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Abstract Allergic rhinitis, often caused by allergies from grass, tree or weed pollen, affects a large proportion of the UK population, and leads to significant costs to the National Health Service. The existing UK pollen forecast, produced manually, provides a single daily level for each of 16 regions. We present here an implementation of a pollen modelling capability within the Met Office Numerical Atmospheric-dispersion Modelling Environment (NAME) dispersion model. This will provide taxa-specific outputs at high temporal (hourly) and spatial (5 km) resolutions, which will eventually transform the level of detail in a future forecast system and therefore be of significantly greater use to the public and health professionals for managing pollen risks. Initial developments are for the three taxa which are the most allergenic across the UK population: birch, oak and grass. Pollen grain emission maps have been estimated using species distribution modelling methods. The timing of the pollen season is controlled within NAME by an accumulated temperature sum parametrisation, while pollen release is estimated with short term meteorological dependencies based on precipitation, wind speed and the vapour pressure deficit, along with a diurnal cycle. We show that, when run in hindcast mode, NAME performance (verified against pollen observations) is comparable with the Copernicus Atmosphere Monitoring Service ensemble median prediction for birch and grass. Evaluation of NAME for simulating the UK Daily Pollen Index shows an improved correlation coefficient compared to the existing manual forecast.
Neal et al. (Mon,) studied this question.
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