A bivariate extension of the Hosking and Wallis goodness-of-fit measure for regional distributions

This study presents a bivariate extension of the goodness-of-fit measure for regional frequency distributions developed by Hosking and Wallis (1993) for use with the method of L-moments. Utilizing the approximate joint normal distribution of the regional L-skewness and L-kurtosis, a graphical representation of the confidence region on the L-moment diagram can be constructed as an ellipsoid. Candidate distributions can then be accepted where the corresponding theoretical relationship between the L-skewness and L-kurtosis intersects the confidence region, and the chosen distribution would be the one that minimizes the Mahalanobis distance measure. Based on a set of Monte Carlo simulations, it is demonstrated that the new bivariate measure generally selects the true population distribution more frequently than the original method. Results are presented to show that the new measure remains robust when applied to regions where the level of intersite correlation is at a level found in real world regions. Finally the method is applied to two different case studies involving annual maximum peak flow data from Italian and British catchments to identify suitable regional frequency distributions.This study presents a bivariate extension of the goodness-of-fit measure for regional frequency distributions developed by Hosking and Wallis (1993) for use with the method of L-moments. Utilizing the approximate joint normal distribution of the regional L-skewness and L-kurtosis, a graphical representation of the confidence region on the L-moment diagram can be constructed as an ellipsoid. Candidate distributions can then be accepted where the corresponding theoretical relationship between the L-skewness and L-kurtosis intersects the confidence region, and the chosen distribution would be the one that minimizes the Mahalanobis distance measure. Based on a set of Monte Carlo simulations, it is demonstrated that the new bivariate measure generally selects the true population distribution more frequently than the original method. Results are presented to show that the new measure remains robust when applied to regions where the level of intersite correlation is at a level found in real world regions. Finally the method is applied to two different case studies involving annual maximum peak flow data from Italian and British catchments to identify suitable regional frequency distributions. Key Points: A new bivariate GOF measure for regional frequency distributions using L-moments New measure performs better than existing Hosking and Wallis measure New measure performs well in homogeneous but moderately correlated region

Observing solar-like oscillations

We review techniques for measuring stellar oscillations in solar-type stars. Despite great efforts, no unambiguous detections have been made. A new method, based on monitoring the equivalent widths of strong lines, shows promise but is yet to be confirmed. We also discuss several subtleties, such as the need to correct for CCD non-linearities and the importance of data weighting

Gravity modes as a way to distinguish between hydrogen- and helium-burning red giant stars

Red giants are evolved stars that have exhausted the supply of hydrogen in their cores and instead burn hydrogen in a surrounding shell. Once a red giant is sufficiently evolved, the helium in the core also undergoes fusion. Outstanding issues in our understanding of red giants include uncertainties in the amount of mass lost at the surface before helium ignition and the amount of internal mixing from rotation and other processes. Progress is hampered by our inability to distinguish between red giants burning helium in the core and those still only burning hydrogen in a shell. Asteroseismology offers a way forward, being a powerful tool for probing the internal structures of stars using their natural oscillation frequencies. Here we report observations of gravity-mode period spacings in red giants that permit a distinction between evolutionary stages to be made. We use high-precision photometry obtained with the Kepler spacecraft over more than a year to measure oscillations in several hundred red giants. We find many stars whose dipole modes show sequences with approximately regular period spacings. These stars fall into two clear groups, allowing us to distinguish unambiguously between hydrogen-shell-burning stars (period spacing mostly about 50 seconds) and those that are also burning helium (period spacing about 100 to 300 seconds).Comment: to appear as a Letter to Natur

Identification of coherent flood regions across Europe by using the longest streamflow records

This study compiles a new dataset, consisting of the longest available flow series from across Europe, and uses it to study the spatial and temporal clustering of flood events across the continent. Hydrological series at 102 gauging stations were collected from 25 European countries. Five geographically distinct large-scale homogeneous regions are identified: (i) an Atlantic region, (ii) a Continental region, (iii) a Scandinavian region, (iv) an Alpine region, and (v) a Mediterranean region. The months with a higher likelihood of flooding were identified in each region. The analysis of the clustering of annual counts of floods revealed an over-dispersion in the Atlantic and Continental regions, forming flood-rich and flood-poor periods, as well as an under-dispersion in the Scandinavian region that points to a regular pattern of flood occurrences at the inter-annual scale. The detection of trends in flood series is attempted by basing it on the identified regions, interpreting the results at a regional scale and for various time periods: 1900-1999; 1920-1999; 1939-1998 and 1956-1995. The results indicate that a decreasing trend in the magnitude of floods was observed mainly in the Continental region in the period 1920-1999 with 22% of the catchments revealing such a trend, as well as a decreasing trend in the timing of floods in the Alpine region in the period 1900-1999 with 75% of the catchments revealing this trend. A mixed pattern of changes in the frequency of floods over a threshold and few significant changes in the timing of floods were detected

Asteroseismology

Asteroseismology is the determination of the interior structures of stars by using their oscillations as seismic waves. Simple explanations of the astrophysical background and some basic theoretical considerations needed in this rapidly evolving field are followed by introductions to the most important concepts and methods on the basis of example. Previous and potential applications of asteroseismology are reviewed and future trends are attempted to be foreseen.Comment: 38 pages, 13 figures, to appear in: "Planets, Stars and Stellar Systems", eds. T. D. Oswalt et al., Springer Verla

Asteroseismology of red giants as a tool for studying stellar populations: first steps

The detection of solar-like oscillations in G and K giants with the CoRoT and Kepler space-based satellites allows robust constraints to be set on the mass and radius of such stars. The availability of these constraints for thousands of giants sampling different regions of the Galaxy promises to enrich our understanding on the Milky Way's constituents. In this contribution we briefly recall which are the relevant constraints that red-giant seismology can currently provide to the study of stellar populations. We then present, for a few nearby stars, the comparison between radius and mass determined using seismic scaling relations and those obtained by other methods.Comment: Proc. of the workshop "Red Giants as Probes of the Structure and Evolution of the Milky Way" (Roma, 15-17 Nov 2010), Astrophysics and Space Science Proceedings, ISBN 978-3-642-18417-8 (eds. A. Miglio, J. Montalban, A. Noels). Part of RedGiantsMilkyWay/2011/ proceedings available at http://arxiv.org/html/1108.4406v

Integrated modeling in urban hydrology: reviewing the role of monitoring technology in overcoming the issue of ‘big data’ requirements

Increasingly, the application of models in urban hydrology has undergone a shift toward integrated structures that recognize the interconnected nature of the urban landscape and both the natural and engineered water cycles. Improvements in computational processing during the past few decades have enabled the application of multiple, connected model structures that link previously disparate systems together, incorporating feedbacks and connections. Many applications of integrated models look to assess the impacts of environmental change on physical dynamics and quality of landscapes. Whilst these integrated structures provide a more robust representation of natural dynamics, they often place considerable data requirements on the user, whereby data are required at contrasting spatial and temporal scales which can often transcend multiple disciplines. Concomitantly, our ability to observe complex, natural phenomena at contrasting scales has improved considerably with the advent of increasingly novel monitoring technologies. This has provided a pathway for reducing model uncertainty and improving our confidence in modeled outputs by implementing suitable monitoring regimes. This commentary assesses how component models of an exemplar integrated model have advanced over the past few decades, with a critical focus on the role of monitoring technologies that have enabled better identification of the key physical process. This reduces the uncertainty of processes at contrasting spatial and temporal scales, through a better characterization of feedbacks which then enhances the utility of integrated model applications

Asteroseismology and Interferometry

Asteroseismology provides us with a unique opportunity to improve our understanding of stellar structure and evolution. Recent developments, including the first systematic studies of solar-like pulsators, have boosted the impact of this field of research within Astrophysics and have led to a significant increase in the size of the research community. In the present paper we start by reviewing the basic observational and theoretical properties of classical and solar-like pulsators and present results from some of the most recent and outstanding studies of these stars. We centre our review on those classes of pulsators for which interferometric studies are expected to provide a significant input. We discuss current limitations to asteroseismic studies, including difficulties in mode identification and in the accurate determination of global parameters of pulsating stars, and, after a brief review of those aspects of interferometry that are most relevant in this context, anticipate how interferometric observations may contribute to overcome these limitations. Moreover, we present results of recent pilot studies of pulsating stars involving both asteroseismic and interferometric constraints and look into the future, summarizing ongoing efforts concerning the development of future instruments and satellite missions which are expected to have an impact in this field of research.Comment: Version as published in The Astronomy and Astrophysics Review, Volume 14, Issue 3-4, pp. 217-36

Wastewater-based epidemiology in hazard forecasting and early-warning systems for global health risks

With the advent of the SARS-CoV-2 pandemic, Wastewater-Based Epidemiology (WBE) has been applied to track community infection in cities worldwide and has proven succesful as an early warning system for identification of hotspots and changingprevalence of infections (both symptomatic and asymptomatic) at a city or sub-city level. Wastewater is only one of environmental compartments that requires consideration. In this manuscript, we have critically evaluated the knowledge-base and preparedness for building early warning systems in a rapidly urbanising world, with particular attention to Africa, which experiences rapid population growth and urbanisation. We have proposed a Digital Urban Environment Fingerprinting Platform (DUEF) – a new approach in hazard forecasting and early-warning systems for global health risks and an extension to the existing concept of smart cities. The urban environment (especially wastewater) contains a complex mixture of substances including toxic chemicals, infectious biological agents and human excretion products. DUEF assumes that these specific endo- and exogenous residues, anonymously pooled by communities’ wastewater, are indicative of community-wide exposure and the resulting effects. DUEF postulates that the measurement of the substances continuously and anonymously pooled by the receiving environment (sewage, surface water, soils and air), can provide near real-time dynamic information about the quantity and type of physical, biological or chemical stressors to which the surveyed systems are exposed, and can create a risk profile on the potential effects of these exposures. Successful development and utilisation of a DUEF globally requires a tiered approach including: Stage I: network building, capacity building, stakeholder engagement as well as a conceptual model, followed by Stage II: DUEF development, Stage III: implementation, and Stage IV: management and utilization. We have identified four key pillars required for the establishment of a DUEF framework: (1) Environmental fingerprints, (2) Socioeconomic fingerprints, (3) Statistics and modelling and (4) Information systems. This manuscript critically evaluates the current knowledge base within each pillar and provides recommendations for further developments with an aim of laying grounds for successful development of global DUEF platforms