ORIGINAL PAPER A method to derive vegetation distribution maps for pollen dispersion models using birch as an example A. Pauling & M. W. Rotach & R. Gehrig & B. Clot & Contributors to the European Aeroallergen Network (EAN) Received: 6 June 2011 /Revised: 24 August 2011 /Accepted: 6 September 2011 # ISB 2011 Abstract Detailed knowledge of the spatial distribution of sources is a crucial prerequisite for the application of pollen dispersion models such as, for example, COSMO-ART (COnsortium for Small-scale MOdeling - Aerosols and Reactive Trace gases). However, this input is not available for the allergy-relevant species such as hazel, alder, birch, grass or ragweed. Hence, plant distribution datasets need to be derived from suitable sources. We present an approach to produce such a dataset from existing sources using birch as an example. The basic idea is to construct a birch dataset using a region with good data coverage for calibration and then to extrapolate this relationship to a larger area by using land use classes. We use the Swiss forest inventory (1 km resolution) in combination with a 74-category land use dataset that covers the non-forested areas of Switzerland as well (resolution 100 m). Then we assign birch density categories of 0%, 0.1%, 0.5% and 2.5% to each of the 74 land use categories. The combination of this derived dataset with the birch distribution from the forest inventory yields a fairly accurate birch distribution encompassing entire Switzerland. The land use categories of the Global Land Cover 2000 (GLC2000; Global Land Cover 2000 database, 2003, European Commission, Joint Research Centre; resolution 1 km) are then calibrated with the Swiss dataset in order to derive a Europe-wide birch distribution dataset and aggregated onto the 7 km COSMO-ART grid. This procedure thus assumes that a certain GLC2000 land use category has the same birch density wherever it may occur in Europe. In order to reduce the strict application of this crucial assumption, the birch density distribution as obtained from the previous steps is weighted using the mean Seasonal Pollen Index (SPI; yearly sums of daily pollen concentrations). For future improvement, region- specific birch densities for the GLC2000 categories could be integrated into the mapping procedure. Keywords Vegetation distribution . Birch pollen . Land use data . Forest inventory . Seasonal Pollen Index Introduction Pollen dispersion models represent a helpful tool for pollen forecasters and allergy sufferers. They provide spatially and temporally highly resolved forecasts, which can be used by general practitioners to make diagnosis and to advise their patients. In addition, these forecasts provide useful information for allergy sufferers to reduce the symptoms. In recent years, various pollen dispersion models have been developed (Hidalgo et al. 2002; Sofiev et al. 2006; Schueler and Schlünzen 2006; Helbig et al. 2004; Vogel et al. 2008). Some of these models have been operational now for some years such as the Finnish Emergency Dispersion Modelling System (SILAM; Sofiev et al. 2006). COSMO- ART (COnsortium for Small-scale MOdeling - Aerosols and Reactive Trace gases; Vogel et al. 2009; Helbig et al. 2004) became pre-operational in 2010 in Germany and Switzerland and was used operationally in 2011. A. Pauling (*) : M. W. Rotach : R. Gehrig : B. Clot Federal Office of Meteorology and Climatology MeteoSwiss, Krähbühlstrasse 58, 8044 Zürich, Switzerland e-mail: andreas.pauling@meteoswiss.ch Present Address: M. W. Rotach Institute of Meteorology and Geophysics, University of Innsbruck, Innrain 52, 6020 Innsbruck, Austria Int J Biometeorol DOI 10.1007/s00484-011-0505-7