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SUMMARY:Viewing Climate Signals through an AI Lens -  Elizabeth A. Barnes\
 , Associate Professor\, Dept. of Atmospheric Science\, CSU\, Fort Collins\
 , USA
DTSTART:20200427T130000Z
DTEND:20200427T140000Z
UID:TALK141808@talks.cam.ac.uk
CONTACT:Jonathan Rosser
DESCRIPTION:Much of climate science is viewed as a signal-to-noise problem
  and the field has many statistical methods for extracting the signal of i
 nterest. Here\, we argue that artificial neural networks (ANNs) are an add
 itional useful tool for the “climate toolbox”. As an example\, we demo
 nstrate their utility for extracting forced climate patterns from model si
 mulations and observations whereby the ANN identifies patterns that are co
 mplex\, non-linear combinations of signal and noise. While neural networks
  are often viewed as black boxes\, we further demonstrate how to visualize
  what the network has learned using recent advances in visualization tools
  within the computer science community. This approach suggests that viewin
 g climate patterns through an AI lens has the power to uncover new insight
 s into climate variability and change.\n
LOCATION:Zoom: https://ukri.zoom.us/j/94221989557
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