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Andrew T. Wittenberg

Abstract

Surface wind stresses are fundamental to understanding El Niño, yet most observational stress products are too short to permit multidecadal ENSO studies. Two exceptions are the Florida State University subjective analysis (FSU1) and the NCEP–NCAR reanalysis (NCEP1), which are widely used in climate research. Here, the focus is on the aspects of the stress most relevant to ENSO—namely, the climatological background, anomaly spectrum, response to SST changes, subannual “noise” forcing, and seasonal phase locking—and how these differ between FSU1 and NCEP1 over the tropical Pacific for 1961–99.

The NCEP1 stress climatology is distinguished from FSU1 by weaker equatorial easterlies, stronger off-equatorial cyclonic curl, stronger southerlies along the Peruvian coast, and weaker convergence zones with weaker seasonality. Compared to FSU1, the NCEP1 zonal stress anomalies ( τ x ) are weaker, less noisy, and show less persistent westerly peaks during El Niño events. NCEP1 also shows a more stationary spectrum that more closely resembles that of equatorial east Pacific SST anomalies. After the 1970s, the equatorial trade winds and stress variability shift east and strengthen in FSU1, while the opposite occurs in NCEP1. Both products show increased mean convergence in the equatorial far west Pacific in recent decades, with weaker mean easterlies near the date line, an increased stress response to SST anomalies, and stronger interannual and subannual τ x in the central equatorial Pacific (Niño-4; 5°N–5°S, 160°E–150°W). The variance of Niño-4 τ x is highly seasonal in both datasets, with an interannual peak in October–November and a subannual peak in November–February; yet apart from interannual Niño-4 τ x after 1980, stress anomalies are not well correlated between the products. Newer and more reliable stress estimates generally fall between NCEP1 and FSU1, with most closer to FSU1.

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Geoffrey Gebbie
,
Ian Eisenman
,
Andrew Wittenberg
, and
Eli Tziperman

Abstract

Westerly wind bursts (WWBs) in the equatorial Pacific are known to play a significant role in the development of El Niño events. They have typically been treated as a purely stochastic external forcing of ENSO. Recent observations, however, show that WWB characteristics depend upon the large-scale SST field. The consequences of such a WWB modulation by SST are examined using an ocean general circulation model coupled to a statistical atmosphere model (i.e., a hybrid coupled model). An explicit WWB component is added to the model with guidance from a 23-yr observational record. The WWB parameterization scheme is constructed such that the likelihood of WWB occurrence increases as the western Pacific warm pool extends: a “semistochastic” formulation, which has both deterministic and stochastic elements. The location of the WWBs is parameterized to migrate with the edge of the warm pool. It is found that modulation of WWBs by SST strongly affects the characteristics of ENSO. In particular, coupled feedbacks between SST and WWBs may be sufficient to transfer the system from a damped regime to one with self-sustained oscillations. Modulated WWBs also play a role in the irregular timing of warm episodes and the asymmetry in the size of warm and cold events in this ENSO model. Parameterizing the modulation of WWBs by an increase of the linear air–sea coupling coefficient seems to miss important dynamical processes, and a purely stochastic representation of WWBs elicits only a weak ocean response. Based upon this evidence, it is proposed that WWBs may need to be treated as an internal part of the coupled ENSO system, and that the detailed knowledge of wind burst dynamics may be necessary to explain the characteristics of ENSO.

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Jonghun Kam
,
Thomas R. Knutson
,
Fanrong Zeng
, and
Andrew T. Wittenberg
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Thomas R. Knutson
,
Jonghun Kam
,
Fanrong Zeng
, and
Andrew T. Wittenberg
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Jonghun Kam
,
Thomas R. Knutson
,
Fanrong Zeng
, and
Andrew T. Wittenberg
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Jonghun Kam
,
Thomas R. Knutson
,
Fanrong Zeng
, and
Andrew T. Wittenberg
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Kit-Yan Choi
,
Gabriel A. Vecchi
, and
Andrew T. Wittenberg

Abstract

The El Niño–Southern Oscillation (ENSO) exhibits well-known asymmetries: 1) warm events are stronger than cold events, 2) strong warm events are more likely to be followed by cold events than vice versa, and 3) cold events are more persistent than warm events. Coupled GCM simulations, however, continue to underestimate many of these observed features.

To shed light on these asymmetries, the authors begin with a widely used delayed-oscillator conceptual model for ENSO and modify it so that wind stress anomalies depend more strongly on SST anomalies (SSTAs) during warm conditions, as is observed. Then the impact of this nonlinearity on ENSO is explored for three dynamical regimes: self-sustained oscillations, stochastically driven oscillations, and self-sustained oscillations disrupted by stochastic forcings. In all three regimes, the nonlinear air–sea coupling preferentially strengthens the feedbacks (both positive and delayed negative) during the ENSO warm phase—producing El Niños that grow to a larger amplitude and overshoot more rapidly and consistently into the opposite phase, than do the La Niñas. Finally, the modified oscillator is applied to observational records and to control simulations from two global coupled ocean–atmosphere–land–ice models [Geophysical Fluid Dynamics Laboratory Climate Model version 2.1 (GFDL CM2.1) and version 2.5 (GFDL CM2.5)] to elucidate the causes of their differing asymmetries.

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Thomas R. Knutson
,
Fanrong Zeng
, and
Andrew T. Wittenberg

Abstract

Regional surface temperature trends from phase 3 of the Coupled Model Intercomparison Project (CMIP3) and CMIP5 twentieth-century runs are compared with observations—at spatial scales ranging from global averages to individual grid points—using simulated intrinsic climate variability from preindustrial control runs to assess whether observed trends are detectable and/or consistent with the models' historical run trends. The CMIP5 models are also used to detect anthropogenic components of the observed trends, by assessing alternative hypotheses based on scenarios driven with either anthropogenic plus natural forcings combined, or with natural forcings only. Modeled variability is assessed via inspection of control run time series, standard deviation maps, spectral analyses, and low-frequency variance consistency tests. The models are found to provide plausible representations of internal climate variability, although there is room for improvement. The influence of observational uncertainty on the trends is assessed and is found to be generally small in comparison with intrinsic climate variability. Observed temperature trends over 1901–2010 are found to contain detectable anthropogenic warming components over a large fraction (about 80%) of the analyzed global area. In about 70% of the analyzed area, the modeled warming is consistent with the observed trends; in about 10% it is significantly greater than simulated. Regions without detectable warming include the high-latitude North Atlantic Ocean, the eastern United States, and parts of the eastern and northern Pacific Ocean. For 1981–2010, the observed warming trends over only about 30% of the globe are found to contain a detectable anthropogenic warming: this includes a number of regions within about 40°–45° of the equator, particularly in the Indian Ocean, western Pacific, South Asia, and tropical Atlantic.

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Tomomichi Ogata
,
Shang-Ping Xie
,
Andrew Wittenberg
, and
De-Zheng Sun

Abstract

The amplitude of El Niño–Southern Oscillation (ENSO) displays pronounced interdecadal modulations in observations. The mechanisms for the amplitude modulation are investigated using a 2000-yr preindustrial control integration from the Geophysical Fluid Dynamics Laboratory Climate Model, version 2.1 (GFDL CM2.1). ENSO amplitude modulation is highly correlated with the second empirical orthogonal function (EOF) mode of tropical Pacific decadal variability (TPDV), which features equatorial zonal dipoles in sea surface temperature (SST) and subsurface temperature along the thermocline. Experiments with an ocean general circulation model indicate that both interannual and decadal-scale wind variability are required to generate decadal-scale tropical Pacific temperature anomalies at the sea surface and along the thermocline. Even a purely interannual and sinusoidal wind forcing can produce substantial decadal-scale effects in the equatorial Pacific, with SST cooling in the west, subsurface warming along the thermocline, and enhanced upper-ocean stratification in the east. A mechanism is proposed by which residual effects of ENSO could serve to alter subsequent ENSO stability, possibly contributing to long-lasting epochs of extreme ENSO behavior via a coupled feedback with TPDV.

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Hui Ding
,
Matthew Newman
,
Michael A. Alexander
, and
Andrew T. Wittenberg

Abstract

Seasonal forecasts made by coupled atmosphere–ocean general circulation models (CGCMs) undergo strong climate drift and initialization shock, driving the model state away from its long-term attractor. Here we explore initializing directly on a model’s own attractor, using an analog approach in which model states close to the observed initial state are drawn from a “library” obtained from prior uninitialized CGCM simulations. The subsequent evolution of those “model-analogs” yields a forecast ensemble, without additional model integration. This technique is applied to four of the eight CGCMs comprising the North American Multimodel Ensemble (NMME) by selecting from prior long control runs those model states whose monthly tropical Indo-Pacific SST and SSH anomalies best resemble the observations at initialization time. Hindcasts are then made for leads of 1–12 months during 1982–2015. Deterministic and probabilistic skill measures of these model-analog hindcast ensembles are comparable to those of the initialized NMME hindcast ensembles, for both the individual models and the multimodel ensemble. In the eastern equatorial Pacific, model-analog hindcast skill exceeds that of the NMME. Despite initializing with a relatively large ensemble spread, model-analogs also reproduce each CGCM’s perfect-model skill, consistent with a coarse-grained view of tropical Indo-Pacific predictability. This study suggests that with little additional effort, sufficiently realistic and long CGCM simulations provide the basis for skillful seasonal forecasts of tropical Indo-Pacific SST anomalies, even without sophisticated data assimilation or additional ensemble forecast integrations. The model-analog method could provide a baseline for forecast skill when developing future models and forecast systems.

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