Understanding the variability of Australian fire weather between 1973 and 2017.

Australian fire weather shows spatiotemporal variability on interannual and multi-decadal time scales. We investigate the climate factors that drive this variability using 39 station-based historical time series of the seasonal 90th-percentile of the McArthur Forest Fire Danger Index (FFDI) extending from 1973 through 2017. Using correlation analyses, we examine the relationship of these time series to the El Niño Southern Oscillation (ENSO), the Southern Annular Mode (SAM) and the Indian Ocean Dipole (IOD), considering both concurrent and time-lagged relationships. Additionally, longer term behaviour of the time series using linear trend analysis is discussed in the context of the climate drivers, Interdecadal Pacific Oscillation (IPO) and anthropogenic climate change. The results show that ENSO is the main driver for interannual variability of fire weather, as defined by FFDI in this study, for most of Australia. In general, El Niño-like conditions lead to more extreme fire weather, with this effect stronger in eastern Australia. However, there are significant regional variations to this general rule. In NSW, particularly along the central coast, negative SAM is a primary influence for elevated fire weather in late-winter and spring. In the southeast (VIC and TAS), the El Niño-like impact is exacerbated when positive IOD conditions are simultaneously observed. The spring conditions are key, and strongly influence what is observed during the following summer. On longer time scales (45 years), linear trends are upward at most stations; this trend is strongest in the southeast and during the spring. The positive trends are not driven by the trends in the climate drivers and they are not consistent with hypothesized impacts of the IPO, either before or after its late-1990s shift to the cold phase. We propose that anthropogenic climate change is the primary driver of the trend, through both higher mean temperatures and potentially through associated shifts in large-scale rainfall patterns. Variations from interannual factors are generally larger in magnitude than the trend effects observed to date.

XMaS @ the ESRF.

This paper describes the motivation for the design and construction of a beamline at the European Synchrotron Radiation Facility (ESRF) for the use of UK material scientists. Although originally focused on the study of magnetic materials, the beamline has been running for 20 years and currently supports a very broad range of science as evidenced by the research topics highlighted in this article. We describe how the beamline will adapt to align with the ESRF's upgrade to a diffraction limited storage ring. This article is part of the theme issue 'Fifty years of synchrotron science: achievements and opportunities'.

Water corrosion of spent nuclear fuel: radiolysis driven dissolution at the UO2/water interface.

X-ray diffraction has been used to probe the radiolytic corrosion of uranium dioxide. Single crystal thin films of UO(2) were exposed to an intense X-ray beam at a synchrotron source in the presence of water, in order to simultaneously provide radiation fields required to split the water into highly oxidising radiolytic products, and to probe the crystal structure and composition of the UO(2) layer, and the morphology of the UO(2)/water interface. By modeling the electron density, surface roughness and layer thickness, we have been able to reproduce the observed reflectivity and diffraction profiles and detect changes in oxide composition and rate of dissolution at the Ångström level, over a timescale of several minutes. A finite element calculation of the highly oxidising hydrogen peroxide product suggests that a more complex surface interaction than simple reaction with H(2)O(2) is responsible for an enhancement in the corrosion rate directly at the interface of water and UO(2), and this may impact on models of long-term storage of spent nuclear fuel.

Inferring hidden causal structure.

We used a new method to assess how people can infer unobserved causal structure from patterns of observed events. Participants were taught to draw causal graphs, and then shown a pattern of associations and interventions on a novel causal system. Given minimal training and no feedback, participants in Experiment 1 used causal graph notation to spontaneously draw structures containing one observed cause, one unobserved common cause, and two unobserved independent causes, depending on the pattern of associations and interventions they saw. We replicated these findings with less-informative training (Experiments 2 and 3) and a new apparatus (Experiment 3) to show that the pattern of data leads to hidden causal inferences across a range of prior constraints on causal knowledge.

Evolving an integral ecology of mind.

A deliberation upon the possibility of generating a comprehensive view of 'mind as a whole' by integrating biology, psychology and sociology, and considering 'Mind' as a dynamical interplay between values existing over many levels and scales of complex systems. This view of mind as a coevolutionary whole is related to similar ecological viewpoints being developed in the fields of artificial life and multi-agent systems. A meta-model of mind is proposed which attempts to integrate the various existing views of mind from a time perspective, and positions the field in a way that we think augurs well for the potential of mind studies based upon modern complex systems science concepts.