Comparison of weather station and climate reanalysis data for modelling temperature-related mortality

BACKGROUND: Epidemiological analyses of health risks associated with non-optimal temperature are traditionally based on ground observations from weather stations. Though generally considered representative the actual ambient conditions and individual’s exposure, their broader application in environmental epidemiology is often constrained by inhomogeneous records sparse density meteorological Climate reanalysis represents an alternative option that provide complete spatio-temporal exposure coverage, yet to be systematically explored for suitability assessing temperature-related at a global scale. AIM: The aim study first comprehensive analysis over multiple regions assess most recent generation datasets impact assessments evaluate comparative performance against traditional station-based data. METHODS: We applied well-established time-series quasi-Poisson regression (with distributed lag non-linear models multivariate meta-regression) model location specific temperature-mortality associations, across 612 cities within 39 countries period 1985–2019, covering wide range climates including low- middle-income countries. Briefly, we compared correlation between daily series derived station ERA5-Land/ERA5 reanalysis, then evaluated differences estimated exposure-response functions relationships, finally using fit statistics. RESULTS: Our findings show last ERA5 products compare well observations, similar risk estimates. However, offers some indication lower tropical regions, likely underestimation heat-related excess mortality. CONCLUSIONS: Reanalysis data represent valid source variables epidemiological risk. consistent coverage also makes it attractive quantifying population attributable fractions, indicator important planners policy makers. KEYWORDS: mortality, temperature, ERA5-Land, models.