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Mechanisms of multiyear variations of Northern Australia wet-season rainfall

Northern Australia wet season (November–April) rainfall exhibits strong variability on multiyear timescales. In order to reveal the underlying mechanisms of this variability, we investigate observational records for the period 1900–2017. At multiyear timescales, the rainfall varies coherently across...

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Detalles Bibliográficos
Autores principales: Sharmila, S., Hendon, Harry H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7083836/
https://www.ncbi.nlm.nih.gov/pubmed/32198353
http://dx.doi.org/10.1038/s41598-020-61482-5
Descripción
Sumario:Northern Australia wet season (November–April) rainfall exhibits strong variability on multiyear timescales. In order to reveal the underlying mechanisms of this variability, we investigate observational records for the period 1900–2017. At multiyear timescales, the rainfall varies coherently across north-western Australia (NW) and north-eastern Australia (NE), but the variability in these two regions is largely independent. The variability in the NE appears to be primarily controlled by the remote influence of low frequency variations of El Niño-Southern Oscillation (ENSO). In contrast, multiyear variations in the NW appear to be largely driven locally and stem from a combination of rainfall-wind-evaporation feedback, whereby enhanced land-based rainfall is associated with westerly wind anomalies to the west that enhance local evaporation over the ocean to feed the enhanced land based rainfall, and soil moisture-rainfall feedback. Soil-moisture and associated evapotranspiration over northern Australia appear to act as sources of memory for sustaining multiyear wet and dry conditions in the NW. Our results imply that predictability of multiyear rainfall variations over the NW may derive from the initial soil moisture state and its memory, while predictability in the NE will be limited by the predictability of the low frequency variations of ENSO.