Spatio-Temporal Climate Data Causality Analytics – An Analysis of ENSO’s Global Impacts
Links to Fileshttps://par.nsf.gov/servlets/purl/10110745
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Type of Work4 pages
conference papers and proceedings
Citation of Original PublicationHua Song et al., SPATIO-TEMPORAL CLIMATE DATA CAUSALITY ANALYTICS – AN ANALYSIS OF ENSO’S GLOBAL IMPACTS, https://par.nsf.gov/servlets/purl/10110745
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Numerous studies have indicated that El Niño and the Southern Oscillation (ENSO) could have determinant impacts on remote weather and climate using the conventional correlation-based methods, which however cannot identify cause-and-effect of such linkage and ultimately determine a direction of causality. This study employs the Vector Auto-Regressive (VAR) model estimation method with the long-term observational data and reanalysis data to demonstrate that ENSO is the modulating factor that can result in abnormal surface temperature, pressure, precipitation and wind circulation remotely. We also carry out the sensitivity simulations using the Community Atmospheric Model (CAM) to further support the causality relations between ENSO and abnormal climate events in remote regions.
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