Exploring sensitive area in the tropical Indian Ocean for El Niño prediction: implication for targeted observation

Zhou, Qian; Duan, Wansuo; Hu, Junya

doi:10.1007/s00343-019-9062-4

Cited by 11 publications

(3 citation statements)

References 41 publications

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“…The oceanic channel dynamics have been shown to be important for the skills of the climate models in simulating ENSO (Xu et al, 2013). The initial condition errors of sea temperature in the Indian Ocean are identified as causal factors of the spring predictability barrier for El Niño, with two types of errors (positive and negative IODlike patterns) emphasize the mechanism of atmospheric bridge and oceanic channel, respectively (Zhou et al, 2019(Zhou et al, , 2020(Zhou et al, , 2021.…”

Section: Introductionmentioning

confidence: 99%

Assessment of the oceanic channel dynamics responsible for the IOD-ENSO precursory teleconnection in CMIP5 climate models

Yuan²,

Wang³

2022

Front. Clim.

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Existed studies have suggested a precursory relation between Indian Ocean Dipole (IOD) and El Niño and the Southern Oscillations (ENSO) with 1-year time lag. The underlying mechanisms were attributed to atmospheric bridge and/or oceanic channel processes. In this study, the oceanic channel dynamics in 23 climate models of the Coupled Model Intercomparison Project phase 5 (CMIP5) are assessed by correlation analyses in comparison with observations. The results show that the lag correlations between the IOD and ENSO anomalies associated with oceanic channel are significant, suggesting important role of oceanic channel dynamics in the cross-basin teleconnection in the analyzed CMIP5 models, consistent with observational analyses. In comparison, the correlations associated with atmospheric bridge are highly dispersive among the models and generally inconsistent with the observational analyses, suggesting model deficiencies. In a single climate model, the lag correlations associated with oceanic channel dynamics are consistent among different ensemble experiments, whereas those associated with atmospheric bridge processes are dispersive.

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Section: Introductionmentioning

confidence: 99%

Assessment of the oceanic channel dynamics responsible for the IOD-ENSO precursory teleconnection in CMIP5 climate models

Yuan²,

Wang³

2022

Front. Clim.

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“…Because of the greenhouse effect, the global climate has produced a major rise in both surface and ocean temperatures in recent years. In order to predict the El Niño or La Niña event, more research on the law of global SST changes is essential [4].…”

Section: Introductionmentioning

confidence: 99%

Time–Frequency Characteristics of Global SST Anomalies in the Past 100 Years: A Metrological Approach

Tang

Hao

Wei

et al. 2022

JMSE

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To comprehensively explore the characteristics of global SST anomalies, a novel time–frequency combination method, based on the COBE data and NCEP/NCAR reanalysis products in the past 100 years, was developed. From the view of the time domain, the global SST generally showed an upward trend from 1920 to 2019, the upward trend was significant after 1988, and the growth mutation occurred in 1930, according to the Mann–Kendall (MK) mutation test. Moreover, we extracted spatiotemporal modes of SST anomalies’ variability by empirical orthogonal function (EOF) analysis and obtained global spatial EOFs that closely correspond to regionally defined climate modes. Our results demonstrated that El Niño–Southern Oscillation (ENSO) is the typical character for the first mode of SST anomaly EOF, and Atlantic multidecadal oscillation (AMO) for the second. From the view of the frequency domain, our data suggested that there is a multi-period nesting phenomenon in global SST variations, in which the first main cycle with the most obvious oscillation was a 30-year cycle and changed in 20-year cycles, and the second cycle was a 15-year cycle and changed in 10-year cycles through wavelet analysis. As for the perspective of time–frequency characteristics, the dominant period of ENSO in the first mode of EOF is 4 years, obtained through filtering and cross wavelet transform. In addition, SST anomalies will maintain an upward trend for the next 60 months, according to the seasonal autoregressive integrated moving average (SARIMA) model, which has the potential value for predicting ENSO.

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“…It is necessary and important to improve the prediction skills of El Niñ o events. While the prediction skills of spring predictability barrier (SPB) related El Niñ o events depending on the sensitive area's selection, Zhou et al (2020) defi ned subsurface of the eastern tropical Indian as the sensitive area. Using the targeted observations to the sensitive area, the SPB-related prediction skills are improved by 20.3% in general and 25.2% while added the tropical Indian ocean.…”

mentioning

confidence: 99%

The variation of marine environment and climate effect in Indo-Pacific Ocean

Zuo

Wang

et al. 2020

J. Ocean. Limnol.

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Exploring sensitive area in the tropical Indian Ocean for El Niño prediction: implication for targeted observation

Cited by 11 publications

References 41 publications

Assessment of the oceanic channel dynamics responsible for the IOD-ENSO precursory teleconnection in CMIP5 climate models

Assessment of the oceanic channel dynamics responsible for the IOD-ENSO precursory teleconnection in CMIP5 climate models

Time–Frequency Characteristics of Global SST Anomalies in the Past 100 Years: A Metrological Approach

The variation of marine environment and climate effect in Indo-Pacific Ocean

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