Ensemble learning models for estimating past changes of terrestrial water storage from climate are presented and tested in the Pearl River basin, China.
machine learning & AI
The Perils of Computing Too Much and Thinking Too Little
Big steps forward are synonymous with new ideas – a thought that merits mindfulness if we aspire to train students to do more than merely train machines.
Machine Learning Can Help Decode Alien Skies—Up to a Point
Astronomers are testing the tools that might help them keep up with the upcoming storm of exoplanet atmosphere data.
Teaching Machines to Detect Climate Extremes
Artificial intelligence can be used to analyze massive amounts of data from climate simulations, but more training data are needed.
Improving Atmospheric Forecasts with Machine Learning
An efficient, low-resolution machine learning model can usefully predict the global atmospheric state as much as 3 days out.
How Machine Learning Redraws the Map of Ocean Ecosystems
Using an unsupervised learning algorithm, scientists can create new maps of ecosystem provinces in the ocean, opening the possibility of sharper data collection and monitoring.
Visualizing Science: How Color Determines What We See
Color plays a major role in the analysis and communication of scientific information. New tools are helping to improve how color can be applied more accurately and effectively to data.
Creating Data Tool Kits That Everyone Can Use
Earth scientists outline challenges to making the growing wealth of available data more accessible and to using data services for interdisciplinary research and applications.
Are Cosmic Rays a Key to Forecasting Volcanic Eruptions?
A combination of relativistic particles and artificial intelligence may provide a new way to forecast when a volcano could erupt.
A New Global Map of Seafloor Fluid Expulsion Anomalies
The first open-source database of SEAfloor FLuid Expulsion Anomalies (SEAFLEASs) at a global scale reveals their distribution and physical parameters.