Analysis of anomalies in ADS-B and its GPS data

Traditionally, the surveillance component of the air traffic management system has been based on radar, which consists of two separate systems: primary radar and secondary radar, which both enable the measurement of the aircraft range and bearing to the radar station. Primary radar is based on signals emitted by a ground station simply being reflected off an object and detected by a ground-based receiver. Secondary radar also emits signals, but relies upon a transponder onboard the aircraft to emit a signal itself, modulated among others by a four-digit aircraft identity (Mode A), aircraft altitude (Mode C) and/or 24-bit unique address (Mode S). Typical accuracies of secondary radar are of the order of 0.03 NM in range and 0.07° in azimuth. However, no position integrity report is provided. Air traffic density is expected to significantly increase in the future. In order to maintain or enhance air travel efficiency, while maintaining safety, more accurate surveillance systems, with the required integrity, will be required. Automatic dependent surveillance–broadcast (ADS-B) is a new aviation surveillance system, envisioned to overcome the limitations of radar and to enhance surveillance performance and thereby increase airspace capacity. However, its high dependence on external systems such as onboard navigation and communication systems also increases the number of potential points of failure. It is important to understand and mitigate these failure modes before the system can reliably be implemented. The present study emerged as an exploratory research as part of a safety assessment framework development for the ADS-B system. It reviews the ADS-B failure modes, data collection and analysis of ADS-B and its corresponding onboard GPS data. The study identifies a set of failures common to certain aircraft models, with consistent error patterns. A key failure mode was found to be associated with the navigation data from the onboard GPS. We discuss the identified failure modes and investigate the nature and causes of these failures. The findings highlight some of the deficiencies of the current ADS-B system, which will need to be addressed before the ADS-B system can reliably be implemented.     

A cross-border regional earthquake early warning system: PRESTo@CE3RN

Since 2002 the Istituto Nazionale di Oceanografia e di Geofisica Sperimentale (OGS) in Udine (Italy), the Agencija Republike Slovenije za Okolje (ARSO) in Ljubljana (Slovenia) and the Zentralanstalt für Meteorologie und Geodynamik (ZAMG) in Vienna (Austria), are collecting, analyzing, archiving and exchanging seismic data in real time, initially in the framework of the EU Interreg IIIa Italia-Austria project “Trans-national seismological networks in the South-Eastern Alps”. As outcome of the successful cooperation, in the 2013 OGS, ARSO and ZAMG decided to officially merge their seismic monitoring efforts into the “Central and Eastern European Earthquake Research Network—CE³RN”. This work reports the results of a nine-month real-time test of the earthquake early warning (EEW) algorithm probabilistic and evolutionary early warning system carried out at the CE³RN. The study allowed identifying the actions to be implemented in order to let the CE³RN become in the next future an efficient cross-border EEW system.

     

Effects of nonlinear model response on allocation of streamflow depletion: exemplified by the case of Beaver Creek,USA

Anomalies found when apportioning responsibility for streamflow depletion are examined. The anomalies arise when responsibility is assigned to the two states that contribute to depletion of Beaver Creek in the Republican River Basin in the United States. The apportioning procedure for this basin presumes that the sum of streamflow depletions, computed by comparing simulation model runs with and without groundwater pumping from individual states, approximates the streamflow depletion when both states are pumping. In the case study presented here, this presumed superposition fails dramatically. The stream drying and aquifer-storage depletion, as represented in the simulation model used for allocation, are examined in detail to understand the hydrologic and numerical basis for the severe nonlinear response. Users of apportioning procedures that rely on superposition should be aware of the presence and likely magnitude of nonlinear responses in modeling tools.     

Why GPS makes distances bigger than they are

Global navigation satellite systems such as the Global Positioning System (GPS) is one of the most important sensors for movement analysis. GPS is widely used to record the trajectories of vehicles, animals and human beings. However, all GPS movement data are affected by both measurement and interpolation errors. In this article we show that measurement error causes a systematic bias in distances recorded with a GPS; the distance between two points recorded with a GPS is – on average – bigger than the true distance between these points. This systematic ‘overestimation of distance’ becomes relevant if the influence of interpolation error can be neglected, which in practice is the case for movement sampled at high frequencies. We provide a mathematical explanation of this phenomenon and illustrate that it functionally depends on the autocorrelation of GPS measurement error (C). We argue that C can be interpreted as a quality measure for movement data recorded with a GPS. If there is a strong autocorrelation between any two consecutive position estimates, they have very similar error. This error cancels out when average speed, distance or direction is calculated along the trajectory. Based on our theoretical findings we introduce a novel approach to determine C in real-world GPS movement data sampled at high frequencies. We apply our approach to pedestrian trajectories and car trajectories. We found that the measurement error in the data was strongly spatially and temporally autocorrelated and give a quality estimate of the data. Most importantly, our findings are not limited to GPS alone. The systematic bias and its implications are bound to occur in any movement data collected with absolute positioning if interpolation error can be neglected.     

Zircon M127 – A Homogeneous Reference Material for SIMS U–Pb Geochronology Combined with Hafnium,Oxygen and,Potentially, Lithium Isotope Analysis

In this article, we document a detailed analytical characterisation of zircon M127, a homogeneous 12.7 carat gemstone from Ratnapura, Sri Lanka. Zircon M127 has TIMS‐determined mean U–Pb radiogenic isotopic ratios of 0.084743 ± 0.000027 for ²⁰⁶Pb/²³⁸U and 0.67676 ± 0.00023 for ²⁰⁷Pb/²³⁵U (weighted means, 2s uncertainties). Its ²⁰⁶Pb/²³⁸U age of 524.36 ± 0.16 Ma (95% confidence uncertainty) is concordant within the uncertainties of decay constants. The δ¹⁸O value (determined by laser fluorination) is 8.26 ± 0.06‰ VSMOW (2s), and the mean ¹⁷⁶Hf/¹⁷⁷Hf ratio (determined by solution ICP‐MS) is 0.282396 ± 0.000004 (2s). The SIMS‐determined δ⁷Li value is ?0.6 ± 0.9‰ (2s), with a mean mass fraction of 1.0 ± 0.1 μg g^?1 Li (2s). Zircon M127 contains ~ 923 μg g^?1 U. The moderate degree of radiation damage corresponds well with the time‐integrated self‐irradiation dose of 1.82 × 10¹⁸ alpha events per gram. This observation, and the (U–Th)/He age of 426 ± 7 Ma (2s), which is typical of unheated Sri Lankan zircon, enable us to exclude any thermal treatment. Zircon M127 is proposed as a reference material for the determination of zircon U–Pb ages by means of SIMS in combination with hafnium and stable isotope (oxygen and potentially also lithium) determination.     

Monotone nonlinear finite-volume method for challenging grids

This article presents a new positivity-preserving finite-volume scheme with a nonlinear two-point flux approximation, which uses optimization techniques for the face stencil calculation. The gradient is reconstructed using harmonic averaging points with the constraint that the sum of the coefficients included in the face stencils must be positive. We compare the proposed scheme to a nonlinear two-point scheme available in literature and a few linear schemes. Using two test cases, taken from the FVCA6 benchmarks, the accuracy of the scheme is investigated. Furthermore, it is shown that the scheme is linearity-preserving on highly complex corner-point grids. Moreover, a two-phase flow problem on the Norne formation, a geological formation in the Norwegian Sea, is simulated. It is demonstrated that the proposed scheme is consistent in contrast to the linear Two-Point Flux Approximation scheme, which is industry standard for simulating subsurface flow on corner-point grids.     

Automated Extraction of a Five‐Year LA‐ICP‐MS Trace Element Data Set of Ten Common Glass and Carbonate Reference Materials: Long‐Term Data Quality,Optimisation and Laser Cell Homogeneity

LA‐ICP‐MS is increasingly applied to obtain quantitative multi‐element data with minimal sample preparation, usually achieved by calibration using reference materials (RMs). However, some ubiquitous RMs, for example the NIST SRM 61× series glasses, suffer from reported value uncertainties for certain elements. Moreover, no long‐term data set of analyses conducted over a range of ablation and tuning conditions exists. Thus, there has been little rigorous examination of the extent to which offsets between measured and reported values are the result of error in these values rather than analytically induced fractionation. We present new software (‘LA‐MINE’), capable of extracting LA‐ICP‐MS data with no user input, and apply this to our system, yielding over 5 years of data (~ 5700 analyses of ten glass and carbonate RMs). We examine the relative importance of systematic analytical bias and possible error in reported values through a mass‐specific breakdown of fourteen of the most commonly determined elements. Furthermore, these data, obtained under a wide range of different ablation conditions, enable specific recommendations of how data quality may be improved, for example the role of diatomic gas, the effect of differential inter‐glass fractionation factors and choice of transport tubing material. Finally, these data demonstrate that the two‐volume Laurin ablation cell is characterised by no discernible spatial heterogeneity in measured trace element ratios.     

A review on missing hydrological data processing

Like almost all fields of science, hydrology has benefited to a large extent from the tremendous improvements in scientific instruments that are able to collect long-time data series and an increase in available computational power and storage capabilities over the last decades. Many model applications and statistical analyses (e.g., extreme value analysis) are based on these time series. Consequently, the quality and the completeness of these time series are essential. Preprocessing of raw data sets by filling data gaps is thus a necessary procedure. Several interpolation techniques with different complexity are available ranging from rather simple to extremely challenging approaches. In this paper, various imputation methods available to the hydrological researchers are reviewed with regard to their suitability for filling gaps in the context of solving hydrological questions. The methodological approaches include arithmetic mean imputation, principal component analysis, regression-based methods and multiple imputation methods. In particular, autoregressive conditional heteroscedasticity (ARCH) models which originate from finance and econometrics will be discussed regarding their applicability to data series characterized by non-constant volatility and heteroscedasticity in hydrological contexts. The review shows that methodological advances driven by other fields of research bear relevance for a more intensive use of these methods in hydrology. Up to now, the hydrological community has paid little attention to the imputation ability of time series models in general and ARCH models in particular.     

The Austrian node of the natural resources satellite remote sensing cloud service platform:examples of Sino-Austrian cooperation

The Austrian node of the Natural Resources Satellite Remote Sensing Cloud Service Platform was established in 2016 through a cooperation agreement between the Land Satellite Remote Sensing Application Center(LASAC),Ministry of Natural Resources of the Peoples Republic of China and the University of Vienna,Austria.Under this agreement panchromatic and multi-spectral data of the Chinese ZY-3 satellite are pushed to the server at the University of Vienna for use in education and research.So far,nearly 500 GB of data have been uploaded to the server.This technical note briefly introduces the ZY-3 system and illustrates the implementation of the agreement by the first China-Sat Workshop and several case studies.Some of them are already completed,others are still ongoing.They include a geometric accuracy validation of ZY-3 data,an animated visualization of image quick views on a spherical display to demonstrate the time series of the image coverage for Austria and Laos,and the use of ZY-3 data to study the spread of bark beetle in the province of Lower Austria.An accuracy study of DTMs from ZY-3 stereo data,as well as a land cover analysis and comparison of Austria with ZY-3 and other sensors are still ongoing.