2016

Application of Deep Convolutional Neural Networks for Detecting Extreme Weather in Climate Datasets

Liu, Yunjie, Racah, Evan, Prabhat et al.

Understand

Detecting extreme events in large datasets is a major challenge in climate science research.

Current algorithms for extreme event detection are build upon human expertise in defining events based on subjective thresholds of relevant physical variables.
Often, multiple competing methods produce vastly different results on the same dataset.
Accurate characterization of extreme events in climate simulations and observational data archives is critical for understanding the trends and potential impacts of such events in a climate change content.

Built on

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