Neiland's Choice

Catalogue for an exhibition with works selected exclusively by Brendan Neiland. Neiland, who attended the Birmingham College of Art and the Royal College of Art, London during the 1960s, has selected works from a range of artists including: Val Archer, Sarah Armstrong-Jones, Sir Peter Blake, Simon Burton, Grace Erskine Crum, Brad Faine, James Fisher, Martin Fuller, Christian Furr, Annabel Gault, Jason Gibilaro, Hugh Gilbert, Michael Harrison, David Hepher, Patrick Hughes, Andrzej Jackowski, David Mach, Danny Markey, Terry New, William Packer, Tom Phillips (RA), Donald Smith, Justine Smith, Steve Thomas, John Wilkins

Constructing a 7-day Ahead Forecast Model for Grass Pollen at North London, United Kingdom

A number of media outlets now issue medium-range (~7 day) weather forecasts on a regular basis. It is therefore logical that aerobiologists should attempt to produce medium-range forecasts for allergenic pollen that cover the same time period as the weather forecasts. The objective of this study is to construct a medium-range (< 7 day) forecast model for grass pollen at north London. The forecast models were produced using regression analysis based on grass pollen and meteorological data from 1990-1999 and tested on data from 2000 and 2002. The modelling process was improved by dividing the grass pollen season into three periods; the pre-peak, peak and post peak periods of grass pollen release. The forecast consisted of five regression models. Two simple linear regression models predicting the start and end date of the peak period, and three multiple regression models forecasting daily average grass pollen counts in the pre-peak, peak and post-peak periods. Overall the forecast models achieved 62% accuracy in 2000 and 47% in 2002, reflecting the fact that the 2002 grass pollen season was of a higher magnitude than any of the other seasons included in the analysis. This study has the potential to make a notable contribution to the field of aerobiology. Winter averages of the North Atlantic Oscillation were used to predict certain characteristics of the grass pollen season, which presents an important advance in aerobiological work. The ability to predict allergenic pollen counts for a period between five and seven days will benefit allergy sufferers. Furthermore, medium-range forecasts for allergenic pollen will be of assistance to the medical profession, including allergists planning treatment and physicians scheduling clinical trials.