Uncovering spatiotemporal micromobility patterns through the lens of space–time cubes and GIS tools

Journal of Geographical Systems - In the past ten years, cities have experienced a burst of micromobility services as they offer a flexible transport option that allows users to cover short trips...     

Real-time multi-model decadal climate predictions

We present the first climate prediction of the coming decade made with multiple models, initialized with prior observations. This prediction accrues from an international activity to exchange decadal predictions in near real-time, in order to assess differences and similarities, provide a consensus view to prevent over-confidence in forecasts from any single model, and establish current collective capability. We stress that the forecast is experimental, since the skill of the multi-model system is as yet unknown. Nevertheless, the forecast systems used here are based on models that have undergone rigorous evaluation and individually have been evaluated for forecast skill. Moreover, it is important to publish forecasts to enable open evaluation, and to provide a focus on climate change in the coming decade. Initialized forecasts of the year 2011 agree well with observations, with a pattern correlation of 0.62 compared to 0.31 for uninitialized projections. In particular, the forecast correctly predicted La Niña in the Pacific, and warm conditions in the north Atlantic and USA. A similar pattern is predicted for 2012 but with a weaker La Niña. Indices of Atlantic multi-decadal variability and Pacific decadal variability show no signal beyond climatology after 2015, while temperature in the Niño3 region is predicted to warm slightly by about 0.5 °C over the coming decade. However, uncertainties are large for individual years and initialization has little impact beyond the first 4 years in most regions. Relative to uninitialized forecasts, initialized forecasts are significantly warmer in the north Atlantic sub-polar gyre and cooler in the north Pacific throughout the decade. They are also significantly cooler in the global average and over most land and ocean regions out to several years ahead. However, in the absence of volcanic eruptions, global temperature is predicted to continue to rise, with each year from 2013 onwards having a 50 % chance of exceeding the current observed record. Verification of these forecasts will provide an important opportunity to test the performance of models and our understanding and knowledge of the drivers of climate change.     

A new method for the determination of the specific kinetic energy (SKE) released to pyroclastic particles at magmatic fragmentation: theory and first experimental results

Brittle magmatic fragmentation plays a crucial role in explosive eruptions. It represents the starting point of hazardous explosive events that can affect large areas surrounding erupting volcanoes. Knowing the initial energy released during this fragmentation process is fundamental for the understanding of the subsequent dynamics of the eruptive gas-particle mixture and consequently for the forecasting of the erupting column’s behavior. The specific kinetic energy (SKE) of the particles quantifies the initial velocity shortly after the fragmentation and is therefore a necessary variable to model the gas-particle conduit flow and eruptive column regime. In this paper, we present a new method for its determination based on fragmentation experiments and identification of the timings of energy release. The results obtained on compositions representative for basaltic and phonolitic melts show a direct dependence on magma material properties: poorly vesiculated basaltic melts from Stromboli show the highest SKE values ranging from 7.3 to 11.8 kJ/kg, while experiments with highly vesiculated samples from Stromboli and Vesuvius result in lower SKE values (3.1 to 3.8 kJ/kg). The described methodology presents a useful tool for quantitative estimation of the kinetic energy release of magmatic fragmentation processes, which can contribute to the improvement of hazard assessment.     

Discriminating the long distance dispersal of fine ash from sustained columns or near ground ash clouds: The example of the Pomici di Avellino eruption (Somma-Vesuvius,Italy)

Ash samples from tephra layers correlated with the Pomici di Avellino (Avellino Pumice) eruption of Somma-Vesuvius were collected in distal archives and their composition and particle morphology investigated in order to infer their behaviour of transportation and deposition. Differences in composition and particle morphologies were recognised for ash particles belonging to the magmatic Plinian and final phreatomagmatic phases of the eruption. The ash particles were dispersed in opposite directions during the two different phases of the eruption, and these directions are also different from that of coarse-grained fallout deposits. In particular, ash generated during magmatic phase and injected in the atmosphere to form a sustained column shows a prevailing SE dispersion, while ash particles generated during the final phreatomagmatic phase and carried by pyroclastic density currents show a general NW dispersion. These opposite dispersions indicate an ash dispersal influenced by both high and low atmosphere dynamics. In particular, the magmatic ash dispersal was first driven by stratospheric wind towards NE and then the falling particles encountered a variable wind field during their settling, which produced the observed preferential SE dispersal. The wind field encountered by the rising ash clouds that accompanied the pyroclastic density currents of the final phreatomagmatic phase was different with respect to that encountered by the magmatic ash, and produced a NW dispersal. These data demonstrate how ash transportation and deposition are greatly influenced by both high and low atmosphere dynamics. In particular, fine-grained particles transported in ash clouds of small-scale pyroclastic density currents may be dispersed over distances and cover areas comparable with those injected into the stratosphere by Plinian, sustained columns. This is a point not completely addressed by present day mitigation plans in case of renewal of activity at Somma-Vesuvius, and can yield important information also for other volcanoes potentially characterised by explosive activity.     

Spectral density regression for bivariate extremes

We introduce a density regression model for the spectral density of a bivariate extreme value distribution, that allows us to assess how extremal dependence can change over a covariate. Inference is performed through a double kernel estimator, which can be seen as an extension of the Nadaraya–Watson estimator where the usual scalar responses are replaced by mean constrained densities on the unit interval. Numerical experiments with the methods illustrate their resilience in a variety of contexts of practical interest. An extreme temperature dataset is used to illustrate our methods.