Large-scale disasters: prediction, control, and mitigation / edited by Mohamed Gad-El-Hak

Incluye bibliografía e índice temático: páginas 573-576

Preface.. About the editor.. List of contributors.. 1 Introduction.. 1.1 What is a large-scale disaster?.. 1.2 Book contents.. References.. 2 The art and science of large-scale disasters.. 2.1 Are disasters a modern curse?.. 2.2 Disaster scope.. 2.3 Facets of large-scale disasters.. 2.4 The science of disaster prediction and control.. 2.4.1 Modeling the disaster's dynamics.. 2.4.2 The fundamental transport equations.. 2.4.3 Closing the equations.. 2.4.4 Compressibility.. 2.4.5 Prandtl's breakthrough.. 2.4.6 Turbulent flows.. 2.4.7 Numerical solutions.. 2.4.8 Other complexities.. 2.4.9 Earthquakes.. 2.4.10 The butterfly effect.. 2.5 Global Earth Observation System of Systems.. 2.6 The art of disaster management.. 2.7 A bit of sociology.. 2.8 Few recent disasters.. 2.8.1 San Francisco Earthquake.. 2.8.2 Hyatt Regency walkway collapse.. 2.8.3 Izmit Earthquake.. 2.8.4 September.. .. 2.8.5 Pacific Tsunami.. 2.8.6 Hurricane Katrina.. 2.8.7 Kashmir Earthquake.. 2.8.8 Hurricane Wilma.. 2.8.9 Hajj stampede of 2006.. 2.8.10 Al-Salam Boccaccio 98.. 2.8.11 Bird flu.. 2.8.12 Energy crisis.. 2.9 Concluding remarks.. References.. 3 Multiscale modeling for large-scale disaster applications.. 3.1 Introduction.. 3.2 Definition and modeling of scales in climate and weather.. 3.2.1 Global climate modeling.. 3.2.2 Long-term climate simulation.. 3.2.3 Limits to predictability.. 3.2.4 Global and regional climate models.. 3.3 Definition and modeling of scales during accidental release of toxic agents in urban environments.. 3.4 Multiscale modeling methods.. 3.4.1 Key challenges.. 3.4.2 Application of modeling methods to large-scale disasters.. 3.4.3 Multiscale modeling techniques.. 3.4.4 Molecular dynamics method.. 3.4.5 Coarse-grained methods.. 3.4.6 Monte Carlo methods.. 3.4.7 Cellular automata.. 3.4.8 Neural networks.. 3.4.9 Mathematical homogenization.. 3.4.10 Quasi-continuum method.. 3.4.11 Heterogeneous multiscale method

3.4.12 Continuum methods.. 3.4.13 Domain decomposition method and parallel computations.. 3.4.14 Lattice Boltzmann method.. 3.5 Summary and outlook.. Acknowledgments.. References.. 4 Addressing the root causes of large-scale disasters.. 4.1 Definitions and context.. 4.1.1 Defining disasters.. 4.1.2 Do natural disasters exist?.. 4.2 Root causes of disaster.. 4.2.1 Case studies.. 4.2.2 Root cause: vulnerability.. 4.2.3 Root causes of vulnerability.. 4.3 Tackling root causes of disaster.. 4.3.1 Principles.. 4.3.2 Illustrative case studies.. 4.4 Conclusions.. References.. 5 Issues in disaster relief logistics.. 5.1 Introduction.. 5.2 Disaster relief issues identified in literature.. 5.3 Supply chain issues.. 5.3.1 Funding issues.. 5.3.2 Needs assessment and procurement.. 5.3.3 Management of information.. 5.3.4 Coordination issues.. 5.3.5 Transportation infrastructure and network design.. 5.3.6 Standardization of relief.. 5.4 Operational issues.. 5.4.1 Personnel issues.. 5.4.2 Availability of technology.. 5.4.3 Local resources.. 5.5 Ethical issues.. 5.5.1 Discrimination.. 5.5.2 Corruption.. 5.6 Political issues.. 5.6.1 Military use in disaster relief.. 5.7 Conclusions and future research directions.. References.. 6 Large-scale disasters: perspectives on medical response.. 6.1 Introduction.. 6.2 Characteristics of disasters.. 6.3 Classification of disasters.. 6.4 Disaster management.. 6.5 Phases of a disaster.. 6.5.1 Phase I: disaster preparedness.. 6.5.2 Phase II: medical response.. 6.5.3 Phase III: recovery.. 6.6 Role of specialists.. 6.7 Disaster evaluation.. 6.8 Failure of disaster response and problems encountered during disaster management.. 6.9 Conclusions.. References.. 7 Augmentation of health care capacity in large-scale disasters.. 7.1 Introduction.. 7.2 Definitions.. 7.3 Capacity augmentation of health care facility.. 7.3.1 Variables of health care capacity.. 7.3.2 Triage priorities

7.3.3 Capacities in the medical assistance chain.. 7.3.4 Mass trauma casualty predictor.. 7.3.5 Increasing hospital bed capacity.. 7.3.6 Adaptation of existing capacity.. 7.3.7 Staff calling in and staff augmentation plan.. 7.3.8 Modification of the standards of care.. 7.3.9 Triage of patients in mass critical care.. 7.4 Cooperative regional capacity augmentation.. 7.5 Off-site patient care.. 7.6 Role of government.. 7.7 Community involvement.. 7.8 Summary.. References.. 8 Energy, climate change, and how to avoid a manmade disaster.. 8.1 Introduction.. 8.2 Energy consumption-now and then.. 8.2.1 How much we use.. 8.2.2 Energy and how we live.. 8.2.3 How much we will use.. 8.3 Carbon dioxide.. 8.3.1 Greenhouse gases.. 8.3.2 Energy balance.. 8.3.3 Climate modeling.. 8.3.4 Global warming and climate change.. 8.4 CO2 emission mitigation.. 8.4.1 Implementing multiple solutions.. 8.4.2 The "wedges".. 8.5 Low-carbon fossil conversion technologies.. 8.5.1 Chemical energy.. 8.5.2 CO2 capture.. 8.5.3 Electrochemical separation.. 8.5.4 Synfuel production.. 8.6 Zero-carbon conversion technologies: nuclear and renewable sources.. 8.6.1 Nuclear energy.. 8.6.2 Hydraulic power.. 8.6.3 Geothermal energy.. 8.6.4 Wind energy.. 8.6.5 Solar energy.. 8.6.6 Biomass energy.. 8.6.7 Renewable sources and storage.. 8.7 Transportation.. 8.8 Conclusions.. References.. 9 Seawater agriculture for energy, warming, food, land, and water.. 9.1 Introduction.. 9.2 Biomass and the Sahara.. 9.3 Saline/salt water agriculture.. 9.4 Additional impacts/benefits of saline/seawater agriculture.. 9.5 Summary.. References.. 10 Natural and anthropogenic aerosol-related hazards affecting megacities.. 10.1 Introduction.. 10.2 Aerosol properties.. 10.3 Sand and dust storms.. 10.3.1 Remote sensing of sand and dust storms.. 10.3.2 Egypt case study.. 10.3.3 India case study.. 10.3.4 Modeling of dust storms (dust cycle model.. 10.4 Air pollution

10.4.1 Cairo air pollution case study.. 10.4.2 Pollution effects forcing on large-scale vegetation in India.. 10.5 Forcing component.. 10.5.1 Egypt case study.. 10.5.2 China case study.. 10.6 Conclusions.. Acknowledgments.. References.. 11 Tsunamis: manifestation and aftermath.. 11.1 Introduction.. 11.2 Causes of tsunamis: a general overview.. 11.3 Hydrodynamics of tsunamis.. 11.4 Ecological impacts of tsunamis-a general overview.. 11.5 The Sumatra Earthquake and Tsunami.. 11.5.1 The Sumatra-Andaman Island Earthquake, 26 December.. 4.. 11.5.2 The Sumatra Tsunami in Sri Lanka.. 11.5.3 Wave observations and impacts on Sri Lanka.. 11.5.4 The impact on Sri Lanka.. 11.6 Tsunami warning systems.. 11.7 Planning for tsunamis.. 11.7.1 Components of the stochastic scheduling network.. 11.8 Conclusions.. Acknowledgments.. References.. 12 Intermediate-scale dynamics of the upper troposphere and stratosphere.. 12.1 Background.. 12.2 More recent interpretation of data.. 12.3 Results from numerical simulations.. 12.4 Implications.. 12.5 Summary.. References.. 13 Coupled weather-chemistry modeling.. 13.1 Introduction.. 13.2 Fully coupled online modeling.. 13.2.1 Grid scale transport of species.. 13.2.2 Subgrid scale transport.. 13.2.3 Dry deposition.. 13.2.4 Gas-phase chemistry.. 13.2.5 Parameterization of aerosols.. 13.2.6 Photolysis frequencies.. 13.3 Online versus offline modeling.. 13.4 Application in global change research.. 13.5 Concluding remarks.. References.. 14 Seasonal-to-decadal prediction using climate models: successes and challenges.. 14.1 Introduction.. 14.2 Potentially predictable phenomena.. 14.3 Successes in dynamical climate prediction.. 14.4 Challenges that remain.. 14.5 Summary.. References.. 15 Climate change and related disasters.. 15.1 Introduction.. 15.1.1 Definitions of climate parameters.. 15.2 A brief review of regional climate modeling.. 15.3 ICTP regional climate model

15.4 Climate change and extreme events.. 15.4.1 Defining changes of extremes.. 15.5 Extremes and climate variability.. 15.6 Regional impact studies.. 15.6.1 Severe summertime flooding in Europe.. 15.6.2 Warming and heat wave.. 15.6.3 Wind storms (hurricanes.. 15.7 Summary.. Acknowledgments.. References.. 16 Impact of climate change on precipitation.. 16.1 Introduction.. 16.2 Precipitation processes in observations and models.. 16.2.1 Evaluation of model simulated changes in precipitation by examination of the diurnal cycle.. 16.2.2 Observed trends in moisture and extreme precipitation events.. 16.3 How should precipitation change as the climate changes?.. 16.4 Questions and issues.. 16.5 Summary.. Acknowledgments.. References.. 17 Weather-related disasters in arid lands.. 17.1 Introduction.. 17.2 Severe weather in arid lands.. 17.2.1 Dust storms and sand storms.. 17.2.2 Rainstorms, floods, and debris flows.. 17.3 Desertification.. 17.3.1 What is desertification?.. 17.3.2 Extent of desertification.. 17.3.3 Anthropogenic contributions to desertification.. 17.3.4 Natural contributions to desertification.. 17.3.5 Additional selected case studies and examples of desertification.. 17.3.6 Physical process feedbacks that may affect desertification.. 17.3.7 Satellite-based methods for detecting and mapping desertification.. 17.4 Summary.. References.. 18 The first hundred years of numerical weather prediction.. 18.1 Forecasting before equations.. 18.2 The birth of theoretical meteorology.. 18.3 Initial attempts of scientifically based weather prediction.. 18.4 Bergen school of meteorology.. 18.5 First numerical integration of the primitive meteorological equations.. 18.6 Weather forecasting after Richardson.. 18.7 Richardson's experiment revisited and the birth of forecasting based on primitive equations.. 18.8 Expansion of the scope of traditional meteorological prediction

18.9 Development of the modern atmospheric prediction systems.. 18.10 From weather prediction to environmental engineering and climate control.. 18.11 Conclusions.. References.. 19 Fundamental issues in numerical weather prediction.. 19.1 Introduction.. 19.2 Disaster-related weather.. 19.3 Disaster prediction strategies.. 19.3.1 Medium-range prediction: páginas -10 days.. 19.3.2 Short-range prediction: páginas -5 days.. 19.3.3 Day-to-day prediction: páginas -3 days.. 19.3.4 Very short-range prediction (<1 day.. 19.4 Fundamental issues: atmospheric predictability.. 19.5 The model.. 19.5.1 Model physics.. 19.5.2 Model dynamics.. 19.5.3 Model numerics.. 19.6 Model data.. 19.7 Conclusions.. References.. 20 Space measurements for disaster response: the International Charter.. 20.1 Introduction.. 20.2 Space remote sensing and disaster management.. 20.3 General principles of remote sensing.. 20.3.1 Optical, thermal, and microwave imaging.. 20.3.2 Image processing, information contents, and interpretation.. 20.3.3 Geophysical parameter retrieval and value adding.. 20.3.4 Image classification and change detection.. 20.4 Space-based initiatives for disaster management.. 20.5 About the charter.. 20.5.1 History and operations.. 20.5.2 A constellation of sensors and satellites.. 20.5.3 Mission summaries.. 20.5.4 Applicable policies.. 20.5.5 Performance update.. 20.6 Disaster coverage.. 20.6.1 Activation criteria.. 20.6.2 Data acquisition planning.. 20.6.3 Reporting and user feedback.. 20.7 Case histories.. 20.7.1 Nyiragongo volcanic eruption.. 20.7.2 Southern Manitoba flood.. 20.7.3 Galicia oil spill.. 20.7.4 South Asian Tsunami.. 20.7.5 French forest fires.. 20.7.6 Hurricane Katrina.. 20.7.7 Kashmir Earthquake.. 20.7.8 Philippines landslide.. 20.7.9 Central Europe floods.. 20.8 Concluding remarks.. Acknowledgments.. References.. 21 Weather satellite measurements: their use for prediction.. 21.1 Introduction

21.2 Weather satellite measurements.. 21.3 Global Earth Observation System of Systems.. 21.4 The current and planned space component.. 21.5 Vegetation index.. 21.6 Flash floods.. 21.7 Severe thunderstorms and hurricanes.. 21.8 Improvements in the satellite observing system.. 21.9 Summary.. Acknowledgments.. References.. Epilogue.. Index

"Extreme" events - including climatic events, such as hurricanes, tornadoes, drought - can cause massive disruption to society, including large death tolls and property damage in the billions of dollars. Events in recent years have shown the importance of being prepared and that countries need to work together to help alleviate the resulting pain and suffering. This volume presents an integrated review of the broad research field of large-scale disasters. It establishes a common framework for predicting, controlling and managing both manmade and natural disasters. There is a particular focus on events caused by weather and climate change. Other topics include air pollution, tsunamis, disaster modeling, the use of remote sensing and the logistics of disaster management. It will appeal to scientists, engineers, first responders and health-care professionals, in addition to graduate students and researchers who have an interest in the prediction, prevention or mitigation of large-scale disasters. • Deals with large-scale disasters from a scientific viewpoint rather than a purely sociological or logistical one, using the tools of nonlinear dynamical systems theory to predict, control or mitigate their effects. • Presents a universal metric through which all natural and manmade disasters can be assessed, placing them all on a common scale, instead of the disparate scales currently used for different disaster types. • Covers both natural and manmade disasters, but focuses on those caused principally by weather and climate change, recognizing the complexity of causes and the contribution of society. eng