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This research investigates how temperature and rainfall affect pollen seasons, suggesting improved allergy forecasts.
Prediction of climate change and airborne pollen concentrations is essential for understanding allergenic risks from aeroallergens. Temperature and rainfall influence the main pollen season (MPS) both before and during the season. Temperature influences the MPS start (MPSS), while rainfall affects the seasonal pollen integral (SPIn). Improving understanding of these relationships enables accurate pollen forecasts for allergy prevention, public health preparedness, and environmental health policies. The study investigates the impact of rainfall before pollen release using the Dry Days Since the Last Rain (DDSLR) method and defines the role of temperature, chilling, and forcing requirements in predicting the MPSS for Quercus and Cupressaceae in Córdoba (Spain) and Tulsa (Oklahoma, USA). Three approaches combining chilling and forcing heat thresholds were applied. All used Growing Degree Days (GDD°) to calculate forcing but differed in chilling calculation: chilling units based on defined thresholds, accumulative chilling temperature, and omitted chilling calculations altogether. The results show that Quercus MPSS occurred in mid-to-late March at both sites. Cupressaceae exhibited greater regional variation. DDSLR effectively predicted the main pollen season end (MPSE) in Córdoba and the SPIn of Cupressaceae in Tulsa (Oklahoma, USA), indicating regional differences in rainfall influence. The chilling threshold was 0 °C in both sites, while forcing thresholds varied by region and species. Methods excluding chilling showed better MPSS prediction. These findings highlight the value of rainfall and temperature in pollen forecasts. Improved models support the development of targeted allergy forecasts and risk management and public health planning in a changing climate.
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Helfman-Hertzog et al. (2026) studied this question.
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