Interannual to Multi-Decadal Variability of Indo-Pacific SST

Low-frequency (decadal to centennial) modes of ocean are important components of climate variability. With the rise of supercomputers, these modes are inferred often from long-term climate simulations after being preprocessed by low-pass filtering. Notably, the few modes that are consistently found in many climate models differ significantly, even in frequency, as every model has biases and model errors. At the same time, validation of the extracted signals against observations is limited by the time span of the observational record (e.g., sea surface temperature and sea ice extent observed during the satellite era), which is oftentimes shorter than the timescales of interest and also significantly altered by anthropogenic factors. More importantly, due to preprocessing as well as the subsequent data analysis techniques (such as EOFs), the results have frequently ambiguous physical interpretation.

Here, we investigate Indo-Pacific Ocean variability from 1300 control run of CCSM4. For that, we apply recently introduced technique called Nonlinear Laplacian Spectral Analysis (NLSA, Giannakis and Majda 2012). Through this technique, drawbacks associated with ad-hoc filtering are avoided as the extracted signals span many temporal scales without preprocessing the input data, enabling detection of low-frequency and intermittent modes not previously accessible with classical EOF-based approaches. Here, we identify spatiotemporal modes covering multiple scales of interest, including several interannual modes such as ENSO, the Indian Ocean Dipole, and Tropical Biennial Oscillation, revealing refined linkages between these patterns. Additionally, the amplitudes of these patterns are modulated by low-frequency envelopes whose character can in certain cases be related to patterns of decadal or longer variability which are also identified. As such, our study unambiguously clarifies interdependencies between interannual modes which are sometimes treated in the climate science community as independent, but also lead to the identification of previously-unknown decadal to centennial modes.

Giannakis, G. and A. J. Majda, 2012: Nonlinear Laplacian spectral analysis for time series with intermittency and low-frequency variability. Proc. Natl. Acad. Sci., 109(7), 2222