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

The dataset presents the 43 year-long reanalysis of pollen seasons for three major allergenic genera of trees in Europe: alder (Alnus), birch (Betula), and olive (Olea). Driven by the meteorological reanalysis ERA5, the atmospheric composition model SILAM predicted the flowering period and calculate...

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Detalles Bibliográficos
Autores: Mikhail Sofiev, M.Sofiev, Julia Palamarchuk, L. Palamarchuk, Rostislav Kouznetsov, R. Kouznetsov, Luis Ruiz Valenzuela (66/80), L. Ruiz Valenzuela
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2024
País:España
Institución:Universidad de Jaén
Repositorio:RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaén
OAI Identifier:oai:ruja.ujaen.es:10953/7218
Acceso en línea:https://www.nature.com/articles/s41597-024-03686-
https://hdl.handle.net/10953/7218
Access Level:acceso abierto
Palabra clave:Allergenic Pollen, predictive flowering models, Aerobiological networks European
2417.08
2417.13
Descripción
Sumario:The dataset presents the 43 year-long reanalysis of pollen seasons for three major allergenic genera of trees in Europe: alder (Alnus), birch (Betula), and olive (Olea). Driven by the meteorological reanalysis ERA5, the atmospheric composition model SILAM predicted the flowering period and calculated the Europe-wide dispersion pattern of pollen for the years 1980-2022. The model applied extended 4- dimensional variational data assimilation of in-situ observations of aerobiological networks in 34 European countries to reproduce the inter-annual variability and trends of pollen production and distribution. The control variable of the assimilation procedure was the total pollen release during each flowering season, implemented as an annual correction factor to the mean pollen productivity. The dataset was designed as an input to studies on climate-induced and anthropogenically driven changes in the European vegetation, biodiversity monitoring, bioaerosol modelling and assessment, as well as, in combination with intra-seasonal observations, for health-related