Quantifying Causes of Arctic Amplification via Deep Learning based Time-series Causal Inference. (arXiv:2303.07122v3 [cs.AI] UPDATED)

The warming of the Arctic, also known as Arctic amplification, is led by
several atmospheric and oceanic drivers. However, the details of its underlying
thermodynamic causes are still unknown. Inferring the causal effects of
atmospheric processes on sea ice melt using fixed treatment effect strategies
leads to unrealistic counterfactual estimations. Such models are also prone to
bias due to time-varying confoundedness. Further, the complex non-linearity in
Earth science data makes it infeasible to perform causal inference using
existing marginal structural …

arxiv causal inference deep learning effects ice inference melt processes series strategies treatment