Marine Cloud Brightening (MCB) is a Solar Radiation Management (SRM) solution to cool the planet by changing the albedo of low-altitude marine clouds to increase reflected shortwave radiation.
Editors’ Highlights
How Space Plasma Can Bend the Laser of Gravitational Wave Detectors
A new study reveals how and to what extent laser beams are bent during propagation through space plasma in TianQin, a geocentric space-borne gravitational wave detector.
Gravity Waves Help Drive Sediment to the Deep Ocean
Laboratory experiments reveal that gravity wave-turbidity current interactions (combined flows) can enhance sediment transport to the deep ocean.
More Braided Rivers from Increasing Flow Variability
Global analysis of satellite data and river flow records show that higher flow intermittency after climate change may lead to an increasing number of threads in braided rivers, thus impacting ecosystems.
Weather Radar Data Reveal the Dynamics of Rapidly Spreading Wildfires
New research demonstrates the use of operational weather radar measurements to track long-range ember fallout and rapid spread of intense wildfires.
Choice of Glen’s n Leads to Differing Projections of Ice Sheet Mass Loss
Glen’s Law describes the simple physics of ice flow that underpins ice sheet models, but parameter choices substantially influence the outcome of model projections.
Amazon River Breezes Mimic Pollution in Clouds
Natural river breezes create clouds over the Amazon that mimic the signs of pollution, complicating climate impact assessments.
Snail-Borne Diseases in Central Africa: Lessons from Citizen Science
The ATRAP project in the Democratic Republic of Congo and Uganda provides insights to the factors that shape citizen science practice in low- and medium-income countries (LMIC).
Timing of Geomagnetic Storms Shapes Their Impact
The impact of geomagnetic storms, which can disrupt satellites, GPS, and power grids, is shown to depend on their onset timing.
Machine Learning Can Improve the Use of Atmospheric Observations in the Tropics
Scientists develop a novel machine learning-based technique that is equally effective in gaining information from observations about the unobserved state variables in the midlatitudes and tropics.
