An 11-year global gridded aerosol optical thickness reanalysis (v1.0) for atmospheric and climate sciences

While stand alone satellite and model aerosol products see wide utilization, there is a significant need in numerous atmospheric and climate applications for a fused product on a regular grid. Aerosol data assimilation is an operational reality at numerous centers, and like meteorological reanalyses...

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Published in:Geoscientific Model Development
Main Authors: Lynch, Peng, Reid, Jeffrey S., Westphal, Douglas L., Zhang, Jianglong, Hogan, Timothy F., Hyer, Edward J., Curtis, Cynthia A., Hegg, Dean A., Shi, Yingxi, Campbell, James R., Rubin, Juli I., Sessions, Walter R., Turk, F. Joseph, Walker, Annette L.
Format: Text
Language:English
Published: 2018
Subjects:
Online Access:https://doi.org/10.5194/gmd-9-1489-2016
https://gmd.copernicus.org/articles/9/1489/2016/
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spelling ftcopernicus:oai:publications.copernicus.org:gmd32506 2023-05-15T13:07:09+02:00 An 11-year global gridded aerosol optical thickness reanalysis (v1.0) for atmospheric and climate sciences Lynch, Peng Reid, Jeffrey S. Westphal, Douglas L. Zhang, Jianglong Hogan, Timothy F. Hyer, Edward J. Curtis, Cynthia A. Hegg, Dean A. Shi, Yingxi Campbell, James R. Rubin, Juli I. Sessions, Walter R. Turk, F. Joseph Walker, Annette L. 2018-09-27 application/pdf https://doi.org/10.5194/gmd-9-1489-2016 https://gmd.copernicus.org/articles/9/1489/2016/ eng eng doi:10.5194/gmd-9-1489-2016 https://gmd.copernicus.org/articles/9/1489/2016/ eISSN: 1991-9603 Text 2018 ftcopernicus https://doi.org/10.5194/gmd-9-1489-2016 2020-07-20T16:24:10Z While stand alone satellite and model aerosol products see wide utilization, there is a significant need in numerous atmospheric and climate applications for a fused product on a regular grid. Aerosol data assimilation is an operational reality at numerous centers, and like meteorological reanalyses, aerosol reanalyses will see significant use in the near future. Here we present a standardized 2003–2013 global 1 × 1° and 6-hourly modal aerosol optical thickness (AOT) reanalysis product. This data set can be applied to basic and applied Earth system science studies of significant aerosol events, aerosol impacts on numerical weather prediction, and electro-optical propagation and sensor performance, among other uses. This paper describes the science of how to develop and score an aerosol reanalysis product. This reanalysis utilizes a modified Navy Aerosol Analysis and Prediction System (NAAPS) at its core and assimilates quality controlled retrievals of AOT from the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua and the Multi-angle Imaging SpectroRadiometer (MISR) on Terra. The aerosol source functions, including dust and smoke, were regionally tuned to obtain the best match between the model fine- and coarse-mode AOTs and the Aerosol Robotic Network (AERONET) AOTs. Other model processes, including deposition, were tuned to minimize the AOT difference between the model and satellite AOT. Aerosol wet deposition in the tropics is driven with satellite-retrieved precipitation, rather than the model field. The final reanalyzed fine- and coarse-mode AOT at 550 nm is shown to have good agreement with AERONET observations, with global mean root mean square error around 0.1 for both fine- and coarse-mode AOTs. This paper includes a discussion of issues particular to aerosol reanalyses that make them distinct from standard meteorological reanalyses, considerations for extending such a reanalysis outside of the NASA A-Train era, and examples of how the aerosol reanalysis can be applied or fused with other model or remote sensing products. Finally, the reanalysis is evaluated in comparison with other available studies of aerosol trends, and the implications of this comparison are discussed. Text Aerosol Robotic Network Copernicus Publications: E-Journals Geoscientific Model Development 9 4 1489 1522
institution Open Polar
collection Copernicus Publications: E-Journals
op_collection_id ftcopernicus
language English
description While stand alone satellite and model aerosol products see wide utilization, there is a significant need in numerous atmospheric and climate applications for a fused product on a regular grid. Aerosol data assimilation is an operational reality at numerous centers, and like meteorological reanalyses, aerosol reanalyses will see significant use in the near future. Here we present a standardized 2003–2013 global 1 × 1° and 6-hourly modal aerosol optical thickness (AOT) reanalysis product. This data set can be applied to basic and applied Earth system science studies of significant aerosol events, aerosol impacts on numerical weather prediction, and electro-optical propagation and sensor performance, among other uses. This paper describes the science of how to develop and score an aerosol reanalysis product. This reanalysis utilizes a modified Navy Aerosol Analysis and Prediction System (NAAPS) at its core and assimilates quality controlled retrievals of AOT from the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua and the Multi-angle Imaging SpectroRadiometer (MISR) on Terra. The aerosol source functions, including dust and smoke, were regionally tuned to obtain the best match between the model fine- and coarse-mode AOTs and the Aerosol Robotic Network (AERONET) AOTs. Other model processes, including deposition, were tuned to minimize the AOT difference between the model and satellite AOT. Aerosol wet deposition in the tropics is driven with satellite-retrieved precipitation, rather than the model field. The final reanalyzed fine- and coarse-mode AOT at 550 nm is shown to have good agreement with AERONET observations, with global mean root mean square error around 0.1 for both fine- and coarse-mode AOTs. This paper includes a discussion of issues particular to aerosol reanalyses that make them distinct from standard meteorological reanalyses, considerations for extending such a reanalysis outside of the NASA A-Train era, and examples of how the aerosol reanalysis can be applied or fused with other model or remote sensing products. Finally, the reanalysis is evaluated in comparison with other available studies of aerosol trends, and the implications of this comparison are discussed.
format Text
author Lynch, Peng
Reid, Jeffrey S.
Westphal, Douglas L.
Zhang, Jianglong
Hogan, Timothy F.
Hyer, Edward J.
Curtis, Cynthia A.
Hegg, Dean A.
Shi, Yingxi
Campbell, James R.
Rubin, Juli I.
Sessions, Walter R.
Turk, F. Joseph
Walker, Annette L.
spellingShingle Lynch, Peng
Reid, Jeffrey S.
Westphal, Douglas L.
Zhang, Jianglong
Hogan, Timothy F.
Hyer, Edward J.
Curtis, Cynthia A.
Hegg, Dean A.
Shi, Yingxi
Campbell, James R.
Rubin, Juli I.
Sessions, Walter R.
Turk, F. Joseph
Walker, Annette L.
An 11-year global gridded aerosol optical thickness reanalysis (v1.0) for atmospheric and climate sciences
author_facet Lynch, Peng
Reid, Jeffrey S.
Westphal, Douglas L.
Zhang, Jianglong
Hogan, Timothy F.
Hyer, Edward J.
Curtis, Cynthia A.
Hegg, Dean A.
Shi, Yingxi
Campbell, James R.
Rubin, Juli I.
Sessions, Walter R.
Turk, F. Joseph
Walker, Annette L.
author_sort Lynch, Peng
title An 11-year global gridded aerosol optical thickness reanalysis (v1.0) for atmospheric and climate sciences
title_short An 11-year global gridded aerosol optical thickness reanalysis (v1.0) for atmospheric and climate sciences
title_full An 11-year global gridded aerosol optical thickness reanalysis (v1.0) for atmospheric and climate sciences
title_fullStr An 11-year global gridded aerosol optical thickness reanalysis (v1.0) for atmospheric and climate sciences
title_full_unstemmed An 11-year global gridded aerosol optical thickness reanalysis (v1.0) for atmospheric and climate sciences
title_sort 11-year global gridded aerosol optical thickness reanalysis (v1.0) for atmospheric and climate sciences
publishDate 2018
url https://doi.org/10.5194/gmd-9-1489-2016
https://gmd.copernicus.org/articles/9/1489/2016/
genre Aerosol Robotic Network
genre_facet Aerosol Robotic Network
op_source eISSN: 1991-9603
op_relation doi:10.5194/gmd-9-1489-2016
https://gmd.copernicus.org/articles/9/1489/2016/
op_doi https://doi.org/10.5194/gmd-9-1489-2016
container_title Geoscientific Model Development
container_volume 9
container_issue 4
container_start_page 1489
op_container_end_page 1522
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