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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ftdoajarticles:oai:doaj.org/article:edc7aede989f45dbbf02f8780d7bd9ce 2023-05-15T13:06:56+02:00 A review and framework for the evaluation of pixel-level uncertainty estimates in satellite aerosol remote sensing A. M. Sayer Y. Govaerts P. Kolmonen A. Lipponen M. Luffarelli T. Mielonen F. Patadia T. Popp A. C. Povey K. Stebel M. L. Witek 2020-02-01T00:00:00Z https://doi.org/10.5194/amt-13-373-2020 https://doaj.org/article/edc7aede989f45dbbf02f8780d7bd9ce EN eng Copernicus Publications https://www.atmos-meas-tech.net/13/373/2020/amt-13-373-2020.pdf https://doaj.org/toc/1867-1381 https://doaj.org/toc/1867-8548 doi:10.5194/amt-13-373-2020 1867-1381 1867-8548 https://doaj.org/article/edc7aede989f45dbbf02f8780d7bd9ce Atmospheric Measurement Techniques, Vol 13, Pp 373-404 (2020) Environmental engineering TA170-171 Earthwork. Foundations TA715-787 article 2020 ftdoajarticles https://doi.org/10.5194/amt-13-373-2020 2022-12-31T12:46:07Z 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 ... Article in Journal/Newspaper Aerosol Robotic Network Directory of Open Access Journals: DOAJ Articles Atmospheric Measurement Techniques 13 2 373 404 |
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Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Environmental engineering TA170-171 Earthwork. Foundations TA715-787 |
spellingShingle |
Environmental engineering TA170-171 Earthwork. Foundations TA715-787 A. M. Sayer Y. Govaerts P. Kolmonen A. Lipponen M. Luffarelli T. Mielonen F. Patadia T. Popp A. C. Povey K. Stebel M. L. Witek A review and framework for the evaluation of pixel-level uncertainty estimates in satellite aerosol remote sensing |
topic_facet |
Environmental engineering TA170-171 Earthwork. Foundations TA715-787 |
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 ... |
format |
Article in Journal/Newspaper |
author |
A. M. Sayer Y. Govaerts P. Kolmonen A. Lipponen M. Luffarelli T. Mielonen F. Patadia T. Popp A. C. Povey K. Stebel M. L. Witek |
author_facet |
A. M. Sayer Y. Govaerts P. Kolmonen A. Lipponen M. Luffarelli T. Mielonen F. Patadia T. Popp A. C. Povey K. Stebel M. L. Witek |
author_sort |
A. M. Sayer |
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://doi.org/10.5194/amt-13-373-2020 https://doaj.org/article/edc7aede989f45dbbf02f8780d7bd9ce |
genre |
Aerosol Robotic Network |
genre_facet |
Aerosol Robotic Network |
op_source |
Atmospheric Measurement Techniques, Vol 13, Pp 373-404 (2020) |
op_relation |
https://www.atmos-meas-tech.net/13/373/2020/amt-13-373-2020.pdf https://doaj.org/toc/1867-1381 https://doaj.org/toc/1867-8548 doi:10.5194/amt-13-373-2020 1867-1381 1867-8548 https://doaj.org/article/edc7aede989f45dbbf02f8780d7bd9ce |
op_doi |
https://doi.org/10.5194/amt-13-373-2020 |
container_title |
Atmospheric Measurement Techniques |
container_volume |
13 |
container_issue |
2 |
container_start_page |
373 |
op_container_end_page |
404 |
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1766027344910221312 |