Multi-model ensemble simulations of olive pollen distribution in Europe in 2014: current status and outlook

Abstract

Abstract. The paper presents the first modelling experiment of the European-scale olive pollen dispersion, analyses the quality of the predictions, and outlines the research needs. A 6-model strong ensemble of Copernicus Atmospheric Monitoring Service (CAMS) was run throughout the olive season of 2014, computing the olive pollen distribution. The simulations have been compared with observations in eight countries, which are members of the European Aeroallergen Network (EAN). Analysis was performed for individual models, the ensemble mean and median, and for a dynamically optimised combination of the ensemble members obtained via fusion of the model predictions with observations. The models, generally reproducing the olive season of 2014, showed noticeable deviations from both observations and each other. In particular, the season was reported to start too early by 8 days, but for some models the error mounted to almost 2 weeks. For the end of the season, the disagreement between the models and the observations varied from a nearly perfect match up to 2 weeks too late. A series of sensitivity studies carried out to understand the origin of the disagreements revealed the crucial role of ambient temperature and consistency of its representation by the meteorological models and heat-sum-based phenological model. In particular, a simple correction to the heat-sum threshold eliminated the shift of the start of the season but its validity in other years remains to be checked. The short-term features of the concentration time series were reproduced better, suggesting that the precipitation events and cold/warm spells, as well as the large-scale transport, were represented rather well. Ensemble averaging led to more robust results. The best skill scores were obtained with data fusion, which used the previous days' observations to identify the optimal weighting coefficients of the individual model forecasts. Such combinations were tested for the forecasting period up to 4 days and shown to remain nearly optimal throughout the whole period.

Do atmospheric events explain the arrival of an invasive ladybird (Harmonia axyridis) in the UK?

“…It is currently used as the official air quality forecasting tool in Finland [35] and is used operationally amongst other CTMs e.g., in the Copernicus Atmosphere Monitoring Service (CAMS) http://macc-raq-op.meteo.fr/, WMO Sand and Dust Storm Warning Advisory and Assessment System (SDS-WAS, North Africa and Europe) https://sds-was.aemet.es and Air quality forecast for China (MarcoPolo-Panda) http://www.marcopolo-panda.eu/forecast/. SILAM gives similar results to other CTMs e.g., [52][53][54][55].…”

A demonstration project of Global Alliance against Chronic Respiratory Diseases: Prediction of interactions between air pollution and allergen exposure—the Mobile Airways Sentinel NetworK-Impact of air POLLution on Asthma and Rhinitis approach

“…Accounting for the pollen release from inflorescences and subsequent transport in the atmosphere requires numerical models, which compute the whole lifecycle of pollen: maturation and presentation, release into the air, atmospheric transport and transformations, and deposition. [ 50 , 55 , 56 ] Such models currently can predict concentrations of up to six pollen types for up to 5 days for the whole Europe ( http://atmosphere.copernicus.eu , http://silam.fmi.fi ). The models COSMO-ART for Central Europe ( http://www.meteoswiss.ch ) and System for Integrated modeLling of Atmospheric coMposition (SILAM) for Northern Europe ( http://silam.fmi.fi ) perform high-resolution forecasts with grid-cell size of 1 and 2.5 km, respectively.…”

“…In Europe, an ensemble of continental-scale pollen models has been developed within the scope of Copernicus Atmospheric Monitoring Service (CAMS) ( http://atmosphere.copernicus.eu ), which has been shown to provide more robust predictions than individual models. [ 55 ] The pollen service is a part of the CAMS European AQ forecasting services. [ 57 ] CAMS AQ forecast is generated for up to 5 days over the globe and up to 4 days for Europe.…”

“…SILAM performs operational pollen forecasts for six pollen species (alder, birch, grass, mugwort, olive, ragweed), trial forecasts for insects (aphids), and AQ forecasts for the globe, Europe and Asia, AQ hindcast for the previous day, as well as re-analysis of AQ from 1950 onwards. A variety of the data assimilation algorithms for pollen are under development, [ 50 , 55 , 59 , 60 ] including the use of the real-life symptom data obtained by the MASK-Air app. [ 61 ]…”

Ensemble forecasts of air quality in eastern China – Part 1: Model description and implementation of the MarcoPolo–Panda prediction system, version 1

“…Building an ensemble of models is an attractive approach to forecast air quality because the inter-model variability provides insight on the robustness of the results or conversely on their uncertainties (McKeen et al, 2005;Vautard et al, 2006;Solazzo et al, 2012). Further, the composite products have usually better overall performance than the results produced by individual systems (McKeen et al, 2005;Galmarini et al, 2013;Riccio et al, 2007;Sofiev et al, , 2017.…”