Journal
CLIMATE DYNAMICS
Volume -, Issue -, Pages -Publisher
SPRINGER
DOI: 10.1007/s00382-023-06804-9
Keywords
ENSO indices; Precipitation and surface temperature; Global influence
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This study examines the correlations between eleven ENSO indices and global precipitation and surface temperature. The results show that Nino3.4 and relative Nino3.4 indices are the strongest for capturing ENSO's impact on global precipitation, while Nino4 and Nino3.4 indices are the strongest for capturing ENSO's influence on surface temperature variations. The study also highlights the regional differences in the relationship between ENSO indices and climate variables.
Knowledge about the El Nino-Southern Oscillation (ENSO) is the scientific foundation for short-term climate prediction, due to its global influence. In operation and research communities, the ENSO state is often represented by various ENSO indices. However, it is unclear which index is the strongest for capturing ENSO's global climate influence. By examining the correlations of eleven ENSO indices with monthly mean global precipitation and surface temperature (TS), we illustrate the similarities and differences in the connections, identify the strongest index, and discuss the physics behind the differences. For the global average, the Nino3.4 and relative Nino3.4 indices are the two strongest indices and the warm pool index is the weakest one for capturing the impact of ENSO on global precipitation, while the Nino4 and Nino3.4 indices are the two strongest indices and the Modoki index is the weakest one for capturing the ENSO's influence on TS variations. In addition to the dependence on the variables and ENSO indices, the representations of climate variability associated with ENSO depend on the region. For example, in Australia, the southern oscillation index has the most significant correlations with precipitation and its correlations with TS are relatively weaker than those of some of the other indices. These differences associated with the various ENSO indices may be due to their representation of the deep convection in the tropical Pacific. These results can serve as a benchmark to understand the global picture of monthly mean precipitation and TS influenced by ENSO and to verify model's ability in capturing these connections.
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