Predictability of El Niño over the past 148 years

Chen, Dake; Cane, Mark A.; Kaplan, Alexey; Zebiak, Stephen E.; Huang, Daji

doi:10.1038/nature02439

Cited by 527 publications

(424 citation statements)

References 29 publications

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“…Both lead ENSO into selfsustained and possibly even chaotic regimes. We speculate that these results may be somewhat relevant to the success of the ENSO hindcasts of Chen et al (2004), who used the CZ model with no explicit representation of WWBs. According to our results, their model may have roughly compensated for the lack of WWBs by using a stronger ocean-atmosphere coupling strength.…”

Section: Discussionmentioning

confidence: 92%

“…Although the evidence described above strongly suggests their importance to ENSO, some reliable ENSO hindcasts have been obtained without including WWBs (e.g., Chen et al 2004). Furthermore, the exceptionally large El Niño of 1997-98, whose occurrence and amplitude were not well predicted by most models (Barnston et al 1999;Landsea and Knaff 2000), had an unusually high occurrence of WWBs (McPhaden 1999;Vecchi and Harrison 2000).…”

Section: Introductionmentioning

confidence: 99%

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Westerly Wind Bursts: ENSO’s Tail Rather than the Dog?

2005

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Westerly wind bursts (WWBs) in the equatorial Pacific occur during the development of most El Niño events and are believed to be a major factor in ENSO's dynamics. Because of their short time scale, WWBs are normally considered part of a stochastic forcing of ENSO, completely external to the interannual ENSO variability. Recent observational studies, however, suggest that the occurrence and characteristics of WWBs may depend to some extent on the state of ENSO components, implying that WWBs, which force ENSO, are modulated by ENSO itself.Satellite and in situ observations are used here to show that WWBs are significantly more likely to occur when the warm pool is extended eastward. Based on these observations, WWBs are added to an intermediate complexity coupled ocean-atmosphere ENSO model. The representation of WWBs is idealized such that their occurrence is modulated by the warm pool extent. The resulting model run is compared with a run in which the WWBs are stochastically applied. The modulation of WWBs by ENSO results in an enhancement of the slow frequency component of the WWBs. This causes the amplitude of ENSO events forced by modulated WWBs to be twice as large as the amplitude of ENSO events forced by stochastic WWBs with the same amplitude and average frequency. Based on this result, it is suggested that the modulation of WWBs by the equatorial Pacific SST is a critical element of ENSO's dynamics, and that WWBs should not be regarded as purely stochastic forcing. In the paradigm proposed here, WWBs are still an important aspect of ENSO's dynamics, but they are treated as being partially stochastic and partially affected by the large-scale ENSO dynamics, rather than being completely external to ENSO.It is further shown that WWB modulation by the large-scale equatorial SST field is roughly equivalent to an increase in the ocean-atmosphere coupling strength, making the coupled equatorial Pacific effectively self-sustained.

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Section: Discussionmentioning

confidence: 92%

Section: Introductionmentioning

confidence: 99%

Westerly Wind Bursts: ENSO’s Tail Rather than the Dog?

2005

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“…The concurrent, OSST data, for nonforecast simulations (lead time less than zero), S denotes the Reynolds version 2 data (Reynolds et al 2002); the real-time persisted SST (FSST p ) and hindcast persisted SST (HSST p ) are undamped and then damped with persisted anomalies initialized from anomalies observed the previous month. The evolving anomalous SST (FSST e ) is from one or more of the following models: the NCEP coupled model (Ji et al 1998), the CFS (Saha et al 2006), the LDEO-5 (Chen et al 2004), and/or the statistical constructed analog (CA) (van den Dool 1994Dool , 2007. More details about the FSST e are provided in Camargo and Barnston (2008 …”

Section: Description Of the Real-time Forecastsmentioning

confidence: 99%

“…2 The tropical Pacific SST has been based on one or more of the following: the NCEP coupled ENSO prediction model (Ji et al 1998), the NCEP Climate Forecast System (NCEP-CFS) (Saha et al 2006), the Lamont-Doherty Earth Observatory intermediate model, version 5 (LDEO-5), (Chen et al 2004), and the statistical constructed analog (CA) model (van den Dool 1994Dool , 2007. 3 A model TC needs to exceed simultaneously thresholds for low-level vorticity (850 hPa), surface wind speed, and vertically integrated local temperature anomaly for at least 2 days, and must also have a relative local minimum of sea level pressure, local maximum of temperature anomalies in various levels, and mean wind speed at 850 hPa larger than at 300 hPa.…”

Section: Description Of the Real-time Forecastsmentioning

confidence: 99%

Experimental Dynamical Seasonal Forecasts of Tropical Cyclone Activity at IRI

Camargo¹,

Barnston²

2009

Weather and Forecasting

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The International Research Institute for Climate and Society (IRI) has been issuing experimental seasonal tropical cyclone activity forecasts for several ocean basins since early 2003. In this paper the method used to obtain these forecasts is described and the forecast performance is evaluated. The forecasts are based on tropical cyclone-like features detected and tracked in a low-resolution climate model, namely ECHAM4.5. The simulation skill of the model using historical observed sea surface temperatures (SSTs) over several decades, as well as with SST anomalies persisted from the previous month's observations, is discussed. These simulation skills are compared with skills of purely statistically based hindcasts using as predictors recently observed SSTs. For the recent 6-yr period during which real-time forecasts have been made, the skill of the raw model output is compared with that of the subjectively modified probabilistic forecasts actually issued.Despite variations from one basin to another, the levels of hindcast skill for the dynamical and statistical forecast approaches are found, overall, to be approximately equivalent at fairly modest but statistically significant levels. The dynamical forecasts require statistical postprossessing (calibration) to be competitive with, and in some circumstances superior to, the statistical models. Skill levels decrease only slowly with increasing lead time up to 2-3 months. During the recent period of real-time forecasts, the issued forecasts have had higher probabilistic skill than the raw model output, due to the forecasters' subjective elimination of the ''overconfidence'' bias in the model's forecasts. Prospects for the future improvement of dynamical tropical cyclone prediction are considered.

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“…Generally, there are two sources that limit ENSO predictability: (i) uncertainty in initial conditions, and the chaotic behavior of the nonlinear dynamics of the coupled system (e.g., Jin et al 1994;Chen et al 2004); and (ii) atmospheric noise (i.e. weather events) and other high-frequency variations such as westerly wind bursts and the Madden-Julian oscillation (e.g., Penland and Sardeshmukh 1995;Kleeman and Moore 1997;Vecchi and 1 parameterizations of physical and dynamical processes also have impacts on the predictability.…”

mentioning

confidence: 99%

ENSO ensemble prediction and predictability for the past 148 years from 1856--2003.

Cheng¹

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Predictability of El Niño over the past 148 years

Cited by 527 publications

References 29 publications

Westerly Wind Bursts: ENSO’s Tail Rather than the Dog?

Westerly Wind Bursts: ENSO’s Tail Rather than the Dog?

Experimental Dynamical Seasonal Forecasts of Tropical Cyclone Activity at IRI

ENSO ensemble prediction and predictability for the past 148 years from 1856--2003.

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