Developing trustworthy artificial intelligence for weather and ocean forecasting, as well as for long-term environmental sustainability, requires integrating collaborative efforts from many sources.
machine learning & AI
Posted inAGU News
The Rise of Machine Learning
Our August issue explores the way we process, analyze, and clearly present the massive amounts of information collected by scientists today.
Posted inEditors' Highlights
Who Wants to Count All the Craters on Mars? Not Me!
Humans found hundreds of thousands of craters on Mars greater than 1 kilometer in diameter, but now computers automate the process delivering crater counts as well as geologically meaningful ages.
Posted inEditors' Highlights
Ensemble Learning Estimates Terrestrial Water Storage Changes
Ensemble learning models for estimating past changes of terrestrial water storage from climate are presented and tested in the Pearl River basin, China.
Posted inNews
Urban Land Could Increase Sixfold by 2100
Experts agree that as urbanization continues through the 21st century, cities need to focus on sustainable development to meet climate goals.
Posted inResearch Spotlights
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.
Posted inFeatures
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.
Posted inScience Updates
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.
Posted inEditors' Highlights
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.
Posted inResearch Spotlights
Machine Learning Improves Weather and Climate Models
New research evaluates the performance of generative adversarial networks for stochastic parameterizations.