Population Exposure to Temperature Extremes in Spain: Integrating High-Resolution Climate and Historical Population Data

Dariya Ordanovich , Spanish National Research Council
Ana Casanueva, Dept. Applied Mathematics and Computer Sciences, Universidad de Cantabria
Diego Ramiro, Institute of Economics, Geography and Demography, Center for Human and Social Sciences, Spanish National Research Council

This work develops a standardized set of population-weighted exposure indicators for administrative units in Spain, designed to align gridded climate data with official statistics. The workflow links daily climate fields with high-resolution population rasters anchored to census years and reconciles aggregates to National Institute of Statistics (INE) totals through time-varying scaling. Population interpolation between anchors is treated as the required intermediate step to align population and climate on a daily basis; administrative labels are attached to environmental grid cells using population shares with a near-tie safeguard, and nominally empty cells fall back to geometric overlap. Building on this alignment, the indicators comprise: (i) core exposure (population-weighted minimum, maximum, mean, and apparent temperature, plus total population); (ii) absolute extremes in populated cells; (iii) threshold counts such as very hot days, freezing conditions, and tropical nights; (iv) population-weighted degree-day summaries; (v) extreme-event metrics for heatwaves and coldwaves based on concurrent exceedance of cell-specific percentiles using a 1971-2000 baseline, reporting population affected, daytime and nighttime magnitude, overall magnitude, event days, and episodes; and (vi) exposure variability within units. Computation is implemented with ERA5-Land and a Spain-wide 2.5 km daily observational grid (1961-2022+) to enable cross-source comparability. All inputs and outputs are versioned, with provenance for anchors, scaling factors, and boundary harmonization. The expected outcome is a set of comparable, administratively aligned, and policy-relevant indicators that represent conditions experienced by residents more accurately than simple area averages, particularly in urban, coastal, and complex orographic contexts.

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 Presented in Session P8. Demographic Trends, History, Data and Methods