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Update to Google’s AI weather model improves forecast accuracy

8 September 2026 at 19:00

Google is one of the major players in AI (meaning machine learning) weather forecast model space. The models it and others generate have their strengths and weaknesses, but the main advantage is that they can have forecast performance similar to traditional models while requiring far less computing horsepower to run. That means they can be run more frequently.

Google recently released version 3 of its WeatherNext model, with the biggest change being that it now ingests some satellite weather data, shortening the lag time between current weather conditions and generating a new forecast. The update is detailed in a white paper.

Reanalysis

Many weather models make use of what’s called a “reanalysis,” which is a sort of model of its own. Reanalyses take in all kinds of weather data and combine them into a single, consistent global snapshot of the atmosphere. That requires that they provide estimates for conditions over locations without real-world measurements, because weather forecast models need to work with a global picture.

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China could supply EV manufacturing boom with recycled EVs

Ars Technica - All

By: Scott K. Johnson

31 July 2026 at 18:29

While recycling is a mathematically obvious response to the finite, non-renewable nature of many resources, the economic math is often challenging. For many materials, it can be hard to compete with virgin materials on a cost basis. Fast-moving technologies like electric vehicles throw in an added complication: By the time a car is scrapped, the industry may have moved on to a different battery chemistry. That reduces the value of recycling the car’s battery back into the production chain.

Still, a study led by Xin Xiong at Nanjing University finds that in China, recycling could become the dominant source of many key materials needed to manufacture EV components over the coming decades.

Modeling manufacturing needs

The researchers set out to model how the supply of recycled materials compares to manufacturing demand in China between 2010 and 2050. It covers materials relevant to batteries across hybrid, battery-electric, and even fuel-cell vehicles (lithium, cobalt, nickel, manganese, phosphorus, sodium, sulfur, and graphite), as well as several critical elements used in electric motors (copper, neodymium, dysprosium, samarium, and cerium).

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