Traditional air quality models struggle with changing emissions, while pure AI systems operate as opaque "black boxes" that can break the laws of physics. To solve this, researchers developed ProNet, a framework that embeds AI directly into atmospheric equations. Tested across 338 cities, ProNet outperformed experienced human forecasters and accurately predicted extreme events—like severe dust storms—without producing "AI hallucinations." Crucially, it also acts as a scientific diagnostic tool, using routine hourly data to uncover and correct hidden flaws in existing chemical models.

Using satellite observations, researchers tracked water storage recovery after 468 severe droughts in large river basins worldwide. Most events were followed by recovery, but persistent deficits clustered in drylands and some inland basins. Recovery trajectories varied across basins and events, reflecting water availability after drought. Recurrent droughts and intensive human water use were associated with prolonged deficits.

Carbonate cerium and neodymium isotope records from South China show that low-oxygen waters invaded shallow habitats twice during the Late Ordovician Mass Extinction, with a brief recovery between the two pulses. Earth-system models suggest that rapid climate swings reorganized continental weathering and nutrient delivery, amplifying marine oxygen loss and ecological stress.