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Abstract. Flooding in the Amazon basin is frequently attributed to modes of large-scale climate variability, but little attention is paid to how these modes influence the timing and duration of floods despite their importance to early warning systems and the significant impacts that these flood characteristics can have on communities. In this study, river discharge data from the Global Flood Awareness System (GloFAS 2.1) and observed data at 58 gauging stations are used to examine whether positive or negative phases of several Pacific and Atlantic indices significantly alter the characteristics of river flows throughout the Amazon basin (1979–2015). Results show significant changes in both flood magnitude and duration, particularly in the north-eastern Amazon for negative El Niño–Southern Oscillation (ENSO) phases when the sea surface temperature (SST) anomaly is positioned in the central tropical Pacific. This response is not identified for the eastern Pacific index, highlighting how the response can differ between ENSO types. Although flood magnitude and duration were found to be highly correlated, the impacts of large-scale climate variability on these characteristics are non-linear; some increases in annual flood maxima coincide with decreases in flood duration. The impact of flood timing, however, does not follow any notable pattern for all indices analysed. Finally, observed and simulated changes are found to be much more highly correlated for negative ENSO phases compared to the positive phase, meaning that GloFAS struggles to accurately simulate the differences in flood characteristics between El Niño and neutral years. These results have important implications for both the social and physical sectors working towards the improvement of early warning action systems for floods.

Alcohol use, binge drinking, and alcohol use disorders have been increasing among older adults in the US population, including adults over 50 as well as adults over 65. Increases in consumption are sharper among women, and among those who use additional substances such as cannabis, and those who are relatively healthy in older adulthood (i.e. those without multimorbidites). This commentary describes these trends as well as provides hypotheses, and the data underlying them, for both supply-side (alcohol marketing and messaging) and demand-side (healthier aging, increased financial stress) potential drivers of these increases. The need for additional resources and focus on older adult drinking is increasingly urgent, as alcohol-attributable deaths escalate among older adults in the United States.

Photovoltaic (PV) systems play an important role in contemporary electricity production as a ubiquitous renewable energy source. However, the performance of a PV system is susceptible to unexpected faults that occur inside its various components. In this paper, we propose a quickest fault detection algorithm for PV systems under the sequential change detection framework. In particular, multiple meters are employed to measure different output signals of the PV system. The time correlation of the faulty signal and the signal correlation among different meters are exploited by a vector AR model in modeling the post-change signal. In order to tackle the difficulty that no prior knowledge about the fault is available, we develop a change detection algorithm based on the generalized local likelihood ratio test. Extensive simulation results demonstrate that the proposed method achieves high adaptivity and fast detection in dealing with various types of faults in PV systems.

Abstract The dynamics of isolated-photon plus two-jet production in pp collisions at a centre-of-mass energy of 13 TeV are studied with the ATLAS detector at the LHC using a dataset corresponding to an integrated luminosity of 36.1 fb−1. Cross sections are measured as functions of a variety of observables, including angular correlations and invariant masses of the objects in the final state, γ + jet + jet. Measurements are also performed in phase-space regions enriched in each of the two underlying physical mechanisms, namely direct and fragmentation processes. The measurements cover the range of photon (jet) transverse momenta from 150 GeV (100 GeV) to 2 TeV. The tree-level plus parton-shower predictions from Sherpa and Pythia as well as the next-to-leading-order QCD predictions from Sherpa are compared with the measurements. The next-to-leading-order QCD predictions describe the data adequately in shape and normalisation except for regions of phase space such as those with high values of the invariant mass or rapidity separation of the two jets, where the predictions overestimate the data.