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

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...

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Detalles Bibliográficos
Autores principales: Zink, Katrin, Kaufmann, Pirmin, Petitpierre, Blaise, Broennimann, Olivier, Guisan, Antoine, Gentilini, Eros, Rotach, Mathias W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5179590/
https://www.ncbi.nlm.nih.gov/pubmed/27317399
http://dx.doi.org/10.1007/s00484-016-1188-x
Descripción
Sumario: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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00484-016-1188-x) contains supplementary material, which is available to authorized users.