Computer scientists and weather scientists have taken the first steps toward creating an AI agent capable of analyzing and answering questions in natural language, such as English, about data from AI-driven weather and climate forecasting models. Recently, models driven by AI and deep learning have considerably improved weather forecasting. But analyzing the resulting data remains difficult and time-consuming. A main issue is that these types of AI models are not able to describe their findings in plain language. A secondary issue is that these models are not able to reason about text information, such as meteorology reports and weather bulletins. The UC San Diego research team aims to address both.

First study to use crowdsourced comments to assess effects of heat underground. Researchers collected comments from X and Google Reviews published between 2008 and 2024. Study focused on subway systems in Boston, New York and London. As above-ground temperatures rise, below-ground thermal complaints increase. Knowing when people are uncomfortable could inform targeted interventions.

Urban scavengers like spotted hyenas are preventing over a thousand tonnes of carbon emissions annually in Ethiopia’s second-largest city, according to new research revealing the predators’ role as accidental eco-warriors.

Even if temporary breaches of temperature targets occur, global CO₂ emissions still need to reach net zero by mid-century. New research shows how overshoot affects policy priorities, risk distribution, and mitigation strategies – while keeping the core Paris Agreement objective intact.