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Volume 17, issue 20 | Copyright
Atmos. Chem. Phys., 17, 12341-12360, 2017
https://doi.org/10.5194/acp-17-12341-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 17 Oct 2017

Research article | 17 Oct 2017

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

Mikhail Sofiev1, Olga Ritenberga2, Roberto Albertini3, Joaquim Arteta4, Jordina Belmonte5,6, Carmi Geller Bernstein7, Maira Bonini8, Sevcan Celenk9, Athanasios Damialis10,11, John Douros12, Hendrik Elbern13, Elmar Friese13, Carmen Galan14, Gilles Oliver15, Ivana Hrga16, Rostislav Kouznetsov1,22, Kai Krajsek17, Donat Magyar18, Jonathan Parmentier4, Matthieu Plu4, Marje Prank1, Lennart Robertson19, Birthe Marie Steensen20, Michel Thibaudon15, Arjo Segers21, Barbara Stepanovich16, Alvaro M. Valdebenito20, Julius Vira1, and Despoina Vokou11 Mikhail Sofiev et al.
  • 1Finnish Meteorological Institute, Erik Palmenin Aukio 1, Helsinki, Finland
  • 2University of Latvia, Latvia
  • 3Department of Medicine and Surgery, University of Parma, Italy
  • 4CNRM UMR 3589, Météo-France/CNRS, Toulouse, France
  • 5Institute of Environmental Sciences and Technology (ICTA), Universitat Autònoma de Barcelona, Spain
  • 6Depatment of Animal Biology, Plant Biology and Ecology, Universitat Autònoma de Barcelona, Spain
  • 7Sheba Medical Center, Ramat Gan Zabludowicz Center for Autoimmune Diseases, Israel
  • 8Agenzia Tutela della Salute della Città Metropolitana di Milano/LHA ATS Città Metropolitana Milano, Italy
  • 9Biology department, Uludag University, Turkey
  • 10Chair and Institute of Environmental Medicine, UNIKA-T, Technical University of Munich and Helmholtz Zentrum München – German Research Center for Environmental Health, Augsburg, Germany
  • 11Department of Ecology, School of Biology, Aristotle University of Thessaloniki, Greece
  • 12Royal Netherlands Meteorological Institute, De Bilt, the Netherlands
  • 13Rhenish Institute for Environmental Research at the University of Cologne, Germany
  • 14Dpto. Botánica, Ecología y Fisiol. Vegetal, University of Cordoba, Spain
  • 15RNSA, Brussieu, France
  • 16Andrija Stampar Teaching Institute of Public Health, Croatia
  • 17Institute of Energy and Climate Research (IEK-8), Forschungszentrum Jülich, Germany
  • 18National Centre of Public Health, Hungary
  • 19Swedish Meteorological and Hydrological Institute SMHI, Sweden
  • 20MET Norway
  • 21TNO, the Netherlands
  • 22IAPh, Russian Academy of Sciences, Moscow, Russia

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.

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This work presents the features and evaluates the quality of the Copernicus Atmospheric Monitoring Service forecasts of olive pollen distribution in Europe. It is shown that the models can predict the main features of the observed pollen distribution but have more difficulties in capturing the season start and end, which appeared shifted by a few days. We also demonstrated that the combined use of model predictions with up-to-date measurements (data fusion) can strongly improve the results.
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