Sensor networks and data mining allow for fully automated, real-time monitoring of radio waves.
data management
Posted inEditors' Highlights
Listening to the Clouds
The assimilation of cloud-cleared infrared data improves numerical weather forecasting, especially for hurricanes, by providing thermodynamic information in cloudy atmosphere.
Posted inResearch Spotlights
Preserving a 45-Year Record of Sunspots
Maps reveal how the Sun’s magnetic field evolves through solar cycles.
Posted inScience Updates
Connecting Scientific Data and Real-World Samples
International Symposium on Linking Environmental Data and Samples; Canberra, Australia, 29 May to 2 June 2017
Posted inScience Updates
Linking Instrumental and Proxy Data Climate Records
Treatment of the Climatic Signal in Time and Space: From Instrumental and Proxy Data to Modelling; Rouen, France, 18–20 April 2017
Posted inEditors' Highlights
Addition by Subtraction: Raising the Bar for Satellite Imagery
When it comes to forecaster analysis of complex satellite imagery, less can be more, and a new technique aims to simplify imagery interpretation by suppressing the background noise.
Posted inAGU News
Eric F. Wood Receives 2017 Robert E. Horton Medal
Eric F. Wood was awarded the 2017 Robert E. Horton Medal at the American Geophysical Union Fall Meeting Honors Ceremony, held on 13 December 2017 in New Orleans, La. The medal is for “outstanding contributions to hydrology.”
Posted inNews
Hurricanes Expose Vulnerabilities in Puerto Rico Seismic Network
Could overreliance on cell networks to transmit data leave instruments in the dark after the next storm hits?
Posted inNews
New Model Predicts Lightning Strikes; Alert System to Follow
Data from thousands of past storms help guide a new forecast model that predicts where and when lightning may hit.
Posted inAGU News
Enabling FAIR Data Across the Earth and Space Sciences
Data experts from publishers, repositories, and other organizations met last month to kick off a project to promote open and Findable, Accessible, Interoperable, and Reusable (FAIR) data principles.