European pollen reanalysis, 1980-2022, for alder, birch, and olive, v.1.0


The dataset is the European reanalysis of pollen seasons for alder, birch, and olive. Driven by the European meteorological reanalysis ERA5, the atmospheric composition model SILAM had calculated the flowering and pollen dispersion patterns from these trees for the period of 1980-2022 for Europe. The model used an extended 4-dimensional variational data assimilation (4D-VAR) of daily in-situ pollen observations of aerobiological networks in 33 countries. The aim was to reproduce the inter-annual variability of pollen production and abundance for these trees over entire Europe. The control variable of assimilation was the total pollen release during a flowering season computed independently for each year and type of tree. It was processed to an annual correction factor to the mean productivity of the species. This correction was constant throughout each pollen season but varied in space and between the years. The pollen assimilation had resulted in a consistent improvement of representation of the inter-seasonal variations of seasonal pollen integral SPIn. Note: due to its large size, the dataset is located at the external long-term storage pointed out by the URL below.

Three sets of simulations have been performed with the SILAM atmospheric composition model ( (i) the first-guess run, (ii) the data assimilation (DA) run, and (iii) the final run. All simulations used zero lateral boundary conditions and a fully reflective top boundary. (i) The first guess (reference) run was made with the unconstrained model, through the whole period for all species not accounting for any year-to-year variability of pollen production. It set the starting point for the reanalysis. The horizontal grid was 700 x 420 grid cells, resolution 0.1deg x 0.1deg, the longitude range of (25W-45E), and the latitude range of (30N-72N). The vertical structure consisted of 9 uneven stacked layers, up to 6725 m above the surface: 25m, 50m, 100m, 200m, 400m, 750m, 1200m, 2000m, 2000m thick. The model output included hourly 3D concentrations and 2D dry and wet deposition fields of pollen. (ii) The data assimilation run used an extended procedure allowing for correction of emission flux and generating the set of annual pollen emission correction maps for each year and species. Due to high computational demand of 4D-VAR, the assimilation was performed with the resolution 0.25deg x 0.25deg and a vertical with 6 layers of 50m, 100m, 400m, 1000m, 2000m, and 3000m thick. The domain was also reduced to cover the observational network with ~5deg margin: horizontal grid 200 x 168, the longitude range of (10W-40E), the latitude range of (30N-72N). The DA run produced two types of output: the annual emission correction maps for each year and species, and near-surface pollen concentrations. The latter was used to calculate the constant-in-time bias-reducing correction map, mean over the entire period. (iii) The final run used the annual emission correction map from the DA run, extrapolated to the east and linearly down-scaled from the DA grid to the source grid, which was additionally scaled with the bias-reducing map. The rest of the setup was identical to the first-guess run. The formal analysis was applied to detect and remove unreliable time series of pollen observations. Before the use in assimilation procedures the daily time series were transformed to their two-days averages.

The following variables are provided in the dataset: - hourly 2D near-surface pollen concentrations - [ cnc_srf_POLLEN_ ] - hourly 3D pollen concentrations - [ cnc_3D_POLLEN_ ] - hourly 2D dry and wet pollen deposition fields - [ dd_POLLEN_, wd_POLLEN_ ] - hourly 2D pollen emission fields - [ emf_POLLEN_ ] - seasonal 2D footprint area of the pollen monitoring stations - [ cnc_POLLEN_ ] All fields are provided in the output horizontal grid; the 3D fields are provided for the mid-points of the output vertical layers (marked levels below) All fields cover the full reanalysis period of 1980-2022.

The reanalysis output is grouped in directories by species and types of variables: - hourly 3-D pollen concentrations, [pollen / m3] cnc_3D_POLLEN_ALDER cnc_3D_POLLEN_BIRCH/ cnc_3D_POLLEN_OLIVE/ - hourly near-surface concentrations (the 1st layer of the 3D fields), [pollen / m3] cnc_srf_POLLEN_ALDER/ cnc_srf_POLLEN_BIRCH/ cnc_srf_POLLEN_OLIVE/ - hourly dry deposition flux of pollen [pollen / m2 sec] dd_POLLEN_ALDER/ dd_POLLEN_BIRCH/ dd_POLLEN_OLIVE - hourly emission flux of pollen [pollen / m2 sec] emf_POLLEN_ALDER emf_POLLEN_BIRCH emf_POLLEN_OLIVE - hourly wet deposition flux of pollen [pollen / m2 sec] wd_POLLEN_ALDER wd_POLLEN_BIRCH wd_POLLEN_OLIVE - seasonal 2D footprint area of the pollen monitoring stations [relative]

All files are in the NetCDF 4 format, closely following the CF-1.3 convention (, visited 3.12.2023), tested for viewing with GrADS v.2.0, Python 3.7 or higher netCDF4 library, and NASA PanoPly netCDF/HDF/GRIB data viewer ( visited 3.12.2023).

Metadata Access
Creator Sofiev, Mikhail; Palamarchuk, Julia; Kouznetsov, Rostislav; Adams-Groom, Beverley; Antunes, Célia M.; Ariño, Arturo H.; Bastl, Maximilian; Belmonte, Jordina; Berger, Uwe E.; Bonini, Maira; Bruffaerts, Nicolas; Buters, Jeroen; Carinanos, Paloma; Celenk, Sevcan; Ceriotti, Valentina; Charalampopoulos, Athanasios; Clewlow, Yolanda; Clot, Bernard; Dahl, Aslog; Damialis, Athanasios; De Linares, Concepción; De Weger, Letty A.; Dirr, Lukas; Ekebom, Agneta; Fatahi, Yalda; Piotrowska-Weryszko, Krystyna; Fernández González, Maria Delia; Fernández-Rodríguez, Santiago; Galán, Carmen; Gedda, Björn; Gehrig, Regula; Gonzalez, Roldan Nestor; Grewling, Lukasz; Hajkova, Lenka; Hänninen, Risto; Hentges, François; Jantunen, Juha; Kadantsev, Evgeny; Kasprzyk, Idalia; Kloster, Mathilde; Kluska, Katarzyna; Koenders, Mieke; Lafférsová, Janka; Leru, Poliana; Louna-Korteniemi, Maria; Magyar, Donát; Majkowska-Wojciechowska, Barbara; Mitrovic, Mirjana; Myszkowska, Dorota; Oliver, Gilles; Östensson, Pia; Pätsi, Sanna; Pérez-Badia, Rosa; Prank, Marje; Przedpelska-Wasowicz, Ewa Maria; Rajo, F. Javier Rodríguyez; Ramfjord, Hallvard; Rapiejko, Joanna; Rodinkova, Victoria; Rojo, Jesús; Ruiz-Valenzuela, Luis; Rybnicek, Ondrej; Saarto, Annika; Sauliene, Ingrida; Seliger, Andreja Kofol; Severova, Elena; Shalaboda, Valentina; Sikoparija, Branko; Siljamo, Pilvi; Soares, Joana; Sozinova, Olga; Stjepanović, Barbara; Teinemaa, Erik; Uppstu, Andreas; Vill, Mart; Vira, Julius; Visez, Nicolas; Vitikainen, Tiina; Vokou, Despoina; Abramidze, Tamuna; Fernández González, María; Lipiec, Agnieszka; Stangel, Anders; Tyuryakov, Svyatoslav; Trigo, M. Mar; Weryszko-Chmielewska, Elżbieta; Karppinen, Ari
Instrument System of rIntegrated modeLling of Atmospheric coMposition (SILAM)
Publisher Finnish Meteorological Institute
Contributor Finnish Meteorological Institute (FMI); Aerobiological networks from 33 European countries
Publication Year 2023
Funding Reference Horizon Europe 101086109; Horizon Europe 101057131; Horizon Europe 101060784; Copernicus; Academy of Finland 318194; Academy of Finland 329215; Academy of Finland 355851
Rights CC-BY; info:eu-repo/semantics/openAccess
OpenAccess true
Contact mikhail.sofiev(at)
Language English
Resource Type Dataset
Version 1.0
Discipline Environmental science
Spatial Coverage (-25.000W, 30.000S, 45.000E, 72.000N); Europe
Temporal Coverage 1979-12-31T22:00:00.000Z 2022-12-31T22:00:00.000Z