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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Volume 8, issue 6 | Copyright
Atmos. Meas. Tech., 8, 2359-2369, 2015
https://doi.org/10.5194/amt-8-2359-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 08 Jun 2015

Research article | 08 Jun 2015

Vertical level selection for temperature and trace gas profile retrievals using IASI

R. A. Vincent1,2, A Dudhia1, and L. J. Ventress1 R. A. Vincent et al.
  • 1Atmospheric, Oceanic and Planetary Physics, Clarendon Laboratory, Parks Road, Oxford, OX1 3PU, UK
  • 2Air Force Institute of Technology, Wright-Patterson Air Force Base, Ohio, 45433, USA

Abstract. This work presents a new iterative method for optimally selecting a vertical retrieval grid based on the location of the information while accounting for inter-level correlations. Sample atmospheres initially created to parametrise the Radiative Transfer Model for the Television Infrared Observation Satellite Operational Vertical Sounder (RTTOV) forward model are used to compare the presented iterative selection method with two other common approaches, which are using levels of equal vertical spacing and selecting levels based on the cumulative trace of the averaging kernel matrix (AKM). This new method is shown to outperform compared methods for simulated profile retrievals of temperature, H2O, O3, CH4, and CO with the Infrared Atmospheric Sounding Interferometer (IASI). However, the benefits of using the more complicated iterative approach compared to the simpler cumulative trace method are slight and may not justify the added effort for the cases studied, but may be useful in other scenarios where temperature and trace gases have strong vertical gradients with significant estimate sensitivity. Furthermore, comparing retrievals using a globally optimised static grid vs. a locally adapted one shows that a static grid performs nearly as well for retrievals of O3, CH4, and CO. However, developers of temperature and H2O retrieval schemes may at least consider using adaptive or location specific vertical retrieval grids.

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This work presents a new iterative method for optimally selecting a vertical retrieval grid based on the location of information while accounting for inter-level correlations. Sample atmospheres initially created to parametrise the RTTOV forward model are used to compare the presented iterative vertical selection method with two other common approaches. The iterative method is shown to outperform the other methods in terms of degrees of freedom, but at the expense of simplicity.
This work presents a new iterative method for optimally selecting a vertical retrieval grid...
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