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Data · dataset · 2026

Improving retrieval quality for airborne limb sounders by horizontal regularisation

Listed in National Center for Atmospheric Research

Modern airborne infrared limb sounders are capable of measuring profiles so fast that neighbouring profiles are very similar to one another.

Description

This can be exploited by retrieving whole 2-D cross-sections instead of simple 1-D profiles. This paper presents algorithms that are able to perform such a large-scale retrieval and that efficiently produce typical diagnostic quantities.

The characteristics and capabilities of the proposed method are analysed and demonstrated in a detailed case study using a series of profiles that were measured by CRISTA-NF (Cryogenic Infrared Spectrometers and Telescope for the Atmosphere-New Frontiers). It is shown that cross-section retrievals can either reduce noise-induced artefacts or produce finer vertical structures while maintaining the same image noise level.

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Further, it is discussed how the presented methodology can also be applied to improve the retrievals for other instrument types including current satellite-borne nadir-sounders and near-future satellite-borne limb sounders.

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Provenance · 1 source records, 8 field assertions
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National Center for Atmospheric Researchd5f2cb55-bb2c-464b-8600-12ed02ce123511 d agoJSON v1
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concepts[field].local:field:earth-environmentalmapping · data ucar educonnector:data_ucar_edu@1.0.0
concepts[field].local:field:ocean-atmosphericmapping · data ucar educonnector:data_ucar_edu@1.0.0
concepts[modality].local:modality:imageenrichment · data ucar edukeyword-concept-rules@1.0.0title+description (75%)
created_datesource · data ucar educonnector:data_ucar_edu@1.0.0
descriptionsource · data ucar educonnector:data_ucar_edu@1.0.0/notes
publication_datesource · data ucar educonnector:data_ucar_edu@1.0.0
titlesource · data ucar educonnector:data_ucar_edu@1.0.0/title
updated_datesource · data ucar educonnector:data_ucar_edu@1.0.0