Evaluate the historical performance and future projections of compound heatwave and drought (CHD) extremes across the contiguous United States using CMIP6 global climate models, providing insights for regional adaptation strategies in response to
The objective of this study is to explore and analyze the spatial patterning of sociodemographic disparities in extreme heat exposure across multiple scales within the Conterminous United States (CONUS).
Important insights into many data science problems that are traditionally analyzed via statistical models can be obtained by re-formulating and evaluating within a large-scale optimization framework.
Spatial optimization seeks optimal allocation or arrangement of spatial units under constraints such as distance, adjacency, contiguity, and pattern. Evolutionary Algorithms (EAs) are well-known optimization heuristics.