A time series analysis of sound propagation in a strongly multipathshallow water environment with an adiabatic normal mode approach

Measured time series were generated by small omnidirectional explosive sources in a shallow water area. A bottom-mounted hydrophone recorded sound signals that propagated over a sloping bottom. The time series in the 250-500 Hz band were analyzed with a broad-band adiabatic normal mode approach. The measured waveforms contain numerous bottom interacting multipaths that are complicated by the subbottom structure that contains high-velocity layers near the water-sediment interface. Several of the details of the geoacoustic structure and the depth of the water column at the receiver are inferred from comparisons of the measured data to simulated time series. The sensitivity of broad-band matched-field ambiguity surfaces in the range-depth plane for a single receiver to selected waveguide parameters is examined. A consistent analysis is made where the simulated time series are compared to the measured time series along with the single-receiver matched-field localization solutions for ranges out to 5 km. In this range interval, it was found that the peak cross-correlation between the measured and simulated time series varied between 0.84 and 0.69. The difference between the GPS range and the range obtained from the matched-field solution varied from 0 to 63 m. The geoacoustic structure obtained in the analysis consists of an 8-m low-velocity sediment layer over an 8-m high-velocity layer followed by a higher velocity, infinite half-space     

Molekular Connectivity Indizes als strukturchemische Stoffparameter ökotoxikologischer Relevanz

The molecular connectivity index developed by Randic as a numerical expression characterizes the position and bond of atoms in the molecular structure. Since significant correlations between the molar refraction as well as electron polarizability and ecotoxicologically relevant parameters of substances were determined in the preceding investigations, such connections are investigated also for this index and sorption coefficients, bioconcentration factors and toxicity data. By the example of 56 differentiated organic substances, significant regression relations are demonstrated between bioconcentration factors, sorption coefficients and toxicity data as well as the valency molecular connectivity indices. By these regressions it is possible to determine essential distribution and action parameters of chemical substances from the structure for assesing an ecotoxicological risk. The possibilities resulting from this for predicting ecotoxicologically relevant parameters of substances are discussed.     

Implications of diverse sedimentation patterns in Hala Lake, Qinghai Province, China for reconstructing Late Quaternary climate

Hala Lake is located in the Qilian Mountains, Qinghai Province, China, at 4,078?m a.s.l. Its sediments contain an archive of climate and hydrologic changes during the Late Quaternary, as it is located close to the area influenced by the East-Asian summer monsoon and westerly-driven air masses. Sedimentation patterns and depositional conditions within the lake were investigated using eight sediment cores from different water depths, and this information was used to evaluate the feasibility of using a single core to reconstruct past climate and hydrological conditions. Long core H7, from the center of the lake (65?m water depth) and core H8 from a western, near-shore location (20?m water depth), were compared in detail using sediment composition and geochemical data (X-ray fluorescence, loss-on-ignition and CNS analysis). Age models were constructed using 17 AMS radiocarbon dates and indicate negligible reservoir error for sediments from the lake center and?~1,000?year errors for the near-shore sediment core. Cores H1?CH5 and HHLS21-1 revealed a sediment succession from sand and silty clay to laminated clay on the southern side of the lake. Undisturbed, finely laminated sediments were found at water depths???15?m. Core H5 (2.5?m long), from 31?m water depth, yielded abundant green algal mats mixed with clayey lake deposits and was difficult to interpret. Algae occurred between 25 and 32?m water depth and influenced the dissolved oxygen content of the stratified lake. Comparison of cores H7 and H8 yielded prominent mismatches for different time periods, which may, in part, be attributed to internal lacustrine processes, independent of climate influence. We thus conclude that data from a single sediment core may lead to different climate inferences. Common shifts among proxy data, however, showed that major climate shifts, of regional to global significance, can be tracked and allow reconstruction of lake level changes over the last 24,000?years. Results indicate advance of glaciers into the lake basin during the LGM, at which time the lake experienced lowest levels, 25?C50?m below present stage. Stepwise refilling began at ca. 16 kyr BP and reached the ?25?m level during the B?lling/Aller?d warm phase, ca. 13.5 kyr BP. A desiccation episode falls within the Younger Dryas, followed by a substantial lake level rise during the first millennium of the Holocene, a result of climate warming, which promoted glacier melt. By ca. 7.6 kyr BP, the lake reached a stable high stand similar to the present level, which persisted until ca. 6 kyr BP. Disturbed sediments in core H7 indicate a single mass flow that was most likely triggered by a major seismic event?~8.5 kyr BP. Subsequent lake development remains unclear as a consequence of data mismatches, but may indicate a general trend to deteriorating conditions and lake level lowstands at ca. 5.0?C4.2, 2.0 and 0.5 kyr BP.     

Preprocessing of gravity gradients at the GOCE high-level processing facility

One of the products derived from the gravity field and steady-state ocean circulation explorer (GOCE) observations are the gravity gradients. These gravity gradients are provided in the gradiometer reference frame (GRF) and are calibrated in-flight using satellite shaking and star sensor data. To use these gravity gradients for application in Earth scienes and gravity field analysis, additional preprocessing needs to be done, including corrections for temporal gravity field signals to isolate the static gravity field part, screening for outliers, calibration by comparison with existing external gravity field information and error assessment. The temporal gravity gradient corrections consist of tidal and nontidal corrections. These are all generally below the gravity gradient error level, which is predicted to show a 1/f behaviour for low frequencies. In the outlier detection, the 1/f error is compensated for by subtracting a local median from the data, while the data error is assessed using the median absolute deviation. The local median acts as a high-pass filter and it is robust as is the median absolute deviation. Three different methods have been implemented for the calibration of the gravity gradients. All three methods use a high-pass filter to compensate for the 1/f gravity gradient error. The baseline method uses state-of-the-art global gravity field models and the most accurate results are obtained if star sensor misalignments are estimated along with the calibration parameters. A second calibration method uses GOCE GPS data to estimate a low-degree gravity field model as well as gravity gradient scale factors. Both methods allow to estimate gravity gradient scale factors down to the 10⁻³ level. The third calibration method uses high accurate terrestrial gravity data in selected regions to validate the gravity gradient scale factors, focussing on the measurement band. Gravity gradient scale factors may be estimated down to the 10⁻² level with this method.     

Calibrating the GOCE accelerations with star sensor data and a global gravity field model

A reliable and accurate gradiometer calibration is essential for the scientific return of the gravity field and steady-state ocean circulation explorer (GOCE) mission. This paper describes a new method for external calibration of the GOCE gradiometer accelerations. A global gravity field model in combination with star sensor quaternions is used to compute reference differential accelerations, which may be used to estimate various combinations of gradiometer scale factors, internal gradiometer misalignments and misalignments between star sensor and gradiometer. In many aspects, the new method is complementary to the GOCE in-flight calibration. In contrast to the in-flight calibration, which requires a satellite-shaking phase, the new method uses data from the nominal measurement phases. The results of a simulation study show that gradiometer scale factors can be estimated on a weekly basis with accuracies better than 2 × 10⁻³ for the ultrasensitive and 10⁻² for the less sensitive axes, which is compatible with the requirements of the gravity gradient error. Based on a 58-day data set, scale factors are found that can reduce the errors of the in-flight-calibrated measurements. The elements of the complete inverse calibration matrix, representing both the internal gradiometer misalignments and scale factors, can be estimated with accuracies in general better than 10⁻³.     

Troposphere gradients from the ECMWF in VLBI analysis

Modeling path delays in the neutral atmosphere for the analysis of Very Long Baseline Interferometry (VLBI) observations has been improved significantly in recent years by the use of elevation-dependent mapping functions based on data from numerical weather models. In this paper, we present a fast way of extracting both, hydrostatic and wet, linear horizontal gradients for the troposphere from data of the European Centre for Medium-range Weather Forecasts (ECMWF) model, as it is realized at the Vienna University of Technology on a routine basis for all stations of the International GNSS (Global Navigation Satellite Systems) Service (IGS) and International VLBI Service for Geodesy and Astrometry (IVS) stations. This approach only uses information about the refractivity gradients at the site vertical, but no information from the line-of-sight. VLBI analysis of the CONT02 and CONT05 campaigns, as well as all IVS-R1 and IVS-R4 sessions in the first half of 2006, shows that fixing these a priori gradients improves the repeatability for 74% (40 out of 54) of the VLBI baseline lengths compared to fixing zero or constant a priori gradients, and improves the repeatability for the majority of baselines compared to estimating 24-h offsets for the gradients. Only if 6-h offsets are estimated, the baseline length repeatabilities significantly improve, no matter which a priori gradients are used.     

Modeling thermal deformation of VLBI antennas with a new temperature model

Temperature variations at very long baseline interferometry (VLBI) sites cause thermal deformations of the VLBI antennas and corresponding displacements of the VLBI reference points. The thermal deformation effects typically contain seasonal and daily signatures. The amplitudes of the annual vertical motion of the antenna reference point can reach several millimeters, depending on the design of the antenna structure, on the material, and on the environmental effects such as global station position, station height and climatology effects. Simple methods to correct this effect use the difference of the environmental temperature with respect to a defined reference temperature, the antenna dimensions, the elevation of the antenna, the material of antenna structure. Applying these simple models for thermal deformation in the VLBI data analysis improves the baseline length repeatability by 3.5%. A comparison of these simple models with local thermal deformation measurements at the antennas in Onsala and Wettzell show that the local measurements and the modeled corrections agree well when the temperature of the antenna structure is used, but agree less good when the surrounding air temperatures are used. To overcome this problem we present a method to model temperature penetration into the antenna structures, that allows to model thermal deformation effects that agree with the observed vertical deformation of the Onsala and Wettzell radio telescopes with a root mean square deviation of 0.07 and 0.13 mm, respectively. Possible implementations in the VLBI analysis are presented, and the definition of an adequate reference temperature is discussed.     

Gibbs sampler by sampling-importance-resampling

Among the Markov chain Monte Carlo methods, the Gibbs sampler has the advantage that it samples from the conditional distributions for each unknown parameter, thus decomposing the sample space. In the case the conditional distributions are not tractable, the Gibbs sampler by means of sampling-importance-resampling is presented here. It uses the prior density function of a Bayesian analysis as the importance sampling distribution. This leads to a fast convergence of the Gibbs sampler as demonstrated by the smoothing with preserving the edges of 3D images of emission tomography.     

Universal time from VLBI single-baseline observations during CONT08

The IVS Intensive sessions are single-baseline, 1-h VLBI sessions carried out everyday in order to determine Universal Time (UT1). We investigate different possibilities to improve the results of such sessions. We do this investigation by extracting 2-h single-baseline sessions from the CONT08 data set. These are analysed like normal Intensives, and the results are compared to the results of the analysis of the full CONT08 data set. We find that tropospheric asymmetry is the major error source for the single-baseline sessions. It is possible to improve the accuracy of the estimated UT1 either by using accurate a priori tropospheric gradients or by estimating gradients in the data analysis.     

Approximating covariance matrices estimated in multivariate models by estimated auto- and cross-covariances

Quantities like tropospheric zenith delays or station coordinates are repeatedly measured at permanent VLBI or GPS stations so that time series for the quantities at each station are obtained. The covariances of these quantities can be estimated in a multivariate linear model. The covariances are needed for computing uncertainties of results derived from these quantities. The covariance matrix for many permanent stations becomes large, the need for simplifying it may therefore arise under the condition that the uncertainties of derived results still agree. This is accomplished by assuming that the different time series of a quantity like the station height for each permanent station can be combined to obtain one time series. The covariance matrix then follows from the estimates of the auto- and cross-covariance functions of the combined time series. A further approximation is found, if compactly supported covariance functions are fitted to an estimated autocovariance function in order to obtain a covariance matrix which is representative of different kinds of measurements. The simplification of a covariance matrix estimated in a multivariate model is investigated here for the coordinates of points of a grid measured repeatedly by a laserscanner. The approximations are checked by determining the uncertainty of the sum of distances to the points of the grid. To obtain a realistic value for this uncertainty, the covariances of the measured coordinates have to be considered. Three different setups of measurements are analyzed and a covariance matrix is found which is representative for all three setups. Covariance matrices for the measurements of laserscanners can therefore be determined in advance without estimating them for each application.