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Essays on Using Climate Information in Disaster and Climate Risk Management

Within the growing concern about the short-term and lasting impacts of natural hazard-based disasters on lives, livelihoods and economies, the ability to manage disaster and climate risk is central to sustainable development. As many recent disasters are directly or indirectly related to weather or climate, and with the expectation that climate variability and change may exacerbate the frequency and/or intensity of related hazards and extreme weather events, climate information has become a critical component of disaster and climate risk management. However, despite its increasing use, as well as money, time and effort into gathering and processing the relevant data, few studies highlight the connection between climate information and development outcomes.

Using a Caribbean lens, this dissertation explores how the awareness, provision and use of weather and climate information, including storm advisories/forecasts and satellite-based rainfall data, may be linked to development outcomes, both in terms of localized impacts of weather- and climate-related events but also within the wider macro-economy. I explore if development outcomes may vary by event day-of-week timing (hypothesizing a relation to possible differences in climate information provision), study whether there may be a human element of improving climate information, and analyze climate information details to best understand its potential use in Caribbean small states. Such research aligns well with ongoing efforts to understand and predict extreme events, as well as connect disasters to socio-economic outcomes, and can also enrich perspectives which concern assessing vulnerability to disasters and recommending solutions to improve risk communication and strengthen disaster preparedness and resilience.

Identiferoai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/d8-2rqg-n386
Date January 2020
CreatorsDookie, Denyse Shivani
Source SetsColumbia University
LanguageEnglish
Detected LanguageEnglish
TypeTheses

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