Cosmic dust opens window on ancient atmosphere
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Updates every hour. Last Updated: 30-Jul-2025 15:11 ET (30-Jul-2025 19:11 GMT/UTC)
Researchers have devised a new machine learning method to improve large-scale climate model projections and demonstrated that the new tool makes the models more accurate at both the global and regional level. This advance should provide policymakers with improved climate projections that can be used to inform policy and planning decisions.
Tiny droplets of sea spray generated at the ocean surface can affect the intensity and evolution of hurricanes and other tropical storms.
Their impact, however, is not well understood because of the difficulty of measuring spray concentration and the size and velocity of individual droplets under high wind conditions.
At The University of Texas at Dallas, researchers are studying sea spray, particularly spume, or foam, droplets, in the lab to develop a model based on machine learning to improve hurricane forecasting. The model incorporates the effects of the spray generation function, which quantifies the rate at which droplets form.
Current methods to predict landslides rely primarily on rainfall intensity. Now, a new model combines various water-related factors with machine learning. When applied to more than 600 landslides in California, model identified the conditions that caused 89% of the events.
The global marine heatwaves (MHWs) of 2023 were unprecedented in their intensity, persistence, and scale, according to a new study. The findings provide insights into the region-specific drivers of these events, linking them to broader changes in the planet’s climate system. They may also portend an emerging climate tipping point. Marine heatwaves (MHWs) are intense and prolonged episodes of unusually warm ocean temperatures. These events pose severe threats to marine ecosystems, often resulting in widespread coral bleaching and mass mortality events. They also carry serious economic consequences by disrupting fisheries and aquaculture. It’s widely understood that human-driven climate change is driving a rapid increase in the frequency and intensity of MHWs. In 2023, regions across the globe, including the North Atlantic, Tropical Pacific, South Pacific, and North Pacific, experienced extreme MHWs. However, the causes underlying the onset, persistence, and intensification of widespread MHWs remain poorly understood.
To better understand the MHWs of 2023, Tianyun Dong and colleagues conducted a global analysis using combined satellite observations and ocean reanalysis data, including those from the ECCO2 (Estimating the Circulation and Climate of the Ocean-Phase II) high-resolution project. According to the findings, MHWs of 2023 set new records for intensity, duration, and geographic extent, lasting four times the historical average and covering 96% of the global ocean surface. Regionally, the most intense warming occurred in the North Atlantic, Tropical Eastern Pacific, North Pacific, and Southwest Pacific, collectively accounting for 90% of the oceanic heating anomalies. Dong et al. show that the North Atlantic MHW, which began as early as mid-2022, persisted for 525 days, while the Southwest Pacific event broke prior records with its vast spatial extent and prolonged duration. What’s more, in the Tropical Eastern Pacific, temperature anomalies peaked at 1.63 degrees Celsius during the onset of El Niño. Using a mixed-layer heat budget analysis, the authors discovered diverse regional drivers contributing to the formation and persistence of these events, including increased solar radiation due to reduced cloud cover, weakened winds, and ocean current anomalies. According to the authors, the 2023 MHWs may mark a fundamental shift in ocean–atmosphere dynamics, potentially serving as an early warning of an approaching tipping point in Earth’s climate system.