Influence of the North Atlantic Oscillation on Grass Pollen Counts in Europe

Relationships between temporal variations in the North Atlantic Oscillation (NAO) and grass pollen counts at 13 sites in Europe, ranging from Córdoba in the South-West and Turku in the North-East, were studied in order to determine spatial differences in the amount of influence exerted by the NAO on the timing and magnitude of grass pollen seasons. There were a number of significant (p<0.05) relationships between the NAO and start dates of the grass pollen season at the 13 pollen-monitoring sites. The strongest associations were generally recorded near to the Atlantic coast. Several significant correlations also existed between winter averages of the NAO and grass pollen season severity. Traditional methods for predicting the start or magnitude of grass pollen seasons have centred on the use of local meteorological observations, but this study has shown the importance of considering large-scale patterns of climate variability like the NAO.

Long-term and Short-term Forecast Models for Poaceae (Grass) Pollen in Poznan, Poland, Constructed Using Regression Analysis

Airborne concentrations of Poaceae pollen have been monitored in Poznań for more than ten years and the length of the dataset is now considered sufficient for statistical analysis. The objective of this paper is to produce long-range forecasts that predict certain characteristics of the grass pollen season (such as the start, peak and end dates of the grass pollen season) as well as short-term forecasts that predict daily variations in grass pollen counts for the next day or next few days throughout the main grass pollen season. The method of forecasting was regression analysis. Correlation analysis was used to examine the relationship between grass pollen counts and the factors that affect its production, release and dispersal. The models were constructed with data from 1994-2004 and tested on data from 2005 and 2006. The forecast models predicted the start of the grass pollen season to within 2 days and achieved 61% and 70% accuracy on a scale of 1-4 when forecasting variations in daily grass pollen counts in 2005 and 2006 respectively. This study has emphasised how important the weather during the few weeks or months preceding pollination is to grass pollen production, and draws attention to the importance of considering large-scale patterns of climate variability (indices of the North Atlantic Oscillation) when constructing forecast models for allergenic pollen.