71 citations · 81 across the 4 of their papers we have counts for
4 papers · 1 filter
Indicator patterns of forced change learned by an artificial neural network
Elizabeth A. Barnes, Benjamin Toms, James W. Hurrell +3
Many problems in climate science require the identification of signals obscured by both the "noise" of internal climate variability and differences across models. Following previou…
Evaluation, Tuning and Interpretation of Neural Networks for Meteorological Applications
Imme Ebert-Uphoff, Kyle A. Hilburn
Neural networks have opened up many new opportunities to utilize remotely sensed images in meteorology. Common applications include image classification, e.g., to determine whether…
Development and Interpretation of a Neural Network-Based Synthetic Radar Reflectivity Estimator Using GOES-R Satellite Observations
Kyle A. Hilburn, Imme Ebert-Uphoff, Steven D. Miller
The objective of this research is to develop techniques for assimilating GOES-R Series observations in precipitating scenes for the purpose of improving short-term convective-scale…
Physically Interpretable Neural Networks for the Geosciences: Applications to Earth System Variability
Benjamin A. Toms, Elizabeth A. Barnes, Imme Ebert-Uphoff
Neural networks have become increasingly prevalent within the geosciences, although a common limitation of their usage has been a lack of methods to interpret what the networks lea…