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Scientific computing cannot credibly drive global decarbonization while ignoring its own runaway compute footprints and disposable, unmaintained software ecosystems.
Simple neural networks can accurately emulate complex aerosol microphysics in climate models, but only with careful attention to scaling and training convergence.
