Causal conclusions concerning climate changes
Project description
CO2 is a primary driver of climate, yet its large variations over the last
million years remain a puzzle, which casts doubt on the credibility of our future climate projections. Over the last decade, however, there have been numerous theoretical, observational and numerical breakthroughs, which together promise a better data-driven understanding of the causal mechanisms behind CO2 and climate fluctuations:
- novel causal inference methods based on machine learning
- a doubling of both resolution and length of the ice-core records
- Earth System Models (ESM) that realistically simulate the climate carbon-cycle system
The objective of this project is to integrate these developments in a novel framework termed CINCH that can improve our causal explanations of past and predictions of future climate changes. The focus of the present initiation project is to apply CINCH to the well dated and synchronized ice core records from Greenland and Antarctica for the period of 60 to 20,000 years ago to test the following hypothesis: The observed large-scale variability of CO2 is caused by periodic collapses of the North Atlantic marine productivity, and not by changes to Southern Ocean temperature or winds.
