Lin Piao

Quantitative Ecology and Data-Driven Theory

Lin Piao is a visiting scholar from Peking University, China where she is pursuing her PhD in geophysics. She is particularly interested in nonlinear time series analyses, focusing on long-term memory, scale-dependency, and asymmetry structure. Additionally, she is interested in causality analyses in nonlinear climate systems.

In geophysics, Pearson cross-correlation is generally used in uncovering the relationship between different variables obtained from climate system. However, it has quite a lot limitations: unable to reveal distinct correlations on different timescales which corresponding to different physical mechanisms, unable to find non-stationary relationship (“mirage correlation” maybe caused by nonlinear system) and so on. In this case, Convergent Cross Mapping (CCM) proves to be a more powerful method which might be more suitable for determining causal links in nonlinear climate system. During her time in the Sugihara lab, Lin is trying to identify causal factors contributing to global sea level change on different timescales.