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@@ -25,15 +25,14 @@ uncertainties to be integrated **within** data‑processing codes themselves,
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turning them from external annotations into active elements of
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computational workflows.
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> The concept presented here grew out of earlier, project‑specific
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> implementations of AD‑based uncertainty propagation. AD workflows
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> were instrumental within the [FIDUCEO](https://www.fiduceo.eu)
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> project to enable the multi‑mission remote sensing calibration
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> that underpins Earth climate data records
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> [NPL Report CMSC 26/03](https://eprintspublications.npl.co.uk/2828/1/cmsc26.pdf)
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> ranks AD as the most accurate. The concept presented here grew out
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> of earlier, project‑specific implementations of AD‑based uncertainty
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> propagation. AD workflows were instrumental within the [FIDUCEO](https://www.fiduceo.eu)
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> project to enable the multi‑mission remote sensing calibration that
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> underpins Earth climate data records
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> ([Quast et al. 2019](https://doi.org/10.3390/rs11050480);
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> [Giering et al., 2019](https://doi.org/10.3390/rs11091002)).
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> [NPL Report CMSC 26/03](https://eprintspublications.npl.co.uk/2828/1/cmsc26.pdf)
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> ranks AD as the most accurate.
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## Synopsis
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