International Journal of Biometeorology

, Volume 48, Issue 2, pp 65–73

Two statistical approaches to forecasting the start and duration of the pollen season of Ambrosia in the area of Lyon (France)

  • Mohamed Laaidi
  • Michel Thibaudon
  • Jean-Pierre Besancenot
Original Article

DOI: 10.1007/s00484-003-0182-2

Cite this article as:
Laaidi, M., Thibaudon, M. & Besancenot, JP. Int J Biometeorol (2003) 48: 65. doi:10.1007/s00484-003-0182-2

Abstract

The aim of the present study was to forecast the start and duration of the pollen season of Ambrosia from meteorological data, in order to provide early information to allergists and allergic people. We used the airborne pollen data from Lyon (France), sampled using a Hirst trap from 1987 to 1999, and the meteorological data for the same period: air temperature (minimal, maximal, and average), rainfall, relative humidity, sunshine duration and soil temperature. Two forecasting models were used, one summing the temperatures and the other making use of a multiple regression on 10-day or monthly meteorological parameters. The start of the pollen season was predicted with both methods, results being more accurate with the regression (the errors between the predicted and the observed SDP ranging from 0 to 3 days). The duration of the pollen season was predicted by a regression model, errors ranging from 0 to 7 days. The models were later tested with satisfactory results from 2 additional years (2000 and 2001). Such forecasting models are helpful for allergic people, who have to begin their anti-allergic treatment before the start of the pollen season and not when the symptoms have appeared, since a preventive treatment is more efficient than a curative one. The regression allows predictions to be made 3–5 weeks in advance and so it is of particular interest. The forecasts will be broadcast on the Internet.

Keywords

Ambrosia Pollen Forecast Meteorology 

Copyright information

© ISB 2003

Authors and Affiliations

  • Mohamed Laaidi
    • 1
  • Michel Thibaudon
    • 2
  • Jean-Pierre Besancenot
    • 1
  1. 1.Climat et Santé, Centre d'Épidémiologie de Population, Faculté de Médecine, BP 87900, 21079 Dijon Cedex, France
  2. 2.Réseau National de Surveillance Aérobiologique (RNSA), La Croix Bayard, 69930 Saint-Clément-les-Places, France

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