Stanford researchers have combined machine learning with high-resolution satellite and airplane observations to understand the physics behind large-scale ice movements in Antarctica. The results show that current models are missing key complexity needed to accurately predict the dynamics and mass loss of the Antarctic ice sheet now and in the future.

Researchers identified a strong negative North Atlantic Oscillation in 2009–2010 as the tipping point that pushed sargassum into the tropical Atlantic, confirming vertical mixing, not rivers, as the primary nutrient source fueling the massive blooms since 2011.

SAN ANTONIO — March 12, 2025 — Four small suitcase-sized spacecraft, designed and built by Southwest Research Institute headquartered in San Antonio, launched from Vandenberg Space Force Base in California on March 11. NASA’s Polarimeter to Unify the Corona and Heliosphere, or PUNCH, constellation has spread out in a low-Earth orbit along the day-night line, providing a clear view in all directions for its two-year primary mission.

- University of Leicester paleontologists publish new book on technofossils

- Offers a glimpse of how today’s technology will become the fossils of the future

- Scientists suggest that wind turbine blades, made from difficult to recycle materials, may be among the most surprising fossils found by future palaeontologists

A new study by scientists and graduates at the University of Plymouth has investigated one aspect of how the future environmental conditions created by the changing global climate might affect earliest development within Christmas Island’s red crab population

As climate change and population growth increase pressure on global food production, regional-scale crop growth and associated process (CROP-AP) models have become essential tools for understanding and predicting agricultural productivity. A new review, published in Science China Earth Sciences, categorizes these models into four types—statistical models, crop growth models, hydrology-crop coupling models, and ecosystem models. The study explores their main functions from five aspects: crop yield prediction, crop water consumption, agricultural non-point source pollution, greenhouse gas emissions, and climate change impact and responses, and identifies key future research directions, including model validation and calibration, the ability to simulate the coupling of crop physiology and human activities, enhancing model scalability, multi-model ensembles, data and code sharing, and the integration of artificial intelligence.