Spatio-Temporal Climate Data Causality Analytics – An Analysis of ENSO’s Global Impacts
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Hua 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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This is a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law
Abstract
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.