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Evolution of principal nonlinear patterns of global sea surface temperature in XX century

Name
Andrey
Surname
Gavrilov
Scientific organization
Institute of Applied Physics of the Russian Academy of Sciences
Academic degree
M.Sc.
Position
Junior Research Scientist
Scientific discipline
Earth Sciences, Ecology & Environmental Management
Topic
Evolution of principal nonlinear patterns of global sea surface temperature in XX century
Abstract
In the report we will consider the empirical method of observed spatially-distributed data expansion into principal nonlinear dynamical modes holding the dynamical properties of the system. This method applied to HadISST1 global sea surface temperature dataset on the 1870-2014 years interval provides low-dimensional modes which resolve annual cycle and large-scale patterns reflecting El Nino Southern Oscillation variability and decadal transitions of Pacific Decadal Oscillation.
Keywords
Empirical modeling, principal nonlinear modes, climate, teleconnections
Summary

1. Method of principal nonlinear dynamical modes extraction from observed spatially-distributed data is suggested

2. The main modes of global sea surface temperature hold annual cycle, ENSO variability, evolution of PDO pattern, and also can track the evolution and possible critical changes of climate teleconnections