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A statistical model for predicting the inter-annual variability of birchpollen abundance in Northern and North-Eastern Europe
University of Latvia Faculty of Geography and Earth Sciences.
Finnish Meteorological Institute.
Finnish Meteorological Institute.
Unit of Aerobiology, University of Turku.
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2018 (English)In: Science of the Total Environment, ISSN 0048-9697, E-ISSN 1879-1026, Vol. 615, p. 228-239Article in journal (Refereed) Published
Abstract [en]

The paper suggests amethodology for predicting next-year seasonal pollen index (SPI, a sumof daily-mean pollen concentrations)over large regions and demonstrates its performance for birch in Northern andNorth-Eastern Europe. Astatistical model is constructed using meteorological, geophysical and biological characteristics of the previous year).A cluster analysis of multi-annual data of European Aeroallergen Network (EAN) revealed several large regions inEurope, where the observed SPI exhibits similar patterns of the multi-annual variability.We built the model for thenorthern cluster of stations, which covers Finland, Sweden, Baltic States, part of Belarus, and, probably, Russia andNorway,where the lack of data did not allow for conclusive analysis. The constructed modelwas capable of predictingthe SPI with correlation coefficient reaching up to 0.9 for somestations, odds ratio is infinitely high for 50% of sites insidethe region and the fraction of prediction fallingwithin factor of 2 from observations, stays within 40–70%. In particular,model successfully reproduced both the bi-annual cycle of the SPI and years when this cycle breaks down.

Place, publisher, year, edition, pages
Elsevier, 2018. Vol. 615, p. 228-239
Keywords [en]
Seasonal pollen index, Birch pollen, Inter-annual variability, Pollen forecasting
National Category
Other Biological Topics
Research subject
Man and the environment
Identifiers
URN: urn:nbn:se:nrm:diva-2532DOI: 10.1016/j.scitotenv.2017.09.061OAI: oai:DiVA.org:nrm-2532DiVA, id: diva2:1164890
Available from: 2017-12-12 Created: 2017-12-12 Last updated: 2018-02-26Bibliographically approved

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Ekebom, Agneta
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