A review and framework for the evaluation of pixel-level uncertainty estimates in satellite aerosol remote sensing
Recent years have seen the increasing inclusion of per-retrieval prognostic (predictive) uncertainty estimates within satellite aerosol optical depth (AOD) data sets, providing users with quantitative tools to assist in the optimal use of these data. Prognostic estimates contrast with diagnostic (i....
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ftdlr:oai:elib.dlr.de:134299 2023-05-15T13:07:09+02:00 A review and framework for the evaluation of pixel-level uncertainty estimates in satellite aerosol remote sensing Sayer, A.M. Govaerts, Yves Kolmonen, Pekka Lipponen, Antti Luffarelli, Marta Mielonen, Tero Patadia, Falguni Popp, Thomas Povey, Adam Stebel, Kerstin Witek, Marcin l. 2020 application/pdf https://elib.dlr.de/134299/ https://elib.dlr.de/134299/1/amt-13-373-2020%5B1%5D.pdf https://www.atmos-meas-tech.net/13/373/2020/ en eng Copernicus Publications https://elib.dlr.de/134299/1/amt-13-373-2020%5B1%5D.pdf Sayer, A.M. und Govaerts, Yves und Kolmonen, Pekka und Lipponen, Antti und Luffarelli, Marta und Mielonen, Tero und Patadia, Falguni und Popp, Thomas und Povey, Adam und Stebel, Kerstin und Witek, Marcin l. (2020) A review and framework for the evaluation of pixel-level uncertainty estimates in satellite aerosol remote sensing. Atmospheric Measurement Techniques (AMT), 13, Seiten 373-404. Copernicus Publications. DOI:10.5194/amt-13-373-2020 <https://doi.org/10.5194/amt-13-373-2020> ISSN 1867-1381 cc_by CC-BY Atmosphäre Zeitschriftenbeitrag PeerReviewed 2020 ftdlr https://doi.org/10.5194/amt-13-373-2020 2021-03-08T00:03:52Z Recent years have seen the increasing inclusion of per-retrieval prognostic (predictive) uncertainty estimates within satellite aerosol optical depth (AOD) data sets, providing users with quantitative tools to assist in the optimal use of these data. Prognostic estimates contrast with diagnostic (i.e. relative to some external truth) ones, which are typically obtained using sensitivity and/or validation analyses. Up to now, however, the quality of these uncertainty estimates has not been routinely assessed. This study presents a review of existing prognostic and diagnostic approaches for quantifying uncertainty in satellite AOD retrievals, and it presents a general framework to evaluate them based on the expected statistical properties of ensembles of estimated uncertainties and actual retrieval errors. It is hoped that this framework will be adopted as a complement to existing AOD validation exercises; it is not restricted to AOD and can in principle be applied to other quantities for which a reference validation data set is available. This framework is then applied to assess the uncertainties provided by several satellite data sets (seven over land, five over water), which draw on methods from the empirical to sensitivity analyses to formal error propagation, at 12 Aerosol Robotic Network (AERONET) sites. The AERONET sites are divided into those for which it is expected that the techniques will perform well and those for which some complexity about the site may provide a more severe test. Overall, all techniques show some skill in that larger estimated uncertainties are generally associated with larger observed errors, although they are sometimes poorly calibrated (i.e. too small or too large in magnitude). No technique uniformly performs best. For powerful formal uncertainty propagation approaches such as optimal estimation, the results illustrate some of the difficulties in appropriate population of the covariance matrices required by the technique. When the data sets are confronted by a situation strongly counter to the retrieval forward model (e.g. potentially mixed land-water surfaces or aerosol optical properties outside the family of assumptions), some algorithms fail to provide a retrieval, while others do but with a quantitatively unreliable uncertainty estimate. The discussion suggests paths forward for the refinement of these techniques. Other Non-Article Part of Journal/Newspaper Aerosol Robotic Network German Aerospace Center: elib - DLR electronic library Atmospheric Measurement Techniques 13 2 373 404 |
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German Aerospace Center: elib - DLR electronic library |
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English |
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Atmosphäre |
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Atmosphäre Sayer, A.M. Govaerts, Yves Kolmonen, Pekka Lipponen, Antti Luffarelli, Marta Mielonen, Tero Patadia, Falguni Popp, Thomas Povey, Adam Stebel, Kerstin Witek, Marcin l. A review and framework for the evaluation of pixel-level uncertainty estimates in satellite aerosol remote sensing |
topic_facet |
Atmosphäre |
description |
Recent years have seen the increasing inclusion of per-retrieval prognostic (predictive) uncertainty estimates within satellite aerosol optical depth (AOD) data sets, providing users with quantitative tools to assist in the optimal use of these data. Prognostic estimates contrast with diagnostic (i.e. relative to some external truth) ones, which are typically obtained using sensitivity and/or validation analyses. Up to now, however, the quality of these uncertainty estimates has not been routinely assessed. This study presents a review of existing prognostic and diagnostic approaches for quantifying uncertainty in satellite AOD retrievals, and it presents a general framework to evaluate them based on the expected statistical properties of ensembles of estimated uncertainties and actual retrieval errors. It is hoped that this framework will be adopted as a complement to existing AOD validation exercises; it is not restricted to AOD and can in principle be applied to other quantities for which a reference validation data set is available. This framework is then applied to assess the uncertainties provided by several satellite data sets (seven over land, five over water), which draw on methods from the empirical to sensitivity analyses to formal error propagation, at 12 Aerosol Robotic Network (AERONET) sites. The AERONET sites are divided into those for which it is expected that the techniques will perform well and those for which some complexity about the site may provide a more severe test. Overall, all techniques show some skill in that larger estimated uncertainties are generally associated with larger observed errors, although they are sometimes poorly calibrated (i.e. too small or too large in magnitude). No technique uniformly performs best. For powerful formal uncertainty propagation approaches such as optimal estimation, the results illustrate some of the difficulties in appropriate population of the covariance matrices required by the technique. When the data sets are confronted by a situation strongly counter to the retrieval forward model (e.g. potentially mixed land-water surfaces or aerosol optical properties outside the family of assumptions), some algorithms fail to provide a retrieval, while others do but with a quantitatively unreliable uncertainty estimate. The discussion suggests paths forward for the refinement of these techniques. |
format |
Other Non-Article Part of Journal/Newspaper |
author |
Sayer, A.M. Govaerts, Yves Kolmonen, Pekka Lipponen, Antti Luffarelli, Marta Mielonen, Tero Patadia, Falguni Popp, Thomas Povey, Adam Stebel, Kerstin Witek, Marcin l. |
author_facet |
Sayer, A.M. Govaerts, Yves Kolmonen, Pekka Lipponen, Antti Luffarelli, Marta Mielonen, Tero Patadia, Falguni Popp, Thomas Povey, Adam Stebel, Kerstin Witek, Marcin l. |
author_sort |
Sayer, A.M. |
title |
A review and framework for the evaluation of pixel-level uncertainty estimates in satellite aerosol remote sensing |
title_short |
A review and framework for the evaluation of pixel-level uncertainty estimates in satellite aerosol remote sensing |
title_full |
A review and framework for the evaluation of pixel-level uncertainty estimates in satellite aerosol remote sensing |
title_fullStr |
A review and framework for the evaluation of pixel-level uncertainty estimates in satellite aerosol remote sensing |
title_full_unstemmed |
A review and framework for the evaluation of pixel-level uncertainty estimates in satellite aerosol remote sensing |
title_sort |
review and framework for the evaluation of pixel-level uncertainty estimates in satellite aerosol remote sensing |
publisher |
Copernicus Publications |
publishDate |
2020 |
url |
https://elib.dlr.de/134299/ https://elib.dlr.de/134299/1/amt-13-373-2020%5B1%5D.pdf https://www.atmos-meas-tech.net/13/373/2020/ |
genre |
Aerosol Robotic Network |
genre_facet |
Aerosol Robotic Network |
op_relation |
https://elib.dlr.de/134299/1/amt-13-373-2020%5B1%5D.pdf Sayer, A.M. und Govaerts, Yves und Kolmonen, Pekka und Lipponen, Antti und Luffarelli, Marta und Mielonen, Tero und Patadia, Falguni und Popp, Thomas und Povey, Adam und Stebel, Kerstin und Witek, Marcin l. (2020) A review and framework for the evaluation of pixel-level uncertainty estimates in satellite aerosol remote sensing. Atmospheric Measurement Techniques (AMT), 13, Seiten 373-404. Copernicus Publications. DOI:10.5194/amt-13-373-2020 <https://doi.org/10.5194/amt-13-373-2020> ISSN 1867-1381 |
op_rights |
cc_by |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.5194/amt-13-373-2020 |
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Atmospheric Measurement Techniques |
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13 |
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2 |
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1766037065788555264 |