The Buffon's needle problem and the design of a geophysical survey

A logical procedure for designing a geophysical survey when sampling an area with a regular grid can be summarized as follows: model the expected anomaly, estimate the expected noise level, estimate the area of the anomaly above the noise level, choose the spacing, in both the x - and y -directions, of the measurement grid. This last step can be approached according to two main strategies: either when applying the sampling theorem to the shortest dimension of the anomaly or when using a coarser grid, leaving a more complete definition of the anomaly to a later fitting. When following this second option, it can be constructive to estimate the probability of intercepting a given anomaly with a specific segment of profile and a given profile spacing. This latter procedure is analysed by considering a rectangle approximating the plane projection of the anomaly shape and taking into account various ratios between the grid spacing and the rectangle sides. The formulae for estimating the probability of intersecting a given anomaly with a given segment of a given profile spacing are calculated. To demonstrate the accuracy of the results, a Monte-Carlo simulation on a synthetic magnetic map was performed, obtaining, for different ratios between the sides, segment length and profile interval, an agreement better than 0.1% with the analytical formulae.     

A procedure for landslide susceptibility zonation by the conditional analysis method

Numerous methods have been proposed for landslide probability zonation of the landscape by means of a Geographic Information System (GIS). Among the multivariate methods, i.e. those methods which simultaneously take into account all the factors contributing to instability, the Conditional Analysis method applied to a subdivision of the territory into Unique Condition Units is particularly straightforward from a conceptual point of view and particularly suited to the use of a GIS. In fact, working on the principle that future landslides are more likely to occur under those conditions which led to past instability, landslide susceptibility is defined by computing the landslide density in correspondence with different combinations of instability factors. The conceptual simplicity of this method, however, does not necessarily imply that it is simple to implement, especially as it requires rather complex operations and a high number of GIS commands. Moreover, there is the possibility that, in order to achieve satisfactory results, the procedure has to be repeated a few times changing the factors or modifying the class subdivision. To solve this problem, we created a shell program which, by combining the shell commands, the GIS Geographical Research Analysis Support System (GRASS) commands and the gawk language commands, carries out the whole procedure automatically. This makes the construction of a Landslide Susceptibility Map easy and fast for large areas too, and even when a high spatial resolution is adopted, as shown by application of the procedure to the Parma River basin, in the Italian Northern Apennines.     

The effect of the 19F(α, p)22Ne reaction rate uncertainty on the yield of fluorine from Wolf–Rayet stars

In the light of recent recalculations of the  ¹⁹F(α, p)²²Ne  reaction rate, we present results of the expected yield of ¹⁹F from Wolf–Rayet (WR) stars. In addition to using the recommended rate, we have computed models using the upper and lower limits for the rate, and hence we constrain the uncertainty in the yield with respect to this reaction. We find a yield of  3.1 × 10⁻⁴ M_⊙  of ¹⁹F with our recommended rate, and a difference of a factor of 2 between the yields computed with the upper and lower limits. In comparison with previous work we find a difference in the yield of a factor of approximately 4, connected with a different choice of mass loss. Model uncertainties must be carefully evaluated in order to obtain a reliable estimate of the yield, together with its uncertainties, of fluorine from WR stars.     

On the MHD Acceleration of Astrophysical Jets

We present a 2.5D magnetohydrodynamic (MHD) simulation of the acceleration of a collimated jet from a magnetized accretion disk. We employ a MHD Adaptive Mesh Refinement (AMR) code (FLASH—University of Chicago). Thanks to this tool we can follow the evolution of the system for many dynamical timescales with a high-spatial resolution. Assuming an initial condition in which a Keplerian disk, thus with no accretion motions, is threaded by a uniform poloidal magnetic field, we show how both the accretion flow and the acceleration of the outflow occur, and we present in detail which are the forces responsible for the jet launching and collimation. Our simulation also shows how the collimating forces due to the self-generated toroidal magnetic field can produce some peculiar knotty features.     

Accuracy assessment of the GPS-TEC calibration constants by means of a simulation technique

During the last 2 decades, Global Positioning System (GPS) measurements have become a very important data-source for ionospheric studies. However, it is not a direct and easy task to obtain accurate ionospheric information from these measurements because it is necessary to perform a careful estimation of the calibration constants affecting the GPS observations, the so-called differential code biases (DCBs). In this paper, the most common approximations used in several GPS calibration methods, e.g. the La Plata Ionospheric Model (LPIM), are applied to a set of specially computed synthetic slant Total Electron Content datasets to assess the accuracy of the DCB estimation in a global scale scenario. These synthetic datasets were generated using a modified version of the NeQuick model, and have two important features: they show a realistic temporal and spatial behavior and all a-priori DCBs are set to zero by construction. Then, after the application of the calibration method the deviations from zero of the estimated DCBs are direct indicators of the accuracy of the method. To evaluate the effect of the solar activity radiation level the analysis was performed for years 2001 (high solar activity) and 2006 (low solar activity). To take into account seasonal changes of the ionosphere behavior, the analysis was repeated for three consecutive days close to each equinox and solstice of every year. Then, a data package comprising 24 days from approximately 200 IGS permanent stations was processed. In order to avoid unwanted geomagnetic storms effects, the selected days correspond to periods of quiet geomagnetic conditions. The most important results of this work are: i) the estimated DCBs can be affected by errors around ±8 TECu for high solar activity and ±3 TECu for low solar activity; and ii) DCB errors present a systematic behavior depending on the modip coordinate, that is more evident for the positive modip region.     

The impact of soil moisture–atmosphere coupling on daily maximum surface temperatures in Southeastern South America

Based on a series of experiments conducted by two regional climate models (RCA4 and LMDZ) with and without soil moisture-atmosphere coupling, we investigate the role of soil moisture on the occurrence of surface air temperature extremes and its persistence in Southeastern South America. Our analysis reveals that both factors, soil moisture-atmosphere coupling and relatively drier soil conditions, enhance the temperature extremes. In addition, the existence of soil-atmosphere coupling and the associated soil moisture variability is crucial for the development of the extremes in SESA. The key role of soil-atmosphere coupling is also reflected in the intrinsic persistence of hot days, which is greater in simulations with interactive soil moisture than in those with prescribed soil conditions. In the absence of soil-atmosphere coupling, the imprint of the anomalous dry (and also wet) soil conditions on the intensity and persistence of hot days is weaker.

     

Resolution effects on regional climate model simulations of seasonal precipitation over Europe

We analyze a set of nine regional climate model simulations for the period 1961–2000 performed at 25 and 50 km horizontal grid spacing over a European domain in order to determine the effects of horizontal resolution on the simulation of precipitation. All of the models represent the seasonal mean spatial patterns and amount of precipitation fairly well. Most models exhibit a tendency to over-predict precipitation, resulting in a domain-average total bias for the ensemble mean of about 20% in winter (DJF) and less than 10% in summer (JJA) at both resolutions, although this bias could be artificially enhanced by the lack of a gauge correction in the observations. A majority of the models show increased precipitation at 25 km relative to 50 km over the oceans and inland seas in DJF, JJA, and ANN (annual average), although the response is strongest during JJA. The ratio of convective precipitation to total precipitation decreases over land for most models at 25 km. In addition, there is an increase in interannual variability in many of the models at 25 km grid spacing. Comparison with gridded observations indicates that a majority of models show improved skill in simulating both the spatial pattern and temporal evolution of precipitation at 25 km compared to 50 km during the summer months, but not in winter or on an annual mean basis. Model skill at higher resolution in simulating the spatial and temporal character of seasonal precipitation is found especially for Great Britain. This geographic dependence of the increased skill suggests that observed data of sufficient density are necessary to capture fine-scale climate signals. As climate models increase their horizontal resolution, it is thus a key priority to produce high quality fine scale observations for model evaluation.