Climate Driver Choice Fidelity

Background: Predicting the non-linear, spatially divergent public health consequences of various climate change pathways (SSPs) requires robust spatio-temporal modeling beyond simple linear extrapolations.

Question / Future Work: What are the robust limits and trade-offs of using aggregate climate drivers (like summer mean temperature) versus event-based metrics (like heatwave duration/intensity metrics) in time-series forecasting models aimed at predicting future heatwave-related mortality across heterogeneous urban environments?

Why It Matters: Understanding the optimal choice of climate driver—simple aggregates vs. complex event metrics—is crucial for improving the fidelity and interpretability of future climate-health impact assessments.

Evidence: A time-series forecasting framework was applied using summer mean temperature as the primary climate driver to project mortality trajectories through the end of the 21st century.