Updated MISR over-water research aerosol retrieval algorithm – Part 2: A multi-angle aerosol retrieval algorithm for shallow, turbid, oligotrophic, and eutrophic waters
Coastal waters serve as transport pathways to the ocean for all agricultural and other runoff from terrestrial sources, and many are the sites for upwelling of nutrient-rich, deep water; they are also some of the most biologically productive on Earth. Estimating the impact coastal waters have on the...
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ftdoajarticles:oai:doaj.org/article:47ddd7ad0cd645f3881e3a43ea0c32e0 2023-05-15T13:06:59+02:00 Updated MISR over-water research aerosol retrieval algorithm – Part 2: A multi-angle aerosol retrieval algorithm for shallow, turbid, oligotrophic, and eutrophic waters J. A. Limbacher R. A. Kahn 2019-01-01T00:00:00Z https://doi.org/10.5194/amt-12-675-2019 https://doaj.org/article/47ddd7ad0cd645f3881e3a43ea0c32e0 EN eng Copernicus Publications https://www.atmos-meas-tech.net/12/675/2019/amt-12-675-2019.pdf https://doaj.org/toc/1867-1381 https://doaj.org/toc/1867-8548 doi:10.5194/amt-12-675-2019 1867-1381 1867-8548 https://doaj.org/article/47ddd7ad0cd645f3881e3a43ea0c32e0 Atmospheric Measurement Techniques, Vol 12, Pp 675-689 (2019) Environmental engineering TA170-171 Earthwork. Foundations TA715-787 article 2019 ftdoajarticles https://doi.org/10.5194/amt-12-675-2019 2022-12-31T10:03:54Z Coastal waters serve as transport pathways to the ocean for all agricultural and other runoff from terrestrial sources, and many are the sites for upwelling of nutrient-rich, deep water; they are also some of the most biologically productive on Earth. Estimating the impact coastal waters have on the global carbon budget requires relating satellite-based remote-sensing retrievals of biological productivity (e.g., chlorophyll a concentration) to in situ measurements taken in near-surface waters. The Multi-angle Imaging SpectroRadiometer (MISR) can uniquely constrain the “atmospheric correction” needed to derive ocean color from remote-sensing imagers. Here, we retrieve aerosol amount and type from MISR over all types of water. The primary limitation is an upper bound on aerosol optical depth (AOD), as the algorithm must be able to distinguish the surface. This updated MISR research aerosol retrieval algorithm (RA) also assumes that light reflection by the underlying ocean surface is Lambertian. The RA computes the ocean surface reflectance ( R rs ) analytically for a given AOD, aerosol optical model, and wind speed. We provide retrieval examples over shallow, turbid, and eutrophic waters and introduce a productivity and turbidity index (PTI), calculated from retrieved spectral R rs , that distinguished water types (similar to the the normalized difference vegetation index, NDVI, over land). We also validate the new algorithm by comparing spectral AOD and Ångström exponent (ANG) results with 2419 collocated AErosol RObotic NETwork (AERONET) observations. For AERONET 558 nm interpolated AOD < 1.0, the root-mean-square error (RMSE) is 0.04 and linear correlation coefficient is 0.95. For the 502 cloud-free MISR and AERONET collocations with an AERONET AOD > 0.20, the ANG RMSE is 0.25 and r is 0.89. Although MISR RA AOD retrieval quality does not appear to be substantially impacted by the presence of turbid water, the MISR-RA-retrieved Ångström exponent seems to suffer from increased uncertainty under such ... Article in Journal/Newspaper Aerosol Robotic Network Directory of Open Access Journals: DOAJ Articles Atmospheric Measurement Techniques 12 1 675 689 |
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Open Polar |
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Directory of Open Access Journals: DOAJ Articles |
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ftdoajarticles |
language |
English |
topic |
Environmental engineering TA170-171 Earthwork. Foundations TA715-787 |
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Environmental engineering TA170-171 Earthwork. Foundations TA715-787 J. A. Limbacher R. A. Kahn Updated MISR over-water research aerosol retrieval algorithm – Part 2: A multi-angle aerosol retrieval algorithm for shallow, turbid, oligotrophic, and eutrophic waters |
topic_facet |
Environmental engineering TA170-171 Earthwork. Foundations TA715-787 |
description |
Coastal waters serve as transport pathways to the ocean for all agricultural and other runoff from terrestrial sources, and many are the sites for upwelling of nutrient-rich, deep water; they are also some of the most biologically productive on Earth. Estimating the impact coastal waters have on the global carbon budget requires relating satellite-based remote-sensing retrievals of biological productivity (e.g., chlorophyll a concentration) to in situ measurements taken in near-surface waters. The Multi-angle Imaging SpectroRadiometer (MISR) can uniquely constrain the “atmospheric correction” needed to derive ocean color from remote-sensing imagers. Here, we retrieve aerosol amount and type from MISR over all types of water. The primary limitation is an upper bound on aerosol optical depth (AOD), as the algorithm must be able to distinguish the surface. This updated MISR research aerosol retrieval algorithm (RA) also assumes that light reflection by the underlying ocean surface is Lambertian. The RA computes the ocean surface reflectance ( R rs ) analytically for a given AOD, aerosol optical model, and wind speed. We provide retrieval examples over shallow, turbid, and eutrophic waters and introduce a productivity and turbidity index (PTI), calculated from retrieved spectral R rs , that distinguished water types (similar to the the normalized difference vegetation index, NDVI, over land). We also validate the new algorithm by comparing spectral AOD and Ångström exponent (ANG) results with 2419 collocated AErosol RObotic NETwork (AERONET) observations. For AERONET 558 nm interpolated AOD < 1.0, the root-mean-square error (RMSE) is 0.04 and linear correlation coefficient is 0.95. For the 502 cloud-free MISR and AERONET collocations with an AERONET AOD > 0.20, the ANG RMSE is 0.25 and r is 0.89. Although MISR RA AOD retrieval quality does not appear to be substantially impacted by the presence of turbid water, the MISR-RA-retrieved Ångström exponent seems to suffer from increased uncertainty under such ... |
format |
Article in Journal/Newspaper |
author |
J. A. Limbacher R. A. Kahn |
author_facet |
J. A. Limbacher R. A. Kahn |
author_sort |
J. A. Limbacher |
title |
Updated MISR over-water research aerosol retrieval algorithm – Part 2: A multi-angle aerosol retrieval algorithm for shallow, turbid, oligotrophic, and eutrophic waters |
title_short |
Updated MISR over-water research aerosol retrieval algorithm – Part 2: A multi-angle aerosol retrieval algorithm for shallow, turbid, oligotrophic, and eutrophic waters |
title_full |
Updated MISR over-water research aerosol retrieval algorithm – Part 2: A multi-angle aerosol retrieval algorithm for shallow, turbid, oligotrophic, and eutrophic waters |
title_fullStr |
Updated MISR over-water research aerosol retrieval algorithm – Part 2: A multi-angle aerosol retrieval algorithm for shallow, turbid, oligotrophic, and eutrophic waters |
title_full_unstemmed |
Updated MISR over-water research aerosol retrieval algorithm – Part 2: A multi-angle aerosol retrieval algorithm for shallow, turbid, oligotrophic, and eutrophic waters |
title_sort |
updated misr over-water research aerosol retrieval algorithm – part 2: a multi-angle aerosol retrieval algorithm for shallow, turbid, oligotrophic, and eutrophic waters |
publisher |
Copernicus Publications |
publishDate |
2019 |
url |
https://doi.org/10.5194/amt-12-675-2019 https://doaj.org/article/47ddd7ad0cd645f3881e3a43ea0c32e0 |
genre |
Aerosol Robotic Network |
genre_facet |
Aerosol Robotic Network |
op_source |
Atmospheric Measurement Techniques, Vol 12, Pp 675-689 (2019) |
op_relation |
https://www.atmos-meas-tech.net/12/675/2019/amt-12-675-2019.pdf https://doaj.org/toc/1867-1381 https://doaj.org/toc/1867-8548 doi:10.5194/amt-12-675-2019 1867-1381 1867-8548 https://doaj.org/article/47ddd7ad0cd645f3881e3a43ea0c32e0 |
op_doi |
https://doi.org/10.5194/amt-12-675-2019 |
container_title |
Atmospheric Measurement Techniques |
container_volume |
12 |
container_issue |
1 |
container_start_page |
675 |
op_container_end_page |
689 |
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1766030162277695488 |