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@ARTICLE{Sofiev:842557,
      author       = {Sofiev, Mikhail and Ritenberga, Olga and Albertini, Roberto
                      and Arteta, Joaquim and Belmonte, Jordina and Bernstein,
                      Carmi Geller and Bonini, Maira and Celenk, Sevcan and
                      Damialis, Athanasios and Douros, John and Elbern, Hendrik
                      and Friese, Elmar and Galan, Carmen and Oliver, Gilles and
                      Hrga, Ivana and Kouznetsov, Rostislav and Krajsek, Kai and
                      Magyar, Donat and Parmentier, Jonathan and Plu, Matthieu and
                      Prank, Marje and Robertson, Lennart and Steensen, Birthe
                      Marie and Thibaudon, Michel and Segers, Arjo and
                      Stepanovich, Barbara and Valdebenito, Alvaro M. and Vira,
                      Julius and Vokou, Despoina},
      title        = {{M}ulti-model ensemble simulations of olive pollen
                      distribution in {E}urope in 2014: current status and
                      outlook},
      journal      = {Atmospheric chemistry and physics},
      volume       = {17},
      number       = {20},
      issn         = {1680-7324},
      address      = {Katlenburg-Lindau},
      publisher    = {EGU},
      reportid     = {FZJ-2018-00776},
      pages        = {12341 - 12360},
      year         = {2017},
      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.},
      cin          = {IEK-8 / JSC},
      ddc          = {550},
      cid          = {I:(DE-Juel1)IEK-8-20101013 / I:(DE-Juel1)JSC-20090406},
      pnm          = {243 - Tropospheric trace substances and their
                      transformation processes (POF3-243)},
      pid          = {G:(DE-HGF)POF3-243},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000413112300002},
      doi          = {10.5194/acp-17-12341-2017},
      url          = {https://juser.fz-juelich.de/record/842557},
}