An unexpectedly strong solar storm rocked our planet on April 23, 2023, sparking auroras as far south as southern Texas in the U.S. and taking the world by surprise. 

Two days earlier, the Sun blasted a coronal mass ejection (CME) — a cloud of energetic particles, magnetic fields, and solar material — toward Earth. But the CME wasn’t especially fast or massive, suggesting the storm would be minor. But it became severe.

Using NASA heliophysics missions, new studies of this storm and others are helping scientists learn why some CMEs have more intense effects — and better predict the impacts of future solar eruptions on our lives.

Researchers at the School of Veterinary Medicine at the University of Pennsylvania and their collaborators examine how common food waste recycling methods, including composting, could have a huge impact on greenhouse gas emissions mitigation and the sparing of natural resources such as land and water. Food loss and waste, in particular, are “a big deal,” says Zhengxia Dou. They account for almost a third of the food produced for human consumption.

Trees in tropical forests are dying at an increased rate, with consequences for biodiversity, carbon storage, and the global climate. While deforestation is the primary cause of forest loss, intact forests are also experiencing a rise in tree death. Drought, higher temperatures, and fires have been the leading suspects, but a new paper led by Evan Gora, a forest ecologist at Cary Institute of Ecosystem Studies, identifies an underappreciated threat: thunderstorms, which are becoming more frequent with climate change.

Researchers extend classical CNOP method for deep learning forecasting models with multi-time-slice-input structure.  It reveals when—not just where—input errors matter most in targeted observations. This improves forecasts for ocean-atmospheric variables, especially high-impact environmental events.

First openly available ensemble model using Artificial Intelligence goes live - delivering forecasts over 10 times faster and cutting energy usage by 1000