17 research outputs found

    Couplage bidirectionnel feu-atmosphère pour la propagation des incendies de forêt : modélisation, incertitudes et sensibilités

    Get PDF
    Les incendies de forêt font partie des phénomènes naturels destructeurs représentant un enjeu écologique majeur et un problème pour la sécurité des populations. La propagation d'un incendie aux échelles géographiques (i.e. pour un incendie de plusieurs dizaines voire centaines d'hectares) peut être modélisée en adoptant une description simplifiée du feu, sous la forme d'un front unidimensionnel se déplaçant sur surface combustible hétérogène, et en l'intégrant au sein d'un modèle de météorologie locale. Lorsque le modèle atmosphérique et le modèle de feu s'échangent des informations comme le vent de surface et les flux de chaleur générés par l'incendie, on parle de modèle couplé feu-atmosphère. Dans ces travaux de thèse, le modèle de feu Blaze a été développé et intégré au modèle de météorologie de méso-échelle MésoNH afin de reconstruire la chronologie détaillée d'un incendie et de fournir ainsi un cadre d'étude des interactions entre un incendie et la micro-météorologie. Le modèle couplé MésoNH-Blaze a été validé sur le brûlage dirigé FireFlux I, un feu de prairie d'une trentaine d'hectares. La réponse du modèle couplé MésoNH-Blaze à différents choix de modélisation et différents scénarios atmosphériques a été étudiée pour quantifier les incertitudes associées aux quantités d'intérêt (la position et les flux de chaleur sensibles du front de feu par exemple) et identifier les paramètres les plus influents. Les résultats ont montré une influence significative de la turbulence atmosphérique sur la vitesse de propagation et le vent induit par le feu. L'étude de sensibilité a également montré l'impact de la vitesse de propagation à la tête du front de feu à la vitesse du vent de surface, à l'indice foliaire et à la température d'inflammation de la paramétrisation de Balbi. Les flux de chaleur sensible et latente sont quant à eux principalement influencés par la charge de combustible mort et la teneur en humidité du combustible mort, respectivement. Dans sa version standard, le modèle atmosphérique MésoNH repose sur l'hypothèse anélastique. Celle-ci permet de supprimer les ondes acoustiques dans l'atmosphère en négligeant les variations horizontales et temporelles de densité de l'air dans l'équation de conservation de la masse. La validité de cette hypothèse est discutable au voisinage des zones de flammes sujettes à d'importants dégagements de chaleur. La version compressible de MésoNH, qui ne fait pas d'hypothèse sur la densité de l'air dans l'équation de continuité, développée précédemment pour l'atmosphère sèche, a été étendue à l'atmosphère humide dans le cadre de cette thèse. Elle a tout d'abord été appliquée sur des cas dynamiques simplifiés. Puis une comparaison entre les systèmes anélastique et compressible a été réalisée à l'aide du modèle couplé MésoNH-Blaze sur le cas FireFlux I. Les résultats ont montré que les effets compressibles deviennent importants à très haute résolution spatiale (10 m), en induisant une accélération du vent horizontal à l'avant du front de feu qui tend à accélérer la propagation du front de flamme, et en déclenchant une activité ondulatoire augmentant l'énergie spectrale des plus courtes longueurs d'onde. Ces structures de fine échelle nécessiteront une validation approfondie, mais montrent un certain degré de réalisme. Le système MésoNH-Blaze fournit un cadre numérique pour mieux comprendre les processus atmosphériques associés à un incendie tels que la dynamique de panache.Wildfires are among the destructive natural phenomena that represent a major ecological challenge and a problem for public safety. Fire spread on geographical scales (i.e., for a wildfire of several tens or even hundreds of hectares) can be modelled by assuming a simplified description of the fire, in the form of a one-dimensional front moving over a heterogeneous combustible surface, and by embedding it within a local weather model. When the atmospheric model and the fire model exchange information such as surface wind and heat fluxes generated by the fire, it is referred to as a coupled fire-atmosphere model. In this thesis work, the fire model Blaze was developed and integrated with the mesoscale meteorological model MésoNH in order to reconstruct the detailed chronology of a fire and thus provide a framework for studying wildfire and micro-meteorology interactions. The coupled MésoNH-Blaze model has been validated on the FireFlux I prescribed burn, a tall grass fire of about 30 hectares. The response of the coupled MésoNH-Blaze model to different modeling choices and atmospheric scenarios was studied to quantify the uncertainties associated with the quantities of interest (the position and sensitive heat fluxes of the fire front for example) and to identify the most influential parameters. The results showed a significant influence of atmospheric turbulence on the propagation speed and the wind induced by the fire. The sensitivity study also showed the impact of the propagation speed at the head of the fire front on the surface wind speed, the leaf area index and the ignition temperature of the Balbi's parameterization. Sensitive and latent heat fluxes are mainly influenced by the dead fuel load and the moisture content of the dead fuel, respectively. In its standard version, the atmospheric model MésoNH is based on the anelastic assumption. This allows to suppress acoustic waves in the atmosphere by neglecting horizontal and temporal variations in air density in the mass conservation equation. The relevance of this hypothesis is questionable in the vicinity of flame zones subject to important heat releases. The compressible version of MésoNH, which does not make a specific assumption on air density in the continuity equation, previously developed for the dry atmosphere, has been extended to the humid atmosphere in this thesis. It was first applied on simplified dynamic cases. Then a comparison between anelastic and compressible systems was performed using the coupled model MésoNH-Blaze on the FireFlux I case. The results showed that the compressible effects become important at very high spatial resolution (10 m), by inducing a horizontal wind acceleration in front of the fire front which tends to accelerate the fire rate of spread, and by triggering a wave motion activity increasing the spectral energy of the shortest wavelengths. These fine-scale structures will require further validation but show a certain degree of realism. The MésoNH-Blaze system provides a numerical framework to better understand the atmospheric processes associated with a fire such as plume dynamics

    Swarm Intelligence

    Get PDF
    Swarm Intelligence has emerged as one of the most studied artificial intelligence branches during the last decade, constituting the fastest growing stream in the bio-inspired computation community. A clear trend can be deduced analyzing some of the most renowned scientific databases available, showing that the interest aroused by this branch has increased at a notable pace in the last years. This book describes the prominent theories and recent developments of Swarm Intelligence methods, and their application in all fields covered by engineering. This book unleashes a great opportunity for researchers, lecturers, and practitioners interested in Swarm Intelligence, optimization problems, and artificial intelligence

    Near Real-Time Automated Early Mapping of the Perimeter of Large Forest Fires from the Aggregation of VIIRS and MODIS Active Fires in Mexico

    Get PDF
    In contrast with current operational products of burned area, which are generally available one month after the fire, active fires are readily available, with potential application for early evaluation of approximate fire perimeters to support fire management decision making in near real time. While previous coarse-scale studies have focused on relating the number of active fires to a burned area, some local-scale studies have proposed the spatial aggregation of active fires to directly obtain early estimate perimeters from active fires. Nevertheless, further analysis of this latter technique, including the definition of aggregation distance and large-scale testing, is still required. There is a need for studies that evaluate the potential of active fire aggregation for rapid initial fire perimeter delineation, particularly taking advantage of the improved spatial resolution of the Visible Infrared Imaging Radiometer (VIIRS) 375 m, over large areas and long periods of study. The current study tested the use of convex hull algorithms for deriving coarse-scale perimeters from Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) active fire detections, compared against the mapped perimeter of the MODIS collection 6 (MCD64A1) burned area. We analyzed the effect of aggregation distance (750, 1000, 1125 and 1500 m) on the relationships of active fire perimeters with MCD64A1, for both individual fire perimeter prediction and total burned area estimation, for the period 2012–2108 in Mexico. The aggregation of active fire detections from MODIS and VIIRS demonstrated a potential to offer coarse-scale early estimates of the perimeters of large fires, which can be available to support fire monitoring and management in near real time. Total burned area predicted from aggregated active fires followed the same temporal behavior as the standard MCD64A1 burned area, with potential to also account for the role of smaller fires detected by the thermal anomalies. The proposed methodology, based on easily available algorithms of point aggregation, is susceptible to be utilized both for near real-time and historical fire perimeter evaluation elsewhere. Future studies might test active fires aggregation between regions or biomes with contrasting fuel characteristics and human activity patterns against medium resolution (e.g., Landsat and Sentinel) fire perimeters. Furthermore, coarse-scale active fire perimeters might be utilized to locate areas where such higher-resolution imagery can be downloaded to improve the evaluation of fire extent and impactFunding for this study was provided by CONAFOR/CONACYT Projects “CO2-2014-3-252620” and “CO-2018-2-A3-S-131553” for the development and enhancement of a Forest Fire Danger Prediction System for Mexico, funded by the Sectorial Fund for forest research, development and technological innovation “Fondo Sectorial para la investigación, el desarrollo y la innovación tecnológica forestal”S

    Agent-Based Modelling of Public Space Activity in Real-Time

    Get PDF
    Understanding how urban space is used by its inhabitants is vital in improving the overall quality of a city's built environment, as it can highlight needs and requirements of everyday life to be addressed in any urban development. Our investigation of urban activity is often approached through spatial models and simulations on the one hand, and urban data on the other. The work presented here explores potential combinations of the two, by coupling urban models with real-time urban data feeds for continuous short-term forecasting of urban activity. This aim is approached through the development of a model of activity in urban public spaces using the agent-based modelling paradigm, calibrated to real-time data input, and applied to the simulation of current activity in public spaces at a fine spatio-temporal scale. Observations about human spatial behaviour are identified in the literature on public spaces and implemented within a 3D modelling framework, thereby extending existing pedestrian and crowd agent-based modelling approaches. Furthermore, a review and evaluation of real-time data feeds pertaining to activity in public spaces is performed, focussing on open and publicly available datasets, and a forecasting model is developed using social media and other datasets as a proxy for current user activity. The resulting real-time model of public space activity is then evaluated through two case studies focussing on two major urban parks in London, UK. The model performs well in capturing park visitor activity in terms of spatial dispersion. Real-time data feeds examined are found to be capable of capturing park visitor activity to some degree; however they are found to be inadequate in supporting a fully fledged, detailed real-time model of public space activity. Finally, potential future trajectories of the approaches are identified in the increasing availability of online 3D mapping data when combined with advances in computational efficiency and data availability, in extending current data visualisation approaches into expansive, fine-scale simulations of real-time urban activity

    Path planning for first responders in the presence of moving obstacles

    Get PDF
    Navigation services have gained much importance for all kinds of human activities ranging from tourist navigation to support of rescue teams in disaster management. However, despite the considerable amount of route guidance research that has been performed, many issues that are related to navigation for first responders still need to be addressed. During disasters, emergencies can result in different types of moving obstacles (e.g., fires, plumes, floods), which make some parts of the road network temporarily unavailable. After such incidents occur, responders have to go to different destinations to perform their tasks in the environment affected by the disaster. Therefore they need a path planner that is capable of dealing with such moving obstacles, as well as generating and coordinating their routes quickly and efficiently. During the past decades, more and more hazard simulations, which can modify the models with incorporation of dynamic data from the field, have been developed. These hazard simulations use methods such as data assimilation, stochastic estimation, and adaptive measurement techniques, and are able to generate more reliable results of hazards. This would allow the hazard simulation models to provide valuable information regarding the state of road networks affected by hazards, which supports path planning for first responders among the moving obstacles. The objective of this research is to develop an integrated navigation system for first responders in the presence of moving obstacles. Such system should be able to navigate one or more responders to one or multiple destinations avoiding the moving obstacles, using the predicted information of the moving obstacles generated from by hazard simulations. In this dissertation, the objective we have is expressed as the following research question: How do we safely and efficiently navigate one or more first responders to one or more destinations avoiding moving obstacles? To address the above research questions, this research has been conducted using the following outline: 1). literature review; 2). conceptual design and analysis; 3). implementation of the prototype; and 4). assessment of the prototype and adaption. We investigated previous research related to navigation in disasters, and designed an integrated navigation system architecture, assisting responders in spatial data storage, processing and analysis.Within this architecture, we employ hazard models to provide the predicted information about the obstacles, and select a geo-database to store the data needed for emergency navigation. Throughout the development of the prototype navigation system, we have proposed: a taxonomy of navigation among obstacles, which categorizes navigation cases on basis of type and multiplicity of first responders, destinations, and obstacles; a multi-agent system, which supports information collection from hazard simulations, spatio-temporal data processing and analysis, connection with a geo-database, and route generation in dynamic environments affected by disasters; data models, which structure the information required for finding paths among moving obstacles, capturing both static information, such as the type of the response team, the topology of the road network, and dynamic information, such as changing availabilities of roads during disasters, the uncertainty of the moving obstacles generated from hazard simulations, and the position of the vehicle; path planning algorithms, which generate routes for one or more responders in the presence of moving obstacles. Using the speed of vehicles, departure time, and the predicted information about the state of the road network, etc., three versions (I, II, and III) of Moving Obstacle Avoiding A* (MOAAStar) algorithms are developed: 1). MOAAstar– I/Non-waiting, which supports path planning in the case of forest fires; 2). MOAAstar–II/Waiting, which introduces waiting options to avoid moving obstacles like plumes; 3). MOAAstar–III/Uncertainty, which can handle the uncertainty in predictions of moving obstacles and incorporate the profile of responders into the routing. We have applied the developed prototype navigation system to different navigation cases with moving obstacles. The main conclusions drawn from our applications are summarized as follows: In the proposed taxonomy, we have identified 16 navigation cases that could occur in disaster response and need to be investigated. In addressing these navigation problems, it would be quite useful to employ computer simulations and models, which can make reliable predicted information about responders, the targets, and obstacles, in finding safe routes for the responders. The approach we provide is general and not limited to the cases of plumes and fires. In our data model, the data about the movement of hazards is represented as moving polygons. This allows the data model to be easily adjusted to merge and organize information from models of different types of disasters. For example, the areas that are affected by floods can also be represented as moving polygons. To facilitate the route calculation, not only the data of obstacles but also the information about the state of road networks affected by obstacles need to be structured and stored in the database. In planning routes for responders, the routing algorithms should incorporate the dynamic data of obstacles to be able to avoid the hazards. Besides, other factors, such as the operation time of tasks, the required arrival time, and departure time, also need to be considered to achieve the objectives in a rescue process, e.g., to minimize the delays caused by the moving obstacles. The profile of responders is quite important for generation of feasible routes for a specific disaster situation. The responders may have different protective equipment that allows them to pass through different types of moving obstacles, and thus can have different classification of risk levels to define the state of the road network. By taking into account the profile of the responders, the navigation system can propose customized and safe routes to them, which would facilitate their disaster response processes. On the basis of our findings, we suggest the following topics for future work: As presented Wang and Zlatanova (2013c), there are still a couple of navigation cases that need to be addressed, especially the ones that involve dynamic destinations. More algorithms would be needed to solve these navigation problems. Besides, some extreme cases (e.g., the obstacle covers the target point during the course of an incident) also need to be investigated. Using standard Web services, an Android navigation application, which can provide navigation services in the environment affected by hazards, needs to be developed and tested in both the daily practice and real disasters. In this application, a user interface with various styling options should also be designed for different situations, e.g., waiting and moving, day and night, and urgent and non-urgent. Because the communication infrastructure may not be available or work properly during a disaster response, a decentralized method is needed to allow different users to negotiate with each other and to make local agreements on the distribution of tasks in case there is no support from the central planning system. Another type of multi-agent system would be needed to handle this situation. Introduce variable traveling speed into the re-routing process. The vehicle speed plays an important role in generation of routes avoiding moving obstacle, and can be influenced by many factors, such as the obstacles, the type of vehicles, traffic conditions, and the type of roads. Therefore, it would be needed to investigate how to derive the current and future speed from trajectories of vehicles. Apply the system to aid navigation in various types of natural disasters, using different hazard simulation models (e.g., flood model). More types of agents would be needed and integrated into the system to handle heterogeneous data from these models. Extensions of the data model are also required to meet a wider range of informational needs when multiple disasters occur simultaneously

    Distributed Signal Processing and Data Fusion Methods for Large Scale Wireless Sensor Network Applications

    Get PDF
    Σε αυτή τη Διδακτορική Διατριβή μελετάμε το πρόβλημα της παρακολούθησης και πρόβλεψης της εξέλιξης συνεχών αντικειμένων (π.χ. καταστροφικά περιβαλλοντικά φαινόμενα που διαχέονται) με τη χρήση Ασυρμάτων Δικτύων Αισθητήρων (ΑΔΑ) ευρείας κλίμακας. Προτείνουμε μια ευέλικτη αλλά και πρακτική προσέγγιση με δύο κύρια συστατικά: α) Ασύγχρονο συνεργατικό αλγόριθμο ΑΔΑ που εκτιμά, χρησιμοποιώντας δυναμικά σχηματιζόμενες ομάδες από τρεις συνεργαζόμενους κόμβους, τα τοπικά χαρακτηριστικά της εξέλιξης (διεύθυνση, φορά και ταχύτητα) του μετώπου, καθώς και β) Αλγόριθμο που ανακατασκευάζει το συνολικό μέτωπο του συνεχούς αντικειμένου συνδυάζοντας την πληροφορία των τοπικών εκτιμήσεων. Επιπλέον, ο αλγόριθμος ανακατασκευής, εκμεταλλευόμενος την δυνατότητα εκτίμησης της αβεβαιότητα ως προς τα τοπικά χαρακτηριστικά εξέλιξης, μπορεί να προβλέπει και την πιθανότητα το κάθε σημείο της περιοχής να έχει καλυφθεί από το συνεχές αντικείμενο σε κάθε χρονική στιγμή. Μέσω πλήθους προσομοιώσεων επικυρώσαμε την ικανότητα του συνεργατικού αλγορίθμου να εκτιμά με ακρίβεια τα τοπικά χαρακτηριστικά εξέλιξης πολύπλοκων συνεχών αντικειμένων, καθώς και την ευρωστία του σε αστοχίες των αισθητηρίων κόμβων κατά την επικοινωνία τους αλλά και λόγω της πιθανής ολοσχερούς καταστροφής τους. Τέλος, παρουσιάζουμε τη δυνατότητα του αλγορίθμου ανακατασκευής να παρακολουθεί με ακρίβεια την εξέλιξη μετώπων συνεχών αντικειμένων με πολύπλοκα σχήματα, χρησιμοποιώντας σχετικά μικρό αριθμό τοπικών εκτιμήσεων στις οποίες μπορεί να έχει υπεισέλθει και σημαντικό σφάλμα.In this Dissertation we study the problem of tracking the boundary of a continuous object (e.g. a hazardous diffusive phenomenon) and predicting its local and global spatio-temporal evolution characteristics using large-scale Wireless Sensor Networks (WSNs). We introduce a practical WSN-based approach consisting of two main components: a) An asynchronous collaborative in-network processing algorithm that estimates, using dynamically formed node triplets (clusters), local front model evolution parameters (orientation, direction and speed) of the expanding continuous object, and b) an algorithm that reconstruct the overall hazard's boundary by combining the produced local front estimates as they are becoming available to a fusion center. Based on the estimated uncertainties of local front model parameters, the reconstruction can provide for each point of the considered area the probability to be reached by the hazard’s front. Extensive computer simulations demonstrate that the proposed algorithm can estimate accurately the evolution characteristics of complex diffusive continuous objects, while it remains robust to sensor node and communication link failures. Finally, we show that it can track with accuracy the evolution of continuous objects with complex shapes, using a relatively small number of potentially distorted local front estimates

    Μέθοδοι κατανεμημένης επεξεργασίας σήματος και σύντηξης δεδομένων για εφαρμογές ασυρμάτων δικτύων αισθητήρων ευρείας κλίμακας

    Get PDF
    Σε αυτή τη Διδακτορική Διατριβή μελετάμε το πρόβλημα της παρακολούθησης και πρόβλεψης της εξέλιξης συνεχών αντικειμένων (π.χ. καταστροφικά περιβαλλοντικά φαινόμενα που διαχέονται) με τη χρήση Ασυρμάτων Δικτύων Αισθητήρων (ΑΔΑ) ευρείας κλίμακας. Προτείνουμε μια ευέλικτη αλλά και πρακτική προσέγγιση με δύο κύρια συστατικά: α) Ασύγχρονο συνεργατικό αλγόριθμο ΑΔΑ που εκτιμά, χρησιμοποιώντας δυναμικά σχηματιζόμενες ομάδες από τρεις συνεργαζόμενους κόμβους, τα τοπικά χαρακτηριστικά της εξέλιξης (διεύθυνση, φορά και ταχύτητα) του μετώπου, καθώς και β) Αλγόριθμο που ανακατασκευάζει το συνολικό μέτωπο του συνεχούς αντικειμένου συνδυάζοντας την πληροφορία των τοπικών εκτιμήσεων. Επιπλέον, ο αλγόριθμος ανακατασκευής, εκμεταλλευόμενος την δυνατότητα εκτίμησης της αβεβαιότητα ως προς τα τοπικά χαρακτηριστικά εξέλιξης, μπορεί να προβλέπει και την πιθανότητα το κάθε σημείο της περιοχής να έχει καλυφθεί από το συνεχές αντικείμενο σε κάθε χρονική στιγμή. Μέσω πλήθους προσομοιώσεων επικυρώσαμε την ικανότητα του συνεργατικού αλγορίθμου να εκτιμά με ακρίβεια τα τοπικά χαρακτηριστικά εξέλιξης πολύπλοκων συνεχών αντικειμένων, καθώς και την ευρωστία του σε αστοχίες των αισθητηρίων κόμβων κατά την επικοινωνία τους αλλά και λόγω της πιθανής ολοσχερούς καταστροφής τους. Τέλος, παρουσιάζουμε τη δυνατότητα του αλγορίθμου ανακατασκευής να παρακολουθεί με ακρίβεια την εξέλιξη μετώπων συνεχών αντικειμένων με πολύπλοκα σχήματα, χρησιμοποιώντας σχετικά μικρό αριθμό τοπικών εκτιμήσεων στις οποίες μπορεί να έχει υπεισέλθει και σημαντικό σφάλμα. In this Dissertation we study the problem of tracking the boundary of a continuous object (e.g. a hazardous diffusive phenomenon) and predicting its local and global spatio-temporal evolution characteristics using large-scale Wireless Sensor Networks (WSNs). We introduce a practical WSN-based approach consisting of two main components: a) An asynchronous collaborative in-network processing algorithm that estimates, using dynamically formed node triplets (clusters), local front model evolution parameters (orientation, direction and speed) of the expanding continuous object, and b) an algorithm that reconstruct the overall hazard's boundary by combining the produced local front estimates as they are becoming available to a fusion center. Based on the estimated uncertainties of local front model parameters, the reconstruction can provide for each point of the considered area the probability to be reached by the hazard’s front. Extensive computer simulations demonstrate that the proposed algorithm can estimate accurately the evolution characteristics of complex diffusive continuous objects, while it remains robust to sensor node and communication link failures. Finally, we show that it can track with accuracy the evolution of continuous objects with complex shapes, using a relatively small number of potentially distorted local front estimates

    A perennial simulation framework for integrated crisis management studies

    Get PDF
    Ph.DDOCTOR OF PHILOSOPH

    Assimilation of Perimeter Data and Coupling with Fuel Moisture in a Wildland Fire - Atmosphere DDDAS

    Get PDF
    We present a methodology to change the state of the Weather Research Forecasting (WRF) model coupled with the fire spread code SFIRE, based on Rothermel's formula and the level set method, and with a fuel moisture model. The fire perimeter in the model changes in response to data while the model is running. However, the atmosphere state takes time to develop in response to the forcing by the heat flux from the fire. Therefore, an artificial fire history is created from an earlier fire perimeter to the new perimeter, and replayed with the proper heat fluxes to allow the atmosphere state to adjust. The method is an extension of an earlier method to start the coupled fire model from a developed fire perimeter rather than an ignition point. The level set method is also used to identify parameters of the simulation, such as the spread rate and the fuel moisture. The coupled model is available from openwfm.org, and it extends the WRF-Fire code in WRF release.Comment: ICCS 2012, 10 pages; corrected some DOI typesetting in the reference

    Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation: Special Report of the Intergovernmental Panel on Climate Change

    Get PDF
    This Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (SREX) has been jointly coordinated by Working Groups I (WGI) and II (WGII) of the Intergovernmental Panel on Climate Change (IPCC). The report focuses on the relationship between climate change and extreme weather and climate events, the impacts of such events, and the strategies to manage the associated risks. The IPCC was jointly established in 1988 by the World Meteorological Organization (WMO) and the United Nations Environment Programme (UNEP), in particular to assess in a comprehensive, objective, and transparent manner all the relevant scientific, technical, and socioeconomic information to contribute in understanding the scientific basis of risk of human-induced climate change, the potential impacts, and the adaptation and mitigation options. Beginning in 1990, the IPCC has produced a series of Assessment Reports, Special Reports, Technical Papers, methodologies, and other key documents which have since become the standard references for policymakers and scientists.This Special Report, in particular, contributes to frame the challenge of dealing with extreme weather and climate events as an issue in decisionmaking under uncertainty, analyzing response in the context of risk management. The report consists of nine chapters, covering risk management; observed and projected changes in extreme weather and climate events; exposure and vulnerability to as well as losses resulting from such events; adaptation options from the local to the international scale; the role of sustainable development in modulating risks; and insights from specific case studies
    corecore