Representativeness of point-wise phenological Betula data collected in different parts of Europe

Peer reviewe

Numerical modelling of the pest insect migration in the atmosphere

201

Early warning System for Bird-Cherry Oat Aphid Migrations based on the Atmospheric Dispersion Model SILAM

201

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

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

MACC regional multi-model ensemble simulations of birch pollen dispersion in Europe

This paper presents the first ensemble modelling experiment in relation to birch pollen in Europe. The seven-model European ensemble of MACC-ENS, tested in trial simulations over the flowering season of 2010, was run through the flowering season of 2013. The simulations have been compared with observations in 11 countries, all members of the European Aeroallergen Network, for both individual models and the ensemble mean and median. It is shown that the models successfully reproduced the timing of the very late season of 2013, generally within a couple of days from the observed start of the season. The end of the season was generally predicted later than observed, by 5 days or more, which is a known feature of the source term used in the study. Absolute pollen concentrations during the season were somewhat underestimated in the southern part of the birch habitat. In the northern part of Europe, a record-low pollen season was strongly overestimated by all models. The median of the multi-model ensemble demonstrated robust performance, successfully eliminating the impact of outliers, which was particularly useful since for most models this was the first experience of pollen forecasting

The Urban Climate Services URCLIM project

International audienc