Solar wind induction in Mercury: Constraints on the formation of a magnetosphere

The discovery of Mercury's magnetosphere by Mariner 10 was surprising since the conventional view of regenerative planetary dynamos had been that the spin requirement would likely have been in excess of the observed spin rate of Mercury. Also internal fluid motions were not expected to be sufficiently large. This paper explores the alternative model of the formation of Mercury's magnetosphere via electromagnetic induction forced by the solar wind. It is shown, however, that the constraints are so severe as to limit severely the applicability of such a model. Although induction is easily observed on the Moon, the modification of the magnetic boundary condition associated with a plasma magnetosphere on Mercury rules out its formation via induction except for interplanetary driving fields which are decreasing in amplitude. That model is explored but retains the difficulty that induced magnetospheres tend to be of small radial and temporal extent compared to that inferred by Ness et al. for Mercury.     

Stochastic evaluation of simple pairing approaches to reconstruct incomplete rainfall time series

Two-station pairing approaches are routinely used to infill missing information in incomplete rainfall databases. We evaluated the performance of three simple methodologies to reconstruct incomplete time series in presence of variable nonlinear correlation between data pairs. Nonlinearity stems from the statistics describing the marginal peak-over-threshold (POT) values of rainfall events. A Monte Carlo analysis was developed to quantitatively assess expected errors from the use of chronological pairing (CP) with linear and nonlinear regression and frequency pairing (FP). CP is based on a priori selection of regression functions, while FP is based on matching the probability of non-exceedance of an event from one time series with the probability of non-exceedance of a similar event from another time series. We adopted a generalized Pareto (GP) model to describe POT events, and a t-copula algorithm to generate reference nonlinearly correlated pairs of random temporal distributions distributed according with the GP model. The results suggest that the optimal methodology strongly depends on GP statistics. In general, CP seems to provide the lowest errors when GP statistics were similar and correlation became linear; we found that a power-2 function performs well for the selected statistics when the number of missing points is limited. FP outperforms the other methods when POT statistics are different and variables are markedly nonlinearly correlated. Ensemble-based results seem to be supported by the analysis of observed precipitation at two real-world gauge stations.     

Adaptive particle swarm optimization for optimal orbital elements of binary stars

The paper presents an adaptive particle swarm optimization (APSO) as an alternative method to determine the optimal orbital elements of the star η Bootis of MK type G0 IV. The proposed algorithm transforms the problem of finding periodic orbits into the problem of detecting global minimizers as a function, to get a best fit of Keplerian and Phase curves. The experimental results demonstrate that the proposed approach of APSO generally more accurate than the standard particle swarm optimization (PSO) and other published optimization algorithms, in terms of solution accuracy, convergence speed and algorithm reliability.     

Exact Bianchi type-II, VIII and IX perfect fluid cosmological models in Saez-Ballester theory of gravitation

Exact Bianchi type-II, VIII and IX cosmological models are obtained in a scalar tensor theory proposed by Saez and Ballester (Phys. Lett. A 113:467, 1986) with perfect fluid as a source. Some physical and geometrical properties of the models are studied. It is observed that the models are free from initial singularities and they are expanding with time.     

Stability of equilibrium points in the generalized perturbed restricted three-body problem

This paper studies the existence and stability of equilibrium points under the influence of small perturbations in the Coriolis and the centrifugal forces, together with the non-sphericity of the primaries. The problem is generalized in the sense that the bigger and smaller primaries are respectively triaxial and oblate spheroidal bodies. It is found that the locations of equilibrium points are affected by the non-sphericity of the bodies and the change in the centrifugal force. It is also seen that the triangular points are stable for 0<μ<μ _c and unstable for \(\mu_{c}\le\mu <\frac{1}{2}\), where μ _c is the critical mass parameter depending on the above perturbations, triaxiality and oblateness. It is further observed that collinear points remain unstable.     

The Problem of the Height Dependence of Magnetic Fields in Sunspots

To understand the physics of sunspots, it is important to know the properties of their magnetic field, and especially its height stratification plays a substantial role. There are mainly two methods to assess this stratification, but they yield different magnetic gradients in the photospheric layers. Determinations based on the several spectral lines of different formation heights and the slope of their profiles result in gradients of ?2 to ?3 G?km^?1, or even steeper. This is similar for the total magnetic field strength and for the vertical component of the magnetic field. The other option is to determine the horizontal partial derivatives of the magnetic field, and with the condition \(\operatorname{div} {{\boldsymbol {B}}} = 0\) also the vertical derivative is known. With this method, gradients of ?0.5 G?km^?1 and even shallower are obtained. Obviously, these results do not agree. If chromospheric spectral lines are included, only shallow gradients around ?0.5 G?km^?1 are obtained. Shallow gradients are also found from gyro-resonance measurements in the radio wave range 300?–?2000 GHz.Some indirect methods are also considered, but they cannot clarify the total picture. An analysis of a numerical simulation of a sunspot indicates a shallow gradient over a wide height range, but with slightly steeper gradients in deep layers.Several ideas to explain the discrepancy are also discussed. With no doubts cast on Maxwell’s equations, the first one is to look at the uncertainties of the formation heights of spectral lines, but a wider range of these heights would require an extension of the solar photosphere that is incompatible with observations and the theory of stellar atmospheres. Submerging and rising magnetic flux might play a role in the outer penumbra, if the resolution is too low to separate them, but it is not likely that this effect acts also in the umbra. A quick investigation assuming a spatial small scale structure of sunspots together with twist and writhe of individual flux tubes shows a reduction of the measured magnetic field strength for spectral lines sensitive to a larger height range. However, sophisticated investigations are required to prove that the explanation for the discrepancy lies here, and the problem of the height gradient of the magnetic field in sunspots is still not solved.     

The smoke is rising but where is the fire? Exploring effective online map design for wildfire warnings

The current study sought to offer guidance for developing effective web-based mapping tools for wildfire warnings by identifying (1) the important content for facilitating individuals’ decision-making, and (2) the optimal interface design for ensuring usability and ease of information access. A map-based warning tool was prototyped in the Australian context, followed by a usability and effectiveness evaluation through individual interviews and verbal protocol analysis to assess participants’ interaction with the mapping interface and information in response to the simulated warning scenario. The results demonstrated variations in participants’ approaches to wildfire warning response, revealing varied information needs. Specifically, most participants relied on their own assessment of the prospective threat, requiring specific wildfire-related information before eliciting a response. In contrast, the decision of a minority of the participants was motivated by response guidance from agencies, and accurate wildfire information was less important for their response. Imperative information for both types of residents therefore needs to be highlighted in a map-based warning tool to cater to a wide audience. Furthermore, a number of heuristics were identified for designing effective interactive functions to facilitate the control of, and access to, the various maps and textual information presented on the map-based warning interface.     

A low-dimensional subsurface model for saturated and unsaturated flow processes: ability to address heterogeneity

A low-dimensional model that describes both saturated and unsaturated flow processes in a single equation is presented. Subsurface flow processes in the groundwater, the vadose zone, and the capillary fringe are accounted for through the computation of aggregated hydrodynamic parameters that result from the integration of the governing flow equations from the bedrock to the land surface. The three-dimensional subsurface flow dynamics are thus described by a two-dimensional equation, allowing for a drastic reduction of model unknowns and simplification of the model parameterizations. This approach is compared with a full resolution of the Richards equation in different synthetic test cases. Because the model reduction stems from the vertical integration of the flow equations, the test cases all use different configurations of heterogeneity for vertical cross-sections of a soil-aquifer system. The low-dimensional flow model shows strong consistency with results from a complete resolution of the Richards equation for both the water table and fluxes. The proposed approach is therefore well suited to the accurate reproduction of complex subsurface flow processes.     

A simulation study of capillary transport,preferential retention and distribution of salts in historic sandstone buildings

Salt crystallisation is a major problem of deterioration in historic stone buildings, monuments and sculptures. The capillary rise of soil water is one of the primary sources of salts in stone structures, which evaporates leaving the salts behind. It has been noted that the spatial distribution profile of different species of salts crystallised in historic stone buildings is not homogeneous, i.e. different salts crystallise at different locations. The capillary transport and inhomogeneous spatial distribution of different salts in the porous building materials has been considered to be a result of solubility-dependent crystallisation; however, the factors responsible for this phenomenon are not clearly known. This paper aims to investigate the factors influencing the differential distribution of salts during capillary rise of soil water. In this study, the capillary transport of salts was simulated on two different sandstones—Locharbriggs, a Permo–Triassic, red sandstone and Stoke Hall, a Carboniferous, buff sandstone. The experiments were carried out under controlled environmental conditions to eliminate the possibility of evaporation-driven crystallisation of salts depending on their solubilities. The results indicate that fractionation or differential distribution of salts takes place even in the absence of evaporation and crystallisation. The sandstones exhibit properties like an ion exchange column, and ionic species present in the salt solution show differential distribution within the porous network of sandstone.     

Markov Chain Random Fields for Estimation of Categorical Variables

Multi-dimensional Markov chain conditional simulation (or interpolation) models have potential for predicting and simulating categorical variables more accurately from sample data because they can incorporate interclass relationships. This paper introduces a Markov chain random field (MCRF) theory for building one to multi-dimensional Markov chain models for conditional simulation (or interpolation). A MCRF is defined as a single spatial Markov chain that moves (or jumps) in a space, with its conditional probability distribution at each location entirely depending on its nearest known neighbors in different directions. A general solution for conditional probability distribution of a random variable in a MCRF is derived explicitly based on the Bayes’ theorem and conditional independence assumption. One to multi-dimensional Markov chain models for prediction and conditional simulation of categorical variables can be drawn from the general solution and MCRF-based multi-dimensional Markov chain models are nonlinear.