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Title: Modelling extreme climatic events and their economic impacts : a risk management application to China's rural sector
Author: Chavez, Eric
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2013
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Many economic systems present high levels of vulnerability to weather variability and extreme weather events. On the other hand, the statistics of weather, including of its extreme events, are changing slowly in time. In fact, an increasing body of scientic evidence, derived from both observations and model simulations, indicates that the climate system never was nor is it likely to ever be statistically stationary. This research proposes, therefore, a methodological framework to characterize the cascading climate-toeconomy risk pro les of economic systems under weather variability, subject to di erent global warming scenarios. A weather-index and machine learning-based methodology is introduced to encode and characterize economic systems vulnerability to weather variability. This methodology, in turn, is enclosed in a weather-within-climate" stochastic downscaling approach, in order to quantify the interaction of low- and high-frequency climate variability and project risk pro les in future climate scenarios. Probabilistic, weatherdriven, physical-loss risk pro les are then used to model supply shock-driven economic losses, both direct and indirect, in a particular region or country. Given the acute vulnerability of its rural population to weather variability and global warming, this methodology is applied to the study of the risk pro le of weather-driven loss in the rural sector in a developing country, China. Climate-to-economy risk pro les are developed for weather-driven losses of several staple crops, subject to di erent technological and climate scenarios. Implications for the design of risk management policy mixes are then discussed. Finally, a three pillars"-based risk management strategy is proposed to create an enabling environment for continuous rural development and food security.
Supervisor: Conway, Gordon ; Makuch, Zen Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available