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  • Other Sources  (3)
  • Disaster  (3)
  • Springer Netherlands  (3)
  • AMS (American Meteorological Society)
  • American Association of Petroleum Geologists (AAPG)
  • Potsdam Institute for Climate Impact Research
  • 2020-2024  (3)
  • 1995-1999
Collection
  • Other Sources  (3)
Source
Keywords
Publisher
  • Springer Netherlands  (3)
  • AMS (American Meteorological Society)
  • American Association of Petroleum Geologists (AAPG)
  • Potsdam Institute for Climate Impact Research
Language
Years
  • 2020-2024  (3)
  • 1995-1999
Year
  • 1
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    Natural hazards and climate change are not drivers of disasters (2021)
    Springer Netherlands
    Details
    Publication Date: 2023-08-25
    Description: Many nations face challenges in assessing, understanding, and responding to the time-dependent nature of disaster risk. Changes in the intensity of occurrences of extreme events coupled with changes in vulnerability and exposure alter the impacts of natural hazards on society in mostly negative ways. Here an interrelationship between natural hazard (NH), climate change (CC), vulnerability (V), exposure (E), and decisionmaking (DM) is considered. While NHs trigger disasters and CC is likely to intensify occurrences of disasters, V and E present major drivers of disasters. Informed DM on disaster risk reduction should be based on scientific evidence from NH and CC, knowledge of V and E, and relevant options for actions on preventive disaster measures as a part of preparedness and public awareness.
    Description: Russian Science Foundation http://dx.doi.org/10.13039/501100006769
    Description: Karlsruher Institut für Technologie (KIT) (4220)
    Keywords: ddc:363.7 ; Disaster ; Vulnerability ; Exposure ; Natural hazard ; Risk ; Climate change ; Preparedness ; Public awareness
    Language: English
    Type: doc-type:article
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  • 2
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    Risk of extreme high fatalities due to weather and climate hazards and its connection to large-scale climate variability (2020)
    Springer Netherlands
    Details
    Publication Date: 2023-06-14
    Description: Weather and climate hazards cause too many fatalities each year. These weather and climate hazards are projected to increase in frequency and intensity due to global warming. Here, we use a disaster database to investigate continentally aggregated fatality data for trends. We also examine whether modes of climate variability affect the propensity of fatalities. Furthermore, we quantify fatality risk by computing effective return periods which depend on modes of climate variability. We find statistically significant increasing trends for heat waves and floods for worldwide aggregated data. Significant trends occur in the number of fatalities in Asia where fatalities due to heat waves and floods are increasing, while storm-related fatalities are decreasing. However, when normalized by population size, the trends are no longer significant. Furthermore, the number of fatalities can be well described probabilistically by an extreme value distribution, a generalized Pareto distribution (GPD). Based on the GPD, we evaluate covariates which affect the number of fatalities aggregated over all hazard types. For this purpose, we evaluate combinations of modes of climate variability and socio-economic indicators as covariates. We find no evidence for a significant direct impact from socio-economic indicators; however, we find significant evidence for the impact from modes of climate variability on the number of fatalities. The important modes of climate variability affecting the number of fatalities are tropical cyclone activity, modes of sea surface temperature and atmospheric teleconnection patterns. This offers the potential of predictability of the number of fatalities given that most of these climate modes are predictable on seasonal to inter-annual time scales.
    Description: Deutsche Forschungsgemeinschaft https://doi.org/10.13039/501100001659
    Description: Deutsche Forschungsgemeinschaft (DE)
    Description: Bundesministerium für Bildung und Forschung https://doi.org/10.13039/501100002347
    Keywords: ddc:551.6 ; Weather ; Disaster ; Global warming ; Extreme events
    Language: English
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  • 3
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    Optimization-based decision-making models for disaster recovery and reconstruction planning of transportation networks (2020)
    Springer Netherlands
    Details
    Publication Date: 2023-06-19
    Description: The purpose of this study is to analyze optimization-based decision-making models for the problem of Disaster Recovery Planning of Transportation Networks (DRPTN). In the past three decades, seminal optimization problems have been structured and solved for the critical and sensitive problem of DRPTN. The extent of our knowledge on the practicality of the methods and performance of results is however limited. To evaluate the applicability of those context-sensitive models in real-world situations, there is a need to examine the conceptual and technical structure behind the existing body of work. To this end, this paper performs a systematic search targeting DRPTN publications. Thereafter, we review the identified literature based on the four phases of the optimization-based decision-making modeling process as problem definition, problem formulation, problem-solving, and model validation. Then, through content analysis and descriptive statistics, we investigate the methodology of studies within each of these phases. Eventually, we detect and discuss four research improvement areas as [1] developing conceptual or systematic decision support in the selection of decision attributes and problem structuring, [2] integrating recovery problems with traffic management models, [3] avoiding uncertainty due to the type of solving algorithms, and [4] reducing subjectivity in the validation process of disaster recovery models. Finally, we provide suggestions as well as possible directions for future research.
    Description: https://dx.doi.org/10.14279/depositonce-9077
    Keywords: ddc:304.28 ; Disaster ; Recovery ; Reconstruction ; Transportation network ; Optimization
    Language: English
    Type: doc-type:article
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