Gravity reduction with three-dimensional atmospheric pressure data for precise ground gravity measurements

The redistribution of air masses induces gravity variations (atmospheric pressure effect) up to about 20 μgal. These variations are disturbing signals in gravity records and they must be removed very carefully for detecting weak gravity signals. In the past, different methods have been developed for modelling of the atmospheric pressure effect. These methods use local or two-dimensional (2D) surface atmospheric pressure data and a standard height-dependent air density distribution. The atmospheric pressure effect is consisting of the elastic deformation and attraction term. The deformation term can be well modelled with 2D surface atmospheric pressure data, for instance with the Green's function method. For modelling of the attraction term, three-dimensional (3D) data are required. Results with 2D data are insufficient.From European Centre for Medium-Range Weather Forecasts (ECMWF) 3D atmospheric pressure data are now available. The ECMWF data used here are characterised by a spacing of Δ and Δλ = 0.5°, 60 pressure levels up to a height of 60 km and an interval of 6 h. These data are used for modelling of the atmospheric attraction term. Two attraction models have been developed based on the point mass attraction of air segments and the gravity potential of the air masses. The modelling shows a surface pressure-independent part of gravity variations induced by mass redistribution of the atmosphere in the order of some μgal. This part can only be determined by using 3D atmospheric pressure data. It has been calculated for the Vienna Superconducting Gravimeter site.From this follows that the gravity reduction can be improved by applying the 3D atmospheric attraction model for analysing long-periodic tidal waves including the polar tide. The same improvement is expected for reduction of long-term absolute gravity measurements or comparison of gravity measurements at different seasonal times. By using 3D atmospheric pressure data, the gravity correction can be improved up to some μgal.     

Regional moment tensor uncertainty due to mismodeling of the crust

The retrieval of earthquake moment tensor (MT) requires the response of the medium, in which seismic waves travel from the hypocenter to the stations, to be known. In inverting long-period (LP) seismic data (teleseismic and LP regional records), a gross earth model is sufficient; with decreasing periods, a more detailed model is needed. This is the case when waveforms of weak earthquakes at regional distances are to be inverted. Regional moment tensors (RMTs) of mostly Mediterranean earthquakes are determined on a routine basis by the Swiss Seismological Survey (SED) by using averaged models of the earth's crust. By inverting broad-band records of the M_w=4.8 earthquake near Udine, N Italy, on Feb. 14, 2002, we tested the sensitivity of the MT solution with respect to possible errors in the earth model used and in the location of the hypocenter depth. We perturbed the P and S velocities and the thickness in the 1-D earth model in the range from 3% to 30% of the parameter values and constructed estimates of confidence regions of the MT and error bars of the source time function (STF) and scalar moment in three frequency bands. Similarly, these error characteristics were determined assuming a mislocation in the hypocenter depth. We found that, in the band of periods from 25 to 50 s, the mechanism is resolved well (at the confidence level 95% at least) up to an earth model uncertainty of 30%, in the passband 10–25 s up to about 10%, but it is undetermined completely at periods of 5–10 s. An error in hypocenter depth of as much as double the value reported by the location procedure does not destroy the resolution of the mechanism at periods above 10 s. In the RMT catalog of the SED, earthquakes of M_w greater than about 3.5 are processed at periods above 30 s; thus, the solutions for these events are robust with respect to a possible uncertainty in the earth model used. Mechanisms of weaker earthquakes, retrieved from short periods, should be interpreted with caution.     

Kinetic energy–rainfall intensity relationship for Central Cebu, Philippines for soil erosion studies

In the study of soil erosion, specifically on detachment of soil particles by raindrop impact, kinetic energy is a commonly suggested indicator of the raindrop's ability to detach soil particles from the soil mass. Since direct measurement of kinetic energy requires sophisticated and costly instruments, the alternative approach is to estimate it from rainfall intensity. The present study aims at establishing a relationship between rainfall intensity and kinetic energy for rainfalls in Central Cebu, Philippines as a preface of a wider regional investigation.

Drop size distributions of rainfalls were measured using the disdrometer RD-80. There are two forms of kinetic energy considered here. One is kinetic energy per unit area per unit time (KE_R, J m⁻² h⁻¹) and the other is kinetic energy per unit area per unit depth (KE, J m⁻² mm⁻¹). Relationships between kinetic energy per unit area per unit time (KE_R) and rainfall intensity (I) were obtained using linear and power relations. The exponential model and the logarithmic model were fitted to the KE–I data to obtain corresponding relationships between kinetic energy per unit area per unit depth of rainfall (KE) and rainfall intensity (I). The equation obtained from the exponential model produced smaller standard error of estimates than the logarithmic model.     

Evaluation of current statistical approaches for predictive geomorphological mapping

Predictive models are increasingly used in geomorphology, but systematic evaluations of novel statistical techniques are still limited. The aim of this study was to compare the accuracy of generalized linear models (GLM), generalized additive models (GAM), classification tree analysis (CTA), neural networks (ANN) and multiple adaptive regression splines (MARS) in predictive geomorphological modelling. Five different distribution models both for non-sorted and sorted patterned ground were constructed on the basis of four terrain parameters and four soil variables. To evaluate the models, the original data set of 9997 squares of 1 ha in size was randomly divided into model training (70%, n=6998) and model evaluation sets (30%, n=2999).In general, active sorted patterned ground is clearly defined in upper fell areas with high slope angle and till soils. Active non-sorted patterned ground is more common in valleys with higher soil moisture and fine-scale concave topography. The predictive performance of each model was evaluated using the area under the receiver operating characteristic curve (AUC) and the Kappa value. The relatively high discrimination capacity of all models, AUC=0.85–0.88 and Kappa=0.49–0.56, implies that the model's predictions provide an acceptable index of sorted and non-sorted patterned ground occurrence. The best performance for model calibration data for both data sets was achieved by the CTA. However, when the predictive mapping ability was explored through the evaluation data set, the model accuracies of CTA decreased clearly compared to the other modelling techniques. For model evaluation data MARS performed marginally best.Our results show that the digital elevation model and soil data can be used to predict relatively robustly the activity of patterned ground in fine scale in a subarctic landscape. This indicates that predictive geomorphological modelling has the advantage of providing relevant and useful information on earth surface processes over extensive areas, such data being unavailable through more conventional survey methods.     

Crustal structure of the Lofoten–Vesterålen continental margin, off Norway

By compiling wide-angle seismic velocity profiles along the 400-km-long Lofoten–Vesterålen continental margin off Norway, and integrating them with an extensive seismic reflection data set and crustal-scale two-dimensional gravity modelling, we outline the crustal margin structure. The structure is illustrated by across-margin regional transects and by contour maps of depth to Moho, thickness of the crystalline crust, and thickness of the 7+ km/s lower crustal body. The data reveal a normal thickness oceanic crust seaward of anomaly 23 and an increase in thickness towards the continent–ocean boundary associated with breakup magmatism. The southern boundary of the Lofoten–Vesterålen margin, the Bivrost Fracture Zone and its landward prolongation, appears as a major across-margin magmatic and structural crustal feature that governed the evolution of the margin. In particular, a steeply dipping and relatively narrow, 10–40-km-wide, Moho-gradient zone exists within a continent–ocean transition, which decreases in width northward along the Lofoten–Vesterålen margin. To the south, the zone continues along the Vøring margin, however it is offset 70–80 km to the northwest along the Bivrost Fracture Zone/Lineament. Here, the Moho-gradient zone corresponds to a distinct, 25-km-wide, zone of rapid landward increase in crustal thickness that defines the transition between the Lofoten platform and the Vøring Basin. The continental crust on the Lofoten–Vesterålen margin reaches a thickness of 26 km and appears to have experienced only moderate extension, contrasting with the greatly extended crust in the Vøring Basin farther south. There are also distinct differences between the Lofoten and Vesterålen margin segments as revealed by changes in structural style and crustal thickness as well as in the extent of elongate potential-field anomalies. These changes may be related to transfer zones. Gravity modelling shows that the prominent belt of shelf-edge gravity anomalies results from a shallow basement structural relief, while the elongate Lofoten Islands belt requires increased lower crustal densities along the entire area of crustal thinning beneath the islands. Furthermore, gravity modelling offers a robust diagnostic tool for the existence of the lower crustal body. From modelling results and previous studies on- and off-shore mid-Norway, we postulate that the development of a core complex in the middle to lower crust in the Lofoten Islands region, which has been exhumed along detachments during large-scale extension, brought high-grade, lower crustal rocks, possibly including accreted decompressional melts, to shallower levels.     

Diamond in metasedimentary crustal rocks from Pohorje,Eastern Alps: a window to deep continental subduction

We report the first finding of diamond and moissanite in metasedimentary crustal rocks of Pohorje Mountains (Slovenia) in the Austroalpine ultrahigh‐pressure (UHP) metamorphic terrane of the Eastern Alps. Microscopic observations and Raman spectroscopy show that diamond occurs in situ as inclusions in garnet, being heterogeneously distributed. Under the optical microscope, diamond‐bearing inclusions are of cuboidal to rounded shape and of pinkish, yellow to brownish colour. The Raman spectra of the investigated diamond show a sharp, first order peak of sp³‐bonded carbon, in most cases centred between 1332 and 1330 cm^?1, with a full width at half maximum between 3 and 5 cm^?1. Several spectra show Raman bands typical for disordered graphitic (sp²‐bonded) carbon. Detailed observations show that diamond occurs either as a monomineralic, single‐crystal inclusion or it is associated with SiC (moissanite), CO₂ and CH₄ in polyphase inclusions_. This rare record of diamond occurring with moissanite as fluid‐inclusion daughter minerals implies the crystallization of diamond and moissanite from a supercritical fluid at reducing conditions. Thermodynamic modelling suggests that diamond‐bearing gneisses attained P–T conditions of ≥3.5 GPa and 800–850 °C, similar to eclogites and garnet peridotites. We argue that diamond formed when carbonaceous sediment underwent UHP metamorphism at mantle depth exceeding 100 km during continental subduction in the Late Cretaceous (c. 95–92 Ma). The finding of diamond confirms UHP metamorphism in the Pohorje Mountains, the most deeply subducted part of Austroalpine units.