{"title":"印度洋减弱ENSO春季可预测性障碍:印度洋盆地和偶极子模态的作用","authors":"Yishuai Jin, Xing Meng, Li Zhang, Yingying Zhao, Wenju Cai, Lixin Wu","doi":"10.1175/jcli-d-22-0800.1","DOIUrl":null,"url":null,"abstract":"\nPrediction of El Niño-Southern Oscillation (ENSO) is hindered by a spring predictability barrier (SPB). In this paper, we investigate effects of the Indian Ocean (IO) on the SPB. Using a seasonally-varying extended IO-ENSO recharge oscillator model, we find that the SPB is much weakened when IO is coupled with ENSO. In order to gauge the relative role of the Indian Ocean Dipole (IOD) and the Indian Ocean Basin (IOB) modes in weakening ENSO SPB, we develop an empirical dynamical model – Linear Inverse Model (LIM). By coupling/decoupling IOB or IOD with ENSO, we show that the IOB significantly weakens Eastern Pacific and Central Pacific ENSO SPBs, while the IOD plays a weaker role. The evolution of the optimum initial structures also illustrates the importance of the IOB in ENSO SPB. Moreover, the IOB strongly influences the forecast skill of La Niña SPB rather than El Niño SPB. This point is also identified through six coupled models from North American multimodel ensemble. It may be related to the role of IO in the asymmetry in the duration of El Niño and La Niña. The IOB-induced easterly wind anomalies are conducive to the development of La Niña and thus the prediction of La Niña events, while these anomalous easterlies are less important during the development of El Niño and the related forecast of El Niño events.","PeriodicalId":15472,"journal":{"name":"Journal of Climate","volume":" ","pages":""},"PeriodicalIF":4.8000,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"The Indian Ocean weakens ENSO Spring Predictability Barrier: Role of the Indian Ocean Basin and Dipole modes\",\"authors\":\"Yishuai Jin, Xing Meng, Li Zhang, Yingying Zhao, Wenju Cai, Lixin Wu\",\"doi\":\"10.1175/jcli-d-22-0800.1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\nPrediction of El Niño-Southern Oscillation (ENSO) is hindered by a spring predictability barrier (SPB). In this paper, we investigate effects of the Indian Ocean (IO) on the SPB. Using a seasonally-varying extended IO-ENSO recharge oscillator model, we find that the SPB is much weakened when IO is coupled with ENSO. In order to gauge the relative role of the Indian Ocean Dipole (IOD) and the Indian Ocean Basin (IOB) modes in weakening ENSO SPB, we develop an empirical dynamical model – Linear Inverse Model (LIM). By coupling/decoupling IOB or IOD with ENSO, we show that the IOB significantly weakens Eastern Pacific and Central Pacific ENSO SPBs, while the IOD plays a weaker role. The evolution of the optimum initial structures also illustrates the importance of the IOB in ENSO SPB. Moreover, the IOB strongly influences the forecast skill of La Niña SPB rather than El Niño SPB. This point is also identified through six coupled models from North American multimodel ensemble. It may be related to the role of IO in the asymmetry in the duration of El Niño and La Niña. The IOB-induced easterly wind anomalies are conducive to the development of La Niña and thus the prediction of La Niña events, while these anomalous easterlies are less important during the development of El Niño and the related forecast of El Niño events.\",\"PeriodicalId\":15472,\"journal\":{\"name\":\"Journal of Climate\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":4.8000,\"publicationDate\":\"2023-09-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Climate\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.1175/jcli-d-22-0800.1\",\"RegionNum\":2,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"METEOROLOGY & ATMOSPHERIC SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Climate","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1175/jcli-d-22-0800.1","RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
The Indian Ocean weakens ENSO Spring Predictability Barrier: Role of the Indian Ocean Basin and Dipole modes
Prediction of El Niño-Southern Oscillation (ENSO) is hindered by a spring predictability barrier (SPB). In this paper, we investigate effects of the Indian Ocean (IO) on the SPB. Using a seasonally-varying extended IO-ENSO recharge oscillator model, we find that the SPB is much weakened when IO is coupled with ENSO. In order to gauge the relative role of the Indian Ocean Dipole (IOD) and the Indian Ocean Basin (IOB) modes in weakening ENSO SPB, we develop an empirical dynamical model – Linear Inverse Model (LIM). By coupling/decoupling IOB or IOD with ENSO, we show that the IOB significantly weakens Eastern Pacific and Central Pacific ENSO SPBs, while the IOD plays a weaker role. The evolution of the optimum initial structures also illustrates the importance of the IOB in ENSO SPB. Moreover, the IOB strongly influences the forecast skill of La Niña SPB rather than El Niño SPB. This point is also identified through six coupled models from North American multimodel ensemble. It may be related to the role of IO in the asymmetry in the duration of El Niño and La Niña. The IOB-induced easterly wind anomalies are conducive to the development of La Niña and thus the prediction of La Niña events, while these anomalous easterlies are less important during the development of El Niño and the related forecast of El Niño events.
期刊介绍:
The Journal of Climate (JCLI) (ISSN: 0894-8755; eISSN: 1520-0442) publishes research that advances basic understanding of the dynamics and physics of the climate system on large spatial scales, including variability of the atmosphere, oceans, land surface, and cryosphere; past, present, and projected future changes in the climate system; and climate simulation and prediction.