NH035-04
Assessment of Tropical Cyclone Wind-Related Risks to Wellbeing in the Philippines

Tuesday, 15 December 2020: 19:20
Virtual
Jane Wilson Baldwin, Lamont-Doherty Earth Observatory, Palisades, NY, United States, Suzana J Camargo, Lamont-Doherty Earth Observat., Palisades, NY, United States, Adam H Sobel, Columbia University, Department of Applied Physics and Applied Mathematics, New York, NY, United States, Chia-Ying Lee, Lamont-Doherty Earth Observatory, Columbia University, Palisades, NY, United States, Brian James Walsh, World Bank, Washington, United States and Stephane Hallegatte, World Bank, Washington, DC, United States
Abstract:
Traditionally, tropical cyclone (TC) risks have been framed as potential asset losses. Unfortunately, this method does not accurately reflect impacts to health and wellbeing across the income distribution (i.e., a $10 reduction in consumption caused by an asset loss is much more impactful for a poor than rich household). Here, we pair state-of-the-art TC hazard and economic modeling methods to calculate risks to wellbeing from TCs, better reflecting risks across the income distribution. Given limitations of the observed record of tropical cyclones, we employ the statistical-dynamical Columbia tropical cyclone Hazard model (CHaz) to model land-falling TC hazards in the Philippines. We determine exposed value on land via the WorldPop population dataset normalized by country-level economic performance values. Potential present-day tropical cyclones from CHaz are flown over this map of exposed value and modified by vulnerability curves to determine traditional asset losses. Finally, these asset losses are modified using machinery developed in the World Bank’s Unbreakable report to estimate reductions in consumption and wellbeing from TC wind hazards. In particular, data from the global Family Income & Expenditure Survey is utilized to transform asset losses to consumption and wellbeing losses. We will present revised maps of tropical cyclone wind-related risks, differences between asset losses and wellbeing losses highlighted by this modeling framework, and sensitivity of these results to different assumptions especially vulnerability curves. We will conclude by discussing future applications and extensions of this work, including risk assessment across the globe.