AI RESEARCH
Adversarial Attacks on Downstream Weather Forecasting Models: Application to Tropical Cyclone Trajectory Prediction
arXiv CS.LG
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ArXi:2510.10140v2 Announce Type: replace Deep learning-based weather forecasting (DLWF) models leverage past weather observations to generate future forecasts, ing a wide range of downstream applications, including tropical cyclone (TC) prediction. In this paper, we investigate their vulnerability to adversarial attacks, where subtle perturbations to the upstream forecasts can alter the downstream TC trajectory predictions.