Will AI replace Atmospheric Scientist?

More exposed than 84% of the occupations in the index.

Averaged across 27 O*NET tasks, weighted by importance.

Atmospheric and space scientists are experiencing a major paradigm shift driven by AI. Deep learning models (such as GraphCast and Pangu-Weather) are achieving state-of-the-art results in weather forecasting at a fraction of the computational cost of traditional numerical weather prediction models. In addition to ML-based forecasting models, AI coding assistants drastically speed up custom software development, data processing of satellite/radar streams, and complex climate modeling. AI-fluent atmospheric scientists can analyze vastly larger datasets, iterate on models significantly faster, and produce richer forecasting products than non-fluent peers.