Articles | Volume 16, issue 5
Research article
07 Mar 2023
Research article |  | 07 Mar 2023

Data quality enhancement for field experiments in atmospheric chemistry via sequential Monte Carlo filters

Lenard L. Röder, Patrick Dewald, Clara M. Nussbaumer, Jan Schuladen, John N. Crowley, Jos Lelieveld, and Horst Fischer

Data sets

Data from TO2021 campaign J. N. Crowley, P. Dewald, C. M. Nussbaumer, A. Ringsdorf, A. Edtbauer, J. Schuladen, H. Fischer, J. Williams, L. Röder, and Z. Hamryszczak

Model code and software

lenroed/smc-boxmodel: Initial Release lenroed

Short summary
Field experiments in atmospheric chemistry provide insights into chemical interactions of our atmosphere. However, high data coverage and accuracy are needed to enable further analysis. In this study, we explore a statistical method that combines knowledge about the chemical reactions with information from measurements to increase the quality of field experiment datasets. We test the algorithm for several applications and discuss limitations that depend on the specific variable and the dynamics.