But, are the results physically robust? This is the $1m question, and while the preliminary results showing global conservation of energy are encouraging, there’s certainly room for improvement (watch this space!).

It turns out you can using a variety of machine learning techniques, and pretty well! There are the differences between the emulators and the full model but they’re mostly small

These are physically very robust (arguably more so than the full models) but only predict global mean temperature. In ClimateBench we ask: can we emulate the full spatial response of the models, and not just for temperature??