Magnitude and Symmetry of Divergent Heat Flux Anomalies Associated with the El Niño–Southern Oscillation

El Niño-Southern Oscillation (ENSO) alters the flow of heat from tropical to polar latitudes. Improved global scale understanding of ENSO-induced climate variability is complicated by irregularly spaced climate observations over land and the lack of observations over oceans. Observational inconsistencies suggest modelling efforts may be needed, but explicitly modelling precipitation or surface air temperature is complicated by parameterizations of subgrid-scale processes. However, modeling anomalies by quantifying the residual of mass and energy budgets does not rely on subgrid-scale parameterization and thus may improve understanding of global scale ENSO-induced precipitation and surface temperature anomalies. The objective of the current work was to quantify the magnitude and symmetry of vertically integrated latent and sensible heat flux divergence anomalies that represent the residual (i.e. sources and sinks) of atmospheric mass and energy budgets at seasonal and monthly (December, January, February) scales. High spatial (~80 km) and temporal (6-hourly) resolution ERA-Interim output was used to quantify heat flux divergence anomalies during all ENSO events (n = 25) occurring between 1979 and 2016. Results show regionally distinct patterns during each ENSO phase and despite a larger symmetric component, asymmetry is shown to be fundamental to ENSO-induced weather anomalies. The asymmetric component was particularly large across the North Atlantic Ocean and Eurasia invalidating the common assumption that each phase of ENSO results in equal and opposite weather anomalies at the global scale. Based on results, the authors hypothesize that asymmetries may be proportional to differences in position or magnitude of sea surface temperature anomalies during each phase of ENSO. The current work advances understanding of ENSO dynamics and the problem of ENSO-induced anomalies at the global scale, which may increase predictability of future ENSO-induced precipitation and surface temperature anomalies.