Adaptación del sector turístico al cambio climático en España. La importancia de las acciones a escala local y en empresas turísticas

El 5º Informe del IPCC (Panel Intergubernamental de Cambio Climático, 2014) señala que el turismo será una de las actividades económicas que mayores efectos negativos experimentará en las próximas décadas debido al calentamiento térmico del planeta. En España, el turismo es una fuente principal de ingresos y de creación de puestos de trabajo en su economía. De ahí que sea necesaria la puesta en marcha de medidas de adaptación a la nueva realidad climática que, en nuestro país, va a suponer cambios en el confort climático de los destinos e incremento de extremos atmosféricos. Frente a los planes de adaptación al cambio climático en la actividad turística, elaborados por los gobiernos estatal y regional, que apenas se han desarrollado en España, la escala local muestra interesantes ejemplos de acciones de adaptación al cambio climático, desarrolladas tanto por los municipios (energía, transporte, vivienda, planificación urbanística) como por la propia empresa turística (hoteles, campings, apartamentos). Medidas de ahorro de agua y luz, fomento del transporte público y de las energías limpias, creación de zonas verdes urbanas y adaptación a los extremos atmosféricos destacan como acciones de mitigación del cambio climático en los destinos turísticos principales de nuestro país.

Climate change and the long-term viability of the World’s busiest heavy haul ice road

Climate models project that the northern high latitudes will warm at a rate in excess of the global mean. This will pose severe problems for Arctic and sub-Arctic infrastructure dependent on maintaining low temperatures for structural integrity. This is the case for the economically important Tibbitt to Contwoyto Winter Road (TCWR)—the world’s busiest heavy haul ice road, spanning 400 km across mostly frozen lakes within the Northwest Territories of Canada. In this study, future climate scenarios are developed for the region using statistical downscaling methods. In addition, changes in lake ice thickness are projected based on historical relationships between measured ice thickness and air temperatures. These projections are used to infer the theoretical operational dates of the TCWR based on weight limits for trucks on the ice. Results across three climate models driven by four RCPs reveal a considerable warming trend over the coming decades. Projected changes in ice thickness reveal a trend towards thinner lake ice and a reduced time window when lake ice is at sufficient thickness to support trucks on the ice road, driven by increasing future temperatures. Given the uncertainties inherent in climate modelling and the resultant projections, caution should be exercised in interpreting the magnitude of these scenarios. More certain is the direction of change, with a clear trend towards winter warming that will reduce the operation time window of the TCWR. This illustrates the need for planners and policymakers to consider future changes in climate when planning annual haulage along the TCWR.

Modélisation de l'évolution hydroclimatique des flux et stocks d'eau verte et d'eau bleue du bassin versant de la Garonne

La gestion intégrée de la ressource en eau implique de distinguer les parcours de l’eau qui sont accessibles aux sociétés de ceux qui ne le sont pas. Les cheminements de l’eau sont nombreux et fortement variables d’un lieu à l’autre. Il est possible de simplifier cette question en s’attardant plutôt aux deux destinations de l’eau. L’eau bleue forme les réserves et les flux dans l’hydrosystème : cours d’eau, nappes et écoulements souterrains. L’eau verte est le flux invisible de vapeur d’eau qui rejoint l’atmosphère. Elle inclut l’eau consommée par les plantes et l’eau dans les sols. Or, un grand nombre d’études ne portent que sur un seul type d’eau bleue, en ne s’intéressant généralement qu’au devenir des débits ou, plus rarement, à la recharge des nappes. Le portrait global est alors manquant. Dans un même temps, les changements climatiques viennent impacter ce cheminement de l’eau en faisant varier de manière distincte les différents composants de cycle hydrologique. L’étude réalisée ici utilise l’outil de modélisation SWAT afin de réaliser le suivi de toutes les composantes du cycle hydrologique et de quantifier l’impact des changements climatiques sur l’hydrosystème du bassin versant de la Garonne. Une première partie du travail a permis d’affiner la mise en place du modèle pour répondre au mieux à la problématique posée. Un soin particulier a été apporté à l’utilisation de données météorologiques sur grille (SAFRAN) ainsi qu’à la prise en compte de la neige sur les reliefs. Le calage des paramètres du modèle a été testé dans un contexte differential split sampling, en calant puis validant sur des années contrastées en terme climatique afin d’appréhender la robustesse de la simulation dans un contexte de changements climatiques. Cette étape a permis une amélioration substantielle des performances sur la période de calage (2000-2010) ainsi que la mise en évidence de la stabilité du modèle face aux changements climatiques. Par suite, des simulations sur une période d’un siècle (1960-2050) ont été produites puis analysées en deux phases : i) La période passée (1960-2000), basée sur les observations climatiques, a servi de période de validation à long terme du modèle sur la simulation des débits, avec de très bonnes performances. L’analyse des différents composants hydrologiques met en évidence un impact fort sur les flux et stocks d’eau verte, avec une diminution de la teneur en eau des sols et une augmentation importante de l’évapotranspiration. Les composantes de l’eau bleue sont principalement perturbées au niveau du stock de neige et des débits qui présentent tous les deux une baisse substantielle. ii) Des projections hydrologiques ont été réalisées (2010-2050) en sélectionnant une gamme de scénarios et de modèles climatiques issus d’une mise à l’échelle dynamique. L’analyse de simulation vient en bonne part confirmer les conclusions tirées de la période passée : un impact important sur l’eau verte, avec toujours une baisse de la teneur en eau des sols et une augmentation de l’évapotranspiration potentielle. Les simulations montrent que la teneur en eau des sols pendant la période estivale est telle qu’elle en vient à réduire les flux d’évapotranspiration réelle, mettant en évidence le possible déficit futur des stocks d’eau verte. En outre, si l’analyse des composantes de l’eau bleue montre toujours une diminution significative du stock de neige, les débits semblent cette fois en hausse pendant l’automne et l’hiver. Ces résultats sont un signe de l’«accélération» des composantes d’eau bleue de surface, probablement en relation avec l’augmentation des évènements extrêmes de précipitation. Ce travail a permis de réaliser une analyse des variations de la plupart des composantes du cycle hydrologique à l’échelle d’un bassin versant, confirmant l’importance de prendre en compte toutes ces composantes pour évaluer l’impact des changements climatiques et plus largement des changements environnementaux sur la ressource en eau.

Double Fourier analysis for Emotion Identification in Voiced Speech

We propose a novel analysis alternative, based on two Fourier Transforms for emotion recognition from speech -- Fourier analysis allows for display and synthesizes different signals, in terms of power spectral density distributions -- A spectrogram of the voice signal is obtained performing a short time Fourier Transform with Gaussian windows, this spectrogram portraits frequency related features, such as vocal tract resonances and quasi-periodic excitations during voiced sounds -- Emotions induce such characteristics in speech, which become apparent in spectrogram time-frequency distributions -- Later, the signal time-frequency representation from spectrogram is considered an image, and processed through a 2-dimensional Fourier Transform in order to perform the spatial Fourier analysis from it -- Finally features related with emotions in voiced speech are extracted and presented

Climate change and impacts on family farming in the North and Northeast of Brazil.

The starting point for this study was the consideration of future climate change scenarios and their uncertainties. The paper presents the global projections from the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) and compares them with regional scenarios (downscaling) developed by the Brazilian National Institute for Space Research (Instituto Nacional de Pesquisas Espaciais - INPE), with a focus on two main IPCC scenarios (RCP4.5 and RCP8.5) and two main global models (MIROC and Hadley Centre) for the periods 2011-2040 and 2041-2070. It aims to identify the main trends in terms of changes in temperature and precipitation for the North and Northeast regions of Brazil (more specifically, in the Amazon, semi-arid and cerrado biomes).

Climate change and irrigation water requirement at Jaguaribe river basin, semi-arid northeast of Brazil.

Summary: Climate change has a potential to impact rainfall, temperature and air humidity, which have relation to plant evapotranspiration and crop water requirement. The purpose of this research is to assess climate change impacts on irrigation water demand, based on future scenarios derived from the PRECIS (Providing Regional Climates for Impacts Studies), using boundary conditions of the HadCM3 submitted to a dynamic downscaling nested to the Hadley Centre regional circulation model HadRM3P. Monthly time series for average temperature and rainfall were generated for 1961-90 (baseline) and the future (2040). The reference evapotranspiration was estimated using monthly average temperature. Projected climate change impact on irrigation water demand demonstrated to be a result of evapotranspiration and rainfall trend. Impacts were mapped over the target region by using geostatistical methods. An increase of the average crop water needs was estimated to be 18.7% and 22.2% higher for 2040 A2 and B2 scenarios, respectively. Objective ? To analyze the climate change impacts on irrigation water requirements, using downscaling techniques of a climate change model, at the river basin scale. Method: The study area was delimited between 4º39?30? and 5º40?00? South and 37º35?30? and 38º27?00? West. The crop pattern in the target area was characterized, regarding type of irrigated crops, respective areas and cropping schedules, as well as the area and type of irrigation systems adopted. The PRECIS (Providing Regional Climates for Impacts Studies) system (Jones et al., 2004) was used for generating climate predictions for the target area, using the boundary conditions of the Hadley Centre model HadCM3 (Johns et al., 2003). The considered time scale of interest for climate change impacts evaluation was the year of 2040, representing the period of 2025 to 2055. The output data from the climate model was interpolated, considering latitude/longitude, by applying ordinary kriging tools available at a Geographic Information System, in order to produce thematic maps.

Leveraging Symbiotic Relationships for Emulation of Computer Networks

The lack of analytical models that can accurately describe large-scale networked systems makes empirical experimentation indispensable for understanding complex behaviors. Research on network testbeds for testing network protocols and distributed services, including physical, emulated, and federated testbeds, has made steady progress. Although the success of these testbeds is undeniable, they fail to provide: 1) scalability, for handling large-scale networks with hundreds or thousands of hosts and routers organized in different scenarios, 2) flexibility, for testing new protocols or applications in diverse settings, and 3) inter-operability, for combining simulated and real network entities in experiments. This dissertation tackles these issues in three different dimensions. First, we present SVEET, a system that enables inter-operability between real and simulated hosts. In order to increase the scalability of networks under study, SVEET enables time-dilated synchronization between real hosts and the discrete-event simulator. Realistic TCP congestion control algorithms are implemented in the simulator to allow seamless interactions between real and simulated hosts. SVEET is validated via extensive experiments and its capabilities are assessed through case studies involving real applications. Second, we present PrimoGENI, a system that allows a distributed discrete-event simulator, running in real-time, to interact with real network entities in a federated environment. PrimoGENI greatly enhances the flexibility of network experiments, through which a great variety of network conditions can be reproduced to examine what-if questions. Furthermore, PrimoGENI performs resource management functions, on behalf of the user, for instantiating network experiments on shared infrastructures. Finally, to further increase the scalability of network testbeds to handle large-scale high-capacity networks, we present a novel symbiotic simulation approach. We present SymbioSim, a testbed for large-scale network experimentation where a high-performance simulation system closely cooperates with an emulation system in a mutually beneficial way. On the one hand, the simulation system benefits from incorporating the traffic metadata from real applications in the emulation system to reproduce the realistic traffic conditions. On the other hand, the emulation system benefits from receiving the continuous updates from the simulation system to calibrate the traffic between real applications. Specific techniques that support the symbiotic approach include: 1) a model downscaling scheme that can significantly reduce the complexity of the large-scale simulation model, resulting in an efficient emulation system for modulating the high-capacity network traffic between real applications; 2) a queuing network model for the downscaled emulation system to accurately represent the network effects of the simulated traffic; and 3) techniques for reducing the synchronization overhead between the simulation and emulation systems.

Water Demand and Allocation in the Mara River Basin, Kenya/Tanzania in the Face of Land Use Dynamics and Climate Variability

The Mara River Basin (MRB) is endowed with pristine biodiversity, socio-cultural heritage and natural resources. The purpose of my study is to develop and apply an integrated water resource allocation framework for the MRB based on the hydrological processes, water demand and economic factors. The basin was partitioned into twelve sub-basins and the rainfall runoff processes was modeled using the Soil and Water Assessment Tool (SWAT) after satisfactory Nash-Sutcliff efficiency of 0.68 for calibration and 0.43 for validation at Mara Mines station. The impact and uncertainty of climate change on the hydrology of the MRB was assessed using SWAT and three scenarios of statistically downscaled outputs from twenty Global Circulation Models. Results predicted the wet season getting more wet and the dry season getting drier, with a general increasing trend of annual rainfall through 2050. Three blocks of water demand (environmental, normal and flood) were estimated from consumptive water use by human, wildlife, livestock, tourism, irrigation and industry. Water demand projections suggest human consumption is expected to surpass irrigation as the highest water demand sector by 2030. Monthly volume of water was estimated in three blocks of current minimum reliability, reserve (>95%), normal (80–95%) and flood (40%) for more than 5 months in a year. The assessment of water price and marginal productivity showed that current water use hardly responds to a change in price or productivity of water. Finally, a water allocation model was developed and applied to investigate the optimum monthly allocation among sectors and sub-basins by maximizing the use value and hydrological reliability of water. Model results demonstrated that the status on reserve and normal volumes can be improved to ‘low’ or ‘moderate’ by updating the existing reliability to meet prevailing demand. Flow volumes and rates for four scenarios of reliability were presented. Results showed that the water allocation framework can be used as comprehensive tool in the management of MRB, and possibly be extended similar watersheds.

Non-invasive winding fault detection for induction machines based on stray flux magnetic sensors

Non-intrusive monitoring of health state of induction machines within industrial process and harsh environments poses a technical challenge. In the field, winding failures are a major fault accounting for over 45% of total machine failures. In the literature, many condition monitoring techniques based on different failure mechanisms and fault indicators have been developed where the machine current signature analysis (MCSA) is a very popular and effective method at this stage. However, it is extremely difficult to distinguish different types of failures and hard to obtain local information if a non-intrusive method is adopted. Typically, some sensors need to be installed inside the machines for collecting key information, which leads to disruption to the machine operation and additional costs. This paper presents a new non-invasive monitoring method based on GMRs to measure stray flux leaked from the machines. It is focused on the influence of potential winding failures on the stray magnetic flux in induction machines. Finite element analysis and experimental tests on a 1.5-kW machine are presented to validate the proposed method. With time-frequency spectrogram analysis, it is proven to be effective to detect several winding faults by referencing stray flux information. The novelty lies in the implement of GMR sensing and analysis of machine faults.

Coastal modelling studies for forecasting and remediation solutions

The coastal area along the Emilia-Romagna (ER), in the Italian side of the northern Adriatic Sea, is considered to implement an unstructured numerical ocean model with the aim to develop innovative tools for the coastal management and a forecasting system for the storm surge risk reduction. The Adriatic Sea has been the focus of several studies because of its peculiar dynamics driven by many forcings acting at basin and local scales. The ER coast is particularly exposed to storm surge events. In particular conditions, winds, tides and seicehs may combine and contribute to the flooding of the coastal area. The global sea level rise expected in the next decades will increase even more the hazard along the ER and Adriatic coast. Reliable Adriatic and Mediterranean scale numerical ocean models are now available to allow the dynamical downscaling of very high-resolution models in limited coastal areas. In this work the numerical ocean model SHYFEM is implemented in the Goro lagoon (named GOLFEM) and along the ER coast (ShyfER) to test innovative solutions against sea related coastal hazards. GOLFEM was succesfully applied to analyze the Goro lagoon dynamics and to assess the dynamical effects of human interventions through the analysis of what-if scenarios. The assessment of storm surge hazard in the Goro lagoon was carried out through the development of an ensemble storm surge forecasting system with GOLFEM using forcing from different operational meteorological and ocean models showing the fundamental importance of the boundary conditions. The ShyfER domain is used to investigate innovative solutions against storm surge related hazard along the ER coast. The seagrass is assessed as a nature-based solution (NBS) for coastal protection under present and future climate conditions. The results show negligible effects on sea level but sensible effects in reducing bottom current velocity.

Urban air quality: new high-resolution modeling approaches and forecasting tools for citizens

Air pollution is one of the greatest health risks in the world. At the same time, the strong correlation with climate change, as well as with Urban Heat Island and Heat Waves, make more intense the effects of all these phenomena. A good air quality and high levels of thermal comfort are the big goals to be reached in urban areas in coming years. Air quality forecast help decision makers to improve air quality and public health strategies, mitigating the occurrence of acute air pollution episodes. Air quality forecasting approaches combine an ensemble of models to provide forecasts from global to regional air pollution and downscaling for selected countries and regions. The development of models dedicated to urban air quality issues requires a good set of data regarding the urban morphology and building material characteristics. Only few examples of air quality forecast system at urban scale exist in the literature and often they are limited to selected cities. This thesis develops by setting up a methodology for the development of a forecasting tool. The forecasting tool can be adapted to all cities and uses a new parametrization for vegetated areas. The parametrization method, based on aerodynamic parameters, produce the urban spatially varying roughness. At the core of the forecasting tool there is a dispersion model (urban scale) used in forecasting mode, and the meteorological and background concentration forecasts provided by two regional numerical weather forecasting models. The tool produces the 1-day spatial forecast of NO2, PM10, O3 concentration, the air temperature, the air humidity and BLQ-Air index values. The tool is automatized to run every day, the maps produced are displayed on the e-Globus platform, updated every day. The results obtained indicate that the forecasting output were in good agreement with the observed measurements.

SPHERA, a new Italian convection-permitting regional reanalysis: improving heavy-rainfall representation and describing hail-prone environments

Extreme weather events related to deep convection are high-impact critical phenomena whose reliable numerical simulation is still challenging. High-resolution (convection-permitting) modeling setups allow to switch off physical parameterizations accountable for substantial errors in convection representation. A new convection-permitting reanalysis over Italy (SPHERA) has been produced at ARPAE to enhance the representation and understanding of extreme weather situations. SPHERA is obtained through a dynamical downscaling of the global reanalysis ERA5 using the non-hydrostatic model COSMO at 2.2 km grid spacing over 1995-2020. This thesis aims to verify the expectations placed on SPHERA by analyzing two weather phenomena that are particularly challenging to simulate: heavy rainfall and hail. A quantitative statistical analysis over Italy during 2003-2017 for daily and hourly precipitation is presented to compare the performance of SPHERA with its driver ERA5 considering the national network of rain gauges as reference. Furthermore, two extreme precipitation events are deeply investigated. SPHERA shows a quantitative added skill over ERA5 for moderate to severe and rapid accumulations in terms of adherence to the observations, higher detailing of the spatial fields, and more precise temporal matching. These results prompted the use of SPHERA for the investigation of hailstorms, for which the combination of multiple information is crucial to reduce the substantial uncertainties permeating their understanding. A proxy for hail is developed by combining hail-favoring environmental numerical predictors with observations of ESWD hail reports and satellite overshooting top detections. The procedure is applied to the extended summer season (April-October) of 2016-2018 over the whole SPHERA spatial domain. The results indicate maximum hail likelihood over pre-Alpine regions and the northern Adriatic sea around 15 UTC in June-July, in agreement with recent European hail climatologies. The method demonstrates enhanced performance in case of severe hail occurrences and the ability to separate between ambient signatures depending on hail severity.

Submesoscale features in regions with different baroclinic deformation radius

In questo studio, un modello nidificato "child" ad alta risoluzione (risoluzione 1/48°) è ottenuto attraverso la piattaforma SURF. Il modello "child" è ottenuto tramite "downscaling" dei campi medi giornalieri dal modello globale "parent" (1/12°). Questo permette di osservare le caratteristiche della sottomesoscala in due regioni dell'oceano Atlantico settentrionale, Azzorre e Bermuda, dal 4 al 12 gennaio 2021. Questa tesi si propone di condurre un'analisi preliminare della relazione fra il raggio di deformazione baroclino e l'esordio dell'attività di sottomesoscala, nelle regioni di interesse. A questo scopo, vengono effettuati molti confronti fra i campi risultanti dal "parent" e dal "child". In particolare, ci concentriamo sulla Mixed-Layer Instability (MLI) studiata attraverso variabili come la Mixed-Layer Depth (MLD), la vorticità relativa, le velocità orizzontali e verticali, l'energia cinetica e la frequenza di Brunt-Vaisala. Dai risultati, mentre il modello "parent" sembra inadeguato, quello "child" è in grado di rilevare la MLI e la presenza di filamenti e scie topografiche in entrambe le regioni, riproducendo meglio le correnti orizzontali e verticali alla sottomesoscala. Ciò fornisce una connessione tra mesoscala e sottomesoscala: mentre nelle Azzorre la MLI sembra svolgere un ruolo chiave nella ristratificazione della colonna d'acqua, lo stesso non sembra nelle Bermuda dove i vortici di mesoscala sono più ampi, influendo maggiormente sulla stratificazione verticale. Qui, i processi di ristratificazione sembrerebbero correlati alle mesoscale piuttosto che alle sottomesoscale. La MLI giocherebbe comunque un ruolo nella generazione di correnti alla sottomesoscala, insieme ad altri processi come la frontogenesi e le scie topografiche. In conclusione, il valore del raggio di deformazione baroclino non sembra influenzare l'attivazione dei processi di sottomesoscala, mentre sembrerebbe determinare l'importanza della MLI nel processo di ristratificazione.

Sviluppo e sperimentazione di una tecnica a base regionale per la generazione di serie temporali di portata in sezioni fluviali non strumentate

La conoscenza del regime dei deflussi di un corso d’acqua è uno strumento imprescindibile in diverse applicazioni tecniche, dalla progettazione di opere idrauliche alla calibrazione di modelli afflussi-deflussi. Tuttavia, poiché questa informazione non è sempre disponibile, si sono sviluppati in letteratura metodi regionali in grado di trasferire il dato di portata disponibile su sezioni idrologicamente simili alla sezione di interesse. Nel presente lavoro di Tesi, è stato sviluppato un algoritmo di generazione di serie di deflussi sintetici per sezioni non strumentate a partire da serie osservate in sezioni ad esse sincrone nei deflussi. L’algoritmo sfrutta una curva di durata regionale relativa al sito di interesse, stimata attraverso il metodo della portata indice: la portata indice è valutata da un modello multiregressivo mentre la curva regionale adimensionale è ottenuta dalle osservazioni di portata in sezioni strumentate, applicando il criterio della Regione di Influenza. La tecnica è stata verificata su una sezione dell’asta principale del Fiume Marecchia (nell’Italia settentrionale), caratterizzata da limitate osservazioni idrometriche, sfruttando i dati osservati su bacini orientali della Regione Emilia-Romagna. Per l’applicazione del metodo del deflusso indice, si è reso necessario anche il reperimento di indici morfologici e climatici, estraendo solo quelli più rappresentativi del dataset. Inoltre, vista la brevità degli eventi di piena nel bacino del Marecchia, si è messa a punto una procedura per discretizzare a passo orario le portate ricostruite degli eventi più significativi, sulla base delle osservazioni orarie nei bacini strumentati. L’algoritmo mostra buone prestazioni nel replicare le portate osservate, specialmente le piene, mentre sottostima le portate medio-basse. L’accordo tra osservazioni e simulazioni si è rivelato pienamente soddisfacente per la sezione del Fiume Marecchia considerata nelle indagini.