1,721,680 research outputs found
Low energy solar neutrinos with borexino
No full textLow energy solar neutrinos are a unique tool to investigate the nuclear reactionsthat fuel the Sun. The Borexino experiment, based on a 270 ton ultra-pure liquid scintillator detector at Laboratori Nazionali del Gran Sasso, was conceivedto measure solar neutrino fluxes in the MeV and sub-MeV energy range. Thedata taking started on 2007 and thanks to the unprecedented level of radiopurity achieved in the inner part of the detector, a real time spectroscopy ofthe main components of the pp chain was possible. After a purification process, in the phase II data, the simultaneous fit of all the pp-chain componentswas performed and the interaction rates of pp, 7Be and pep were extractedwith the highest precision to date. In this paper, after a description of themain properties of Borexino detector, the most important analysis techniques,necessary for the data selection and for the final fit of the phase II data will beexplained
Exploring the linkage between dew point temperature and precipitation extremes: A multi-time-scale analysis on a semi-arid Mediterranean region
Full text linkUnderstanding warming climate implications on precipitation is of crucial importance, especially for areas particularly subjected to climate changes and land use/cover modifications, which could be extremely vulnerable to phenomena typically caused by rainfall extremes, such as floods and landslides. Past decade has been witnessing an increasing interest on simple modeling approaches based on the observation of commonly available meteorological variables and their physical linkages. In particular, based on the well-known thermodynamic Clausius-Clapeyron (CC) equation, it was widely investigated the scaling relation between rainfall extremes and variables representative of the near surface humidity, typically the surface air temperature, through the use of general regression models. In some cases, conventional approaches have shown some evident limitations related to the use of surface temperature as covariate, limited size of the analyzed datasets and some climatic peculiarities of the investigated areas, especially for tropical, arid and semi-arid environments. The use of quantile regression instead of general regression and dew point temperature instead of surface temperatures have recently revealed promising potentialities for overcoming some of the above limitations for wet areas, while it has been scarcely tested in arid and semi-arid regions. The purpose of this study is to analyze the suitability of a quantile regression-based approach in a semi-arid Mediterranean region and to explore the impact of different modeling choices on the estimation of the scaling rate. More specifically, the sensitivity of extreme precipitation to dew point temperature is investigated through a multi-time-scale analysis, performed on a wide regional dataset of Sicily (Italy) including high temporal resolution climatic data from 86 gauges. The role of the considered rainfall accumulation period, conditional quantile and time-lag between precipitation-dew point temperature paired data is investigated considering different spatial and temporal data aggregation. The results reveal scaling rate values always below the theoretical CC-rate. Hourly and sub-hourly rainfall extremes are more sensitive to changes in dew point temperature than longer precipitation. The analysis of the driest and hottest season shows a dew point temperature dependence of extreme rainfall more complex than for the other seasons. Compared to the use of general regression, the scaling relationship observed with the quantile regression approach, here used, is more regular across different gauges and sub-regions, rainfall accumulation periods and seasons, with similar scaling rates, confirming promising potentialities areas also for semi-arid regions
Exploring the use of multi-gene genetic programming in regional models for the simulation of monthly river runoff series
No full textThe use of new data-driven approaches based on the so-called expert systems to simulate runoff generation processes is a promising frontier that may allow for overcoming some modeling difficulties related to more complex traditional approaches. The present study highlights the potential of expert systems in creating regional hydrological models, for which they can benefit from the availability of large database. Different soft computing models for the reconstruction of the monthly natural runoff in river basins are explored, focusing on a new class of heuristic models, which is the Multi-Gene Genetic Programming (MGGP). The region under study is Sicily (Italy), where a regression based rainfall-runoff model, here used as benchmark model, was previously built starting from the analysis of a regional database relative to several gauged watersheds across the region. In the present study, different models are created using the same dataset, including: six MGGPs generated considering different modeling set-up; a Multi-Layer Perceptron Artificial Neural Network (ANN); two new hybrid models (ANN-MGGP), combining a Classifier ANN and two MGGPs that simulate separately low and high runoff. Results show how all the soft computing models perform similarly and outperform the benchmark model, demonstrating that MGGP can be considered as a valid alternative to the much more consolidated ANN technique. The new introduced hybrid ANN-MGGP is the only model showing at least satisfactory performance (i.e. Nash-Sutcliffe Efficiency above 0.5) over the full range of 38 watersheds explored, representing a useful regional tool for reconstructing monthly runoff series also at ungauged sites
Classification of Extreme Rainfall for a Mediterranean Region by Means of Atmospheric Circulation Patterns and Reanalysis Data
Full text linkThe atmospheric circulation can be recognized as one of the causes of severe rainfall events occurrence. Such events, especially when are characterized by short durations and high intensities, result in flood events in the Mediterranean area. It is very important to understand how these heavy rainfall events, which can be usually identified with convective rainfall, are related to the different types of atmospheric circulation. In order to do this, some weather circulation patterns (WPs), which have been derived for the Europe, have been first connected with the rainfall annual maxima (AMAX) recorded over the Sicily. The analyses allowed to identify those WPs that are more likely to result into the occurrence of the AMAX. Secondly, two ERA-Interim reanalysis indexes have been used to define a criterion to distinguish those AMAX mainly due to a convective component from those more related to a stratiform precipitation, also detecting a transient zone between these two types of events. Finally, the main results have been connected together with the aim to define a set of triggering factors of extreme rainfall events
Precipitazione e pattern di circolazione atmosferica in Sicilia
Full text linkGli eventi di precipitazione intensa possono spesso causare perdita di vite umane e ingenti danni di
tipo economico, soprattutto nei casi in cui questi colpiscano piccoli bacini caratterizzati da bassi tempi
di corrivazione.
Dal momento che alcuni schemi di circolazione atmosferica comportano un accumulo di umidità in
certe parti dell’atmosfera, a seguito del quale possono scatenarsi eventi di particolare entità, la
circolazione atmosferica può essere utilizzata come un indicatore del verificarsi di eventi di
precipitazione intensa.
Nel presente lavoro si è cercato di trovare una relazione tra alcuni pattern di circolazione atmosferica,
sviluppati dal UK Met Office, e i massimi annuali di precipitazione registrati dalla rete di stazioni
pluviografiche siciliane dell’Osservatorio delle Acque. Le analisi condotte hanno portato
all’identificazione di pattern specifici di circolazione atmosferica che determinano l’occorrenza di
massimi annuali per le cinque durate canoniche (1, 3, 6, 12 e 24 ore).
Attraverso l’utilizzo di due indici di rianalisi forniti dall’archivio ERA-Interim del European Centre
for Medium-Range Weather Forecast (ECMWF), il Convective Available Potential Energy (CAPE) e
il Vertical Integral of Divergence of Moisture Flux (VIDMF), inoltre, è stato possibile distinguere gli
eventi di precipitazione convettiva (bassa durata ed elevata intensità) da quelli stratiformi (elevate
durate e basse intensità), facendo anche un’analisi stagionale degli eventi, dal momento che la Sicilia è
caratterizzata da eventi convettivi che si registrano prevalentemente in estate e da eventi stratiformi
che si verificano durante la stagione invernale.
In definitiva, lo studio ha permesso di trovare una relazione tra eventi di particolare intensità e pattern
atmosferici che potrebbe essere utilizzata per mettere a punto un sistema per la previsione di eventi
potenzialmente dannosi per i loro effetti a terra (es., possibili inondazioni o piene lampo) una volta
noti i pattern di circolazione atmosferica previsti
Caratterizzazione dei periodi siccitosi ed umidi in Sicilia mediante lo Standardized Precipitation Evapotraspiration Index
No full textWeather circulation patterns as precursor of heavy rainfall events: an application to Sicily, Italy
Full text linkSince the impacts of climate change on the environment have been constantly rising over the last
decades, scientists have paid much attention to understanding the effects of this phenomenon.
Climate change leads to different kinds of extremes, such as heavy rainfall events, characterized
by short duration and high intensity, and drought, which can cause the problem of water scarcity
over a certain area. These types of extreme events cause several damages for the affected areas
since they can result in loss of human lives and economic damages. In particular, heavy rainfall
events, which are often associated with convective precipitation because of their characteristics,
may result in flash floods, especially when they hit small catchments with low times of
concentration, thus causing economic damages and, more relevantly, human lives losses.
The increasing occurrence of heavy rainfall events in many areas of Europe, also in Italy, over the
last few years, has contributed to raising the importance of understanding which factors could be
recognized as drivers of these events. In this perspective, it is possible to identify in atmospheric
circulation one of the causes of severe rainfall events occurrence since some air fluxes, generated
from certain schemes of atmospheric circulation, could lead to the accumulation of moisture
within a certain volume of the atmosphere, hence to the occurrence of rainfall.
Since even the Sicily (Italy) has been experimenting heavy rainfall events and consequent flash
floods and urban floods in the last years, this work aims to find out a relationship between some
weather circulation patterns, developed by the UK Met Office, and the rainfall Annual MAXima
(AMAX) for the Sicily, recorded by the rain gauge network of Autorità di Bacino - Regione Siciliana.
The possible connection between AMAX and WPs has been investigated in order to define some
specific schemes of atmospheric circulation that are responsible for leading to the occurrence of
AMAX in Sicily. In order to do this, a database containing the AMAX of all the available gauges for
the Sicily has been used. A distinction between AMAX occurred in summer and winter season and
their related WPs has been performed as well, with the goal to understand the possible influence
of WPs on the summer and winter AMAX. Furthermore, in order to distinguish convective from
stratiform AMAX, some analyses on reanalysis data, namely the CAPE and the Vertical Integral of
Divergence of Moisture Flux (VIDMF), have been done
Climate changes' effects on vegetation water stress in Mediterranena areas
No full textMany recent studies have demonstrated that CO(2) increase is driving the climate in Mediterranean areas towards important changes, mainly represented by a temperature increase and a contemporaneous rainfall reduction. Starting from this premise, the primary aim of the present study is to investigate the effects of potential climatic changes on vegetational stress in Mediterranean ecosystems. Particular attention is here focussed only on the plants' water stress in water controlled ecosystems, mainly related to soil water balance. The interactions among climate, soil and vegetation are evaluated numerically by means of an ecohydrological model. In this work, different future climatic scenarios and their effects on woody and grassy vegetation are analysed, and the results show an increase in water stress for woody and grass vegetations: trees could suffer more because of the higher evapotranspiration rates and the decrease of the winter recharge. Results are strictly dependent on the future rainfall seasonal distribution and the possible modification in rainfall frequency and intensity
Spatial distribution of rainfall trends in Sicily (1921–2000)
Full text linkThe 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
ECOHYDROLOGY IN MEDITERRANEAN AREAS: A NUMERICAL MODEL TO DESCRIBE GROWING SEASONS OUT OF PHASE WITH PRECIPITATIONS
No full textThe 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
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