Towards Refining U.S. Ammonia Emissions with CrIS Observations through Four-dimensional Variational Assimilation
Abstract
Chemical transport models such as the Community Multiscale Air Quality (CMAQ) model provide a platform for evaluating the influence of emissions on atmospheric composition. They are designed to represent scientific consensus on the chemical and physical transformations of emitted species into pollutant concentrations. For processes represented with sufficient certainty, such as inorganic aerosol thermodynamics, the difference in modeled and observed concentrations is useful for evaluating the emissions inventory. Specifically, these differences in concentration can be leveraged in a four-dimensional variational assimilation framework to provide revised estimates of emissions with spatial specificity.
This work introduces the CMAQ adjoint integrated in a Python-based four-dimensional variational framework. Given the difficulty of estimating emissions of ammonia from the agricultural sector and the complexity of relating emissions to concentrations of this condensable species, this work focuses on the refinement of ammonia emissions through satellite observations of ammonia from the Cross-track Infrared Sounder (CrIS).The assimilation of CrIS pseudo-observations demonstrates the capability of the framework to improve estimates of perturbed emissions.- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2018
- Bibcode:
- 2018AGUFM.A21A..06C
- Keywords:
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- 0322 Constituent sources and sinks;
- ATMOSPHERIC COMPOSITION AND STRUCTUREDE: 1910 Data assimilation;
- integration and fusion;
- INFORMATICSDE: 1986 Statistical methods: Inferential;
- INFORMATICSDE: 3260 Inverse theory;
- MATHEMATICAL GEOPHYSICS