 |
| Titel |
Known and unknown unknowns: uncertainty estimation in satellite remote sensing |
| VerfasserIn |
A. C. Povey, R. G. Grainger |
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| ISSN |
1867-1381
|
| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Measurement Techniques ; 8, no. 11 ; Nr. 8, no. 11 (2015-11-06), S.4699-4718 |
| Datensatznummer |
250116679
|
| Publikation (Nr.) |
 copernicus.org/amt-8-4699-2015.pdf |
|
|
|
|
|
| Zusammenfassung |
This paper discusses a best-practice representation of uncertainty in
satellite remote sensing data. An estimate of uncertainty is necessary to
make appropriate use of the information conveyed by a measurement.
Traditional error propagation quantifies the uncertainty in a measurement due
to well-understood perturbations in a measurement and in auxiliary data – known, quantified "unknowns". The under-constrained nature of most satellite
remote sensing observations requires the use of various approximations and
assumptions that produce non-linear systematic errors that are not readily
assessed – known, unquantifiable "unknowns". Additional errors result from
the inability to resolve all scales of variation in the measured quantity –
unknown "unknowns". The latter two categories of error are dominant in
under-constrained remote sensing retrievals, and the difficulty of their
quantification limits the utility of existing uncertainty estimates,
degrading confidence in such data.
This paper proposes the use of ensemble techniques to present multiple
self-consistent realisations of a data set as a means of depicting
unquantified uncertainties. These are generated using various systems
(different algorithms or forward models) believed to be appropriate to the
conditions observed. Benefiting from the experience of the climate modelling
community, an ensemble provides a user with a more complete representation of
the uncertainty as understood by the data producer and greater freedom to
consider different realisations of the data. |
| |
|
| Teil von |
|
|
|
|
|
|
|
|