Event Description
Estimates of the risk of climate change on society, such as the impact of future heat on mortality or agricultural yields, rely on projections from global climate models (GCMs), which are typically bias-corrected and downscaled before use. Future projections of climate impacts are affected by uncertainty in the underlying climate data through multiple pathways, only some of which are regularly accounted for in the literature. This event will present new research on the sensitivity of projections of heat-related mortality to three sources of climate uncertainty: the internal variability stemming from the chaotic nature of the climate system and observational uncertainty arising from imperfect estimates of the true historical climate, both of which are rarely considered in projections of climate impacts, and the impact of recently-discovered systemic biases in climate models in the equatorial Pacific Ocean. This research is based on new ensembles of climate models, including a set of bias-corrected and downscaled Large Ensembles from the CMIP6 generation spanning over 1000 future projections of daily temperature created for this work, and is designed to provide more general guidance on when impact modelers are most likely to have to consider which sources of climate uncertainty to avoid undercounting dangerous tail risks.
Event Speaker
Kevin Schwarzwald, postdoctoral scholar in climate at Columbia University
Event Information
Free and open to the public; registration required for in-person and online attendance. For more information, please visit the event webpage or email Anita Lam-Wright at [email protected].
Hosted by the Columbia Climate School.
