Abstract
<p>The marine boundary layer offers a unique opportunity to investigate the electrical properties of the atmosphere, as the effect of natural radioactivity in driving near surface ionization is significantly reduced over the ocean, and the concentration of aerosols is also typically lower than over land. This work addresses the temporal variability of the atmospheric electric field in the South Atlantic marine boundary layer based on measurements from the SAIL (Space-Atmosphere-Ocean Interactions in the marine boundary Layer) project. The SAIL monitoring campaign took place on board the Portuguese navy tall ship NRP Sagres during its circumnavigation expedition in 2020.  Two identical field mills (CS110, Campbell Scientific) were installed on the same mast but at different heights (about 5 and 22 meters), recording the atmospheric electric field every 1-second. Hourly averages of the atmospheric electric field are analyzed for the ship’s leg from 3<sup>rd</sup> to 25<sup>th</sup> March, between Buenos Aires (South America) and Cape Town (South Africa). The median daily curve of the electric field has a shape compatible with the Carnegie curve, but significant variability is found in the daily pattern of individual days, with only about 30% of the days exhibiting a diurnal pattern consistent with the Carnegie curve.</p>

Abstract
A non-parametric identification algorithm is proposed to identify Linear Time Periodic (LTP) systems. The period is unknown and can be any real positive number. The system is modelled as an ARX Linear Parameter Varying (LPV) system with a virtual scheduling signal consisting of two orthogonal sinusoids (a sine and a cosine) with a period equal to the system period. Hence, the system parameters are polynomial functions of the scheduling vector. As these polynomials may have infinite degree, a non-parametric model is adopted to describe the LPV system. This model is identified by a Gaussian Process Regression (GPR) algorithm where the system period is a hyperparameter. The performance of the proposed identification algorithm is illustrated through the identification of a simulated LTP continuous system described by a state-space model. The ARX-LTP discrete-time model estimated in the noiseless case was taken as the true model. Copyright (C) 2021 The Authors.

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AbstractIn this study, the geochemistry and mineralogy of regoliths formed on Fogo Island (Cape Verde), a polygenic stratovolcano built during the Quaternary, are used to assess the geomorphological factors that control the early stages of basalt weathering. Fogo Island soils are mainly derived from relatively homogenous silica-undersaturated basaltic rocks. However, a discernible exotic component is recognised in areas most exposed to prevailing winds by ratios on non-mobile elements that are hosted in different amounts by basaltic rocks (e.g., Th, Sc and Ti). Weathering extent is evidenced by a relative depletion in mobile elements (e.g., Na, Ca, Mg) and an enrichment in non-mobile elements (e.g., Ti, Fe, Sc, Al), the decomposition of the most labile minerals (olivines), and the enrichment in secondary components (phyllosilicates and some Fe-oxides, such as hematite-goethite), along with quartz supplied from non-volcanic areas. It depends on bedrock age and type (pyroclastic deposits vs. lava-flows). In particular, soils covering older volcanic units tend to be more affected by chemical alteration than those overlying younger units. In addition, more intense weathering is observed in locations characterised by a combination of moderate elevation, slopes with low gradient and relatively high rainfall. The present investigation shows that even in low humidity environments recently formed basalt are affected by weathering, with the extent of chemical decomposition being mainly determined by the age of surface exposure and local orographic/climatic features.

Abstract
Geophysical techniques can be successfully applied towards the detection of buried explosive devices, the ground-penetrating radar (GPR) being an example of one such method. This technology works through emission and reception of electromagnetic radio waves being thus able to detect the presence of a subsurface object fundamentally due to reflections from contrasting electromagnetic properties between the object and the surrounding medium (e.g., soil). Many factors can influence the success of a GPR survey (e.g., target type, soil type, environmental conditions, GPR antenna frequency, data processing techniques), being essential to know and understand their likely effects before performing GPR studies, mainly in real cases. In this paper, through the analysis of case studies related to the use of GPR technology towards the detection of buried explosive devices, we intend to arrange and layout the main prior knowledge that a forensic geophysical expert must have when dealing with this type of fieldwork.