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Climate change has been significantly disturbing the dynamics of different earth system components, such as land surface and ocean, as well as the interactive relationship between different components. Here we aim to investigate the sea surface temperature dynamics and its remote connection to the precipitation patterns. Previous efforts on the remote ocean-land remote coupling are mostly relied on linear based statistical inference framework, disregarding the nonlinearity of the earth system dynamics. Here we apply a new inference framework that fully adapts to nonlinear system to quantify the coupling strength between Atlantic Oceanic temperature signals (AMO index) and US precipitation patterns. We found that the linear based coupling patterns are significantly different from the nonlinear based coupling patterns, which provides important insights into the system nonlinearity. We also conduct uncertainty analysis to quantify the estimated coupling strength uncertainty and discuss the robustness of the climate coupling between AMO and US precipitation.

Directional information coupling dynamics in complex climate system