The modelled El Nino-mean state-seasonal cycle interactions in 23 coupled ocean-atmosphere GCMs, including the recent IPCC AR4 models, are assessed and compared to observations and theory. The models ...show a clear improvement over previous generations in simulating the tropical Pacific climatology. Systematic biases still include too strong mean and seasonal cycle of trade winds. El Nino amplitude is shown to be an inverse function of the mean trade winds in agreement with the observed shift of 1976 and with theoretical studies. El Nino amplitude is further shown to be an inverse function of the relative strength of the seasonal cycle. When most of the energy is within the seasonal cycle, little is left for inter-annual signals and vice versa. An interannual coupling strength (ICS) is defined and its relation with the modelled El Nino frequency is compared to that predicted by theoretical models. An assessment of the modelled El Nino in term of SST mode (S-mode) or thermocline mode (T-mode) shows that most models are locked into a S-mode and that only a few models exhibit a hybrid mode, like in observations. It is concluded that several basic El Nino-mean state-seasonal cycle relationships proposed by either theory or analysis of observations seem to be reproduced by CGCMs. This is especially true for the amplitude of El Nino and is less clear for its frequency. Most of these relationships, first established for the pre-industrial control simulations, hold for the double and quadruple CO sub(2) stabilized scenarios. The models that exhibit the largest El Nino amplitude change in these greenhouse gas (GHG) increase scenarios are those that exhibit a mode change towards a T-mode (either from S-mode to hybrid or hybrid to T-mode). This follows the observed 1976 climate shift in the tropical Pacific, and supports the-still debated-finding of studies that associated this shift to increased GHGs. In many respects, these models are also among those that best simulate the tropical Pacific climatology (ECHAM5/MPI-OM, GFDL-CM2.0, GFDL-CM2.1, MRI-CGM2.3.2, UKMO-HadCM3). Results from this large subset of models suggest the likelihood of increased El Nino amplitude in a warmer climate, though there is considerable spread of El Nino behaviour among the models and the changes in the subsurface thermocline properties that may be important for El Nino change could not be assessed. There are no clear indications of an El Nino frequency change with increased GHG.
Westerly wind bursts (WWBs) that occur in the western tropical Pacific are believed to play an important role in the development of El Niño events. Here, following the study of Lengaigne et al. (Clim ...Dyn 23(6):601–620,
2004
), we conduct numerical simulations in which we reexamine the response of the climate system to an observed wind burst added to a coupled general circulation model. Two sets of twin ensemble experiments are conducted (each set has control and perturbed experiments). In the first set, the initial ocean heat content of the system is higher than the model climatology (recharged), while in the second set it is nearly normal (neutral). For the recharged state, in the absence of WWBs, a moderate El Niño with a maximum warming in the central Pacific (CP) develops in about a year. In contrast, for the neutral state, there develops a weak La Niña. However, when the WWB is imposed, the situation dramatically changes: the recharged state slides into an El Niño with a maximum warming in the eastern Pacific, while the neutral set produces a weak CP El Niño instead of previous La Niña conditions. The different response of the system to the exact same perturbations is controlled by the initial state of the ocean and the subsequent ocean–atmosphere interactions involving the interplay between the eastward shift of the warm pool and the warming of the eastern equatorial Pacific. Consequently, the observed diversity of El Niño, including the occurrence of extreme events, may depend on stochastic atmospheric processes, modulating El Niño properties within a broad continuum.
Stratospheric aerosols from large tropical explosive volcanic eruptions backscatter shortwave radiation and reduce the global mean surface temperature. Observations suggest that they also favour an ...El Niño within 2 years following the eruption. Modelling studies have, however, so far reached no consensus on either the sign or physical mechanism of El Niño response to volcanism. Here we show that an El Niño tends to peak during the year following large eruptions in simulations of the Fifth Coupled Model Intercomparison Project (CMIP5). Targeted climate model simulations further emphasize that Pinatubo-like eruptions tend to shorten La Niñas, lengthen El Niños and induce anomalous warming when occurring during neutral states. Volcanically induced cooling in tropical Africa weakens the West African monsoon, and the resulting atmospheric Kelvin wave drives equatorial westerly wind anomalies over the western Pacific. This wind anomaly is further amplified by air-sea interactions in the Pacific, favouring an El Niño-like response.El Niño tends to follow 2 years after volcanic eruptions, but the physical mechanism behind this phenomenon is unclear. Here the authors use model simulations to show that a Pinatubo-like eruption cools tropical Africa and drives westerly wind anomalies in the Pacific favouring an El Niño response.
Previous studies using coupled general circulation models (GCMs) suggest that the atmosphere model plays a dominant role in the modeled El Niño–Southern Oscillation (ENSO), and that intermodel ...differences in the thermodynamical damping of sea surface temperatures (SSTs) are a dominant contributor to the ENSO amplitude diversity. This study presents a detailed analysis of the shortwave flux feedback (α
SW) in 12 Coupled Model Intercomparison Project phase 3 (CMIP3) simulations, motivated by findings thatα
SWis the primary contributor to model thermodynamical damping errors.
A “feedback decomposition method,” developed to elucidate theα
SWbiases, shows that all models underestimate the dynamical atmospheric response to SSTs in the eastern equatorial Pacific, leading to underestimatedα
SWvalues. Biases in the cloud response to dynamics and the shortwave interception by clouds also contribute to errors inα
SW. Changes in theα
SWfeedback between the coupled and corresponding atmosphere-only simulations are related to changes in the mean dynamics.
A large nonlinearity is found in the observed and modeled SW flux feedback, hidden when linearly calculatingα
SW. In the observations, two physical mechanisms are proposed to explain this nonlinearity: 1) a weaker subsidence response to cold SST anomalies than the ascent response to warm SST anomalies and 2) a nonlinear high-level cloud cover response to SST. The shortwave flux feedback nonlinearity tends to be underestimated by the models, linked to an underestimated nonlinearity in the dynamical response to SST. The process-based methodology presented in this study may help to correct model ENSO atmospheric biases, ultimately leading to an improved simulation of ENSO in GCMs.
In this study, we apply ocean energetics as a diagnostic tool to investigate the impact of westerly wind bursts (WWBs) on the evolution, diversity, and predictability of El Niño events. Following ...Fedorov et al. (2014), we add an observed WWB to simulations within a comprehensive coupled model and explore changes in the available potential energy (APE) of the tropical Pacific basin. We find that WWB impacts strongly depend on the ocean initial state and can range from a Central Pacific (CP) to Eastern Pacific (EP) warming, which is closely reflected by the ocean energetics. Consequently, the APE can be used to quantify the diversity of El Niño events within this continuum—higher negative APE values typically correspond to EP events, lower values to CP events. We also find that a superimposed WWB enhances El Niño predictability even before the spring predictability barrier, if one uses the APE as a predictor.
Key Points
Ocean energetics is powerful in studying the impact of WWBs on ENSO diversity
APE provides a good proxy to quantify the diversity of El Niño events
WWBs could enhance ENSO predictability even before spring prediction barrier
UNDERSTANDING ENSO DIVERSITY Capotondi, Antonietta; Wittenberg, Andrew T.; Newmaman, Matthew ...
Bulletin of the American Meteorological Society,
06/2015, Volume:
96, Issue:
6
Journal Article
Peer reviewed
Open access
El Niño–Southern Oscillation (ENSO) is a naturally occurring mode of tropical Pacific variability, with global impacts on society and natural ecosystems. While it has long been known that El Niño ...events display a diverse range of amplitudes, triggers, spatial patterns, and life cycles, the realization that ENSO’s impacts can be highly sensitive to this event-to-event diversity is driving a renewed interest in the subject. This paper surveys our current state of knowledge of ENSO diversity, identifies key gaps in understanding, and outlines some promising future research directions.
The western equatorial Pacific oceanic heat content (warm water volume in the west or WWVw) is the best El Niño–Southern Oscillation (ENSO) predictor beyond 1‐year lead. Using observations and ...selected Coupled Model Intercomparison Project Phase 5 simulations, we show that a discharged WWVw in boreal fall is a better predictor of La Niña than a recharged WWVw for El Niño 13 months later, both in terms of occurrence and amplitude. These results are robust when considering the heat content across the entire equatorial Pacific (WWV) at shorter lead times, including all Coupled Model Intercomparison Project Phase 5 models or excluding Niño‐Niña and Niña‐Niño phase transitions. Suggested mechanisms for this asymmetry include (1) the negatively skewed WWVw distribution with stronger discharges related to stronger wind stress anomalies during El Niño and (2) the stronger positive Bjerknes feedback loop during El Niño. The possible role of stronger subseasonal wind variations during El Niño is also discussed.
Plain language summary
El Niño and La Niña have strong societal impacts at the global scale, especially large‐amplitude El Niño events like in 1982–1983, 1997–1998, and 2015–2016. It is hence important to identify early warning signals for the occurrence of El Niño/La Niña. The equatorial Pacific Ocean heat content is a well‐known predictor of El Niño/La Niña several seasons ahead. In this study, we show that negative heat content anomalies lead more systematically to La Niña events than positive heat content to El Niño events. We suggest that the enhanced predictability of La Niña relative to El Niño is due to larger negative heat content anomalies ahead of La Niña events and a more unstable (and hence less predictable) ocean‐atmosphere system during El Niño.
Key Points
The western equatorial Pacific heat content is the best El Niño‐Southern Oscillation oceanic predictor beyond 1‐year lead
This relation is asymmetrical: La Niña amplitude and occurrence is more predictable than that of El Niño
Weak western Pacific heat content recharges, stronger air‐sea coupling, and atmospheric stochasticity contribute to this asymmetry
Several studies using ocean–atmosphere general circulation models (GCMs) suggest that the atmospheric component plays a dominant role in the modelled El Niño-Southern Oscillation (ENSO). To help ...elucidate these findings, the two main atmosphere feedbacks relevant to ENSO, the Bjerknes positive feedback (
μ
) and the heat flux negative feedback (
α
), are here analysed in nine AMIP runs of the CMIP3 multimodel dataset. We find that these models generally have improved feedbacks compared to the coupled runs which were analysed in part I of this study. The Bjerknes feedback,
μ
, is increased in most AMIP runs compared to the coupled run counterparts, and exhibits both positive and negative biases with respect to ERA40. As in the coupled runs, the shortwave and latent heat flux feedbacks are the two dominant components of
α
in the AMIP runs. We investigate the mechanisms behind these two important feedbacks, in particular focusing on the strong 1997–1998 El Niño. Biases in the shortwave flux feedback,
α
SW
, are the main source of model uncertainty in
α
. Most models do not successfully represent the negative α
SW
in the East Pacific, primarily due to an overly strong low-cloud positive feedback in the far eastern Pacific. Biases in the cloud response to dynamical changes dominate the modelled
α
SW
biases, though errors in the large-scale circulation response to sea surface temperature (SST) forcing also play a role. Analysis of the cloud radiative forcing in the East Pacific reveals model biases in low cloud amount and optical thickness which may affect
α
SW
. We further show that the negative latent heat flux feedback,
α
LH
, exhibits less diversity than
α
SW
and is primarily driven by variations in the near-surface specific humidity difference. However, biases in both the near-surface wind speed and humidity response to SST forcing can explain the inter-model α
LH
differences.
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