Published December 24, 2023 | Version 1.0
Dataset Metadata-only

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

Creators

  • 1. Finnish Meteorological Institute, Helsinki, Finland
  • 2. University of Worcester, School of Science and Environment, Worcester, UK
  • 3. University of Évora, School of Health and Human Development, Department of Medical and Health Sciences & Institute of Earth Sciences - ICT, Évora, Portugal
  • 4. University of Navarra, Biodiversity and Environment Institute, Pamplona, Spain
  • 5. Department of Otorhinolaryngology, Medical University of Vienna, Austria
  • 6. Departament de Biologia Animal, Biologia Vegetal i Ecologia, Universitat Autònoma de Barcelona (UAB), Bellaterra, Spain
  • 7. Institut de Ciència i Tecnologia Ambientals (ICTA-UAB), Universitat Autònoma de Barcelona, Bellaterra, Spain
  • 8. University of Innsbruck, Department of Botany, Innsbruck, Austria
  • 9. Department of Hygiene and Health Prevention, Agency for Health Protection of Metropolitan Area of Milan (ATS), Milan, Italy
  • 10. Mycology and Aerobiology, Sciensano, Brussels, Belgium
  • 11. Center of Allergy & Environment (ZAUM), Member of the German Center for Lung Research (DZL), Technical University and Helmholtz Center Munich, Munich, Germany
  • 12. Department of Botany, University of Granada, Granada, Spain
  • 13. Andalusian Institute for Earth System Research (IISTA-CEAMA), University of Granada, Granada, Spain
  • 14. Bursa Uludag University, Faculty of Arts and Science, Department of Biology, Aerobiology Laboratory, 16059 Görükle- Bursa, Türkiye
  • 15. Department of Hygiene and Health Prevention, Agency for Health Protection of the Metropolitan Area of Milan (ATS), Milan, Italy
  • 16. Department of Ecology, School of Biology, Aristotle University of Thessaloniki, Thessaloniki, Greece
  • 17. Health, air quality, & UK pollen forecasting, UK Met Office, Exeter, UK
  • 18. Federal Office of Meteorology and Climatology MeteoSwiss, Zurich, Switzerland
  • 19. Department of Biological and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden
  • 20. Terrestrial Ecology and Climate Change, Department of Ecology, School of Biology, Aristotle University of Thessaloniki, Thessaloniki, Greece
  • 21. Department of Pulmonology, Leiden University Medical Center, Leiden, the Netherlands
  • 22. Palynological Laboratory, Swedish Museum of Natural History, Stockholm, Sweden
  • 23. Departament of Botany and Plant Physiology, Subdepartament of Aerobiology, University of Life Sciences, Lublin, Poland
  • 24. Biodiversity and Environmental Management, University of León, León, Spain
  • 25. Institute of Atmospheric Sciences and Climate-CNR, Bologna, Italy
  • 26. Department of Construction, School of Technology, University of Extremadura, Avda. de la Universidad s/n, Cáceres, Spain
  • 27. Inter-University Institute for Earth System Research (IISTA), International Campus of Excellence on Agri-food (ceiA3), University of Cordoba, Spain
  • 28. Pollen Laboratory, Department of Biological and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden
  • 29. Laboratory of Aerobiology, Department of Systematic and Environmental Botany, Faculty of Biology, Adam Mickiewicz University, Poznan, Poland
  • 30. Czech Hydrometeorological Institute, Prague, Czech Republic
  • 31. Luxembourg
  • 32. South Karelia Allergy and Environment Institute, Imatra, Finland
  • 33. College of Natural Sciences University of Rzeszow, Rzeszow, Poland
  • 34. The Asthma and Allergy Association, Roskilde, Denmark
  • 35. Institute of Biology, College of Natural Sciences University of Rzeszow, Rzeszow, Poland
  • 36. Elkerliek Helmond, Helmond, Netherlands
  • 37. Regional Public Health Office department of medical microbiology, Slovakia
  • 38. Allergology & Clinical Immunology, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
  • 39. Biodiversity Unit, University of Turku, Turku, Finland
  • 40. National Center for Public Health and Pharmacy, Hungary
  • 41. Aeroallergen Monitoring Centre "AMoC", Department of Immunology and Allergy, Poland
  • 42. Medical University of Lodz, Poland
  • 43. Serbian Environmental Protection Agency, Belgrade, Serbia
  • 44. Jagiellonian University Medical College, Department of Clinical and Environmental Allergology, Kraków, Poland
  • 45. French Aerobiological Monitoring Network (RNSA), Brussieu, France
  • 46. University of Castilla-La Mancha, Institute of Environmental Sciences, Toledo, Spain
  • 47. Icelandic Institute of Natural History, Akureyri, Iceland
  • 48. Sciences Faculty, University of Vigo, Ourense, 32002, Spain
  • 49. Department of Biology, NTNU, Trondheim, Norway
  • 50. Allergen Reseach Center, Warsaw, Poland
  • 51. National Pirogov Memorial Medical University, Vinnytsya, Ukraine
  • 52. Department of Pharmacology, Pharmacognosy and Botany, Faculty of Pharmacy, Complutense University of Madrid, Madrid, Spain
  • 53. Department of Biology Animal, Plant Biology and Ecology, University of Jaén, Jaén, Spain
  • 54. University Institute of research in Olive Groves and Olive Oils, University of Jaén, Jaén, Spain
  • 55. Czech Pollen Information Service, Czech Republic
  • 56. Vilnius University Siauliai Academy, Siauliai, Lithuania
  • 57. National Laboratory of Health, Environment and Food, Slovenia
  • 58. Faculty of Biology, Moscow State University, Moscow, Russia
  • 59. Faculty of Biology, Shenzhen MSU -BIT University, Shenzhen, China
  • 60. Retired from Faculty of Pharmacy of the Belarusian State Medical University, Minsk, Belarus
  • 61. BioSense Institute Research Institute for Information Technologies in Biosystems, University of Novi Sad, Novi Sad, Serbia
  • 62. NILU - Stiftelsen Norwegian Institute for Air Research, Kjeller, Norway
  • 63. University of Latvia, Riga, Latvia
  • 64. Laboratory of Aerobiology at Teaching Institute of Public Health dr.Andrija Stampar, Zagreb, Croatia
  • 65. Estonian Environmental research Institute (under Estonian Environmental Research Centre), Estonia
  • 66. Université de Lille, CNRS, UMR, 8516, LASIRE - Laboratoire de Spectroscopie pour les Interactions, la Réactivité et l'Environnement, F-59000, Lille, France
  • 67. Center for Allergy and Immunology Research, Tbilisi, Georgia
  • 68. Department of the Prevention of Environmental Hazard, Allergology and Immunology, Medical University of Warsaw, Poland
  • 69. Department of Botany and Plant Physiology, Subdepartment of Aerobiology, University of Life Sciences in Lublin, Poland
  • 70. Department of Botany and Plant Physiology, University of Malaga, Malaga, Spain

Contributors

Description

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.

Methods

Three sets of simulations have been performed with the SILAM atmospheric composition model (http://silam.fmi.fi): (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.

Table of contents

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]

Technical info

All files are in the NetCDF 4 format, closely following the CF-1.3 convention (https://cfconventions.org, 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 (https://www.giss.nasa.gov/tools/panoply visited 3.12.2023).

Additional details

Identifiers

URL
https://etsin.fairdata.fi/dataset/6b16c94c-3009-4501-9291-7e0c702a87a2
b2rec
980bc5264c6848859a3ab542a88979f9

Funding

Horizon Europe
SYLVA 101086109
Horizon Europe
CATALYSE 101057131
Horizon Europe
EO4EU 101060784
Copernicus
CAMS2_40
Academy of Finland
PS4A 318194
Academy of Finland
ALL-IMPRESS 329215
Academy of Finland
SPORELIFE 355851

Instruments

System of rIntegrated modeLling of Atmospheric coMposition (SILAM)
undefined (Other)

FMI metadata

Link to external data location (URL)
https://european-pollen-reanalysis-v1-0.lake.fmi.fi/index.html
Process step
Reference run: SILAM unconstrained simulatinos over the 1980-2022, SILAM 4D-VAR data assimilation of the EAN in-situ data, 1980-2022, Bias-reduction calibration of the assimilated emission corrections
Lineage
The dataset has been evaluated against in-situ observations of EAN
Parameter
  • Parameter name: cnc_POLLEN_ALDER_m22
  • Parameter unit: pollen / m3
  • Parameter description: Near-surface and multi-layer concentration of alder pollen
  • Parameter name: cnc_POLLEN_BIRCH_m22
  • Parameter unit: pollen / m3
  • Parameter description: Near-surface and multi-layer concentration of birch pollen
  • Parameter name: cnc_POLLEN_OLIVE_m28
  • Parameter unit: pollen / m3
  • Parameter description: Near-surface and multi-layer concentration of olive pollen
  • Parameter name: dd_POLLEN_ALDER_m22
  • Parameter unit: pollen / m2
  • Parameter description: Dry deposition of alder pollen, cumulative since the start of the year
  • Parameter name: wd_POLLEN_ALDER_m22
  • Parameter unit: pollen / m2
  • Parameter description: Wet deposition of alder pollen, cumulative since the start of the year
  • Parameter name: dd_POLLEN_BIRCH_m22
  • Parameter unit: pollen / m2
  • Parameter description: Dry deposition of birch pollen, cumulative since the start of the year
  • Parameter name: wd_POLLEN_BIRCH_m22
  • Parameter unit: pollen / m2
  • Parameter description: Wet deposition of birch pollen, cumulative since the start of the year
  • Parameter name: dd_POLLEN_OLIVE_m28
  • Parameter unit: pollen / m2
  • Parameter description: Dry deposition of olive pollen, cumulative since the start of the year
  • Parameter name: wd_POLLEN_OLIVE_m28
  • Parameter unit: pollen / m2
  • Parameter description: Wet deposition of ollive pollen, cumulative since the start of the year
  • Parameter name: emf_POLLEN_ALDER_m22
  • Parameter unit: pollen / m2 sec
  • Parameter description: Emission flux of alder pollen
  • Parameter name: emf_POLLEN_BIRCH_m22
  • Parameter unit: pollen / m2 sec
  • Parameter description: Emission flux of birch pollen
  • Parameter name: emf_POLLEN_OLIVE_m28
  • Parameter unit: pollen / m2 sec
  • Parameter description: Emission flux of olive pollen
  • Parameter name: cnc_POLLEN_ALDER_m22_adj
  • Parameter unit: 1 / m3
  • Parameter description: sensitivity distribution (footprint) for alder pollen observations
  • Parameter name: cnc_POLLEN_BIRCH_m22_adj
  • Parameter unit: 1 / m3
  • Parameter description: sensitivity distribution (footprint) for birch pollen observations
  • Parameter name: cnc_POLLEN_OLIVE_m28_adj
  • Parameter unit: 1 / m3
  • Parameter description: sensitivity distribution (footprint) for olive pollen observations
Data levels (meter, hectoPascal, degree, sigma pressure levels, other) in vertical direction(+/-) for example 1500 m or 850 hPa
  • Level: near surface
  • Level: 12.5
  • Level unit: meter
  • Level: 50
  • Level unit: meter
  • Level: 125
  • Level unit: meter
  • Level: 275
  • Level unit: meter
  • Level: 575
  • Level unit: meter
  • Level: 1150
  • Level unit: meter
  • Level: 2125
  • Level unit: meter
  • Level: 3725
  • Level unit: meter
  • Level: 5725
  • Level unit: meter
Resolution
10
Resolution unit
km
Topic category
environment

Temporal Coverage

Ranges:

Start date: 1979-12-31
End date: 2022-12-31

Locations

Europe Envelope:
(Lon: 72.0, Lat: -25.0 )
(Lon: 30.0, Lat: 45.0 )