The Spatial and Temporal Structure of ENSO Nonlinearity

• Published in: Journal of climate Vol. 17; no. 15; pp. 3026 - 3036
• Main Authors: Monahan, Adam Hugh, Dai, Aiguo
• Format: Journal Article
• Language: English
• Published: Boston, MA American Meteorological Society 01.08.2004
• Subjects: Air temperature; Atmospherics; Climate models; Datasets; Earth, ocean, space; El Nino; Exact sciences and technology; External geophysics; Forecasting models; La Nina; Nonlinearity; Ocean currents; Physics of the oceans; Principal components analysis; Sea surface temperature; Sea-air exchange processes; Skewed distribution; Standard deviation; Surface waves; Temperature; Time series; Equatorial Pacific; Pacific Ocean; Atmosphere model; General circulation models; Empirical orthogonal function; Surface temperature; Sea surface temperature; Spatial variation; Time variation; Ocean model; La Niña; El Niño; Atmospheric temperature; Covariance; Southern oscillation; Numerical simulation; Anomaly; Principal component analysis; Ocean atmosphere interaction
• ISSN: 0894-8755; 1520-0442
• DOI: 10.1175/1520-0442(2004)017<3026:tsatso>2.0.co;2

The spatial structure of asymmetries in sea surface temperature (SST) and surface air temperature (SAT) between average El Niño and La Niña events is considered. It is demonstrated that in historical SST and SAT reconstructions, the anomaly spatial pattern that changes sign between El Niño and La Niña events (the “linear” signal) strongly resembles that of principal component analysis (PCA) mode 1, while that which does not change sign (the “nonlinear” signal) resembles the pattern of PCA mode 2. The linear and nonlinear patterns also strongly resemble the standard deviation and skewness fields, respectively. Furthermore, temporal subsampling of long (130 yr) SST reconstructions suggests that the magnitude of the nonlinear signal and its similarity to PCA mode 2 are functions of the strength of ENSO, as measured by the standard deviation of the PCA mode-1 time series. Finally, it is found that of several coupled general circulation models (GCMs) considered, the spatial and temporal structure of the El Niño–La Niña asymmetry is captured only by the GFDL R30 model, despite large biases in its covariance structure.