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Danielle G. Udy, Tessa R. Vance, Anthony S. Kiem, Neil J. Holbrook, and Mark A. J. Curran


Weather systems in the southern Indian Ocean (SIO) drive synoptic-scale precipitation variability in East Antarctica and southern Australia. Improved understanding of these dynamical linkages is beneficial to diagnose long-term climate changes from climate proxy records as well as informing regional weather and climate forecasts. Self-organizing maps (SOMs) are used to group daily 500-hPa geopotential height (z500; ERA-Interim) anomalies into nine regional synoptic types based on their dominant patterns over the SIO (30°–75°S, 40°–180°E) from January 1979 to October 2018. The pattern anomalies represented include four meridional, three mixed meridional–zonal, one zonal, and one transitional node. The frequency of the meridional nodes shows limited association with the phase of the southern annular mode (SAM), especially during September–November. The zonal and mixed patterns were nevertheless strongly and significantly correlated with SAM, although the regional synoptic representation of SAM+ conditions was not zonally symmetric and was represented by three separate nodes. We recommend consideration of how different synoptic conditions vary the atmospheric representation of SAM+ in any given season in the SIO. These different types of SAM+ mean a hemispheric index fails to capture the regional variability in surface weather conditions that is primarily driven by the synoptic variability rather than the absolute polarity of the SAM.

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Michelle Ho, Danielle C. Verdon-Kidd, Anthony S. Kiem, and Russell N. Drysdale


Recent advances in the collection and analysis of paleoclimate data have provided significant insights into preinstrumental environmental events and processes, enabling a greater understanding of long-term environmental change and associated hydroclimatic risks. Unfortunately, it is often the case that there is a dearth of readily available paleoclimate data from regions where such insights and long-term data are most needed. The Murray–Darling basin (MDB), known as Australia’s “food bowl,” is an example of such a region where currently there are very limited in situ paleoclimate data available. While previous studies have utilized paleoclimate proxy records of large-scale climate mechanisms to infer preinstrumental MDB hydroclimatic variability, there is a lack of studies that utilize Australian terrestrial proxy records to garner similar information. Given the immediate need for improved understanding of MDB hydroclimatic variability, this paper identifies key locations in Australia where existing and as yet unrealized paleoclimate records will be most useful in reconstructing such information. To identify these key locations, rainfall relationships between MDB and non-MDB locations were explored through correlations and principal component analysis. An objective analysis using optimal interpolation was then used to pinpoint the most strategic locations to further develop proxy records and gain insights into the benefits of obtaining this additional information. The findings reveal that there is potential for the future assembly of high-resolution paleoclimate records in Australia capable of informing MDB rainfall variability, in particular southeast Australia and central-northern Australia. This study highlights the need for further investment in the development of these potential proxy sources to subsequently enable improved assessments of long-term hydroclimatic risks.

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