Van der Waals and resonance interactions between accelerated atoms in vacuum and the Unruh effect

We discuss different physical effects related to the uniform acceleration of atoms in vacuum, in the framework of quantum electrodynamics. We first investigate the van der Waals/Casimir-Polder dispersion and resonance interactions between two uniformly accelerated atoms in vacuum. We show that the atomic acceleration significantly affects the van der Waals force, yielding a different scaling of the interaction with the interatomic distance and an explicit time dependence of the interaction energy. We argue how these results could allow for an indirect detection of the Unruh effect through dispersion interactions between atoms. We then consider the resonance interaction between two accelerated atoms, prepared in a correlated Bell-type state, and interacting with the electromagnetic field in the vacuum state, separating vacuum fluctuations and radiation reaction contributions, both in the free-space and in the presence of a perfectly reflecting plate. We show that nonthermal effects of acceleration manifest in the resonance interaction, yielding a change of the distance dependence of the resonance interaction energy. This suggests that the equivalence between temperature and acceleration does not apply to all radiative properties of accelerated atoms. To further explore this aspect, we evaluate the resonance interaction between two atoms in non inertial motion in the coaccelerated (Rindler) frame and show that in this case the assumption of an Unruh temperature for the field is not required for a complete equivalence of locally inertial and coaccelerated points of views.Comment: 8 pages, Proceedings of the Eighth International Workshop DICE 2016 Spacetime - Matter - Quantum Mechanic

ECOHYDROLOGY IN MEDITERRANEAN AREAS: A NUMERICAL MODEL TO DESCRIBE GROWING SEASONS OUT OF PHASE WITH PRECIPITATIONS

The probabilistic description of soil moisture dynamics is a relatively new topic in hydrology. The most common ecohydrological models start from a stochastic differential equation describing the soil water balance, where the unknown quantity, the soil moisture, depends both on spaces and time. Most of the solutions existing in literature are obtained in a probabilistic framework and under steady-state condition; even if this last condition allows the analytical handling of the problem, it has considerably simplified the same problem by subtracting generalities from it. The steady-state hypothesis, appears perfectly applicable in arid and semiarid climatic areas like those of African's or middle American's savannas, but it seems to be no more valid in areas with Mediterranean climate, where, notoriously, the wet season foregoes the growing season, recharging water into the soil. This moisture stored at the beginning of the growing season (known as soil moisture initial condition) has a great importance, especially for deep-rooted vegetation, by enabling survival in absence of rainfalls during the growing season and, however, keeping the water stress low during the first period of the same season. The aim of this paper is to analyze the soil moisture dynamics using a simple non-steady numerical ecohydrological model. The numerical model here proposed is able to reproduce soil moisture probability density function, obtained analytically in previous studies for different climates and soils in steady-state conditions; consequently it can be used to compute both the soil moisture time-profile and the vegetation static water stress time-profile in non-steady conditions. Here the differences between the steady-analytical and the non-steady numerical probability density functions are analyzed, showing how the proposed numerical model is able to capture the effects of winter recharge on the soil moisture. The dynamic water stress is also numerically evaluated, implicitly taking into account the soil moisture condition at the beginning of the growing season. It is also shown the role of different annual climatic parameterizations on the soil moisture probability density function and on the vegetation water stress evaluation

Daily rainfall statistics in Sicily (1920-2000)

Rainfall characteristics are crucial for vegetation patterns formation and evolution in Mediterranean ecosystems. Changes in rainfall frequency and intensity could cause vegetation water stress for some plant species and benefit, at the same time, other species, driving coexistence and competition dynamics. The changes in the precipitation characteristics are sometimes more important than the changes in the total amount of precipitation in determining the partitioning between green and blue water with several implications for both the vegetation communities health and water resource management. Decreasing rainfall is a clear signature of climate change in Mediterranean countries. Annual and winter totals have been demonstrated to decrease in the past century and GCMs forecast a progressive worsening of the current situation even if it is still not clear if and how rainfall could be modified in its temporal and seasonal patterns. This study aims to analyze daily rainfall properties in Sicily in the last century. Namely the daily depths and interarrival times between events are investigated in about 50 stations, also characterizing seasonal rainfall features. The presence of significant trend has been detected using the non parametric Mann Kendall test

Climate changes effects on vegetation in Mediterranean areas

The Mediterranean ecosystems evolved under climatic conditions characterized by precipitations markedly out of phase with the growing period for the vegetation there established. In such environments, deep and shallow rooted species cohabit and compete each other. The formers, being characterized by deeper root, are able to utilize the water stored during the dormant season, while the conditions of shallow rooted plant are closely related to the intermittence of the precipitations. A numerical model has been here used in order to carry out an analysis of the potential climate changes influence on the vegetation state in a typical Mediterranean environment, such as Sicilian one. The most important consequences arising from climate changes in the Mediterranean area, due to the CO2 increase, are the temperatures raise and the contemporaneous rainfall reduction. Probably, this reduction could be accompanied by an increase in events intensity and, at the same time, by a decrease in the number of annual events. There are very few information about possible changes in the distribution of the rainfall events over the year. However, according to the analysis of the recorded trend, it is possible to predict that the rainfall reduction will be mainly concentrated during the autumnal and wintry months. The goal of this work is a quantitative evaluation of the effects due to the climatic forcing changes, on vegetation water stress. In particular, great attention is paid to the effects that rainfall decrease may have on vegetation, by itself or coupled with the temperature increase. A detailed investigation on the influence of the variations in rainfall seasonality, frequency and intensity is carried out. In this work two vegetation covers, with shallow and deep rooting depth (grass and tree) laying on three different soil types (loamy sand, sandy loam and clay) are considered. Simulations on Mediterranean ecosystems have lead to recognize the role of the rainfall amount, frequency and temporal distribution. Rainfall decrease increases the vegetation water stress much more than temperature increase do. Intense and rare rainfall events, as they are expected to be, could attenuate the effects of rainfall reduction because of the less interception correlated to them. The future rainfall distribution over the year is also crucial for vegetation water stress. If the current ratio between the growing season and the dormant season rainfall will be kept, trees and grasses will suffer a common increase of water stress, which seems more severe for trees than for grasses. Otherwise, if the rainfall reduction will be concentrated during the wintry periods, as emerges from literature, grasses will have some advantages over the trees species. In this conditions grasses will keep the water stress similar to the nowadays value, while trees will suffer for the lack of the winter recharge increasing their water stress

Ecohydrology in Mediterranean areas: a numerical model to describe growing seasons out of phase with precipitations

International audienceThe probabilistic description of soil moisture dynamics is a relatively new topic in hydrology. The most common ecohydrological models start from a stochastic differential equation describing the soil water balance, where the unknown quantity, the soil moisture, depends both on spaces and time. Most of the solutions existing in literature are obtained in a probabilistic framework and under steady-state condition; even if this last condition allows the analytical handling of the problem, it has considerably simplified the same problem by subtracting generalities from it. The steady-state hypothesis, appears perfectly applicable in arid and semiarid climatic areas like those of African's or middle American's savannas, but it seems to be no more valid in areas with Mediterranean climate, where, notoriously, the wet season foregoes the growing season, recharging water into the soil. This moisture stored at the beginning of the growing season (known as soil moisture initial condition) has a great importance, especially for deep-rooted vegetation, by enabling survival in absence of rainfalls during the growing season and, however, keeping the water stress low during the first period of the same season. The aim of this paper is to analyze the soil moisture dynamics using a simple non-steady numerical ecohydrological model. The numerical model here proposed is able to reproduce soil moisture probability density function, obtained analytically in previous studies for different climates and soils in steady-state conditions; consequently it can be used to compute both the soil moisture time-profile and the vegetation static water stress time-profile in non-steady conditions. Here the differences between the steady-analytical and the non-steady numerical probability density functions are analyzed, showing how the proposed numerical model is able to capture the effects of winter recharge on the soil moisture. The dynamic water stress is also numerically evaluated, implicitly taking into account the soil moisture condition at the beginning of the growing season. It is also shown the role of different annual climatic parameterizations on the soil moisture probability density function and on the vegetation water stress evaluation. The proposed model is applied to a case study characteristic of Mediterranean climate: the watershed of Eleuterio in Sicily (Italy)

Spatial distribution of rainfall trends in Sicily (1921–2000)

The feared global climate change could have important effects on various environmental variables including rainfall in many countries around the world. Changes in precipitation regime directly affect water resources management, agriculture, hydrology and ecosystems. For this reason it is important to investigate the changes in the spatial and temporal rainfall pattern in order to improve water management strategies. In this study a non-parametric statistical method (Mann–Kendall rank correlation method) is employed in order to verify the existenceof trend in annual, seasonal and monthly rainfall and the distribution of the rainfall during the year. This test is applied to about 250 rain gauge stations in Sicily (Italy) after a series of procedures finalized to the estimation of missing records and to the verification of data consistency. In order to understand the regional pattern of precipitation in Sicily, the detected trends are spatially interpolated using spatial analysis techniques in a GIS environment. The results show the existence of a generalized negative trend for the entire region

Modelling the shrub encroachment in a grassland with a Cellular Automata Model

Abstract. Arid and semi-arid grasslands of southwestern North America have changed dramatically over the last 150 years as a result of shrub encroachment, i.e. the increase in density, cover and biomass of indigenous shrubby plants in grasslands. Numerous studies have documented the expansion of shrublands in the southwestern American grasslands; in particular shrub encroachment has occurred strongly in part of the northern Chihuahuan desert since 1860. This encroachment has been simulated using an ecohydrological Cellular Automata model, CATGraSS. It is a spatially distributed model driven by spatially explicit irradiance and runs on a fine-resolution gridded domain. Plant competition is modelled by keeping track of mortality and establishment of plants; both are calculated probabilistically based on soil moisture stress. For this study CATGraSS has been improved with a stochastic fire module and a grazing function. The model has been implemented in a small area in Sevilleta National Wildlife Refuge (SNWR), characterized by two vegetation types (grass savanna and creosote bush shrub), considering as encroachment causes the fire return period increase, the grazing increase, the seed dispersal caused by animals, the role of wind direction and plant type competition. The model is able to reproduce the encroachment that has occurred in SNWR, simulating an increase of the shrub from 2% in 1860 to the current shrub percentage, 42%, and highlighting among the most influential factors the reduced fire frequency and the increased grazing intensity

Studying the relationships between hourly precipitation extremes and dewpoint temperature in Sicily.

According to the well-known Clausius-Clapeyron relation, the maximum moisture content of the atmosphere increases with approximately 7% per degree temperature raise (CC-scaling rate). Under the hypothesis that relative humidity does not change, an increase in the water vapor should occur at the same rate. For this reason we could expect for the coming years an increase in the intensity of extreme precipitation as a consequence of the global climate warming. Trend on precipitation extremes and possible links to changes in atmospheric temperature and moisture are investigated in different parts of the world, and a number of observational studies has exhibited scaling rates that are either higher (super-CC) or lower (sub-CC) than CC scaling rate depending on the climatic areas under analysis. One of the most common approaches consists in a regression analysis to interpret the relationships between extreme percentiles of rainfall and surface temperature, and this is often due to the lack of availability of consistent historical data series for other variables of interest, such as the relative air humidity. In some applications, combined temperature-humidity measures, such as the dew point temperature, have been used as proxy measures. In this study we investigate, at the regional scale (Sicily, Italy), the scaling rate between hourly precipitation extremes and dew point temperature. This last is then used as a measure of near surface absolute humidity and is computed for each rainfall event at the same time (T0) and, 2 (T2) and 4 (T4) hours before the event occurrence. The scaling rate is studied at both the level of entire hydrological year and the seasonal level, dividing the calendar year in a wet, colder and more rainy, season and a dry warmer season. The high-resolution dataset from the regional agency SIAS (Agro-meteorological Information Service of Sicily) has been used and it is constituted by data of 10-min rainfall, hourly temperature and maximum hourly relative air humidity, collected by 107 gauges from 2003 to 2015. The hourly temperature and maximum hourly relative air humidity data are combined to provide hourly time-series of dew-point temperature at each gauge. The samples from the different gauges are pooled together forming six different samples relative to six different sub-regions defined within the Sicilian island and at the level of entire region (unique regional sample). At the level of single sub-region a binning procedure is used, investigating the suitability of exponential regression models for interpreting the relationships between dew point temperature (median for bin) and extreme rainfall intensity (95th percentile for bin). A LOESS (LOcally-wEighted Scatter-plot Smoothing) regression analysis is considered for the study of the regional sample. Similar results are obtained from the analysis at the annual level and for the wet season, with high coefficients of determination (R2 >0.94) for all the sub-regions, demonstrating the appropriateness of the used regression models, and with sub-CC scaling rate (4-5%°C1). For the dry season, both the R2 and the rates (especially for T2 and T4) are lower; moreover, the LOESS analysis highlights a decreasing scaling rate at higher dew point temperatures