Machine learning is used to retrieve global snowfall occurrence and rate from satellite-based passive microwave sounder observations, trained by snowfall data from a high-quality space borne radar.
machine learning & AI
Posted inResearch Spotlights
Boosting Weather Prediction with Machine Learning
WeatherBench is a data set compiled to serve as a standard for evaluating new approaches to artificial intelligence–driven weather forecasting.
Posted inResearch Spotlights
Modeling Gravity Waves with Machine Learning
Researchers used neural networks to better define the parameterizations necessary for modeling the distribution and characteristics of orographic gravity waves.
Posted inScience Updates
Advancing AI for Earth Science: A Data Systems Perspective
Tackling data challenges and incorporating physics into machine learning models will help unlock the potential of artificial intelligence to answer Earth science questions.
Posted inEditors' Highlights
Machine Learning for Magnetics
Classic interpretation of aeromagnetic anomaly maps involves several steps with limiting boundary conditions; a recent study develops convolutional networks largely bypassing these issues.
Posted inEditors' Vox
Tackling 21st Century Geoscience Problems with Machine Learning
A new cross-journal special collection invites contributions on how machine learning can be used for solid Earth observation, modeling and understanding.
Posted inResearch Spotlights
Interpreting Neural Networks’ Reasoning
New methods that help researchers understand the decision-making processes of neural networks could make the machine learning tool more applicable for the geosciences.
Posted inEditors' Highlights
Machine Learning Predicts Subsidence from Groundwater Pumping
Machine learning and data on aquifer type, sediment thickness, and proxies for irrigation water use has been used to produce the most comprehensive map of land subsidence in the western U.S. to date.
Posted inOpinions
Earth System Modeling Must Become More Energy Efficient
As weather and climate models grow larger and more data intensive, the amount of energy needed to run them continues to increase. Are researchers doing enough to minimize the carbon footprint of their computing?
Posted inOpinions
Weathering Environmental Change Through Advances in AI
Developing trustworthy artificial intelligence for weather and ocean forecasting, as well as for long-term environmental sustainability, requires integrating collaborative efforts from many sources.