Articles | Volume 17, issue 20
https://doi.org/10.5194/acp-17-12341-2017
https://doi.org/10.5194/acp-17-12341-2017
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 Sofiev, Olga Ritenberga, Roberto Albertini, Joaquim Arteta, Jordina Belmonte, Carmi Geller Bernstein, Maira Bonini, Sevcan Celenk, Athanasios Damialis, John Douros, Hendrik Elbern, Elmar Friese, Carmen Galan, Gilles Oliver, Ivana Hrga, Rostislav Kouznetsov, Kai Krajsek, Donat Magyar, Jonathan Parmentier, Matthieu Plu, Marje Prank, Lennart Robertson, Birthe Marie Steensen, Michel Thibaudon, Arjo Segers, Barbara Stepanovich, Alvaro M. Valdebenito, Julius Vira, and Despoina Vokou

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Cited articles

Aguilera, F., Ruiz, L., Fornaciari, M., Romano, B., Galán, C., Oteros, J., Ben Dhiab, A., Msallem, M., and Orlandi, F.: Heat accumulation period in the Mediterranean region: phenological response of the olive in different climate areas (Spain, Italy and Tunisia), Int. J. Biometeorol., 58, 867–876, 2013.
Aguilera, F., Fornaciari, M., Ruiz-Valenzuela, L., Galán, C., Msallem, M., Dhiab, A. Ben, la Guardia, C. D. de, del Mar Trigo, M., Bonofiglio, T., and Orlandi, F.: Phenological models to predict the main flowering phases of olive (Olea europaea L.) along a latitudinal and longitudinal gradient across the Mediterranean region, Int. J. Biometeorol., 59, 629–641, https://doi.org/10.1007/s00484-014-0876-7 2014.
Alba, F. and Diaz De La Guardia, C.: The effect of air temperature on the starting dates of the Ulmus, Platanus and Olea pollen seasons in the SE Iberian Peninsula, Aerobiologia, 14, 191–194, 1998.
Andersen, T. B.: A model to predict the beginning of the pollen season, Grana, 30, 269–275, https://doi.org/10.1080/00173139109427810 1991.
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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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