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Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
https://doi.org/10.5194/acp-2016-1189
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article
02 Feb 2017
Review status
This discussion paper is a preprint. A revision of this manuscript was accepted for the journal Atmospheric Chemistry and Physics (ACP) and is expected to appear here in due course.
Multi-model ensemble simulations of olive pollen distribution in Europe in 2014
Mikhail Sofiev1, Olga Ritenberga2, Roberto Albertini3, Joaquim Arteta4, Jordina Belmonte5,6, Maira Bonini7, Sevcan Celenk8, Athanasios Damialis9,10, John Douros11, Hendrik Elbern12, Elmar Friese12, Carmen Galan13, Oliver Gilles14, Ivana Hrga15, Rostislav Kouznetsov1, Kai Krajsek16, Jonathan Parmentier4, Matthieu Plu4, Marje Prank1, Lennart Robertson17, Birthe Marie Steensen18, Michel Thibaudon14, Arjo Segers19, Barbara Stepanovich15, Alvaro M. Valdebenito18, Julius Vira1, and Despoina Vokou10 1Finnish Meteorological Institute, Erik Palmenin Aukio 1, Finland
2University of Latvia, Latvia
3Department of Clinical and Experimental Medicine, 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
7Agenzia Tutela della Salute della Città Metropolitana di Milano/LHA ATS Città Metropolitana Milano, Italy
8Biology department, Uludag University, Turkey
9Chair and Institute of Environmental Medicine, UNIKA-T, Technical University of Munich and Helmholtz Zentrum München – German Research Center for Environmental Health, Augsburg, Germany
10Department of Ecology, School of Biology, Aristotle University of Thessaloniki, Greece
11Royal Netherlands Meteorological Institute, De Bilt, The Netherlands
12Rhenish Institute for Environmental Research at the University of Cologne, Germany
13University of Cordoba, Spain
14RNSA, Brussieu, France
15Andrija Stampar Teaching Institute of Public Health, Croatia
16Institute of Energy and Climate Research (IEK-8), Forschungszentrum Jülich, Germany
17Swedish Meteorological and Hydrological Institute SMHI, Sweden
18MET Norway
19TNO, Netherlands
Abstract. A 6-models strong European ensemble of Copernicus Atmospheric Monitoring Service (CAMS) was run through the season of 2014 computing the olive pollen dispersion in Europe. The simulations have been compared with observations in 6 countries, members of the European Aeroallergen Network. Analysis was performed for individual models, the ensemble mean and median, and for a dynamically optimized 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 start was reported too early, by 8 days but for some models the error mounted to almost two weeks. For the season end, the disagreement between the models and the observations varied from a nearly perfect match up to two weeks too late. A series of sensitivity studies performed to understand the origin of the disagreements revealed crucial role of ambient temperature, especially systematic biases in its representation by meteorological models. A simple correction to the heat sum threshold eliminated the season shift 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.

Citation: Sofiev, M., Ritenberga, O., Albertini, R., Arteta, J., Belmonte, J., Bonini, M., Celenk, S., Damialis, A., Douros, J., Elbern, H., Friese, E., Galan, C., Gilles, O., Hrga, I., Kouznetsov, R., Krajsek, K., Parmentier, J., Plu, M., Prank, M., Robertson, L., Steensen, B. M., Thibaudon, M., Segers, A., Stepanovich, B., Valdebenito, A. M., Vira, J., and Vokou, D.: Multi-model ensemble simulations of olive pollen distribution in Europe in 2014, Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2016-1189, in review, 2017.
Mikhail Sofiev et al.
Interactive discussionStatus: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version      Supplement - Supplement
 
RC1: 'General comments', Slawomir Potempski, 26 Feb 2017 Printer-friendly Version Supplement 
 
RC2: 'Review of The study “Multi-model ensemble simulation of olive pollen distribution in Europe in 2014” By Sofiev et al', Anonymous Referee #3, 10 Jun 2017 Printer-friendly Version 
 
AC1: 'Response to reviewers', Mikhail Sofiev, 31 Jul 2017 Printer-friendly Version Supplement 
Mikhail Sofiev et al.
Mikhail Sofiev et al.

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Short summary
This work presents the features and evaluates the quality of the Copernicus Atmospheric Monitoring Service (CAMS) 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 combined use of model predictions with up-to-date measurements (data fusion) can strongly improve the results.
This work presents the features and evaluates the quality of the Copernicus Atmospheric...
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