El Niño-Southern Oscillation frequency cascade

Abstract

The El Niño-Southern Oscillation (ENSO) phenomenon, the most pronounced feature of internally generated climate variability, occurs on interannual timescales and impacts the global climate system through an interaction with the annual cycle. The tight coupling between ENSO and the annual cycle is particularly pronounced over the tropical Western Pacific. Here we show that this nonlinear interaction results in a frequency cascade in the atmospheric circulation, which is characterized by deterministic high-frequency variability on near-annual and subannual timescales. Through climate model experiments and observational analysis, it is documented that a substantial fraction of the anomalous Northwest Pacific anticyclone variability, which is the main atmospheric link between ENSO and the East Asian Monsoon system, can be explained by these interactions and is thus deterministic and potentially predictable.

Keywords: ENSO; annual cycle; combination mode; frequency cascade; monsoon.

Fig. 1.

Schematic for the ENSO (E) and combination mode (ExA) anomalous surface circulation pattern and corresponding spectral characteristics. (A) Power spectral density for the normalized N3.4 index of the Hadley Centre Sea Ice and Sea Surface Temperature data set version 1 (HadISST1) 1958–2013 SSTA using the Welch method. (B) As in A but for the theoretical quadratic combination mode (ExA). (C) Regression coefficient of the normalized N3.4 index and the anomalous JRA-55 surface stream function for the same period (ENSO response pattern). (D) Regression coefficient of the normalized combination mode (ExA) index and the anomalous JRA-55 surface stream function (combination mode response pattern). Areas where the anomalous circulation regression coefficient is significant above the 95% confidence level are nonstippled.

Fig. 2.

(A) ENSO SST anomaly forcing pattern for the AGCM experiments. The amplitude of the anomaly pattern is given by the colored shading (no units). The N3.4 (black) and NWP (cyan) regions are marked by two boxes. (B) The time evolution of the N3.4 SST anomaly index (black) and the anomalous ensemble mean circulation index $\overline{\text{NWP}-\text{AC}\left(\text{t}\right)}$ (cyan) for the 2.5-y experiment.

Fig. 3.

(A−E) Power spectral density for the individual reconstruction components for the 2.5-y Sine ENSO AGCM experiment using the averaged coefficients using the fast Fourier transform (FFT) method. (F) Power spectral density for the anomalous ensemble mean circulation index $\overline{\text{NWP}-\text{AC}\left(\text{t}\right)}$ for this experiment (light blue lines) and the full reconstruction (red lines) using all of the terms depicted in A−E. (G−K) Regression coefficient of the normalized respective reconstruction component and the anomalous surface stream function of this experiment: (G) E, (H) E², (I) ExA, (J) E²xA, and (K) ExSA. (L) Regression coefficient of the normalized full reconstruction time series and the anomalous surface stream function of this experiment.

Fig. 4.

Predictability of the observed NWP-AC circulation during major El Niño and La Niña events. Shown are the observed N3.4 index (dashed black line), the JRA-55 NWP-AC index (solid gray line), and the CFSv2 hindcast for the N3.4 index beginning in December (termination phase) of each event (thick magenta line). The error estimate for the NWP-AC index is 1 SD of the NWP-AC circulation in a 50-y integration of CESM CAM4 with only the annual cycle as forcing (gray shading). The error for the N3.4 hindcast is 1 SD in the ensemble spread (thin magenta lines). The reconstruction ${\mathrm{\Psi }}_c$* is used for predicting the circulation (solid orange line for the prediction and thin orange lines for the 1 SD error) and on the observations (dashed orange line). A small offset between observations and the CFSv2 initialization is explained by both the CFSv2 climatology (1999−2010) and the observational uncertainty of the CFSv2 analysis (the SD of the initial conditions is shown by the range of the thin magenta lines during the first month).

Fig. 5.

The ENSO frequency cascade: deterministic transfer of power from interannual to higher frequencies. (A) Power spectral density for the normalized 1958–2013 HadISST1 N3.4 index (black line) and the anomalous JRA-55 surface stream function NWP-AC(t) index (orange line) using the Welch method. (B) FFT power spectral density for the ENSO forcing of each individual frequency experiment (thin black lines), and the anomalous ensemble mean circulation index $\overline{\text{NWP}-\text{AC}\left(\text{t}\right)}$ for each individual frequency experiment (thin blue lines). Power spectral density of the anomalous ensemble mean circulation index $\overline{\text{NWP}-\text{AC}\left(\text{t}\right)}$ of the 1958–2013 experiment using the Welch method (red line). All of the Welch power spectra are scaled by the same factor to approximately match the power estimate of the FFT spectra for better visualization.