Smith, Matthew and Emberlin, Jean (2006) A 30-Day-Ahead Forecast Model for Grass Pollen in North London, United Kingdom. International Journal of Biometeorology, 50 (4). pp. 233-242. ISSN Print: 0020-7128 Online:1432-1254Full text not available from this repository.
A 30-day ahead forecast method has been developed for grass pollen at 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 21st May to 8th 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 1961-1999 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 one to four; and 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 one to four, 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.
The original publication is available at www.springerlink.com
Originally deposited as National Pollen and Aerobiology Research Unit (NPARU)
|Uncontrolled Keywords:||aerobiology, grass pollen counts, London, forecast models, North Atlantic Oscillation|
|Subjects:||G Geography. Anthropology. Recreation > GE Environmental Sciences
Q Science > QR Microbiology > QR180 Immunology
|Divisions:||Academic Departments > Institute of Science and the Environment|
|Depositing User:||Matthew Smith|
|Date Deposited:||12 Jul 2007 15:08|
|Last Modified:||15 Feb 2016 16:13|
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