Impacts of solar intermittency on future photovoltaic reliability

As photovoltaic power is expanding rapidly worldwide, it is imperative to assess its promise under future climate scenarios. While a great deal of research has been devoted to trends in mean solar radiation, less attention has been paid to its intermittent character, a key challenge when compounded with uncertainties related to climate variability. Using both satellite data and climate model outputs, we characterize solar radiation intermittency to assess future photovoltaic reliability. We find that the relation between the future power supply and long-term mean solar radiation trends is spatially heterogeneous, showing power reliability is more sensitive to the fluctuations of mean solar radiation in hot arid regions. Our results highlight how reliability analysis must account simultaneously for the mean and intermittency of solar inputs when assessing the impacts of climate change on photovoltaics.

Xylem-phloem hydraulic coupling explains multiple osmoregulatory responses to salt stress

Salinity is known to affect plant productivity by limiting leaf-level carbon exchange, root water uptake, and carbohydrates transport in the phloem. However, the mechanisms through which plants respond to salt exposure by adjusting leaf gas exchange and xylem-phloem flow are still mostly unexplored. A physically based model coupling xylem, leaf, and phloem flows is here developed to explain different osmoregulation patterns across species. Hydraulic coupling is controlled by leaf water potential, ψ_l , and determined under four different maximization hypotheses: water uptake (1), carbon assimilation (2), sucrose transport (3), or (4) profit function - i.e. carbon gain minus hydraulic risk. All four hypotheses assume that finite transpiration occurs, providing a further constraint on ψ_l . With increasing salinity, the model captures different transpiration patterns observed in halophytes (nonmonotonic) and glycophytes (monotonically decreasing) by reproducing the species-specific strength of xylem-leaf-phloem coupling. Salt tolerance thus emerges as plant's capability of differentiating between salt- and drought-induced hydraulic risk, and to regulate internal flows and osmolytes accordingly. Results are shown to be consistent across optimization schemes (1-3) for both halophytes and glycophytes. In halophytes, however, profit-maximization (4) predicts systematically higher ψ_l than (1-3), pointing to the need of an updated definition of hydraulic cost for halophytes under saline conditions.

North Atlantic controls on wintertime warm extremes and aridification trends in the Middle East

The Middle East is one of the most water stressed regions in the world, receiving the majority of its hydrological input during the winter, in the form of highly variable and scattered precipitation. The persistence of wintertime anticyclonic conditions over the region can deflect storm tracks and result in extended spells of exceptionally hot weather, favoring prolonged droughts and posing a major threat to the already fragile hydrological equilibrium of the Middle East. Despite their potential impacts on water-security, winter warm spells (WWS’s) have received far less attention than their summer counterparts, and the climatic drivers leading to WWS’s onset are still largely unexplored. Here, we investigate their relationship with the internal modes of variability in the Atlantic Ocean, already known to influence winter circulation and extremes in Eurasia and Northern America. We show that the occurrence of WWS’s is strongly correlated with Atlantic variability over decadal time scales. To explain this correlation, we propose a teleconnection mechanism linking Atlantic variability to WWS’s via the propagation of Rossby waves from the North Atlantic pool, and the mediation of the Mediterranean circulation – thereby providing a basis to better predict future warming and aridification trends in the Middle East.

Surface alteration of calcite: interpreting macroscopic observations by means of AFM

Wettability has been recognized to play a fundamental role in the efficacy of water flooding processes of carbonate oil and gas reservoirs.

Causality and persistence in ecological systems: a nonparametric spectral granger causality approach

Abstract Directionality in coupling, defined as the linkage relating causes to their effects at a later time, can be used to explain the core dynamics of ecological systems by untangling direct and feedback relationships between the different components of the systems. Inferring causality from measured ecological variables sampled through time remains a formidable challenge further made difficult by the action of periodic drivers overlapping the natural dynamics of the system. Periodicity in the drivers can often mask the self-sustained oscillations originating from the autonomous dynamics. While linear and direct causal relationships are commonly addressed in the time domain, using the well-established machinery of Granger causality (G-causality), the presence of periodic forcing requires frequency-based statistics (e.g., the Fourier transform), able to distinguish coupling induced by oscillations in external drivers from genuine endogenous interactions. Recent nonparametric spectral extensions of G-causality to the frequency domain pave the way for the scale-by-scale decomposition of causality, which can improve our ability to link oscillatory behaviors of ecological networks to causal mechanisms. The performance of both spectral G-causality and its conditional extension for multivariate systems is explored in quantifying causal interactions within ecological networks. Through two case studies involving synthetic and actual time series, it is demonstrated that conditional G-causality outperforms standard G-causality in identifying causal links and their concomitant timescales.

Stochastic modelling of phytoremediation

Leaching of heavy metals and other contaminants from soils poses a significant environmental threat as it affects the quality of downstream water bodies. Quantifying these losses is particularly important when employing phytoremediation approaches to reduce soil contamination, as contaminant escaping the system through leaching cannot be taken up by vegetation. Despite its undoubted importance, the role of such hydrologic forcing has seldom been fully considered in models describing the long-term contaminant mass balance during phytoremediation. The partitioning of contaminants between leaching and vegetation uptake is controlled by a number of biophysical processes as well as rainfall variability. Here, we develop a novel stochastic framework that provides analytical expressions to quantify the partitioning of contaminants between leaching and plant uptake and the probability of phytoremediation duration as a function of rainfall statistics and soil and vegetation characteristics. Simple expressions for the mean phytoremediation duration and effectiveness (defined as the fraction of contaminant that is recovered in plant biomass) are derived. The proposed framework can be employed to estimate under which conditions phytoremediation is more efficient, as well as to design phytoremediation projects that maximize contaminant recovery and minimize the duration of the remediation process.

On the properties of stochastic intermittency in rainfall processes

In this work we propose a mixed approach to deal with the modelling of rainfall events, based on the analysis of geometrical and statistical properties of rain intermittency in time, combined with the predictability power derived from the analysis of no-rain periods distribution and from the binary decomposition of the rain signal. Some recent hypotheses on the nature of rain intermittency are reviewed too. In particular, the internal intermittent structure of a high resolution pluviometric time series covering one decade and recorded at the tipping bucket station of the University of Genova is analysed, by separating the internal intermittency of rainfall events from the inter-arrival process through a simple geometrical filtering procedure. In this way it is possible to associate no-rain intervals with a probability distribution both in virtue of their position within the event and their percentage. From this analysis, an invariant probability distribution for the no-rain periods within the events is obtained at different aggregation levels and its satisfactory agreement with a typical extreme value distribution is shown.