A statistical model for predicting the inter-annual variability of birch pollen abundance in Northern and North-Eastern Europe

• The paper suggests a methodology for predicting next-year seasonal pollen index (SPI, a sum of daily-mean pollen concentrations) over large regions and demonstrates its performance for birch in Northern and North-Eastern Europe. A statistical 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 in Europe, where the observed SPI exhibits similar patterns of the multi-annual variability. We built the model for the northern cluster of stations, which covers Finland, Sweden, Baltic States, part of Belarus, and, probably, Russia and Norway, where the lack of data did not allow for conclusive analysis. The constructed model was capable of predicting the SPI with correlation coefficient reaching up to 0.9 for some stations, odds ratio is infinitely high for 50% of sites inside the region and the fraction of prediction falling within 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. © 2017 Elsevier B.V.

Ämnesord

NATURVETENSKAP  -- Geovetenskap och miljövetenskap (hsv//swe)

NATURAL SCIENCES  -- Earth and Related Environmental Sciences (hsv//eng)

NATURVETENSKAP  -- Biologi -- Annan biologi (hsv//swe)

NATURAL SCIENCES  -- Biological Sciences -- Other Biological Topics (hsv//eng)

Nyckelord

Birch pollen

Inter-annual variability

Pollen forecasting

Seasonal pollen index

Cluster analysis

Annual variability

Biological characteristic

Correlation coefficient

Interannual variability

Pollen indexes

Similar pattern

Statistical modeling

Forecasting

Seasonal pollen index

Man and the environment

Publikations- och innehållstyp

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