Extreme weather, climate-induced events that are episodic (e.g., hurricane, heatwave) or chronic (e.g., sea-level rise, temperature change) in nature, is occurring with increasing frequency and severity. This places a growing and time-sensitive need on the development and implementation of adaptation policies and practices. To motivate adaptive behavior, however, requires the ability to deliver improved risk-informed decision-making capability. At the crux of this challenge is the provision of full and accurate loss and damage accounting of the overall impact of an extreme weather event, enabling the business case to be made for adaptation investment. We define loss and damage as the manifestation of impacts associated with extreme weather that negatively affect human and natural systems. Progress in the development of adequate loss and damage accounting has been hampered by issues, such as discrepancies in conceptual frameworks, problems associated with data quantity and quality, and lack of standardized analysis methodologies. In this paper, we have discussed the conceptual basis for measuring loss and damage, reviewed the state of loss and damage data collection and modeling, and offered a narrative on the future direction of the practice.
Through the framework of SDG 16 we aim to present a model for the creation of strong institutions that may best endure the negative effects of climate change as well as be best suited to bring about positive change in regard to climate issues. The creation of these strong and fair states originates from an emphasis on fair and effective communication across all levels of citizenship and collective political equality to bring about the most desirable outcomes for every individual within the state. SDG Theme: SDG16 – Peace, Justice, and Strong Institutions Type: E-poster
History has shown that occurrences of extreme weather are becoming more frequent and with greater impact, regardless of one’s geographical location. In a risk analysis setting, what will happen, how likely it is to happen, and what are the consequences, are motivating questions searching for answers. To help address these considerations, this study introduced and applied a hybrid simulation model developed for the purpose of improving understanding of the costs of extreme weather events in the form of loss and damage, based on empirical data in the contiguous United States. Model results are encouraging, showing on average a mean cost estimate within 5% of the historical cost. This creates opportunities to improve the accuracy in estimating the expected costs of such events for a specific event type and geographic location. In turn, by having a more credible price point in determining the cost-effectiveness of various infrastructure adaptation strategies, it can help in making the business case for resilience investment.
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