Inferring Causal Relationships between Tropopause Polar Vortices and Arctic Cyclones [Slides]
- Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Causal inference methods are important to complement predictive machine learning models to improve theoretical understanding of the underlying system in climate science. Granger causality (GC) can determine whether time series value of one variable (e.g., X) can predict the future values of another variable (e.g., Y), but not the other way around.
- Research Organization:
- Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), Biological and Environmental Research (BER)
- DOE Contract Number:
- 89233218CNA000001
- OSTI ID:
- 1994086
- Report Number(s):
- LA-UR--23-28475
- Country of Publication:
- United States
- Language:
- English
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