Evaluation of NASA Deep Blue/SOAR aerosol retrieval algorithms applied to AVHRR measurements

The Deep Blue (DB) and Satellite Ocean Aerosol Retrieval (SOAR) algorithms have previously been applied to observations from sen-sors like the Moderate Resolution Imaging Spectroradiometers (MODIS) and Sea-viewing Wide Field-of-view Sensor (SeaWiFS) to provide records of mid-visible aerosol optical...

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Published in:Journal of Geophysical Research: Atmospheres
Main Authors: Sayer, A. M., Hsu, N. C., Lee, J., Carletta, N., Chen, S.-H., Smirnov, A.
Format: Text
Language:English
Published: 2017
Subjects:
Online Access:http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6101972/
http://www.ncbi.nlm.nih.gov/pubmed/30140601
https://doi.org/10.1002/2017JD026934
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spelling ftpubmed:oai:pubmedcentral.nih.gov:6101972 2023-05-15T13:06:20+02:00 Evaluation of NASA Deep Blue/SOAR aerosol retrieval algorithms applied to AVHRR measurements Sayer, A. M. Hsu, N. C. Lee, J. Carletta, N. Chen, S.-H. Smirnov, A. 2017-07-20 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6101972/ http://www.ncbi.nlm.nih.gov/pubmed/30140601 https://doi.org/10.1002/2017JD026934 en eng http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6101972/ http://www.ncbi.nlm.nih.gov/pubmed/30140601 http://dx.doi.org/10.1002/2017JD026934 Article Text 2017 ftpubmed https://doi.org/10.1002/2017JD026934 2018-09-02T00:42:17Z The Deep Blue (DB) and Satellite Ocean Aerosol Retrieval (SOAR) algorithms have previously been applied to observations from sen-sors like the Moderate Resolution Imaging Spectroradiometers (MODIS) and Sea-viewing Wide Field-of-view Sensor (SeaWiFS) to provide records of mid-visible aerosol optical depth (AOD) and related quantities over land and ocean surfaces respectively. Recently, DB and SOAR have also been applied to Ad-vanced Very High Resolution Radiometer (AVHRR) observations from several platforms (NOAA11, NOAA14, and NOAA18), to demonstrate the potential for extending the DB and SOAR AOD records. This study provides an evaluation of the initial version (V001) of the resulting AVHRR-based AOD data set, including validation against Aerosol Robotic Network (AERONET) and ship-borne observations, and comparison against both other AVHRR AOD Research (GESTAR), Universities Space Research Association. records and MODIS/SeaWiFS products at select long-term AERONET sites. Although it is difficult to distil error characteristics into a simple expression, the results suggest that one standard deviation confidence intervals on retrieved AOD of ±(0.03+15%) over water and ±(0.05+25%) over land represent the typical level of uncertainty, with a tendency towards negative biases in high-AOD conditions, caused by a combination of algorithmic assumptions and sensor calibration issues. Most of the available validation data are for NOAA18 AVHRR, although performance appears to be similar for the NOAA11 and NOAA14 sensors as well. Text Aerosol Robotic Network PubMed Central (PMC) Journal of Geophysical Research: Atmospheres 122 18 9945 9967
institution Open Polar
collection PubMed Central (PMC)
op_collection_id ftpubmed
language English
topic Article
spellingShingle Article
Sayer, A. M.
Hsu, N. C.
Lee, J.
Carletta, N.
Chen, S.-H.
Smirnov, A.
Evaluation of NASA Deep Blue/SOAR aerosol retrieval algorithms applied to AVHRR measurements
topic_facet Article
description The Deep Blue (DB) and Satellite Ocean Aerosol Retrieval (SOAR) algorithms have previously been applied to observations from sen-sors like the Moderate Resolution Imaging Spectroradiometers (MODIS) and Sea-viewing Wide Field-of-view Sensor (SeaWiFS) to provide records of mid-visible aerosol optical depth (AOD) and related quantities over land and ocean surfaces respectively. Recently, DB and SOAR have also been applied to Ad-vanced Very High Resolution Radiometer (AVHRR) observations from several platforms (NOAA11, NOAA14, and NOAA18), to demonstrate the potential for extending the DB and SOAR AOD records. This study provides an evaluation of the initial version (V001) of the resulting AVHRR-based AOD data set, including validation against Aerosol Robotic Network (AERONET) and ship-borne observations, and comparison against both other AVHRR AOD Research (GESTAR), Universities Space Research Association. records and MODIS/SeaWiFS products at select long-term AERONET sites. Although it is difficult to distil error characteristics into a simple expression, the results suggest that one standard deviation confidence intervals on retrieved AOD of ±(0.03+15%) over water and ±(0.05+25%) over land represent the typical level of uncertainty, with a tendency towards negative biases in high-AOD conditions, caused by a combination of algorithmic assumptions and sensor calibration issues. Most of the available validation data are for NOAA18 AVHRR, although performance appears to be similar for the NOAA11 and NOAA14 sensors as well.
format Text
author Sayer, A. M.
Hsu, N. C.
Lee, J.
Carletta, N.
Chen, S.-H.
Smirnov, A.
author_facet Sayer, A. M.
Hsu, N. C.
Lee, J.
Carletta, N.
Chen, S.-H.
Smirnov, A.
author_sort Sayer, A. M.
title Evaluation of NASA Deep Blue/SOAR aerosol retrieval algorithms applied to AVHRR measurements
title_short Evaluation of NASA Deep Blue/SOAR aerosol retrieval algorithms applied to AVHRR measurements
title_full Evaluation of NASA Deep Blue/SOAR aerosol retrieval algorithms applied to AVHRR measurements
title_fullStr Evaluation of NASA Deep Blue/SOAR aerosol retrieval algorithms applied to AVHRR measurements
title_full_unstemmed Evaluation of NASA Deep Blue/SOAR aerosol retrieval algorithms applied to AVHRR measurements
title_sort evaluation of nasa deep blue/soar aerosol retrieval algorithms applied to avhrr measurements
publishDate 2017
url http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6101972/
http://www.ncbi.nlm.nih.gov/pubmed/30140601
https://doi.org/10.1002/2017JD026934
genre Aerosol Robotic Network
genre_facet Aerosol Robotic Network
op_relation http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6101972/
http://www.ncbi.nlm.nih.gov/pubmed/30140601
http://dx.doi.org/10.1002/2017JD026934
op_doi https://doi.org/10.1002/2017JD026934
container_title Journal of Geophysical Research: Atmospheres
container_volume 122
container_issue 18
container_start_page 9945
op_container_end_page 9967
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