A 30-day-ahead forecast method has been developed for grass pollen in north London.
The total period of the grass pollen season is covered by eight multiple regression
models, each covering a 10-day period running consecutively from 21 May to 8 August.
This means that three models were used for each 30-day forecast. The forecast models
were produced using grass pollen and environmental data from 1961 to 1999 and tested
on data from 2000 and 2002. Model accuracy was judged in two ways: the number of times
the forecast model was able to successfully predict the severity (relative to the
1961-1999 dataset as a whole) of grass pollen counts in each of the eight forecast
periods on a scale of 1 to 4; the number of times the forecast model was able to predict
whether grass pollen counts were higher or lower than the mean. The models achieved
62.5% accuracy in both assessment years when predicting the relative severity of grass
pollen counts on a scale of 1 to 4, which equates to six of the eight 10-day periods
being forecast correctly. The models attained 87.5% and 100% accuracy in 2000 and
2002, respectively, when predicting whether grass pollen counts would be higher or
lower than the mean. Attempting to predict pollen counts during distinct 10-day periods
throughout the grass pollen season is a novel approach. The models also employed original
methodology in the use of winter averages of the North Atlantic Oscillation to forecast
10-day means of allergenic pollen counts.