Deep Learning Techniques in Extreme Weather Events: A Review

Extreme weather events pose significant challenges, thereby demanding techniques for accurate analysis and precise forecasting to mitigate its impact. In recent years, deep learning techniques have emerged as a promising approach for weather forecasting and understanding the dynamics of extreme weather events. This review aims to provide a comprehensive overview of the state-of-the-art deep learning in the field. We explore the utilization of deep learning architectures, across various aspects of weather prediction such as thunderstorm, lightning, precipitation, drought, heatwave, cold waves and tropical cyclones. We highlight the potential of deep learning, such as its ability to capture complex patterns and non-linear relationships. Additionally, we discuss the limitations of current approaches and highlight future directions for advancements in the field of meteorology. The insights gained from this systematic review are crucial for the scientific community to make informed decisions and mitigate the impacts of extreme weather events

Landslide and debris flow warning at regional scale. A real-time system using susceptibility mapping, radar rainfall and hydrometeorological thresholds

Rainfall triggered shallow slides and debris flows constitute a significant hazard that causes substantial economic losses and fatalities worldwide. Regional-scale risk mitigation for these processes is challenging. Therefore, landslide early warning systems (LEWS) are a helpful tool to depict the time and location of possible landslide events so that the hazardous situation can be managed more effectively. The main objective of this thesis is to set up a regional-scale LEWS that works in real-time over Catalonia (NE Spain). The developed warning system combines in real-time susceptibility information and rainfall observations to issue qualitative warnings over the region. Susceptibility has been derived combining slope angle and land use and land cover information with a simple fuzzy logic approach. The LEWS input rainfall information consists of high-resolution radar quantitative precipitation estimates (QPEs). To assess if a rainfall situation has the potential to trigger landslides, the LEWS applies a set of intensity duration thresholds. Finally, a warning matrix combines susceptibility and rainfall hazard to obtain a qualitative warning map that classifies the terrain into four warning classes. The evaluation of the LEWS performance has been challenging because of the lack of a systematic inventory, including the time and location of recent landslides events. Within the context of this thesis, a citizen-science initiative has been set up to gather landslide data from reports in social networks. However, some of the reports have significant spatial and temporal uncertainties. With the aim of finding the most suitable mapping unit for real-time warning purposes, the LEWS has been set-up to work using susceptibility maps based on grid-cells of different resolutions and subbasins. 30 m grid-cells have been chosen to compute the warnings as they offer a compromise between performance, interpretability of the results and computational costs. However, from an end users’ perspective visualising 30 m resolution warnings at a regional scale might be difficult. Therefore, subbasins have been proposed as a good option to summarise the warning outputs. A fuzzy verification method has been applied to evaluate the LEWS performance. Generally, the LEWS has been able to issue warnings in the areas where landslides were reported. The results of the fuzzy verification suggest that the LEWS effective resolution is around 1 km. The initial version of the LEWS has been improved by including soil moisture information in the characterisation of the rainfall situation. The outputs of this new approach have been compared with the outputs of LEWS using intensity-duration thresholds. With the new rainfall-soil moisture hydrometeorological thresholds, fewer false alarms were issued in high susceptibility areas where landslides had been observed. Therefore, hydrometeorological thresholds may be useful to improve the LEWS performance. This study provided a significant contribution to regional-scale landslide emergency management and risk mitigation in Catalonia. In addition, the modularity of the proposed LEWS makes it easy to apply in other regions.Els lliscaments superficials i els corrents d’arrossegalls són un fenomen perillós que causa significants perdudes econòmiques i humanes arreu del món. La seva principal causa desencadenant és la pluja. La mitigació del risc degut a aquets processos a escala regional no es senzilla. Ena quest context, els sistemes d’alerta són una eina útil per tal de predir el lloc i el moment en que es poden desencadenar possibles esllavissades en el futur, i poder fer una gestió del risc més eficient. L’objectiu principal d’aquesta tesi és el desenvolupament d’un sistema d’alerta per esllavissades a escala regional, que treballi en temps real a Catalunya. El Sistema d’alerta que s’ha desenvolupat combina informació sobre la susceptibilitat del terreny i estimacions de la pluja d’alta resolució per donar unes alertes qualitatives arreu del territori. La susceptibilitat s’ha obtingut a partir de la combinació d’informació del pendent del terreny, i els usos i les cobertes del sòl utilitzant un mètode de lògica difusa. Les dades de pluja són observacions del radar meteorològic. Per tal d’analitzar si un determinat episodi de pluja te el potencial per desencadenar esllavissades, el sistema d’alerta utilitza un joc de llindars intensitat-durada. Posteriorment, una matriu d’alertes combina la susceptibilitat i la magnitud del episodi de pluja. El resultat, és un mapa d’alertes que classifica el terreny en quatre nivells d’alerta. Amb l’objectiu de definir quina unitat del terreny és la més adient pel càlcul de les alertes en temps real, el sistema d’alerta s’ha configurat per treballar utilitzant mapes de susceptibilitat basats en píxels de diverses resolucions, i en subconques. Finalment, l’opció més convenient és utilitzar píxels de 30 m, ja que ofereixen un compromís entre el funcionament, la facilitat d’interpretació dels resultats i el cost computacional. Tot i això, la visualització de les alertes a escala regional emprant píxels de 30 m pot ser difícil. Per això s’ha proposat utilitzar subconques per oferir un sumari de les alertes. Degut a la manca d’un inventari d’esllavissades sistemàtic, que contingui informació sobre el lloc i el moment en que les esllavissades es van desencadenar, l’avaluació del funcionament del sistema d’alerta ha sigut un repte. En el context d’aquesta tesi, s’ha creat una iniciativa per tal de recol·lectar dades d’esllavissades a partir de posts en xarxes socials. Malauradament, algunes d’aquestes dades estan afectades per incerteses espacials i temporals força importants. Per a l’avaluació el funcionament del sistema d’alerta, s’ha aplicat un mètode de verificació difusa. Generalment, els sistema d’alerta ha estat capaç de generar alertes a les zones on s’havien reportat esllavissades. Els resultats de la verificació difusa suggereixen que la resolució efectiva del sistema d’alerta età al voltant d’1 km. Finalment, la versió inicial del sistema d’alerta s’ha millorat per tal poder incloure informació sobre l’estat d’humitat del terreny en la caracterització de la magnitud del episodi de pluja. Els resultats del sistema d’alerta utilitzant aquest nou enfoc s’han comparat amb els resultats que s’obtenen al córrer el sistema d’alerta utilitzant els llindars intensitat-durada. Mitjançant els nous llindars hidrometeorològics, el sistema emet menys falses alarmes als llocs on s’han desencadenat esllavissades. Per tant, utilitzar llindars hidrometeorològics podria ser útil per millorar el funcionament del sistema d’alerta dissenyat. L’estudi dut a terme en aquesta tesi suposa una important contribució que pot ajudar en la gestió de les emergències degudes a esllavissades a escala regional a Catalunya. A més a més, el fet de que el sistema sigui modular permet la seva fàcil aplicació en d’altres regions en un futur.Enginyeria del terren

Disaster preparedness in humanitarian logistics:A collaborative approach for resource management in floods

The logistical deployment of resources to provide relief to disaster victims and the appropriate planning of these activities are critical to reduce the suffering caused. Disaster management attracts many organisations working alongside each other and sharing resources to cope with an emergency. Consequently, successful operations rely heavily on the collaboration of different organisations. Despite this, there is little research considering the appropriate management of resources from multiple organisations, and none optimising the number of actors required to avoid shortages or convergence. This research introduces a disaster preparedness system based on a combination of multi-objective optimisation and geographical information systems to aid multi-organisational decision-making. A cartographic model is used to avoid the selection of floodable facilities, informing a bi-objective optimisation model used to determine the location of emergency facilities, stock prepositioning, resource allocation and relief distribution, along with the number of actors required to perform these activities. The real conditions of the flood of 2013 in Acapulco, Mexico, provided evidence of the inability of any single organisation to cope with the situation independently. Moreover, data collected showed the unavailability of enough resources to manage a disaster of that magnitude at the time. The results highlighted that the number of government organisations deployed to handle the situation was excessive, leading to high cost without achieving the best possible level of satisfaction. The system proposed showed the potential to achieve better performance in terms of cost and level of service than the approach currently employed by the authorities

An Epistemological Inquiry into the Incorporation of Emergency Management Concept in the Homeland Security with a Post-Disaster Security Centric Focus

The historical roots of the Emergency Management concept in the U.S. date back to 19th century. As disasters occurred, policies relating to disaster response have been developed, and many statuary provisions, including several Federal Disaster Relief Acts, conceptually established the framework of Emergency Management. In 1979, with the foundation of the Federal Emergency Management Agency (FEMA), disaster relief efforts were finally institutionalized, and the federal government acknowledged that Emergency Management included mitigation, preparedness, response and recovery activities as abbreviated \u27MPRR.\u27 However, after 2000, the U.S. experienced two milestone events - the September 11 terrorist attacks in 2001 and Hurricane Katrina in 2005. Following the foundation of the Department of Homeland Security (DHS) in 2002, the definitional context of Emergency Management and its phases/components, simply its essence, evolved and was incorporated into many official documents differently, creating contextual inconsistencies. Recent key official documents embody epistemological problems that have the potential to traumatize the coherence of the Homeland Security contextual framework as well as to impose challenges theoretically to the education and training of Homeland Security/Emergency Management stakeholders. Furthermore, the conceptual design of the Emergency Support Functions (ESF) which have been defined within the context of the National Response Framework (NRF) displays similar problematic symptoms, and existing urban area Public Safety and Security planning processes have also not been supported by methodologies that are aligned with the post-disaster security requirements. To that end, the conceptual framework of Emergency Management and its incorporation in the Homeland Security global architecture should be revised and redefined to enhance coherence and reliability. Coherence in the contextual structure directly links to the system\u27s organizational structure and its viability functions. Also, holistic multi-dimensional system representations/abstractions, which would support appreciation of the system\u27s complex context, should be incorporated in policy documents to be utilized to educate the relevant stakeholders (individuals, teams, etc.) during the training/orientation programs. In addition, the NRF and its ESFs should be reviewed through a post-disaster security centric focus, since the post-disaster environment has unique characteristics that should be addressed by different approaches. In that sense, this dissertation develops a Post-Disaster Security Index (PDSI) Model that provides valuable insights for security agents and other Emergency Management and Homeland Security stakeholders

Challenges and Technical Advances in Flood Early Warning Systems (FEWSs)

Flood early warning systems (FEWSs)—one of the most common flood-impact mitigation measures—are currently in operation globally. The UN Office for Disaster Risk Reduction (UNDRR) strongly advocates for an increase in their availability to reach the targets of the Sendai Framework for Disaster Risk Reduction and Sustainable Development Goals (SDGs). Comprehensive FEWS consists of four components, which includes (1) risk knowledge, (2) monitoring and forecasting, (3) warning, dissemination, and communication, and (4) response capabilities. Operational FEWSs have varying levels of complexity, depending on available data, adopted technology, and know-how. There are apparent differences in sophistication between FEWSs in developed countries that have the financial capabilities, technological infrastructure, and human resources and developing countries where FEWSs tend to be less advanced. Fortunately, recent advances in remote sensing, artificial intelligence (AI), information technologies, and social media are leading to significant changes in the mechanisms of FEWSs and provide the opportunity for all FEWSs to gain additional capability. These technologies are an opportunity for developing countries to overcome the technical limitations that FEWSs have faced so far. This chapter aims to discuss the challenges in FEWSs in brief and exposes technological advances and their benefits in flood forecasting and disaster mitigation

Remote Sensing of Natural Hazards

Each year, natural hazards such as earthquakes, cyclones, flooding, landslides, wildfires, avalanches, volcanic eruption, extreme temperatures, storm surges, drought, etc., result in widespread loss of life, livelihood, and critical infrastructure globally. With the unprecedented growth of the human population, largescale development activities, and changes to the natural environment, the frequency and intensity of extreme natural events and consequent impacts are expected to increase in the future.Technological interventions provide essential provisions for the prevention and mitigation of natural hazards. The data obtained through remote sensing systems with varied spatial, spectral, and temporal resolutions particularly provide prospects for furthering knowledge on spatiotemporal patterns and forecasting of natural hazards. The collection of data using earth observation systems has been valuable for alleviating the adverse effects of natural hazards, especially with their near real-time capabilities for tracking extreme natural events. Remote sensing systems from different platforms also serve as an important decision-support tool for devising response strategies, coordinating rescue operations, and making damage and loss estimations.With these in mind, this book seeks original contributions to the advanced applications of remote sensing and geographic information systems (GIS) techniques in understanding various dimensions of natural hazards through new theory, data products, and robust approaches

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

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