A new study published in Big Earth Data develops a stochastic random forest (RF) classifier to predict extreme wind-gust (WG) occurrences along the western Mediterranean coast by integrating instantaneous and trailing 24-hour meteorological variables across multiple height levels, enabling the model to capture both short-term evolution and immediate atmospheric forcing. It demonstrates strong forecasting performance with high precision, low false-alarm rates, and reliable uncertainty estimation, while identifying barometric-pressure tendencies and humidity as key predictors, highlighting the framework’s potential for early-warning systems, climate resilience, and disaster-risk management. UERRA reanalysis data can be downloaded from the Copernicus Climate Data Store platform: https://cds.climate.copernicus.eu/. Supplementary materials supporting the findings of this study are openly accessible at the public GitHub repository: https://github.com/AI4OCEANS/.

After over seven years of research and development, the student-run AggieSat Laboratory has sent the AggieSat 6 satellite into Earth’s orbit from the Vandenberg Space Force Base in California aboard the Minotaur IV. 

Hyper performing Laser emission technology based on OLED–liquid crystal platforms achieving tens-fold enhanced color purity over OLEDs and continuous wavelength tuning over 135 nm at 1.5 V operation.

Using data from NASA’s James Webb Space Telescope, astronomers led by researchers at the University of California, Riverside have produced the most detailed map of the cosmic web ever made, tracing the network of galaxies all the way back to when the universe was one billion years old. 

For decades, the search for life beyond Earth has revolved around a key question: What molecules should scientists be looking for on other planets or moons? A new study suggests the more revealing clue may not be the molecules themselves, but the hidden order connecting them.