Climate Change Spaces (CliCS) – Novel Approach to Evaluate Coupled Land-Climate Changes on Population and Health Dynamics

William Pan, Duke University

Climate change and disruption of natural systems are impacting human populations in a variety of ways, from food insecurity and health risks to livelihood decisions. However, attribution of climate change risks is often obfuscated for several reasons, including modeling climate data as non-stochastic, misclassifying climate change (i.e., not using definitions from climate scientists), and decoupling land and climate change. We propose a novel approach that can accurately identify locations experiencing both independent or coupled land-climate changes that can more accurately attribute environmental change to demographic and health outcomes. Our approach combines multiple, 30+ year, climate and land cover time series data, including gridded ERA5, CHIRPS, and Land Data Assimilation Data, among others, and applies a spatio-temporal clustering algorithm to define Climate Change Spaces (CLICS) across 40+ climate, hydrology, and land cover parameters. CLICS are areas with one or more environmental parameters significantly changing over a 30-year period. We expect multiple CLICS to be identified within regions (i.e., Precipitation-CLICS, Temperature-CLICS, Forest-CLICS, etc.), that will be merged with demographic and health data to evaluate whether CLICS explain differences in infectious disease, birth rates, and mortality. Analysis will be conducted initially in Latin America where the team has been working since the 1990s.

Keywords: Population, Environment, and Climate Change, Data and Methods, Population and Development, Health and Morbidity

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