Thirty-nine years of satellite data reveal that the prevalence of intense hurricanes, cyclones, and typhoons—category 3 and above on the Saffir-Simpson scale—is increasing.
Statistical analysis
Posted inScience Updates
Data from Past Eruptions Could Reduce Future Volcano Hazards
Optimizing the Use of Volcano Monitoring Database to Anticipate Unrest; Yogyakarta, Indonesia, 26–29 November 2018
Posted inResearch Spotlights
Impact of Hurricanes and Nor’easters on Coastal Forests
Scientists trace severe storms’ effects through tree ring growth patterns.
Posted inResearch Spotlights
How Does Snow Affect the Intensity of Mountain Precipitation?
A new investigation into the sensitivity of extreme precipitation in a changing climate indicates that more winter rainfall and protracted snowmelt may require local adaptations to winter flooding impacts.
Posted inOpinions
Will Clean Air Fade Away?
Government-sponsored research and regulations enabled western U.S. states to clean up their air, despite industrial and population growth. Proposed funding cuts could undo this progress.
Posted inEditors' Vox
Probability Analysis Improves Hazard Assessment
A recent paper in Reviews of Geophysics describes a probabilistic method for evaluating tsunami location, size, and risk to human populations.
Posted inScience Updates
Enhancing Safety in a Volcano's Shadow
A new project gives civil authorities and scientists a common set of tools for assessing volcanic hazards and managing associated risks.
Posted inResearch Spotlights
Improving the Identification of Extreme Precipitation Trends in the U.S.
By greatly reducing the associated uncertainty, a new model is better able to discern statistically significant trends, offering the potential to improve the seasonal forecasting of rare events.
Posted inResearch Spotlights
Tracking Long-Term Changes in Global Sea Level Extremes
Large-scale climate change may drive trends in extreme sea level events.
Posted inResearch Spotlights
What Climate Information Is Most Useful for Predicting Floods?
Basing forecasts on data that preserve variations over space yield more reliable predictions than using standard numerical measures of climatic cycles' intensity.