Predicting the Start of the Birch Pollen Season at London, Derby and Cardiff, United Kingdom, Using a Multiple Regression Model, Based on Data from 1987 to 1997

Adams-Groom, Beverley; Emberlin, Jean; Corden, J.; Millington, W. and Mullins, J. (2002) Predicting the Start of the Birch Pollen Season at London, Derby and Cardiff, United Kingdom, Using a Multiple Regression Model, Based on Data from 1987 to 1997.

View this record at http://eprints.worc.ac.uk/112/
Official URL: 10.1023/A:1020698023134

Abstract

Recent changes in weather in North-West Europe have been reflected in the start dates of pollen seasons. It is therefore necessary to update previous models, such as the one produced by Jones (1995), so that the model will be weighted by current weather patterns. Birch pollen data, collected over a period of eleven years (1987 to 1997 inclusive) from three pollen counting stations in the UK, London, Derby and Cardiff, were analysed to determine the start dates using the Sum75 method. The start dates of the birch pollen seasons of the eleven-year period were then tested for significance against ten-day aggregated variables of temperature and rainfall for each site. The significant variables were entered into multiple regression models until the most valid equation for each site was found. The models were then tested on three years not included in their data sets. The models showed mean differences between actual and predicted start dates, for the eleven years used, of 1.5, 3 and 5 days at Derby, Cardiff and London respectively. For the test years the mean difference was 1, 4.5 and 7.5 days at Derby, Cardiff and London respectively. The most powerful model was for Derby where the corresponding meteorological station is at 0.5 km distance and the weakest was for London where the corresponding meteorological station is much further away at 21 km distance. Weather variables from early February to mid March were found to be the most influential on the start dates of the birch pollen season at the three sites.

Item Type: Article
Keywords: GE Environmental Sciences, QR Microbiology
Members: University of Worcester
Depositing User: ULCC Admin
Date Deposited: 05 Oct 2011 09:18
Last Modified: 08 Nov 2016 13:08
URI: http://collections.crest.ac.uk/id/eprint/1338

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