Implementation of a parallel 4D‐variational chemistry data‐assimilation scheme

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Elbern, Hendrik, et al. “Implementation of a Parallel 4D‐variational Chemistry data‐assimilation Scheme”. Environmental Management and Health, vol. 10, no. 4, 1999, pp. 236-45, https://doi.org/10.1108/09566169910276184.
Elbern, H., Schmidt, H., & Ebel, A. (1999). Implementation of a parallel 4D‐variational chemistry data‐assimilation scheme. Environmental Management and Health, 10(4), 236-245. https://doi.org/10.1108/09566169910276184
Elbern H, Schmidt H, Ebel A. Implementation of a parallel 4D‐variational chemistry data‐assimilation scheme. Environmental Management and Health. 1999;10(4):236-45.
Description

Can atmospheric chemistry be accurately modeled? This paper presents the development and implementation of a four-dimensional variational (4D-var) data assimilation technique for a comprehensive Eulerian chemistry-transport model. The method seeks to analyze the chemical state of the atmosphere using trace gas observations, a chemistry-transport model, and a priori knowledge. The approach involves the parallel implementation of the 4D-var method, including a strategy for storing and recalculating data. Artificial observations generated by the model are used to evaluate the method's performance, demonstrating its ability to adapt the model trajectory to the observational data. Ultimately, this research demonstrates the effectiveness of the 4D-var method for analyzing atmospheric chemistry. By offering valuable insights into model adaptation and data assimilation, it demonstrates its suitability for applications and contributing to a better understanding of atmospheric processes for managing **environment**.

This article in Environmental Management and Health aims to develop a new understanding for those in the environmental management. The model under consideration is the University of Cologne EURAD-CTM2 with the full RADM2 gas phase mechanism. With this research, this paper provides environmental benefits to the air and well as the community.

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The first research to cite this article was titled Adjoint sensitivity analysis of regional air quality models and was published in 2005. The most recent citation comes from a 2016 study titled Adjoint sensitivity analysis of regional air quality models . This article reached its peak citation in 2016 , with 1 citations.It has been cited in 3 different journals, 33% of which are open access. Among related journals, the Journal of Computational Physics cited this research the most, with 3 citations. The chart below illustrates the annual citation trends for this article.
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