The interaction between atmosphere–land–ocean–biosphere systems plays a prominent role on the atmospheric dynamics and on the convective rainfall distribution over the West Africa monsoon area during the boreal summer. In particular, the initialization of convective systems in the Sub – Sahelian region has been directly linked to soil moisture heterogeneities identified as the major triggering, development and propagation of convective systems. The present study aims at investigating African monsoon large scale convective dynamics and rainfall diurnal cycle through an exploration of the hypothesis behind the mechanisms of a monsoon phenomenon as an emergence of a collective dynamics of many propagating convective systems. Such hypothesis is based on the existence of an internal self – regulation mechanism among the various components. To achieve these results a multiple analysis was performed based on remote sensed rainfall dataset, and global and regional modelling data for a period of 5 seasons: 2004 - 2008. Satellite rainfall data and convective occurrence variability were studied for assessing typical spatio – temporal signatures and characteristics with an emphasis to the diurnal cycle footprint. A global model and regional model simulation datasets, specifically developed for this analysis and based on Regional Atmospheric Modelling System – RAMS, have been analysed. Results from numerical model datasets highlight the evidence of a synchronization between the destabilization of the convective boundary layer and rainfall occurrence due to the solar radiation forcing through the latent heat release. This supports the conclusion that the studied interacting systems are associated with a process of mutual adjustment of rhythms. Furthermore, this rainfall internal coherence was studied in relation to the West African Heat Low pressure system, which has a prominent role in the large scale summer variability over the Mediterranean area since it is acting as one of dynamic link between sub tropical and midlatitudes variability.

In the last few years the resolution of numerical weather prediction (nwp) became higher and higher with the progresses of technology and knowledge. As a consequence, a great number of initial data became fundamental for a correct initialization of the models. The potential of radar observations has long been recognized for improving the initial conditions of high-resolution nwp models, while operational application becomes more frequent. The fact that many nwp centres have recently taken into operations convection-permitting forecast models, many of which assimilate radar data, emphasizes the need for an approach to providing quality information which is needed in order to avoid that radar errors degrade the model's initial conditions and, therefore, its forecasts. Environmental risks can can be related with various causes: meteorological, seismical, hydrological/hydraulic. Flash floods have horizontal dimension of 1-20 Km and can be inserted in mesoscale gamma subscale, this scale can be modeled only with nwp model with the highest resolution as the COSMO-2 model. One of the problems of modeling extreme convective events is related with the atmospheric initial conditions, in fact the scale dimension for the assimilation of atmospheric condition in an high resolution model is about 10 Km, a value too high for a correct representation of convection initial conditions. Assimilation of radar data with his resolution of about of Km every 5 or 10 minutes can be a solution for this problem. In this contribution a pragmatic and empirical approach to deriving a radar data quality description is proposed to be used in radar data assimilation and more specifically for the latent heat nudging (lhn) scheme. Later the the nvective capabilities of the cosmo-2 model are investigated through some case studies. Finally, this work shows some preliminary experiments of coupling of a high resolution meteorological model with an Hydrological one.

A year of satellite-borne lidar CALIOP data is analyzed and statistics on occurrence and distribution of bulk properties of cirri are provided. The relationship between environmental and cloud physical parameters and the shape of the backscatter profile (BSP) is investigated. It is found that CALIOP BSP is mainly affected by cloud geometrical thickness while only minor impacts can be attributed to other quantities such as optical depth or temperature. To fit mean BSPs as functions of geometrical thickness and position within the cloud layer, polynomial functions are provided. It is demonstrated that, under realistic hypotheses, the mean BSP is linearly proportional to the IWC profile. The IWC parameterization is included into the RT-RET retrieval algorithm, that is exploited to analyze infrared radiance measurements in presence of cirrus clouds during the ECOWAR field campaign. Retrieved microphysical and optical properties of the observed cloud are used as input parameters in a forward RT simulation run over the 100-1100 cm-1 spectral interval and compared with interferometric data to test the ability of the current single scattering properties database of ice crystal to reproduce realistic optical features. Finally a global scale investigation of cirrus clouds is performed by developing a collocation algorithm that exploits satellite data from multiple sensors (AIRS, CALIOP, MODIS). The resulting data set is utilized to test a new infrared hyperspectral retrieval algorithm. Retrieval products are compared to data and in particular the cloud top height (CTH) product is considered for this purpose. A better agreement of the retrieval with the CALIOP CTH than MODIS is found, even if some cases of underestimation and overestimation are observed.

Basic concepts and definitions relative to Lagrangian Particle Dispersion Models (LPDMs)for the description of turbulent dispersion are introduced. The study focusses on LPDMs that use as input, for the large scale motion, fields produced by Eulerian models, with the small scale motions described by Lagrangian Stochastic Models (LSMs). The data of two different dynamical model have been used: a Large Eddy Simulation (LES) and a General Circulation Model (GCM). After reviewing the small scale closure adopted by the Eulerian model, the development and implementation of appropriate LSMs is outlined. The basic requirement of every LPDM used in this work is its fullfillment of the Well Mixed Condition (WMC). For the dispersion description in the GCM domain, a stochastic model of Markov order 0, consistent with the eddy-viscosity closure of the dynamical model, is implemented. A LSM of Markov order 1, more suitable for shorter timescales, has been implemented for the description of the unresolved motion of the LES fields. Different assumptions on the small scale correlation time are made. Tests of the LSM on GCM fields suggest that the use of an interpolation algorithm able to maintain an analytical consistency between the diffusion coefficient and its derivative is mandatory if the model has to satisfy the WMC. Also a dynamical time step selection scheme based on the diffusion coefficient shape is introduced, and the criteria for the integration step selection are discussed. Absolute and relative dispersion experiments are made with various unresolved motion settings for the LSM on LES data, and the results are compared with laboratory data. The study shows that the unresolved turbulence parameterization has a negligible influence on the absolute dispersion, while it affects the contribution of the relative dispersion and meandering to absolute dispersion, as well as the Lagrangian correlation.

Particulate matter is one of the main atmospheric pollutants, with a great chemical-environmental relevance. Improving knowledge of the sources of particulate matter and of their apportionment is needed to handle and fulfill the legislation regarding this pollutant, to support further development of air policy as well as air pollution management. Various instruments have been used to understand the sources of particulate matter and atmospheric radiotracers at the site of Mt. Cimone (44.18° N, 10.7° E, 2165 m asl), hosting a global WMO-GAW station. Thanks to its characteristics, this location is suitable investigate the regional and long-range transport of polluted air masses on the background Southern-Europe free-troposphere. In particular, PM10 data sampled at the station in the period 1998-2011 were analyzed in the framework of the main meteorological and territorial features. A receptor model based on back trajectories was applied to study the source regions of particulate matter. Simultaneous measurements of atmospheric radionuclides Pb-210 and Be-7 acquired together with PM10 have also been analysed to acquire a better understanding of vertical and horizontal transports able to affect atmospheric composition. Seasonal variations of atmospheric radiotracers have been studied both analysing the long-term time series acquired at the measurement site as well as by means of a state-of-the-art global 3-D chemistry and transport model. Advection patterns characterizing the circulation at the site have been identified by means of clusters of back-trajectories. Finally, the results of a source apportionment study of particulate matter carried on in a midsize town of the Po Valley (actually recognised as one of the most polluted European regions) are reported. An approach exploiting different techniques, and in particular different kinds of models, successfully achieved a characterization of the processes/sources of particulate matter at the two sites, and of atmospheric radiotracers at the site of Mt. Cimone.

Precipitation retrieval over high latitudes, particularly snowfall retrieval over ice and snow, using satellite-based passive microwave spectrometers, is currently an unsolved problem. The challenge results from the large variability of microwave emissivity spectra for snow and ice surfaces, which can mimic, to some degree, the spectral characteristics of snowfall. This work focuses on the investigation of a new snowfall detection algorithm specific for high latitude regions, based on a combination of active and passive sensors able to discriminate between snowing and non snowing areas. The space-borne Cloud Profiling Radar (on CloudSat), the Advanced Microwave Sensor units A and B (on NOAA-16) and the infrared spectrometer MODIS (on AQUA) have been co-located for 365 days, from October 1st 2006 to September 30th, 2007. CloudSat products have been used as truth to calibrate and validate all the proposed algorithms. The methodological approach followed can be summarised into two different steps. In a first step, an empirical search for a threshold, aimed at discriminating the case of no snow, was performed, following Kongoli et al. [2003]. This single-channel approach has not produced appropriate results, a more statistically sound approach was attempted. Two different techniques, which allow to compute the probability above and below a Brightness Temperature (BT) threshold, have been used on the available data. The first technique is based upon a Logistic Distribution to represent the probability of Snow given the predictors. The second technique, defined Bayesian Multivariate Binary Predictor (BMBP), is a fully Bayesian technique not requiring any hypothesis on the shape of the probabilistic model (such as for instance the Logistic), which only requires the estimation of the BT thresholds. The results obtained show that both methods proposed are able to discriminate snowing and non snowing condition over the Polar regions with a probability of correct detection larger than 0.5, highlighting the importance of a multispectral approach.

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L’obiettivo di questo lavoro di tesi è di ottenere un’analisi climatica giornaliera ad alta risoluzione della precipitazione sul territorio del nord Italia realizzata con tecniche di controllo statistico, di analisi e di strumenti di descrizione dei risultati presentati nella recente letteratura. A tal fine, sono stati utilizzati i dati dell’Archivio ARCIS. In seguito alle fasi di controllo qualità, omogeneità e sincronicità i dati sono stati utilizzati per realizzare un’analisi giornaliera su grigliato regolare a 10 km di risoluzione utile alla rappresentazione della variabilità spazio-temporale della precipitazione sul Nord Italia per il periodo 1961-2005. I risultati di tale analisi mettono in evidenza dei valori medi di precipitazione annuale abbastanza intensi sulla parte centrale dell’arco Alpino, con massimi (oltre 2000 mm) sull’estremità orientale e sull’Appennino Ligure. Valori minimi (500 – 600 mm) sono osservati lungo le aree prospicienti il fiume Po, in Val d’Aosta ed in Alto Adige. La corrispondente analisi del trend temporale indica la presenza di lievi cali statisticamente significativi solo in aree limitate del territorio. In coerenza con questi risultati, la variazione nel tempo della precipitazione annuale mediata su tutto il territorio mette in evidenza un’intensa variabilità decennale, ma solo una lieve flessione lineare sull’intero periodo. Il numero annuo di giorni piovosi ed il 90° percentile della precipitazione giornaliera presentano invece trend lineari un po’ più pronunciati. In particolare, sul periodo considerato si nota un calo del numero di giorni piovosi su gran parte del territorio e solo su alcune aree del territorio un aumento dell’intensità del 90° percentile, sia a scala annuale che stagionale. Nell’ultima parte di questo lavoro è stato realizzato uno studio della relazione fra la forzante climatica e l’evoluzione della morfologia dell’Appennino Emiliano-Romagnolo. I risultati mostrano che a parità di quota, di pendenza e di litologia, la franosità è influenzata dalle precipitazioni. / The aim of this thesis is to obtain a high-resolution daily gridded climatic dataset of precipitation over Northern Italy using up to date techniques of statistical and quality control of data and analysis. Data are taken from the ARCIS Archive, and checked for their quality, homogeneity, synchronicity. Afterwards, they were spatially interpolated at the daily basis for the period 1961-2005 on a regular 10 km grid, which is an adequate resolution for the representation of the spatio-temporal variability of the precipitation on Northern Italy. The results of the analysis show average values of annual precipitation fairly intense in the central part of the Alps, with a maximum (over 2000 mm) in eastern Italy and Ligurian Apennines. Minimum values (500-600 mm) are observed in the Po river valley, Aosta Valley and in South Tyrol. The corresponding analysis of the temporal trend shows a slight statistically significant decline of annual precipitation only for limited areas. Consistently with these results the variation of annual precipitation averaged over the entire domain shows an intense decadal variability, but only a slight linearly decrease over the whole period. The annual number of rainy days and the 90th percentile of daily precipitation show a bit more pronounced linear trends. In particularly, over the period considered it is observed a decrease of rainy days over most of the territory and an increased of the intensity of the 90th percentile only in some areas both at annual and seasonal scale. In the last part of this work it is presented a study of relationship between climate forcing and geomorphology evolution over the Emilia-Romagna Apennine area. Results show that at the same altitude, slope and lithology, landslides are influenced by precipitation.

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No description available.