The risk of weather data sabotage is rising

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As weather forecasting shifts from physics-based models to AI-driven systems, the threat of data poisoning increases. Hackers or state actors could theoretically manipulate input sensors to degrade forecast accuracy, causing chaos in agriculture, energy grids, and flight paths. Because AI models are more 'black box' than traditional simulations, detecting subtle sabotage in the training data is significantly harder.