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Proceedings Paper

Modelling of airborne pollen dispersion in the atmosphere in the Catalonia region, Spain: model description, emission scheme and evaluation of model performance for the case of Pinus
Author(s): Michaël Sicard; Oriol Jorba; Rebeca Izquierdo; Marta Alarcón; Concepción De Linares; Jordina Belmonte
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Paper Abstract

Pollination is a biologically-relevant process that affects the structure of ecosystems since pollen contributes to determine the spatial distribution of plant species. It is thus of interest for mapping ecosystem services for policy support and decision making to increase our knowledge of pollen grain behavior in the atmosphere (source, emission, processes involved during their transport, etc.) at fine temporal and spatial scales. First simulations with the Barcelona Supercomputing Center MONARCH dispersion model (known before as NMMB/BSC-CTM) of Pinus pollen in the atmosphere were performed during a 5-day pollination event observed in Barcelona, Spain, between 27 – 31 March, 2015. MONARCH is an online atmospheric composition model that solves the life cycle of water vapor, gases and aerosols within a meteorological model. A new aerosol emission scheme for pollen grains has been implemented in the system. The emission scheme considers wind speed at 10 m, friction velocity, and temperature and specific humidity at 2 m as main drivers of the mobilization of Pinus pollen grains. The meteorological information is available for the emission scheme at each meteorological integration time step. The spatial distribution of the pine species (P. halepensis, P. pinea) that pollinate from February to April in Catalonia has been derived from the Cartography of habitats of Catalonia and the tree density was obtained from the Forest Inventory of Catalonia. A domain over north-east Spain at 9 km x 9 km horizontal resolution covering Catalonia is designed with 48 vertical layers. The initial and boundary meteorological conditions are derived from the fifth major global ECMWF ReAnalysis (ERA-5). To evaluate the model performances, the simulations are compared (i) to groundbased concentration measurements performed with a Hirst collector in Barcelona downtown, and (ii) to vertically-resolved measurements performed 4 km west of Barcelona downtown with a Micro Pulse Lidar (MPL). A method based on the lidar polarization capabilities was used to retrieve the contribution of the pollen to the total signal. The conversion from optical lidar-retrieved properties to concentration was optimized by minimizing the sum of the squared deviations between the lidar-retrieved concentration at the first height and the true (Hirst) concentration measured at the ground. In terms of surface concentration, the simulation performs well during the center of the event with major underestimation at the beginning. As far as the vertical distribution of airborne Pinus pollen is concerned, simulations reproduce well the shape of the profiles but the intensity tends to be underestimated. Three major limitations are identified with the model runs: (1) the poorly known phenology emission function, (2) the temporal development of the convective planetary boundary layer in coastal areas, which directly affects the vertical structure of the pollen dispersion; (3) the development of the sea breeze and a proper representation of the sea coast line, that play a significant role on the skills of the meteorological mesoscale model.

Paper Details

Date Published: 9 October 2019
PDF: 11 pages
Proc. SPIE 11152, Remote Sensing of Clouds and the Atmosphere XXIV, 111520O (9 October 2019);
Show Author Affiliations
Michaël Sicard, Univ. Politècnica de Catalunya (Spain)
Oriol Jorba, Ctr. Nacional de Supercomputación (Spain)
Rebeca Izquierdo, Carlos III Institute of Health (Spain)
Marta Alarcón, Univ. Politècnica de Catalunya (Spain)
Concepción De Linares, Univ. Autònoma de Barcelona (Spain)
Jordina Belmonte, Univ. Autònoma de Barcelona (Spain)


Published in SPIE Proceedings Vol. 11152:
Remote Sensing of Clouds and the Atmosphere XXIV
Adolfo Comerón; Evgueni I. Kassianov; Klaus Schäfer; Richard H. Picard; Konradin Weber; Upendra N. Singh, Editor(s)

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