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Low-frequency Sea Surface Temperature (SST) Variability

PI: Bin Guan
Institution: University of Maryland
Additional Investigators: Sumant Nigam
The project aims to identify and describe all leading modes of low-frequency sea surface temperature (SST) variability in the 20th century coupled climate simulations as well as in observations in a Pan-Pacific area, with special interest in a robust and improved characterization of Pacific Decadal Variability (PDV). The efficiency of the analysis tool, i.e., rotated extended empirical orthogonal function (EOF), has been demonstrated by a pilot analysis of a century-long SST data set; the analysis will be extended to SST output of coupled models run at NOAA, NASA, NCAR, etc. Comparisons will be made among simulated/observed SSTs with respect to spatiotemporal structures of Pacific low-frequency variability, with the focus on PDV structure and evolution. Lead/lag relationships between key atmospheric and oceanic fields will be analyzed in context of PDV, in coupled simulations and in observations. The objective of this project is to improve PDV characterization, develop/filter hypotheses on PDV mechanisms, and assess the capability of the various models in PDV simulation.

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