The relevance of glacier melt in the water cycle of the Alps: the example of Austria

This paper quantifies the contribution of glacier melt to river runoff from compilation and statistical interpretation of data from available studies based on observations or glacio- hydrological modelling for the region of Austria (Austrian Salzach and Inn river basin). A logarithmic fit between the glacier melt contribution and the relative glacierized area was found not only for the long-term mean glacier contributions but also for the glacier melt contribution during the extreme hot an dry summer of 2003. Interestingly, the mean contributions of glacier melt to river runoff do not exceed 15 % for both river catchments and are uncorrelated to glacierization for glacierization values >10 %. This finding, however, has to be seen in the light of the general precipitation increase with altitude for the study region which levels out the increase of absolute melt with glacierization thus resulting in the rather constant value of glacier melt contribution. In order to qualitatively proof this finding another approach has been applied by calculating the quotient <i>q</i><sub>A03</sub> of the mean monthly August runoff in 2003 and the long-term mean August runoff for 38 gauging stations in Austria. The extreme summer 2003 was worth to be analysed as from the meteorological and glaciological point of view an extraordinary situation was observed. During June and July nearly the entire snow-cover melted and during August mainly bare ice melt of glaciers contributed to runoff. The <i>q</i><sub>A03</sub> quotients were calculated between 0.32 for a non-glacierized and 2.0 for a highly glacierized catchment. Using the results of this study the mean and maximum possible glacier melt contribution of catchments can be estimated based on the relative glacierized area. It can also be shown that the found correlation of glacierized area and glacier melt contribution is applicable for the Drau basin where yet no results of modelled glacier melt contributions are available

Vergleichende Untersuchung der endokrinen Ophthalmopathie mittels Ultrasonographie, Computertomographie und Fischbioassay

Bei 35 Patienten mit endokriner Ophthalmopathie (eO) wurde zu den Parametern der Schilddrüsenfunktion (T3, T4, TBI, TRH-Test), dem Szintigramm und der Bestimmung der Schilddrüsenantikörper ergänzend die Ultrasonographie (A-scan) und Computertomographie (CT) der Orbita, sowie der Nachweis exophthalmogener Serumaktivität im Fischbioassay durchgeführt. Charakteristische Sonogramme für eine eO fanden sich in 26 Fällen. Die CT ergab bei 24 von 33 Patienten die Verdickung der musculi recti mediales und/oder der musculi recti laterales, sowie bei 17 Patienten eine Verdichtung im Bereich der Orbitaspitze. Im retrobulbären Bindegewebe zeigte sich nach Kontrastmittelgabe keine signifikante Dichtezunahme. Mit beiden Verfahren zusammen waren nur bei 2 Patienten die Kriterien einer eO nicht erfüllt. Die exophthalmogene Serumaktivität wurde in der IgG-Fraktion im Fischbioassay nachgewiesen; die Trefferquote war mit 69% relativ hoch. Zur Diagnostik der eO kann jedoch der Fischbioassay nicht empfohlen werden

Linkage of cave-ice changes to weather patterns inside and outside the cave Eisriesenwelt (Tennengebirge, Austria)

The behaviour of perennial ice masses in karst caves in relation to the outside climate is still not well understood, though a significant potential of the cave-ice for paleo-climate reconstructions could be expected. This study investigates the relationship between weather patterns inside and outside the cave Eisriesenwelt (Austrian Alps) and ice-surface changes of the ice-covered part of the cave from meteorological observations at three sites (outside the cave, entrance-near inside and in the middle section of the cave) including atmospheric and ice surface measurements as well as an ablation stake network. Whereas ice loss in summer was a general feature from stake measurements for almost all measurement sites in the cave in 2007, 2008 and 2009 (values up to −15 cm yr<sup>−1</sup>), a clear seasonal signal of ice accumulation (e.g. in spring as expected from theory) was not observed. It is shown that under recent climate the cave ice mass balance is more sensitive to winter climate for the inner measurement site and sensitive to winter and summer climate for the entrance-near site. Observed ice surface changes can be well explained by cave atmosphere measurements, indicating a clear annual cycle with weak mass loss in winter due to sublimation, stable ice conditions in spring until summer (autumn for the inner measurement site) and significant melt in late summer to autumn (for the entrance-near site). Interestingly, surface ice melt did not contribute to ablation at the inner site. It is obvious from the spatial sample of ice surface height observations that the ice body is currently in rather balanced state, though the influence of show-cave management on ice mass-balance could not be clearly quantified (but a significant input on accumulation for some parts of the cave is rather plausible)

Temporal changes of inorganic ion deposition in the seasonal snow cover for the Austrian Alps (1983–2014)

A long-term record of inorganic ion concentrations in wet and dry deposition sampled from snow packs at two high altitude glaciers was used to assess impacts of air pollution on remote sites in central Europe. Sampling points were located at Wurtenkees and Goldbergkees near the Sonnblick Observatory (3106 m above sea level), a background site for measuring the status of the atmosphere in Austria's Eastern Alps. Sampling was carried out every spring at the end of the winter accumulation period in the years 1983–2014. Concentrations of major ions (NH4+, SO42−, NO3−, Ca2+, Mg2+, K+, Na+ and Cl−) were determined using ion chromatography (IC) as well as atomic absorption spectroscopy (AAS) in the earlier years. Concentration of H+ was calculated via the measured pH of the samples. Trends in deposition and concentration were analysed for all major ions within the period from 1983 to 2014 using Kendall's tau rank correlation coefficient. From 1983 to 2014, total ion concentration declined ∼25%, i.e. solutions became ∼25% more dilute, indicating reduced acidic atmospheric deposition, even at high altitude in winter snow. SO42− and NO3− concentrations decreased significantly by 70% and 30%, respectively, accompanied by a 54% decrease of H+ concentrations. Ionic concentrations in snowpack were dominated by H+ and SO42− in the earliest decade measured, whereas they were dominated by Ca2+ by the most recent decade. SO42− and H+ depositions, i.e. concentrations multiplied by volume, also showed a significant decrease of more than 50% at both sites. This reflects the successful emission reductions of the precursor gases SO2 and NOx. Seasonal values with significantly elevated spring concentrations of NH4+, SO42− and H+ compared to fall snow reflects the beginning of vertical mixing during spring. All other ions do not show any seasonality. Source identification of the ions was performed using a principal component analysis (PCA). One anthropogenic cluster (SO42−, NO3− and NH4+) coming from road traffic or fossil fuel combustion and animal husbandry, one crustal cluster (Ca2+, Mg2+) originating from local geological input or Saharan dust events as well as one cluster of unknown origin with episodic character (Na+, K+ and Cl−) was found

Uncertainty contributions to low-flow projections in Austria

The main objective of the paper is to understand the contributions to the uncertainty in low-flow projections resulting from hydrological model uncertainty and climate projection uncertainty. Model uncertainty is quantified by different parameterisations of a conceptual semi-distributed hydrologic model (TUWmodel) using 11 objective functions in three different decades (1976–1986, 1987–1997, 1998–2008), which allows for disentangling the effect of the objective function-related uncertainty and temporal stability of model parameters. Climate projection uncertainty is quantified by four future climate scenarios (ECHAM5-A1B, A2, B1 and HADCM3-A1B) using a delta change approach. The approach is tested for 262 basins in Austria. The results indicate that the seasonality of the low-flow regime is an important factor affecting the performance of model calibration in the reference period and the uncertainty of Q95 low-flow projections in the future period. In Austria, the range of simulated Q95 in the reference period is larger in basins with a summer low-flow regime than in basins with a winter low-flow regime. The accuracy of simulated Q95 may result in a range of up to 60 % depending on the decade used for calibration. The low-flow projections of Q95 show an increase of low flows in the Alps, typically in the range of 10–30 % and a decrease in the south-eastern part of Austria mostly in the range −5 to −20 % for the climate change projected for the future period 2021–2050, relative the reference period 1978–2007. The change in seasonality varies between scenarios, but there is a tendency for earlier low flows in the northern Alps and later low flows in eastern Austria. The total uncertainty of Q95 projections is the largest in basins with a winter low-flow regime and, in some basins the range of Q95 projections exceeds 60 %. In basins with summer low flows, the total uncertainty is mostly less than 20 %. The ANOVA assessment of the relative contribution of the three main variance components (i.e. climate scenario, decade used for model calibration and calibration variant representing different objective function) to the low-flow projection uncertainty shows that in basins with summer low flows climate scenarios contribute more than 75 % to the total projection uncertainty. In basins with a winter low-flow regime, the median contribution of climate scenario, decade and objective function is 29, 13 and 13 %, respectively. The implications of the uncertainties identified in this paper for water resource management are discussed

Multi-methodical realisation of Austrian climate maps for 1971–2000

Constantly changing climate, the availability of a higher resolved digital elevation model and further development of geostatistical interpolation methods gave reason for updating the most frequently demanded climate maps out of the Austrian digital climate atlas from 1961–1990 to 1971–2000. To achieve a station density as high as possible, data from eleven national and foreign institutes were collected and gap-filled. According to the climate parameter, different geostatistical interpolation methods (including regionalised multilinear regressions, geographically weighted regressions and curve fitting to base parameter) were applied. The resultant 17 grids concern 30-year-means of air temperature, precipitation and snow parameters as well as derived indices. They are now available for a variety of scientific and planning purposes

Towards endowing collaborative robots with fast learning for minimizing tutors’ demonstrations: what and when to do?

Programming by demonstration allows non-experts in robot programming to train the robots in an intuitive manner. However, this learning paradigm requires multiple demonstrations of the same task, which can be time-consuming and annoying for the human tutor. To overcome this limitation, we propose a fast learning system – based on neural dynamics – that permits collaborative robots to memorize sequential information from single task demonstrations by a human-tutor. Important, the learning system allows not only to memorize long sequences of sub-goals in a task but also the time interval between them. We implement this learning system in Sawyer (a collaborative robot from Rethink Robotics) and test it in a construction task, where the robot observes several human-tutors with different preferences on the sequential order to perform the task and different behavioral time scales. After learning, memory recall (of what and when to do a sub-task) allows the robot to instruct inexperienced human workers, in a particular human-centered task scenario.POFC - Programa Operacional Temático Factores de Competitividade(POCI-01-0247-FEDER-024541

Universal neural field computation

Turing machines and G\"odel numbers are important pillars of the theory of computation. Thus, any computational architecture needs to show how it could relate to Turing machines and how stable implementations of Turing computation are possible. In this chapter, we implement universal Turing computation in a neural field environment. To this end, we employ the canonical symbologram representation of a Turing machine obtained from a G\"odel encoding of its symbolic repertoire and generalized shifts. The resulting nonlinear dynamical automaton (NDA) is a piecewise affine-linear map acting on the unit square that is partitioned into rectangular domains. Instead of looking at point dynamics in phase space, we then consider functional dynamics of probability distributions functions (p.d.f.s) over phase space. This is generally described by a Frobenius-Perron integral transformation that can be regarded as a neural field equation over the unit square as feature space of a dynamic field theory (DFT). Solving the Frobenius-Perron equation yields that uniform p.d.f.s with rectangular support are mapped onto uniform p.d.f.s with rectangular support, again. We call the resulting representation \emph{dynamic field automaton}.Comment: 21 pages; 6 figures. arXiv admin note: text overlap with arXiv:1204.546