A changing climate may portend increasing disaster risk across many countries and business enterprises. While many aspects of the hazards, exposure and vulnerability that constitute disaster risk have been well studied, several challenges remain. A critical aspect that needs to be addressed is the rapid response and recovery from a climate-induced disaster. Often, governments need to allocate funds or design financial instruments that can be activated rapidly to mobilize response and recovery. The proposed research addresses this general problem, focusing on a few selected issues. First, there is the question of how to rapidly detect and index a climate hazard, such as a flood, given proxy remote sensing data on attributes that may be closely related to the hazard. The second is the need to robustly estimate the return periods of extreme climate hazards, and the temporal changes in their projected frequency of occurrence using multi-century climate proxies. The third is the need to assess the potential losses from the event, including the disruption of services, and cascading failure of interlinked infrastructure elements. The fourth is the impact on global and regional supply chains that are induced by the event, and the associated financial impact. For each of these cases, it is useful to ground an analysis and the development of an approach around real world examples, which can then collectively inform a strategy for emergency response. Here, this will be pursued through an analysis of flooding in the Philippines, livestock mortality induced by drought and freezing winter in Mongolia, Hurricane Sandy impacts in New York, supply chain impacts in Thailand, and an end to end analysis of the potential process using data from Thailand and Bangladesh. Collectively, these analyses are expected to inform climate hazard planning and securitization processes with broad applicability at a regional to national level.
Identifer | oai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/D8QN7K6G |
Date | January 2018 |
Creators | Haraguchi, Masahiko |
Source Sets | Columbia University |
Language | English |
Detected Language | English |
Type | Theses |
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