-011-1156-4 10.1175/1520-0442(2002)015<0386:RSOTAP>2.0.CO;2 10.1140/epjb/e2011-10795-8 10.1137/S003614450342480 10.1038/30918 10.1029/2008GL037022 10.1103/PhysRevLett.100.228502 10.1088/1674-1056/21/2/029201 10.2151/sola.2009-035 10.1103/PhysRevE.74.057203 10.1029/2005JE002462 10.1016/j.physa.2003.10.045 10.7498/aps.57.5351 10.1126/science.1131152 10.1080/10020070412331344671 10.1175/BAMS-87-5-585 10.5194/npg-17-371-2010 10.1140/epjst/e2009-01098-2 10.1088/1674-1056/17/7/065 10.1007/s00704-012-0600-7 10.1209/0295-5075/87/48007 10.7498/aps.58.6651 10.1103/PhysRevE.66.041904 10.1007/s00703-005-0125-z 10.1103/RevModPhys.74.47 10.1007/s003820000118 |
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| Notes | A climate network of extreme rainfall over eastern Asia is constructed for the period of 1971-2000, employing the tools of complex networks and a measure of nonlinear correlation called event synchronization （ES）. Using this network, we predict the extreme rainfall for several cases without delay and with n-day delay （1 ≤ n ≤ 10）. The prediction accuracy can reach 58% without delay, 21% with 1-day delay, and 12% with n-day delay （2 ≤ n ≤ 10）. The results reveal that the prediction accuracy is low in years of a weak east Asia summer monsoon （EASM） or 1 year later and high in years of a strong EASM or 1 year later. Furthermore, the prediction accuracy is higher due to the many more links that represent correlations between different grid points and a higher extreme rainfall rate during strong EASM years. prediction, extreme rainfall, synchronization, complex networks 11-5639/O4 He Su-Hong, Feng Tai-Chen, Gong Yan-Chun, Huang Yan-Hua, Wu Cheng-Guo, Gong Zhi-Qiang（ 1.Institute of Science, PLA University of Science, Nanjing 211101, China ;2. Atmosphere and Science College, Lanzhou University, Lanzhou 730000, China;3.Laboratory for Climate Monitoring and Diagnosing, National Climate Center, China Meteorological Administration, Beijing 100081, China ;4.Laboratory for Climate Diagnosis of National Climate Center, China Meteorological Administration, Beijing 100081, China） ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
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| SubjectTerms | Climate Construction equipment Correlation Delay Networks Rainfall Summer Synchronization 东亚夏季风 东部地区 极端降水 网络构建 网络预测 降雨率 非线性相关 预测精度 |
| Title | Predicting extreme rainfall over eastern Asia by using complex networks |
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