Recent hurricane seasons left many communities wondering if this is the new normal. Digital infrastructure designed for citizen data collection may help these communities increase resilience.
data management
Posted inScience Updates
Putting the Cloud to Work for Seismology
The cloud infrastructure developed in the business community has made access to cluster computing possible for even the smallest research groups, enabling new kinds of research workflows in geophysics.
Posted inScience Updates
Compiling a Census for SEAFLEAs
Collaboration to Compile Open-Source Sites of Seafloor Fluid Expulsion Anomalies, AGU Fall Meeting 2018; Washington, D.C., 14 December 2018
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 inScience Updates
A Digital Mayfly Swarm Is Emerging
Low-cost, open-source data collectors and a suite of collaborative online tools are making big leaps in the field of watershed monitoring.
Posted inOpinions
It’s Time to Shift Emphasis Away from Code Sharing
Building well-documented, citable frameworks for Earth data analysis will encourage scientific replicability by addressing the underlying issues that inhibit code sharing.
Posted inScience Updates
Soil Moisture Data Sets Become Fertile Ground for Applications
An integrated data platform harmonizes many disparate soil moisture data sets to better inform disaster response planners, climate scientists and meteorologists, farmers, and others.
Posted inOpinions
Stress Testing for Climate Impacts with “Synthetic Storms”
How well would your city weather a hurricane? Digitally “moving” past storms to new locations simulates the effects of extreme weather events on local infrastructure.
Posted inScience Updates
Launching an Accessible Archive of Environmental Data
A new digital archive enables community use of terrestrial and subsurface ecosystem data sets.
Posted inResearch Spotlights
Evaluating the Efficiency of Data Assimilation
Information is lost when researchers combine statistical models and remote sensing data, but just how much is often unclear. A new study offers a framework to measure the inefficiency.