Indo-Pacific Variability on Seasonal to Multidecadal Time Scales. Part I: Intrinsic SST Modes in Models and Observations

Joanna Slawinska Center for Environmental Prediction, Rutgers, The State University of New Jersey, New Brunswick, New Jersey

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Dimitrios Giannakis Center for Atmosphere Ocean Science, Courant Institute of Mathematical Sciences, New York University, New York, New York

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Abstract

The variability of Indo-Pacific SST on seasonal to multidecadal time scales is investigated using a recently introduced technique called nonlinear Laplacian spectral analysis (NLSA). Through this technique, drawbacks associated with ad hoc prefiltering of the input data are avoided, enabling recovery of low-frequency and intermittent modes not previously accessible via classical approaches. Here, a multiscale hierarchy of spatiotemporal modes is identified for Indo-Pacific SST in millennial control runs of CCSM4 and GFDL CM3 and in HadISST data. On interannual time scales, a mode with spatiotemporal patterns corresponding to the fundamental component of ENSO emerges, along with ENSO-modulated annual modes consistent with combination mode theory. The ENSO combination modes also feature prominent activity in the Indian Ocean, explaining a significant fraction of the SST variance in regions associated with the Indian Ocean dipole and suggesting a deterministic relationship between these patterns. A pattern representing the tropospheric biennial oscillation also emerges along with its associated annual cycle combination modes. On multidecadal time scales, the dominant NLSA mode in the model data is predominantly active in the western tropical Pacific; this pattern is referred to here as the west Pacific multidecadal mode (WPMM). The interdecadal Pacific oscillation also emerges as a distinct NLSA mode, though with smaller explained variance than the WPMM. Analogous modes on interannual and decadal time scales are also identified in HadISST data for the industrial era, as well as in model data of comparable time span, though decadal modes are either absent or of degraded quality in these datasets.

Supplemental information related to this paper is available at the Journals Online website: http://dx.doi.org/10.1175/JCLI-D-16-0176.s1.

Denotes content that is immediately available upon publication as open access.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Joanna Slawinska, joanna.slawinska@nyu.edu

Abstract

The variability of Indo-Pacific SST on seasonal to multidecadal time scales is investigated using a recently introduced technique called nonlinear Laplacian spectral analysis (NLSA). Through this technique, drawbacks associated with ad hoc prefiltering of the input data are avoided, enabling recovery of low-frequency and intermittent modes not previously accessible via classical approaches. Here, a multiscale hierarchy of spatiotemporal modes is identified for Indo-Pacific SST in millennial control runs of CCSM4 and GFDL CM3 and in HadISST data. On interannual time scales, a mode with spatiotemporal patterns corresponding to the fundamental component of ENSO emerges, along with ENSO-modulated annual modes consistent with combination mode theory. The ENSO combination modes also feature prominent activity in the Indian Ocean, explaining a significant fraction of the SST variance in regions associated with the Indian Ocean dipole and suggesting a deterministic relationship between these patterns. A pattern representing the tropospheric biennial oscillation also emerges along with its associated annual cycle combination modes. On multidecadal time scales, the dominant NLSA mode in the model data is predominantly active in the western tropical Pacific; this pattern is referred to here as the west Pacific multidecadal mode (WPMM). The interdecadal Pacific oscillation also emerges as a distinct NLSA mode, though with smaller explained variance than the WPMM. Analogous modes on interannual and decadal time scales are also identified in HadISST data for the industrial era, as well as in model data of comparable time span, though decadal modes are either absent or of degraded quality in these datasets.

Supplemental information related to this paper is available at the Journals Online website: http://dx.doi.org/10.1175/JCLI-D-16-0176.s1.

Denotes content that is immediately available upon publication as open access.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Joanna Slawinska, joanna.slawinska@nyu.edu

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