Probabilistic Envelope Curves for Extreme Rainfall Events - Curve Inviluppo Probabilistiche per Precipitazioni Estreme

A regional envelope curve (REC) of flood flows summarises the current bound on our experience of extreme floods in a region. RECs are available for most regions of the world. Recent scientific papers introduced a probabilistic interpretation of these curves and formulated an empirical estimator of the recurrence interval T associated with a REC, which, in principle, enables us to use RECs for design purposes in ungauged basins. The main aim of this work is twofold. First, it extends the REC concept to extreme rainstorm events by introducing the Depth-Duration Envelope Curves (DDEC), which are defined as the regional upper bound on all the record rainfall depths at present for various rainfall duration. Second, it adapts the probabilistic interpretation proposed for RECs to DDECs and it assesses the suitability of these curves for estimating the T-year rainfall event associated with a given duration and large T values. Probabilistic DDECs are complementary to regional frequency analysis of rainstorms and their utilization in combination with a suitable rainfall-runoff model can provide useful indications on the magnitude of extreme floods for gauged and ungauged basins. The study focuses on two different national datasets, the peak over threshold (POT) series of rainfall depths with duration 30 min., 1, 3, 9 and 24 hrs. obtained for 700 Austrian raingauges and the Annual Maximum Series (AMS) of rainfall depths with duration spanning from 5 min. to 24 hrs. collected at 220 raingauges located in northern-central Italy. The estimation of the recurrence interval of DDEC requires the quantification of the equivalent number of independent data which, in turn, is a function of the cross-correlation among sequences. While the quantification and modelling of intersite dependence is a straightforward task for AMS series, it may be cumbersome for POT series. This paper proposes a possible approach to address this problem.

Simulated switching of the resting state functional connectivity in mouse brain using a real mesoscale connectome

Capire come modellare l'attività del cervello a riposo, resting state, è il primo passo necessario per avvicinarsi a una reale comprensione della dinamica cerebrale. Sperimentalmente si osserva che, quando il cervello non è soggetto a stimoli esterni, particolari reti di regioni cerebrali presentano un'attività neuronale superiore alla media. Nonostante gli sforzi dei ricercatori, non è ancora chiara la relazione che sussiste tra le connessioni strutturali e le connessioni funzionali del sistema cerebrale a riposo, organizzate nella matrice di connettività funzionale. Recenti studi sperimentali mostrano la natura non stazionaria della connettività funzionale in disaccordo con i modelli in letteratura. Il modello implementato nella presente tesi per simulare l'evoluzione temporale del network permette di riprodurre il comportamento dinamico della connettività funzionale. Per la prima volta in questa tesi, secondo i lavori a noi noti, un modello di resting state è implementato nel cervello di un topo. Poco è noto, infatti, riguardo all'architettura funzionale su larga scala del cervello dei topi, nonostante il largo utilizzo di tale sistema nella modellizzazione dei disturbi neurologici. Le connessioni strutturali utilizzate per definire la topologia della rete neurale sono quelle ottenute dall'Allen Institute for Brain Science. Tale strumento fornisce una straordinaria opportunità per riprodurre simulazioni realistiche, poiché, come affermato nell'articolo che presenta tale lavoro, questo connettoma è il più esauriente disponibile, ad oggi, in ogni specie vertebrata. I parametri liberi del modello sono stati scelti in modo da inizializzare il sistema nel range dinamico ottimale per riprodurre il comportamento dinamico della connettività funzionale. Diverse considerazioni e misure sono state effettuate sul segnale BOLD simulato per meglio comprenderne la natura. L'accordo soddisfacente fra i centri funzionali calcolati nel network cerebrale simulato e quelli ottenuti tramite l'indagine sperimentale di Mechling et al., 2014 comprovano la bontà del modello e dei metodi utilizzati per analizzare il segnale simulato.

Mock HI observations of Milky Way-like simulated galaxies

L'obiettivo di questo lavoro di tesi consiste nel descrivere sia il processo necessario per la creazione di osservazioni sintetiche di galassie simulate simili alla Via Lattea nella riga di emissione a 21 cm dell'idrogeno neutro (HI), sia il lavoro di analisi fondamentale che serve a confrontare in modo efficace l'output generato con delle osservazioni di galassie reali. Come prima cosa è descritta la teoria quantistica che sta alla base dell'emissione a 21 cm di HI, illustrando l'importanza di tale riga di emissione nell'ambito dell'astronomia e come si possano ottenere informazioni fondamentali sulle sorgenti di questa radiazione a partire dai dati osservativi. Il lavoro poi si focalizza sull'utilizzo del software MARTINI per la creazione di osservazioni sintetiche della linea a 21 cm per una galassia simulata con proprietà simili alla Via Lattea generata utilizzando il modello numerico SMUGGLE. Infine, si passa ad una breve descrizione dell'analisi dei dati sintetici creati, e al loro confronto con dei dati provenienti da osservazioni reali di galassie con proprietà simili, per ottenere una valutazione qualitativa della bontà del modello SMUGGLE impiegato nella simulazione numerica.

Characterization of ENSO changes under idealised radiative forcing in an intermediate complexity general circulation model

Intermediate-complexity general circulation models are a fundamental tool to investigate the role of internal and external variability within the general circulation of the atmosphere and ocean. The model used in this thesis is an intermediate complexity atmospheric general circulation model (SPEEDY) coupled to a state-of-the-art modelling framework for the ocean (NEMO). We assess to which extent the model allows a realistic simulation of the most prominent natural mode of variability at interannual time scales: El-Niño Southern Oscillation (ENSO). To a good approximation, the model represents the ENSO-induced Sea Surface Temperature (SST) pattern in the equatorial Pacific, despite a cold tongue-like bias. The model underestimates (overestimates) the typical ENSO spatial variability during the winter (summer) seasons. The mid-latitude response to ENSO reveals that the typical poleward stationary Rossby wave train is reasonably well represented. The spectral decomposition of ENSO features a spectrum that lacks periodicity at high frequencies and is overly periodic at interannual timescales. We then implemented an idealised transient mean state change in the SPEEDY model. A warmer climate is simulated by an alteration of the parametrized radiative fluxes that corresponds to doubled carbon dioxide absorptivity. Results indicate that the globally averaged surface air temperature increases of 0.76 K. Regionally, the induced signal on the SST field features a significant warming over the central-western Pacific and an El-Niño-like warming in the subtropics. In general, the model features a weakening of the tropical Walker circulation and a poleward expansion of the local Hadley cell. This response is also detected in a poleward rearrangement of the tropical convective rainfall pattern. The model setting that has been here implemented provides a valid theoretical support for future studies on climate sensitivity and forced modes of variability under mean state changes.

Comparison of different solutions for the hybridization of a motorcycle engine for Formula Student applications and evaluation of the effectiveness on the simulated lap time

Following the latest environmental concerns, the importance of minimising the detrimental effect of emissions of terrestrial vehicles has become a major goal for the whole automotive field. The key to achieve an emission-free long term future is the electrification of vehicle fleets; this huge step cannot be taken without intermediate technologies. In this context, hybrid vehicles are fundamental to reach this goal. Specifically, mild hybrid vehicles represent a trade-off between cost and emissions that could act now as a bridge towards electrification. Like the industry, also student engineering competitions are likely to take the same route: Combustion vehicles may well turn into hybrid vehicles. For this reason, a preliminary design overview is necessary to pinpoint the key performance indicators for the prototypes of the future.

Private sensors and crowdsourced rainfall data: accuracy and effectiveness for monitoring severe events and mapping pluvial flooding in urban areas

The increasing number of extreme rainfall events, combined with the high population density and the imperviousness of the land surface, makes urban areas particularly vulnerable to pluvial flooding. In order to design and manage cities to be able to deal with this issue, the reconstruction of weather phenomena is essential. Among the most interesting data sources which show great potential are the observational networks of private sensors managed by citizens (crowdsourcing). The number of these personal weather stations is consistently increasing, and the spatial distribution roughly follows population density. Precisely for this reason, they perfectly suit this detailed study on the modelling of pluvial flood in urban environments. The uncertainty associated with these measurements of precipitation is still a matter of research. In order to characterise the accuracy and precision of the crowdsourced data, we carried out exploratory data analyses. A comparison between Netatmo hourly precipitation amounts and observations of the same quantity from weather stations managed by national weather services is presented. The crowdsourced stations have very good skills in rain detection but tend to underestimate the reference value. In detail, the accuracy and precision of crowd- sourced data change as precipitation increases, improving the spread going to the extreme values. Then, the ability of this kind of observation to improve the prediction of pluvial flooding is tested. To this aim, the simplified raster-based inundation model incorporated in the Saferplaces web platform is used for simulating pluvial flooding. Different precipitation fields have been produced and tested as input in the model. Two different case studies are analysed over the most densely populated Norwegian city: Oslo. The crowdsourced weather station observations, bias-corrected (i.e. increased by 25%), showed very good skills in detecting flooded areas.

Data analysis and hydrological modelling of rainfall and discharge extremes along the Tione River: implications for the design of water structures

There are many natural events that can negatively affect the urban ecosystem, but weather-climate variations are certainly among the most significant. The history of settlements has been characterized by extreme events like earthquakes and floods, which repeat themselves at different times, causing extensive damage to the built heritage on a structural and urban scale. Changes in climate also alter various climatic subsystems, changing rainfall regimes and hydrological cycles, increasing the frequency and intensity of extreme precipitation events (heavy rainfall).  From an hydrological risk perspective, it is crucial to understand future events that could occur and their magnitude in order to design safer infrastructures. Unfortunately, it is not easy to understand future scenarios as the complexity of climate is enormous.  For this thesis, precipitation and discharge extremes were primarily used as data sources. It is important to underline that the two data sets are not separated: changes in rainfall regime, due to climate change, could significantly affect overflows into receiving water bodies. It is imperative that we understand and model climate change effects on water structures to support the development of adaptation strategies.   The main purpose of this thesis is to search for suitable water structures for a road located along the Tione River. Therefore, through the analysis of the area from a hydrological point of view, we aim to guarantee the safety of the infrastructure over time.   The observations made have the purpose to underline how models such as a stochastic one can improve the quality of an analysis for design purposes, and influence choices.