Publications

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2019
Dias, DF, Subramanian A, Zanna L, Miller AJ.  2019.  Remote and local influences in forecasting Pacific SST: a linear inverse model and a multimodel ensemble study. Climate Dynamics. 52:3183-3201.   10.1007/s00382-018-4323-z   AbstractWebsite

A suite of statistical linear inverse models (LIMs) are used to understand the remote and local SST variability that influences SST predictions over the North Pacific region. Observed monthly SST anomalies in the Pacific are used to construct different regional LIMs for seasonal to decadal predictions. The seasonal forecast skills of the LIMs are compared to that from three operational forecast systems in the North American Multi-Model Ensemble (NMME), revealing that the LIM has better skill in the Northeastern Pacific than NMME models. The LIM is also found to have comparable forecast skill for SST in the Tropical Pacific with NMME models. This skill, however, is highly dependent on the initialization month, with forecasts initialized during the summer having better skill than those initialized during the winter. The data are also bandpass filtered into seasonal, interannual and decadal time scales to identify the relationships between time scales using the structure of the propagator matrix. Moreover, we investigate the influence of the tropics and extra-tropics in the predictability of the SST over the region. The Extratropical North Pacific seems to be a source of predictability for the tropics on seasonal to interannual time scales, while the tropics enhance the forecast skill for the decadal component. These results indicate the importance of temporal scale interactions in improving the predictions on decadal timescales. Hence, we show that LIMs are not only useful as benchmarks for estimates of statistical skill, but also to isolate contributions to the forecast skills from different timescales, spatial scales or even model components.

2018
Yi, DLL, Gan BL, Wu LX, Miller AJ.  2018.  The North Pacific Gyre Oscillation and Mechanisms of Its Decadal Variability in CMIP5 Models. Journal of Climate. 31:2487-2509.   10.1175/jcli-d-17-0344.1   AbstractWebsite

Based on the Simple Ocean Data Assimilation (SODA) product and 37 models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) database, the North Pacific Gyre Oscillation (NPGO) and its decadal generation mechanisms are evaluated by studying the second leading modes of North Pacific sea surface height (SSH) and sea level pressure (SLP) as well as their dynamical connections. It is found that 17 out of 37 models can well simulate the spatial pattern and decadal time scales (10-30 yr) of the NPGO mode, which resembles the observation-based SODA results. Dynamical connections between the oceanic mode (NPGO) and the atmospheric mode [North Pacific Oscillation (NPO)] are strongly evident in both SODA and the 17 models. In particular, about 30%-40% of the variance of the NPGO variability, which generally exhibits a preferred time scale, can be explained by the NPO variability, which has no preferred time scale in most models. Two mechanisms of the decadal NPGO variability that had been proposed by previous studies are evaluated in SODA and the 17 models: 1) stochastic atmospheric forcing and oceanic spatial resonance and 2) low-frequency atmospheric teleconnections excited by the equatorial Pacific. Evaluation reveals that these two mechanisms are valid in SODA and two models (CNRM-CM5 and CNRM-CM5.2), whereas two models (CMCC-CM and CMCC-CMS) prefer the first mechanism and another two models (CMCC-CESM and IPSL-CM5B-LR) prefer the second mechanism. The other 11 models have no evident relations with the proposed two mechanisms, suggesting the need for a fundamental understanding of the decadal NPGO variability in the future.