An AeroCom–AeroSat study: intercomparison of satellite AOD datasets for aerosol model evaluation ...

Authors:- Nick Schutgens, Andrew M. Sayer,, Andreas Heckel, Christina Hsu, Hiren Jethva,, Gerrit de Leeuw, Peter J. T. Leonard, Robert C. Levy, Antti Lipponen, Alexei Lyapustin, Peter North, Thomas Popp, Caroline Poulsen,a, Virginia Sawyer,, Larisa Sogacheva, Gareth Thomas, Omar Torres, Yujie Wang,...

Full description

Bibliographic Details
Main Authors: Schutgens, Nick, Sayer, Andrew, Heckel, Andreas, Hsu, Christina, Wang, Yujie, Et Al
Format: Article in Journal/Newspaper
Language:English
Published: EGU 2020
Subjects:
Online Access:https://dx.doi.org/10.13016/m2ywui-rzvk
https://mdsoar.org/handle/11603/26239
id ftdatacite:10.13016/m2ywui-rzvk
record_format openpolar
spelling ftdatacite:10.13016/m2ywui-rzvk 2023-08-27T04:03:32+02:00 An AeroCom–AeroSat study: intercomparison of satellite AOD datasets for aerosol model evaluation ... Schutgens, Nick Sayer, Andrew Heckel, Andreas Hsu, Christina Wang, Yujie Et Al 2020 https://dx.doi.org/10.13016/m2ywui-rzvk https://mdsoar.org/handle/11603/26239 en eng EGU Public Domain Mark 1.0 This work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law. http://creativecommons.org/publicdomain/mark/1.0/ Text Collection article 2020 ftdatacite https://doi.org/10.13016/m2ywui-rzvk 2023-08-07T14:24:23Z Authors:- Nick Schutgens, Andrew M. Sayer,, Andreas Heckel, Christina Hsu, Hiren Jethva,, Gerrit de Leeuw, Peter J. T. Leonard, Robert C. Levy, Antti Lipponen, Alexei Lyapustin, Peter North, Thomas Popp, Caroline Poulsen,a, Virginia Sawyer,, Larisa Sogacheva, Gareth Thomas, Omar Torres, Yujie Wang, Stefan Kinne, Michael Schulz, and Philip Stier ... : To better understand and characterize current uncertainties in the important observational constraint of climate models of aerosol optical depth (AOD), we evaluate and intercompare 14 satellite products, representing nine different retrieval algorithm families using observations from five different sensors on six different platforms. The satellite products (super-observations consisting of 1◦ × 1 ◦ daily aggregated retrievals drawn from the years 2006, 2008 and 2010) are evaluated with AErosol RObotic NETwork (AERONET) and Maritime Aerosol Network (MAN) data. Results show that different products exhibit different regionally varying biases (both under- and overestimates) that may reach ±50 %, although a typical bias would be 15 %–25 % (depending on the product). In addition to these biases, the products exhibit random errors that can be 1.6 to 3 times as large. Most products show similar performance, although there are a few exceptions with either larger biases or larger random errors. The intercomparison of ... Article in Journal/Newspaper Aerosol Robotic Network DataCite Metadata Store (German National Library of Science and Technology) Andreas ENVELOPE(-60.729,-60.729,-64.008,-64.008) Levy ENVELOPE(-66.567,-66.567,-66.320,-66.320)
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language English
description Authors:- Nick Schutgens, Andrew M. Sayer,, Andreas Heckel, Christina Hsu, Hiren Jethva,, Gerrit de Leeuw, Peter J. T. Leonard, Robert C. Levy, Antti Lipponen, Alexei Lyapustin, Peter North, Thomas Popp, Caroline Poulsen,a, Virginia Sawyer,, Larisa Sogacheva, Gareth Thomas, Omar Torres, Yujie Wang, Stefan Kinne, Michael Schulz, and Philip Stier ... : To better understand and characterize current uncertainties in the important observational constraint of climate models of aerosol optical depth (AOD), we evaluate and intercompare 14 satellite products, representing nine different retrieval algorithm families using observations from five different sensors on six different platforms. The satellite products (super-observations consisting of 1◦ × 1 ◦ daily aggregated retrievals drawn from the years 2006, 2008 and 2010) are evaluated with AErosol RObotic NETwork (AERONET) and Maritime Aerosol Network (MAN) data. Results show that different products exhibit different regionally varying biases (both under- and overestimates) that may reach ±50 %, although a typical bias would be 15 %–25 % (depending on the product). In addition to these biases, the products exhibit random errors that can be 1.6 to 3 times as large. Most products show similar performance, although there are a few exceptions with either larger biases or larger random errors. The intercomparison of ...
format Article in Journal/Newspaper
author Schutgens, Nick
Sayer, Andrew
Heckel, Andreas
Hsu, Christina
Wang, Yujie
Et Al
spellingShingle Schutgens, Nick
Sayer, Andrew
Heckel, Andreas
Hsu, Christina
Wang, Yujie
Et Al
An AeroCom–AeroSat study: intercomparison of satellite AOD datasets for aerosol model evaluation ...
author_facet Schutgens, Nick
Sayer, Andrew
Heckel, Andreas
Hsu, Christina
Wang, Yujie
Et Al
author_sort Schutgens, Nick
title An AeroCom–AeroSat study: intercomparison of satellite AOD datasets for aerosol model evaluation ...
title_short An AeroCom–AeroSat study: intercomparison of satellite AOD datasets for aerosol model evaluation ...
title_full An AeroCom–AeroSat study: intercomparison of satellite AOD datasets for aerosol model evaluation ...
title_fullStr An AeroCom–AeroSat study: intercomparison of satellite AOD datasets for aerosol model evaluation ...
title_full_unstemmed An AeroCom–AeroSat study: intercomparison of satellite AOD datasets for aerosol model evaluation ...
title_sort aerocom–aerosat study: intercomparison of satellite aod datasets for aerosol model evaluation ...
publisher EGU
publishDate 2020
url https://dx.doi.org/10.13016/m2ywui-rzvk
https://mdsoar.org/handle/11603/26239
long_lat ENVELOPE(-60.729,-60.729,-64.008,-64.008)
ENVELOPE(-66.567,-66.567,-66.320,-66.320)
geographic Andreas
Levy
geographic_facet Andreas
Levy
genre Aerosol Robotic Network
genre_facet Aerosol Robotic Network
op_rights Public Domain Mark 1.0
This work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.
http://creativecommons.org/publicdomain/mark/1.0/
op_doi https://doi.org/10.13016/m2ywui-rzvk
_version_ 1775351114306158592