Using Causal Discovery to Learn about Our Planet’s Climate - Recent Progress
نویسندگان
چکیده
Causal discovery is the process of identifying cause-and-effect hypotheses from observational data. We use causal discovery to construct networks that track interactions around the globe based on time series data of atmospheric fields, such as daily geopotential height data. At last year’s workshop we explained the basic concepts of using this approach to identify climate properties. Here we report recent progress, namely (1) an analysis of anticipated changes in the climate’s network structure under enhanced greenhouse gases (GHGs) and (2) computational advances that allow us to move to spatial networks.
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