2016
DOI: 10.1007/s00382-016-3139-y
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Improving the long-lead predictability of El Niño using a novel forecasting scheme based on a dynamic components model

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Cited by 30 publications
(47 citation statements)
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References 73 publications
(137 reference statements)
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“…El Niño‐Southern Oscillation (ENSO) [ Ballester et al ., ] is the dominant source of interannual variability worldwide and one of the most important modes of variability in the tropical Pacific, with far‐reaching influences on the whole climate system [ Jin , ,; Meinen and McPhaden , ; Wang , ; Brown and Fedorov , ; Ballester et al ., ; Petrova et al ., ]. The large amplitude of ENSO anomalies in the tropical Pacific is essentially explained by the strong coupling between the Walker circulation, the zonal gradient of sea surface temperature and the longitudinal tilt of the thermocline (i.e., the so‐called Bjerknes feedback [ Bjerknes , ; Wyrtki , ]).…”
Section: Introductionmentioning
confidence: 99%
“…El Niño‐Southern Oscillation (ENSO) [ Ballester et al ., ] is the dominant source of interannual variability worldwide and one of the most important modes of variability in the tropical Pacific, with far‐reaching influences on the whole climate system [ Jin , ,; Meinen and McPhaden , ; Wang , ; Brown and Fedorov , ; Ballester et al ., ; Petrova et al ., ]. The large amplitude of ENSO anomalies in the tropical Pacific is essentially explained by the strong coupling between the Walker circulation, the zonal gradient of sea surface temperature and the longitudinal tilt of the thermocline (i.e., the so‐called Bjerknes feedback [ Bjerknes , ; Wyrtki , ]).…”
Section: Introductionmentioning
confidence: 99%
“…Forecasts issued in spring or before are still generally unable to foresee whether an EN or a LN event will occur at the end of the year, the so-called spring barrier1516. Although recent advances suggest that it is indeed possible to overcome this predictability limit, either with intermediate6, purely dynamical7 or purely statistical17 models, the value of a real-time operational scheme derived from these results remains to be fully accomplished.…”
mentioning
confidence: 99%
“…A structural timeseries model, which uses subsurface ocean temperature, wind stress, and sea surface temperature as predictor variables, was used to forecast the Niño3•4 index in 2016. 34 We chose this ENSO forecast model based on its ability to predict El Niño events in the past ( figure 2C). The model is comparable in performance to some of the most skilful dynamical ENSO models and generally performs better than other statistical schemes in terms of common skill metrics such as the root mean square error.…”
Section: Enso Forecast Modelmentioning
confidence: 99%