Numerical ragweed pollen forecasts using different source maps: a comparison for France.

Détails

Ressource 1Télécharger: s00484-016-1188-x.pdf (4774.04 [Ko])
Etat: Public
Version: Final published version
ID Serval
serval:BIB_A33C3E640154
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
Numerical ragweed pollen forecasts using different source maps: a comparison for France.
Périodique
International journal of biometeorology
Auteur(s)
Zink K., Kaufmann P., Petitpierre B., Broennimann O., Guisan A., Gentilini E., Rotach M.W.
ISSN
1432-1254 (Electronic)
ISSN-L
0020-7128
Statut éditorial
Publié
Date de publication
01/2017
Peer-reviewed
Oui
Volume
61
Numéro
1
Pages
23-33
Langue
anglais
Notes
Publication types: Journal Article
Publication Status: ppublish
Résumé
One of the key input parameters for numerical pollen forecasts is the distribution of pollen sources. Generally, three different methodologies exist to assemble such distribution maps: (1) plant inventories, (2) land use data in combination with annual pollen counts, and (3) ecological modeling. We have used six exemplary maps for all of these methodologies to study their applicability and usefulness in numerical pollen forecasts. The ragweed pollen season of 2012 in France has been simulated with the numerical weather prediction model COSMO-ART using each of the distribution maps in turn. The simulated pollen concentrations were statistically compared to measured values to derive a ranking of the maps with respect to their performance. Overall, approach (2) resulted in the best correspondence between observed and simulated pollen concentrations for the year 2012. It is shown that maps resulting from ecological modeling that does not include a sophisticated estimation of the plant density have a very low predictive skill. For inventory maps and the maps based on land use data and pollen counts, the results depend very much on the observational site. The use of pollen counts to calibrate the map enhances the performance of the model considerably.

Mots-clé
Air Pollutants/analysis, Allergens/analysis, Antigens, Plant/isolation & purification, Computer Simulation, Environmental Monitoring, Forecasting, France, Models, Theoretical, Plant Extracts/isolation & purification, Reproducibility of Results
Pubmed
Open Access
Oui
Création de la notice
17/02/2017 8:55
Dernière modification de la notice
20/08/2019 15:08
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