Abstract
Abstract. The timing of the first monsoon burst of the season, or
the monsoon onset, can be a critical piece of information for agriculture,
fire management, water management, and emergency response in monsoon regions.
Why do some monsoon seasons start earlier or later than others? Previous
research has investigated the impact of climate influences such as the El
Niño–Southern Oscillation (ENSO) on monsoon variability, but most
studies have considered only the impact on rainfall and not the timing of
the onset. While this question could be applied to any monsoon system,
this research presented in this paper has focused on the Australian monsoon.
Even with the wealth of research available on the variability of the
Australian monsoon season, the timing of the monsoon onset is one aspect of
seasonal variability that still lacks skilful seasonal prediction. To help
us better understand the influence of large-scale climate drivers on
monsoon onset timing, we recreated 11 previously published Australian
monsoon onset datasets and extended these to all cover the same period from
the 1950/1951 through the 2020/2021 Australian wet seasons. The extended
datasets were then tested for correlations with several standard climate
indices to identify which climate drivers could be used as predictors for
monsoon onset timing. The results show that many of the relationships
between monsoon onset dates and ENSO that were previously published are not
as strong when considering the extended datasets. Only a strong La Niña
pattern usually has an impact on monsoon onset timing, while ENSO-neutral
and El Niño patterns lacked a similar relationship. Detrended Indian
Ocean Dipole (IOD) data showed a weak relationship with monsoon onset dates,
but when the trend in the IOD data is retained, the relationship with onset
dates diminishes. Other patterns of climate variability showed little
relationship with Australian monsoon onset dates. Since ENSO is a tropical
climate process with global impacts, it is prudent to further re-examine its
influences in other monsoon regions too, with the aim to evaluate and
improve previously established prediction methodologies.
Cited by
11 articles.
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