The impact of data assimilation into the meteorological WRF model on birch pollen modelling
Authors:
- Małgorzata Werner,
- Daria Bilińska-Prałat,
- Maciej Kryza,
- Jakub Guzikowski,
- Małgorzata Malkiewicz,
- Piotr Rapiejko,
- Kazimiera Chłopek,
- Katarzyna Ewa Dąbrowska-Zapart,
- Agnieszka Lipiec,
- Dariusz Jurkiewicz,
- Ewa Kalinowska,
- Barbara Majkowska-Wojciechowska,
- Dorota Myszkowska,
- Krystyna Piotrowska-Weryszko,
- Małgorzata Puc,
- Anna Rapiejko,
- Grzegorz Siergiejko,
- Elżbieta Weryszko-Chmielewska,
- Andrzej Wieczorkiewicz,
- Monika Ziemianin
Abstract
We analyse the impact of ground-based data assimilation to the Weather Research and Forecasting (WRF) me-teorological model on parameters relevant for birch pollen emission calculations. Then, we use two differentemission databases (BASE–no data assimilation, OBSNUD–data assimilation for the meteorological model) inthe chemical transport model and evaluate birch pollen concentrations. Finally, we apply a scaling factor forthe emissions (BASE and OBSNUD), based on the ratio between simulated and observed seasonal pollen integral(SPIn) to analyse its impact on birch concentrations over Central Europe. Assimilation of observational data sig-nificantly reduces modeloverestimation of air temperature, which isthe mainparameterresponsiblefor the startof pollen emission and amount of released pollen. The results also show that a relatively small bias in air temper-ature from the model can lead to significant differences in heating degree days (HDD) value. This may cause the HDD threshold to be attained several days earlier/later than indicated from observational data which has furtherimpact on the start of pollen emission. Even though the bias for air temperature was reduced for OBSNUD, themodel indicates a start for the birch pollen season that is too early compared to observations. The start date ofthe season was improved at two of the 11 stations in Poland. Data assimilation does not have a significant impacton the season's end or SPIn value. The application of the SPIn factor for the emissions results in a much closerbirch pollen concentration level to observations even though the factor does not improve the start or end ofthe pollen season. The post-processing of modelled meteorologicalfields, such as the application of bias correc-tion, can be considered as a way to further improve the pollen emission modelling.
- Record ID
- USLee05e7423fd74acb83168de3c25615ff
- Author
- Journal series
- Science of the Total Environment, ISSN 0048-9697, e-ISSN 1879-1026
- Issue year
- 2022
- Vol
- 807
- No
- 3
- Pages
- 1-14
- Publication size in sheets
- 0.70
- Keywords in English
- Birch pollen emissions; Data assimilation; Europe; Pollen concentrations; Start of the season; Temperature bias
- ASJC Classification
- ; ; ;
- DOI
- DOI:10.1016/j.scitotenv.2021.151028 Opening in a new tab
- Handle.net URL
- hdl.handle.net/20.500.12128/22076 Opening in a new tab
- URL
- http://hdl.handle.net/20.500.12128/22076 Opening in a new tab
- Language
- eng (en) English
- License
- File
-
- File: 1
- The impact of data assimilation into the meteorological WRF model on birch pollen modelling , File Dabrowska_The impact_of_data_assimilation.pdf / 4 MB
- Dabrowska_The impact_of_data_assimilation.pdf
- publication date: 25-05-2023
- The impact of data assimilation into the meteorological WRF model on birch pollen modelling , File Dabrowska_The impact_of_data_assimilation.pdf / 4 MB
-
- Score (nominal)
- 200
- Score source
- journalList
- Score
- = 200.0, 27-09-2023, ArticleFromJournal
- Publication indicators
- PubMed ID
- 34666079 Opening in a new tab
- Uniform Resource Identifier
- https://opus.us.edu.pl/info/article/USLee05e7423fd74acb83168de3c25615ff/
- URN
urn:uni-kat-prod:USLee05e7423fd74acb83168de3c25615ff
* presented citation count is obtained through Internet information analysis, and it is close to the number calculated by the Publish or PerishOpening in a new tab system.