The motivation for the work presented in this thesis is to retrieve profile information for the atmospheric trace constituents nitrogen dioxide (NO2) and ozone (O3) in the lower troposphere from remote sensing measurements. The remote sensing technique used, referred to as Multiple AXis Differential Optical Absorption Spectroscopy (MAX-DOAS), is a recent technique that represents a significant advance on the well-established DOAS, especially for what it concerns the study of tropospheric trace consituents. NO2 is an important trace gas in the lower troposphere due to the fact that it is involved in the production of tropospheric ozone; ozone and nitrogen dioxide are key factors in determining the quality of air with consequences, for example, on human health and the growth of vegetation. To understand the NO2 and ozone chemistry in more detail not only the concentrations at ground but also the acquisition of the vertical distribution is necessary. In fact, the budget of nitrogen oxides and ozone in the atmosphere is determined both by local emissions and non-local chemical and dynamical processes (i.e. diffusion and transport at various scales) that greatly impact on their vertical and temporal distribution: thus a tool to resolve the vertical profile information is really important. Useful measurement techniques for atmospheric trace species should fulfill at least two main requirements. First, they must be sufficiently sensitive to detect the species under consideration at their ambient concentration levels. Second, they must be specific, which means that the results of the measurement of a particular species must be neither positively nor negatively influenced by any other trace species simultaneously present in the probed volume of air. Air monitoring by spectroscopic techniques has proven to be a very useful tool to fulfill these desirable requirements as well as a number of other important properties. During the last decades, many such instruments have been developed which are based on the absorption properties of the constituents in various regions of the electromagnetic spectrum, ranging from the far infrared to the ultraviolet. Among them, Differential Optical Absorption Spectroscopy (DOAS) has played an important role. DOAS is an established remote sensing technique for atmospheric trace gases probing, which identifies and quantifies the trace gases in the atmosphere taking advantage of their molecular absorption structures in the near UV and visible wavelengths of the electromagnetic spectrum (from 0.25 μm to 0.75 μm). Passive DOAS, in particular, can detect the presence of a trace gas in terms of its integrated concentration over the atmospheric path from the sun to the receiver (the so called slant column density). The receiver can be located at ground, as well as on board an aircraft or a satellite platform. Passive DOAS has, therefore, a flexible measurement configuration that allows multiple applications. The ability to properly interpret passive DOAS measurements of atmospheric constituents depends crucially on how well the optical path of light collected by the system is understood. This is because the final product of DOAS is the concentration of a particular species integrated along the path that radiation covers in the atmosphere. This path is not known a priori and can only be evaluated by Radiative Transfer Models (RTMs). These models are used to calculate the so called vertical column density of a given trace gas, which is obtained by dividing the measured slant column density to the so called air mass factor, which is used to quantify the enhancement of the light path length within the absorber layers. In the case of the standard DOAS set-up, in which radiation is collected along the vertical direction (zenith-sky DOAS), calculations of the air mass factor have been made using “simple” single scattering radiative transfer models. This configuration has its highest sensitivity in the stratosphere, in particular during twilight. This is the result of the large enhancement in stratospheric light path at dawn and dusk combined with a relatively short tropospheric path. In order to increase the sensitivity of the instrument towards tropospheric signals, measurements with the telescope pointing the horizon (offaxis DOAS) have to be performed. In this circumstances, the light path in the lower layers can become very long and necessitate the use of radiative transfer models including multiple scattering, the full treatment of atmospheric sphericity and refraction. In this thesis, a recent development in the well-established DOAS technique is described, referred to as Multiple AXis Differential Optical Absorption Spectroscopy (MAX-DOAS). The MAX-DOAS consists in the simultaneous use of several off-axis directions near the horizon: using this configuration, not only the sensitivity to tropospheric trace gases is greatly improved, but vertical profile information can also be retrieved by combining the simultaneous off-axis measurements with sophisticated RTM calculations and inversion techniques. In particular there is a need for a RTM which is capable of dealing with all the processes intervening along the light path, supporting all DOAS geometries used, and treating multiple scattering events with varying phase functions involved. To achieve these multiple goals a statistical approach based on the Monte Carlo technique should be used. A Monte Carlo RTM generates an ensemble of random photon paths between the light source and the detector, and uses these paths to reconstruct a remote sensing measurement. Within the present study, the Monte Carlo radiative transfer model PROMSAR (PROcessing of Multi-Scattered Atmospheric Radiation) has been developed and used to correctly interpret the slant column densities obtained from MAX-DOAS measurements. In order to derive the vertical concentration profile of a trace gas from its slant column measurement, the AMF is only one part in the quantitative retrieval process. One indispensable requirement is a robust approach to invert the measurements and obtain the unknown concentrations, the air mass factors being known. For this purpose, in the present thesis, we have used the Chahine relaxation method. Ground-based Multiple AXis DOAS, combined with appropriate radiative transfer models and inversion techniques, is a promising tool for atmospheric studies in the lower troposphere and boundary layer, including the retrieval of profile information with a good degree of vertical resolution. This thesis has presented an application of this powerful comprehensive tool for the study of a preserved natural Mediterranean area (the Castel Porziano Estate, located 20 km South-West of Rome) where pollution is transported from remote sources. Application of this tool in densely populated or industrial areas is beginning to look particularly fruitful and represents an important subject for future studies.

The Assimilation in the Unstable Subspace (AUS) was introduced by Trevisan and Uboldi in 2004, and developed by Trevisan, Uboldi and Carrassi, to minimize the analysis and forecast errors by exploiting the flow-dependent instabilities of the forecast-analysis cycle system, which may be thought of as a system forced by observations. In the AUS scheme the assimilation is obtained by confining the analysis increment in the unstable subspace of the forecast-analysis cycle system so that it will have the same structure of the dominant instabilities of the system. The unstable subspace is estimated by Breeding on the Data Assimilation System (BDAS). AUS- BDAS has already been tested in realistic models and observational configurations, including a Quasi-Geostrophicmodel and a high dimensional, primitive equation ocean model; the experiments include both fixed and“adaptive”observations. In these contexts, the AUS-BDAS approach greatly reduces the analysis error, with reasonable computational costs for data assimilation with respect, for example, to a prohibitive full Extended Kalman Filter. This is a follow-up study in which we revisit the AUS-BDAS approach in the more basic, highly nonlinear Lorenz 1963 convective model. We run observation system simulation experiments in a perfect model setting, and with two types of model error as well: random and systematic. In the different configurations examined, and in a perfect model setting, AUS once again shows better efficiency than other advanced data assimilation schemes. In the present study, we develop an iterative scheme that leads to a significant improvement of the overall assimilation performance with respect also to standard AUS. In particular, it boosts the efficiency of regime’s changes tracking, with a low computational cost. Other data assimilation schemes need estimates of ad hoc parameters, which have to be tuned for the specific model at hand. In Numerical Weather Prediction models, tuning of parameters — and in particular an estimate of the model error covariance matrix — may turn out to be quite difficult. Our proposed approach, instead, may be easier to implement in operational models.

No description available.

High spectral resolution radiative transfer (RT) codes are essential tools in the study of the radiative energy transfer in the Earth atmosphere and a support for the development of parameterizations for fast RT codes used in climate and weather prediction models. Cirrus clouds cover permanently 30% of the Earth's surface, representing an important contribution to the Earth-atmosphere radiation balance. The work has been focussed on the development of the RT model LBLMS. The model, widely tested in the infra-red spectral range, has been extended to the short wave spectrum and it has been used in comparison with airborne and satellite measurements to study the optical properties of cirrus clouds. A new database of single scattering properties has been developed for mid latitude cirrus clouds. Ice clouds are treated as a mixture of ice crystals with various habits. The optical properties of the mixture are tested in comparison to radiometric measurements in selected case studies. Finally, a parameterization of the mixture for application to weather prediction and global circulation models has been developed. The bulk optical properties of ice crystals are parameterized as functions of the effective dimension of measured particle size distributions that are representative of mid latitude cirrus clouds. Tests with the Limited Area Weather Prediction model COSMO have shown the impact of the new parameterization with respect to cirrus cloud optical properties based on ice spheres.

Natural hazard related to the volcanic activity represents a potential risk factor, particularly in the vicinity of human settlements. Besides to the risk related to the explosive and effusive activity, the instability of volcanic edifices may develop into large landslides often catastrophically destructive, as shown by the collapse of the northern flank of Mount St. Helens in 1980. A combined approach was applied to analyse slope failures that occurred at Stromboli volcano. SdF slope stability was evaluated by using high-resolution multi-temporal DTMMs and performing limit equilibrium stability analyses. High-resolution topographical data collected with remote sensing techniques and three-dimensional slope stability analysis play a key role in understanding instability mechanism and the related risks. Analyses carried out on the 2002–2003 and 2007 Stromboli eruptions, starting from high-resolution data acquired through airborne remote sensing surveys, permitted the estimation of the lava volumes emplaced on the SdF slope and contributed to the investigation of the link between magma emission and slope instabilities. Limit Equilibrium analyses were performed on the 2001 and 2007 3D models, in order to simulate the slope behavior before 2002-2003 landslide event and after the 2007 eruption. Stability analyses were conducted to understand the mechanisms that controlled the slope deformations which occurred shortly after the 2007 eruption onset, involving the upper part of slope. Limit equilibrium analyses applied to both cases yielded results which are congruent with observations and monitoring data. The results presented in this work undoubtedly indicate that hazard assessment for the island of Stromboli should take into account the fact that a new magma intrusion could lead to further destabilisation of the slope, which may be more significant than the one recently observed because it will affect an already disarranged deposit and fractured and loosened crater area. The two-pronged approach based on the analysis of 3D multi-temporal mapping datasets and on the application of LE methods contributed to better understanding volcano flank behaviour and to be prepared to undertake actions aimed at risk mitigation.

The vertical profile of aerosol in the planetary boundary layer of the Milan urban area is studied in terms of its development and chemical composition in a high-resolution modelling framework. The period of study spans a week in summer of 2007 (12-18 July), when continuous LIDAR measurements and a limited set of balloon profiles were collected in the frame of the ASI/QUITSAT project. LIDAR observations show a diurnal development of an aerosol plume that lifts early morning surface emissions to the top of the boundary layer, reaching maximum concentration around midday. Mountain breeze from Alps clean the bottom of the aerosol layer, typically leaving a residual layer at around 1500-2000 m which may survive for several days. During the last two days under analysis, a dust layer transported from Sahara reaches the upper layers of Milan area and affects the aerosol vertical distribution in the boundary layer. Simulation from the MM5/CHIMERE modelling system, carried out at 1 km horizontal resolution, qualitatively reproduced the general features of the Milan aerosol layer observed with LIDAR, including the rise and fall of the aersol plume, the residual layer in altitude and the Saharan dust event. The simulation highlighted the importance of nitrates and secondary organics in its composition. Several sensitivity tests showed that main driving factors leading to the dominance of nitrates in the plume are temperature and gas absorption process. A modelling study turn to the analysis of the vertical aerosol profiles distribution and knowledge of the characterization of the PM at a site near the city of Milan is performed using a model system composed by a meteorological model MM5 (V3-6), the mesoscale model from PSU/NCAR and a Chemical Transport Model (CTM) CHIMERE to simulate the vertical aerosol profile. LiDAR continuous observations and balloon profiles collected during two intensive campaigns in summer 2007 and in winter 2008 in the frame of the ASI/QUITSAT project have been used to perform comparisons in order to evaluate the ability of the aerosol chemistry transport model CHIMERE to simulate the aerosols dynamics and compositions in this area. The comparisons of model aerosols with measurements are carried out over a full time period between 12 July 2007 and 18 July 2007. The comparisons demonstrate the ability of the model to reproduce correctly the aerosol vertical distributions and their temporal variability. As detected by the LiDAR, the model during the period considered, predicts a diurnal development of a plume during the morning and a clearing during the afternoon, typically the plume reaches the top of the boundary layer around mid day, in this time CHIMERE produces highest concentrations in the upper levels as detected by LiDAR. The model, moreover can reproduce LiDAR observes enhancement aerosols concentrations above the boundary layer, attributing the phenomena to dust out intrusion. Another important information from the model analysis regard the composition , it predicts that a large part of the plume is composed by nitrate, in particular during 13 and 16 July 2007 , pointing to the model tendency to overestimates the nitrous component in the particular matter vertical structure . Sensitivity study carried out in this work show that there are a combination of different factor which determine the major nitrous composition of the “plume” observed and in particular humidity temperature and the absorption phenomena are the mainly candidate to explain the principal difference in composition simulated in the period object of this study , in particular , the CHIMERE model seems to be mostly sensitive to the absorption process.

Thermal infrared (IR, 10.5 – 12.5 m) images from the Meteosat Visible and Infrared Imager (MVIRI) of cold cloud episodes (cloud top brightness temperature < 241 K) are used as a proxy of precipitating clouds to derive a warm season (May-August) climatology of their coherency, duration, span, and speed over Europe and the Mediterranean. The analysis focuses over the 30°-54°N, 15°W-40°E domain in May-August 1996-2005. Harmonic analysis using discrete Fourier transforms is applied together with a statistical analysis and an investigation of the diurnal cycle. This study has the objective to make available a set of results on the propagation dynamics of the cloud systems with the aim of assist numerical modellers in improving summer convection parameterization. The zonal propagation of cold cloud systems is accompanied by a weak meridional component confined to narrow latitude belts. The persistence of cold clouds over the area evidences the role of orography, the Pyrenees, the Alps, the Balkans and Anatolia. A diurnal oscillation is found with a maximum marking the initiation of convection in the lee of the mountains and shifting from about 1400 UTC at 40°E to 1800 UTC at 0°. A moderate eastward propagation of the frequency maximum from all mountain chains across the domain exists and the diurnal maxima are completely suppressed west of 5°W. The mean power spectrum of the cold cloud frequency distribution evidences a period of one day all over Europe disappearing over the ocean (west of 10°W). Other maxima are found in correspondence of 6 to 10 days in the longitudes from 15° W to 0° and indicate the activity of the westerlies with frontal passage over the continent. Longer periods activities (from 15 up to 30 days) were stronger around 10° W and from 5° W to 15° E and are likely related to the Madden Julian Oscillation influence. The maxima of the diurnal signal are in phase with the presence of elevated terrain and with land masses. A median zonal phase speed of 16.1 ms-1 is found for all events ≥ 1000 km and ≥ 20 h and a full set of results divided by years and recurrence categories is also presented.

No description available.

The objective of the work is the evaluation of the potential capabilities of navigation satellite signals to retrieve basic atmospheric parameters. A capillary study have been performed on the assumptions more or less explicitly contained in the common processing steps of navigation signals. A probabilistic procedure has been designed for measuring vertical discretised profiles of pressure, temperature and water vapour and their associated errors. Numerical experiments on a synthetic dataset have been performed with the main objective of quantifying the information that could be gained from such approach, using entropy and relative entropy as testing parameters. A simulator of phase delay and bending of a GNSS signal travelling across the atmosphere has been developed to this aim.

This research activity studied how the uncertainties are concerned and interrelated through the multi-model approach, since it seems to be the bigger challenge of ocean and weather forecasting. Moreover, we tried to reduce model error throughout the superensemble approach. In order to provide this aim, we created different dataset and by means of proper algorithms we obtained the superensamble estimate. We studied the sensitivity of this algorithm in function of its characteristics parameters. Clearly, it is not possible to evaluate a reasonable estimation of the error neglecting the importance of the grid size of ocean model, for the large amount of all the sub grid-phenomena embedded in space discretizations that can be only roughly parametrized instead of an explicit evaluation. For this reason we also developed a high resolution model, in order to calculate for the first time the impact of grid resolution on model error.