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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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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
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author Zink, Katrin
Kaufmann, Pirmin
Petitpierre, Blaise
Broennimann, Olivier
Guisan, Antoine
Gentilini, Eros
Rotach, Mathias W.
author_facet Zink, Katrin
Kaufmann, Pirmin
Petitpierre, Blaise
Broennimann, Olivier
Guisan, Antoine
Gentilini, Eros
Rotach, Mathias W.
author_sort Zink, Katrin
collection PubMed
description 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.
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spelling pubmed-51795902017-01-06 Numerical ragweed pollen forecasts using different source maps: a comparison for France Zink, Katrin Kaufmann, Pirmin Petitpierre, Blaise Broennimann, Olivier Guisan, Antoine Gentilini, Eros Rotach, Mathias W. Int J Biometeorol Original Paper 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. Springer Berlin Heidelberg 2016-06-18 2017 /pmc/articles/PMC5179590/ /pubmed/27317399 http://dx.doi.org/10.1007/s00484-016-1188-x Text en © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Original Paper
Zink, Katrin
Kaufmann, Pirmin
Petitpierre, Blaise
Broennimann, Olivier
Guisan, Antoine
Gentilini, Eros
Rotach, Mathias W.
Numerical ragweed pollen forecasts using different source maps: a comparison for France
title Numerical ragweed pollen forecasts using different source maps: a comparison for France
title_full Numerical ragweed pollen forecasts using different source maps: a comparison for France
title_fullStr Numerical ragweed pollen forecasts using different source maps: a comparison for France
title_full_unstemmed Numerical ragweed pollen forecasts using different source maps: a comparison for France
title_short Numerical ragweed pollen forecasts using different source maps: a comparison for France
title_sort numerical ragweed pollen forecasts using different source maps: a comparison for france
topic Original Paper
url 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
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