Data-driven model for investigation of the mid-Pleistocene transition

Evgeny M Loskutov; Dmitry N Mukhin; Andrey S Gavrilov; Alexander M Feigin

Presentation information

[EJ] Oral

M (Multidisciplinary and Interdisciplinary) » M-GI General Geosciences, Information Geosciences & Simulations

[M-GI29] [EJ] Data-driven analysis, modeling and prediction in geosciences

Sat. May 20, 2017 3:30 PM - 5:00 PM 102 (International Conference Hall 1F)

convener:Tatsu Kuwatani(Japan Agency for Marine-Earth Science and Technology), Dmitri Kondrashov(University of California, Los Angeles), Hiromichi Nagao(Earthquake Research Institute, The University of Tokyo), Sergey Kravtsov(University of Wisconsin Milwaukee), Chairperson:Kenta Yoshida(Japan Agency for Marine-earth Science and Technology), Chairperson:Dmitri Kondrashov(University of California, Los Angeles,)

3:45 PM - 4:00 PM

[MGI29-14] Data-driven model for investigation of the mid-Pleistocene transition

*Evgeny M Loskutov¹, Dmitry N Mukhin¹, Andrey S Gavrilov¹, Alexander M Feigin¹ (1.Institute of Applied Physics RAS)

Keywords:Data-driven Modeling, Critical Transitions, Time Series Analysis, Mid Pleistocene Transition

In this work we apply a data-driven model for the analysis of complex spatially distributed geophysical data. We are focused on the investigation of critical transitions on paleo timescales. Namely we investigated mid-Pleistocene transition which led to change of dominate cycles of glacial variability in Pleistocene.
We demonstrate the good performance of applying our data-driven model to analysis of paleoclimate variability. In particular, we discuss the possibility of detecting, identifying and prediction of the mid-Pleistocene transition by means of nonlinear empirical modeling using the paleoclimate record time series.
The study is supported by Government of Russian Federation (agreement #14.Z50.31.0033 with the Institute of Applied Physics of RAS).