Markov-chain-inspired search for MH370

Abstract

Markov-chain models are constructed for the probabilistic description of the drift of marine debris from Malaysian Airlines flight MH370. En route from Kuala Lumpur to Beijing, MH370 mysteriously disappeared in the southeastern Indian Ocean on 8 March 2014, somewhere along the arc of the 7th ping ring around the Inmarsat-3F1 satellite position when the airplane lost contact. The models are obtained by discretizing the motion of undrogued satellite-tracked surface drifting buoys from the global historical data bank. A spectral analysis, Bayesian estimation, and the computation of most probable paths between the Inmarsat arc and confirmed airplane debris beaching sites are shown to constrain the crash site, near 25°S on the Inmarsat arc. Application of tools from ergodic theory on historical Lagrangian ocean data is shown to constrain the crash site of Malaysian Airlines flight MH370 given airplane debris beaching site information. The disappearance of flight MH370 constitutes one of the most enigmatic episodes in the history of commercial aviation. The tools employed have far-reaching applicability as they are particularly well suited in inverse modeling, critical, for instance, in revealing contamination sources in the ocean and the atmosphere. The only requirement for their success is sufficient spatiotemporal Lagrangian sampling.