This project will investigate temperature-related climate exposures and mortality in Sweden and Europe, with a strong focus on processing large-scale climate forecasting and climate model data. The work will involve repeated downloading, extraction, harmonisation, and processing of high-resolution gridded climate datasets from multiple models, scenarios, time periods, and ensemble members. Raw climate files will be transformed into analysis-ready exposure indicators, including daily temperature measures, heatwaves, cold spells, and lagged exposure variables. A key component will be calculating population-weighted mean climate exposures for Swedish counties and European regions by combining gridded climate data with population distribution and regional boundary files. This requires substantial computation, storage, and parallel processing because the workflow must be repeated across many years, regions, and climate datasets. Access to Tetralith is essential for efficient handling of large NetCDF files, automated download and extraction pipelines, spatial processing, and preparation of harmonised exposure datasets for mortality analyses. The project will produce a reproducible climate-data processing pipeline and population-weighted climate exposure indicators to support climate-health risk assessment and public health preparedness.