Online coupled mesoscale meteorology atmospheric chemistry models have undergone a rapid evolution in recent years. Although mainly developed by the air quality modelling community, these models are also of interest for numerical weather prediction and regional climate modelling as they can consider not only the effects of meteorology on air quality, but also the potentially important effects of atmospheric composition on weather. Two ways of online coupling can be distinguished: online integrated and online access coupling. Online integrated models simulate meteorology and chemistry over the same grid in one model using one main time step for integration. Online access models use independent meteorology and chemistry modules that might even have different grids, but exchange meteorology and chemistry data on a regular and frequent basis. This article offers a comprehensive review of the current research status of online coupled meteorology and atmospheric chemistry modelling within Europe. Eighteen regional online coupled models developed or being used in Europe are described and compared. Topics discussed include a survey of processes relevant to the interactions between atmospheric physics, dynamics and composition; a brief overview of existing online mesoscale models and European model developments; an analysis on how feedback processes are treated in these models; numerical issues associated with coupled models; and several case studies and model performance evaluation methods. Finally, this article highlights selected scientific issues and emerging challenges that require proper consideration to improve the reliability and usability of these models for the three scientific communities: air quality, numerical meteorology modelling (including weather prediction) and climate modelling. This review will be of particular interest to model developers and users in all three fields as it presents a synthesis of scientific progress and provides recommendations for future research directions and priorities in the development, application and evaluation of online coupled models.

Hay fever patients can be helped in managing their symptoms by predicting the severity of the upcoming grass pollen seasons.

The Environment – High Resolution Limited Area Model (Enviro-HIRLAM) is developed as a fully online integrated numerical weather prediction (NWP) and atmospheric chemical transport (ACT) model for research and forecasting of joint meteorological, chemical and biological weather. The integrated modelling system is developed by the Danish Meteorological Institute (DMI) in collaboration with several European universities. It is the baseline system in the HIRLAM Chemical Branch and used in several countries and different applications. The development was initiated at DMI more than 15 years ago. The model is based on the HIRLAM NWP model with online integrated pollutant transport and dispersion, chemistry, aerosol dynamics, deposition and atmospheric composition feedbacks. To make the model suitable for chemical weather forecasting in urban areas, the meteorological part was improved by implementation of urban parameterisations. The dynamical core was improved by implementing a locally mass-conserving semi-Lagrangian numerical advection scheme, which improves forecast accuracy and model performance. The current version (7.2), in comparison with previous versions, has a more advanced and cost-efficient chemistry, aerosol multi-compound approach, aerosol feedbacks (direct and semi-direct) on radiation and (first and second indirect effects) on cloud microphysics. Since 2004, the Enviro-HIRLAM has been used for different studies, including operational pollen forecasting for Denmark since 2009 and operational forecasting atmospheric composition with downscaling for China since 2017. Following the main research and development strategy, further model developments will be extended towards the new NWP platform – HARMONIE. Different aspects of online coupling methodology, research strategy and possible applications of the modelling system, and fit-for-purpose model configurations for the meteorological and air quality communities are discussed.

Information about distribution of pollen sources, i.e. their presence and abundance in a specific region, is important, especially when atmospheric transport models are applied to forecast pollen concentrations. The goal of this study is to evaluate three pollen source maps using an atmospheric transport model and study the effect on the model results by combining these source maps with pollen data. Here we evaluate three maps for the birch taxon: (1) a map derived by combining a land cover data and forest inventory, (2) a map obtained from land cover data and calibrated using model simulations and pollen observations, and (3) a statistical map resulting from analysis of forest inventory and forest plot data. The maps were introduced to the Enviro-HIRLAM (Environment – High Resolution Limited Area Model) as input data to simulate birch pollen concentrations over Europe for the birch pollen season 2006. A total of 18 model runs were performed using each of the selected maps in turn with and without calibration with observed pollen data from 2006. The model results were compared with the pollen observation data at 12 measurement sites located in Finland, Denmark, and Russia. We show that calibration of the maps using pollen observations significantly improved the model performance for all three maps. The findings also indicate the large sensitivity of the model results to the source maps and agree well with other studies on birch showing that pollen or hybrid-based source maps provide the best model performance. This study highlights the importance of including pollen data in the production of source maps for pollen dispersion modelling and for exposure studies.

Episodes with high air pollution and large amounts of aeroallergens expose sensitive individuals to a health damaging cocktail of atmospheric particles. Particulate matter (PM) affects the radiative balance and atmospheric dynamics, hence affecting concentrations of pollutants. The aim of the study is to estimate feedback between meteorology and particles on concentrations of aeroallergens using an extended version of the atmospheric model WRF-Chem. The extension, originally designed for PM and dust, concerns common aeroallergens. We study a birch pollen episode coinciding with an air pollution event containing Saharan dust (late March to early April 2014), using the model results, pollen records from Southern UK and vertical profiles of meteorological observations. During the episode, increased concentrations of birch pollen were calculated over the European continent, causing plumes transported towards the UK. The arrival of these plumes matched well with observations. The lowest parts of the atmospheric boundary layer demonstrate a vertical profile that favours long distance transport, while the pollen record shows pollen types that typically flower at another time. The model calculations show that feedback between meteorology and particles changes pollen concentrations by ±30% and in some cases up to 100%. The atmospheric conditions favoured meteorological feedback mechanisms that changed long distance transport of air pollution and aeroallergens.