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| Home > Publications database > Examining transport in the Upper Troposphere – Lower Stratosphere with the infrared limb imager GLORIA |
| Book/Dissertation / PhD Thesis | FZJ-2023-02232 |
2023
Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag
Jülich
ISBN: 978-3-95806-691-5
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Please use a persistent id in citations: doi:10.34734/FZJ-2023-02232
Abstract: The Gimballed Limb Observer for Radiance Imaging of the Atmosphere (GLORIA) is an airborne infrared limb imager that can measure temperature and trace gas concentration data in the Upper Troposphere and Lower Stratosphere (UTLS) with high vertical resolution (upo to 200 m). In addition to standard 1-D retrievals, a unique 3-D data set can be obtained by flying around the observed air mass and performing a tomographic retrieval. Such data sets have high horizontal resolution (up to 20 km×20 km) as well and can give insight into many important small-scale processes in UTLS, such as mixing, filamentation and internal gravity wave propagation. A 3-D tomographic retrieval is a highly challenging and computationally expensive inverse modelling problem. It typically requires an introduction of some general knowledge of the atmosphere (regularisation) due to its underdetermined nature. The quality of 3-D data strongly depends on regularisation. In this thesis, a consistent, physically motivated (no ad-hoc parameters) regularisation scheme based on spatial derivatives of first order and Laplacian is introduced. As shown by a case study with synthetic data, this scheme, combined with newly developed irregular grid retrieval methods, improves both upon the quality and the computational cost of 3D tomography. It also eliminates grid dependence and the need to tune parameters for each use case. The few physical parameters required can be derived from in situ measurements and model data. Tests show that an 82% reduction in the number of grid points and a 50% reduction in total computation time, compared to previous methods, could be achieved without compromising results. An efficient Monte Carlo technique was also adopted for accuracy estimation of the new retrievals.
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