Climate Research

Learning Drivers of Climate-Induced Human Migrations with Gaussian Processes

Authors: Jose M. Tarraga, Maria Piles, Gustau Camps-Valls
Comments: 12 Pages. 34th ML4D Workshop at Conference on Neural Information Processing Systems (NeurIPS 2020), Vancouver, Canada.

In the current context of climate change, extreme heat waves, droughts and floods are not only impacting the biosphere and atmosphere but the anthroposphere too. Human populations are forcibly displaced, which are now referred to as climate-induced migrants. In this work we investigate which climate and structural factors forced major human displacements in the presence of floods and storms during years 2017-2019. We built, curated and harmonized a database of meteorological and remote sensing indicators along with structural factors of 27 developing countries world-wide. We show how we can use Gaussian Processes to learn what variables can explain the impact of floods and storms in a context of forced displacements and to develop models that reproduce migration flows. Our results at regional, global and disaster-specific scales show the importance of structural factors in the determination of the magnitude of displacements. The study may have both societal, political and economical implications.
Category: Climate Research