GALACSI – The ground layer adaptive optics system for MUSE

MUSE, the Multi-Unit Spectroscopic Explorer, is an adaptive optics (AO)-assisted Integral Field Spectrograph, currently in the Preliminary Design Phase as a second generation instrument for the VLT. MUSE will feature two modes, each with an associated AO mode. The first mode is the wide field mode, mainly aiming at the study of high redshift galaxies. For this mode, the AO system has to deliver an improvement of at least a factor of two over the full 1′ × 1′ field of view. The second mode, the narrow field mode, aims at the high-resolution spectroscopy of nearby extended objects, for example, galaxies and globular clusters. For this mode, the AO system will have to deliver near-diffraction limited performance over a small field of view. In this paper, we discuss the trade-offs in the current design of GALACSI – the MUSE AO system – and illustrate with a number of simulations the expected performance in the wide- and narrow field modes.     

Seismic strengthening of existing RC buildings with external cross-laminated timber (CLT) walls hosting an integrated energetic and architectural renovation

Bulletin of Earthquake Engineering - In this study a timber-based integrated solution is presented to solve at once common issues affecting typical reinforced concrete (RC) existing buildings, such...     

National-scale data-driven rainfall induced landslide susceptibility mapping for China by accounting for incomplete landslide data

China is one of the countries where landslides caused the most fatalities in the last decades.The threat that landslide disasters pose to people might even be greater in the future,due to climate change and the increasing urbanization of mountainous areas.A reliable national-scale rainfall induced landslide suscep-tibility model is therefore of great relevance in order to identify regions more and less prone to landslid-ing as well as to develop suitable risk mitigating strategies.However,relying on imperfect landslide data is inevitable when modelling landslide susceptibility for such a large research area.The purpose of this study is to investigate the influence of incomplete landslide data on national scale statistical landslide susceptibility modeling for China.In this context,it is aimed to explore the benefit of mixed effects mod-elling to counterbalance associated bias propagations.Six influencing factors including lithology,slope,soil moisture index,mean annual precipitation,land use and geological environment regions were selected based on an initial exploratory data analysis.Three sets of influencing variables were designed to represent different solutions to deal with spatially incomplete landslide information:Set 1(disregards the presence of incomplete landslide information),Set 2(excludes factors related to the incompleteness of landslide data),Set 3(accounts for factors related to the incompleteness via random effects).The vari-able sets were then introduced in a generalized additive model(GAM:Set 1 and Set 2)and a generalized additive mixed effect model(GAMM:Set 3)to establish three national-scale statistical landslide suscep-tibility models:models 1,2 and 3.The models were evaluated using the area under the receiver operating characteristics curve(AUROC)given by spatially explicit and non-spatial cross-validation.The spatial pre-diction pattern produced by the models were also investigated.The results show that the landslide inven-tory incompleteness had a substantial impact on the outcomes of the statistical landslide susceptibility models.The cross-validation results provided evidence that the three established models performed well to predict model-independent landslide information with median AUROCs ranging from 0.8 to 0.9.However,although Model 1 reached the highest AUROCs within non-spatial cross-validation(median of 0.9),it was not associated with the most plausible representation of landslide susceptibility.The Model 1 modelling results were inconsistent with geomorphological process knowledge and reflected a large extent the underlying data bias.The Model 2 susceptibility maps provided a less biased picture of landslide susceptibility.However,a lower predicted likelihood of landslide occurrence still existed in areas known to be underrepresented in terms of landslide data(e.g.,the Kuenlun Mountains in the northern Tibetan Plateau).The non-linear mixed-effects model(Model 3)reduced the impact of these biases best by introducing bias-describing variables as random effects.Among the three models,Model 3 was selected as the best national-scale susceptibility model for China as it produced the most plausible portray of rainfall induced landslide susceptibility and the highest spatially explicit predictive perfor-mance(median AUROC of spatial cross validation 0.84)compared to the other two models(median AUROCs of 0.81 and 0.79,respectively).We conclude that ignoring landslide inventory-based incomplete-ness can entail misleading modelling results and that the application of non-linear mixed-effect models can reduce the propagation of such biases into the final results for very large areas.     

Consistency of seven different GNSS global ionospheric mapping techniques during one solar cycle

In the context of the International GNSS Service (IGS), several IGS Ionosphere Associated Analysis Centers have developed different techniques to provide global ionospheric maps (GIMs) of vertical total electron content (VTEC) since 1998. In this paper we present a comparison of the performances of all the GIMs created in the frame of IGS. Indeed we compare the classical ones (for the ionospheric analysis centers CODE, ESA/ESOC, JPL and UPC) with the new ones (NRCAN, CAS, WHU). To assess the quality of them in fair and completely independent ways, two assessment methods are used: a direct comparison to altimeter data (VTEC-altimeter) and to the difference of slant total electron content (STEC) observed in independent ground reference stations (dSTEC-GPS). The main conclusion of this study, performed during one solar cycle, is the consistency of the results between so many different GIM techniques and implementations.     

ShakeMap-based prediction of earthquake-induced mass movements in Switzerland calibrated on historical observations

Natural Hazards - In Switzerland, nearly all historical Mw?~?6 earthquakes have induced damaging landslides, rockslides and snow avalanches that, in some cases, also resulted in damage...     

An experimental investigation of Na incorporation in cordierite in low P/high T metapelites

Mineralogy and Petrology - The aim of this experimental study was to investigate the incorporation of Na in cordierite in metapelites as a function of temperature and pressure using natural...     

Subaqueous landslide-triggered tsunami hazard for Lake Zurich,Switzerland

Subaqueous landslides can induce potentially damaging tsunamis. Tsunamis are not restricted to the marine environment, but have also been documented on lakes in Switzerland and worldwide. For Lake Zurich (central Switzerland), previous work documented multiple, assumedly earthquake-triggered landslides. However, no information about past tsunamis is available for Lake Zurich. In a back-analysis, we model tsunami scenarios as a consequence of the earthquake-triggered landslides in the past. Furthermore, on the basis of a recent map of the earthquake-triggered subaqueous landslide hazard, we present results of a tsunami hazard assessment. The subaqueous landslide progression, wave propagation and inundation are calculated with a combination of open source codes. Although no historic evidence of past tsunamis has been documented for Lake Zurich, a tsunami hazard exists. However, only earthquakes with long return periods are assumed to cause considerable tsunamis. An earthquake with an exceedance probability of 0.5% in 50 years (corresponding to an earthquake with a return period of 9975 years) is assumed to cause tsunamigenic landslides on most lateral slopes of Lake Zurich. A hypothetical tsunami for such an event would create damage especially along the shores of the central basin of Lake Zurich with estimated peak flow depths of up to ~?4.6 m. Our results suggest that for an earthquake with an exceedance probability of 10% in 50 years (i.e., mean return period of 475 years), no considerable tsunami hazard is estimated. Even for a worst-case scenario, the cities of Zurich and Rapperswil, located at the northern and southern ends of the lake, respectively, are assumed to experience very little damage. The presented first-order results of estimated wave heights and inundated zones provide valuable information on tsunami-prone areas that can be used for further investigations and mitigation measures.     

2002 Kuiper prize lecture: Dust Astronomy

Dust particles, like photons, carry information from remote sites in space and time. From knowledge of the dust particles' birthplace and their bulk properties, we can learn about the remote environment out of which the particles were formed. This approach is called “Dust Astronomy” which is carried out by means of a dust telescope on a Dust Observatory in space. Targets for a dust telescope are the local interstellar medium and nearby star forming regions, as well as comets and asteroids. Dust from interstellar and interplanetary sources is distinguished by accurately sensing their trajectories. Trajectory sensors may use the electric charge signals that are induced when charged grains fly through the detector. Modern in-situ dust impact detectors are capable of providing mass, speed, physical and chemical information of dust grains in space. A Dust Observatory mission is feasible with state-of-the-art technology. It will (1) provide the distinction between interstellar dust and interplanetary dust of cometary and asteroidal origin, (2) determine the elemental composition of impacting dust particles, and (3) monitor the fluxes of various dust components as a function of direction and particle masses.     

Topographic signatures of progressive glacial landscape transformation

The Pleistocene glaciations left a distinct topographic footprint in mountain ranges worldwide. The geometric signature of glacial topography has been quantified in various ways, but the temporal development of landscape metrics has not been traced in a landscape evolution model so far. However, such information is needed to interpret the degree of glacial imprint in terms of the integrated signal of temporal and spatial variations in erosion as a function of glacial occupation time. We apply a surface process model for cold-climate conditions to an initially fluvial mountain range. By exploring evolving topographic patterns in model time series, we determine locations where topographic changes reach a maximum and where the initial landscape persists. The signal of glacial erosion, expressed by the overdeepening of valleys and the steepening of valley flanks, develops first at the glacier front and migrates upstream with ongoing glacial erosion. This leads to an increase of mean channel slope and its variance. Above steep flanks and head-walls, however, the observed mean channel slope remains similar to the mean channel slope of the initial fluvial topography. This leads to a characteristic turning point in the channel slope–elevation distribution above the equilibrium line altitude, where a transition from increasing to decreasing channel slope with elevation occurs. We identify this turning point and a high channel slope variance as diagnostic features to quantify glacial imprint. Such features are abundant in glacially imprinted mid-latitude mountain ranges such as the Eastern Alps. By analysing differently glaciated parts of the mountain range, we observe a decreasing clarity of this diagnostic morphometric property with decreasing glacial occupation. However, catchments of the unglaciated eastern fringe of the Alps also feature turning points in their channel slope–elevation distributions, but in contrast to the glaciated domain, the variance of channel slope is small at all elevation levels.