Global validation of columnar water vapor derived from EOS MODIS-MAIAC algorithm against the ground-based AERONET observations ...
The water vapor is a relevant greenhouse gas in the Earth's climate system, and satellite products become one of the most effective way to characterize and monitor the columnar water vapor (CWV) content at global scale. Recently, a new product (MCD19) was released as part of MODIS (Moderate Res...
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ftdatacite:10.13016/m2kgvg-vjye 2023-08-27T04:03:32+02:00 Global validation of columnar water vapor derived from EOS MODIS-MAIAC algorithm against the ground-based AERONET observations ... Martins, Vitor S. Lyapustin, Alexei Wang, Yujie Giles, David M. Smirnov, Alexander Slutsker, Ilya Korkin, Sergey 2019 https://dx.doi.org/10.13016/m2kgvg-vjye https://mdsoar.org/handle/11603/28817 unknown Elsevier 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/ article CreativeWork 2019 ftdatacite https://doi.org/10.13016/m2kgvg-vjye 2023-08-07T09:00:01Z The water vapor is a relevant greenhouse gas in the Earth's climate system, and satellite products become one of the most effective way to characterize and monitor the columnar water vapor (CWV) content at global scale. Recently, a new product (MCD19) was released as part of MODIS (Moderate Resolution Imaging Spectroradiometer) Collection 6 (C6). This operational product from Multi-Angle Implementation for Atmospheric Correction (MAIAC) algorithm includes a high 1 km resolution CWV retrievals. This study presents the first global validation of MAIAC C6 CWV obtained from MODIS MCD19A2 product. This evaluation was performed using Aerosol Robotic Network (AERONET) observations at 265 sites (2000–2017). Overall, the results show a good agreement between MAIAC/AERONET CWV retrievals, with correlation coefficient higher than 0.95 and RMS error lower than 0.250 cm. The binned error analysis revealed an underestimation (~10%) of Aqua CWV retrievals with negative bias for CWV higher than 3.0 cm. In contrast, Terra ... Article in Journal/Newspaper Aerosol Robotic Network DataCite Metadata Store (German National Library of Science and Technology) |
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The water vapor is a relevant greenhouse gas in the Earth's climate system, and satellite products become one of the most effective way to characterize and monitor the columnar water vapor (CWV) content at global scale. Recently, a new product (MCD19) was released as part of MODIS (Moderate Resolution Imaging Spectroradiometer) Collection 6 (C6). This operational product from Multi-Angle Implementation for Atmospheric Correction (MAIAC) algorithm includes a high 1 km resolution CWV retrievals. This study presents the first global validation of MAIAC C6 CWV obtained from MODIS MCD19A2 product. This evaluation was performed using Aerosol Robotic Network (AERONET) observations at 265 sites (2000–2017). Overall, the results show a good agreement between MAIAC/AERONET CWV retrievals, with correlation coefficient higher than 0.95 and RMS error lower than 0.250 cm. The binned error analysis revealed an underestimation (~10%) of Aqua CWV retrievals with negative bias for CWV higher than 3.0 cm. In contrast, Terra ... |
format |
Article in Journal/Newspaper |
author |
Martins, Vitor S. Lyapustin, Alexei Wang, Yujie Giles, David M. Smirnov, Alexander Slutsker, Ilya Korkin, Sergey |
spellingShingle |
Martins, Vitor S. Lyapustin, Alexei Wang, Yujie Giles, David M. Smirnov, Alexander Slutsker, Ilya Korkin, Sergey Global validation of columnar water vapor derived from EOS MODIS-MAIAC algorithm against the ground-based AERONET observations ... |
author_facet |
Martins, Vitor S. Lyapustin, Alexei Wang, Yujie Giles, David M. Smirnov, Alexander Slutsker, Ilya Korkin, Sergey |
author_sort |
Martins, Vitor S. |
title |
Global validation of columnar water vapor derived from EOS MODIS-MAIAC algorithm against the ground-based AERONET observations ... |
title_short |
Global validation of columnar water vapor derived from EOS MODIS-MAIAC algorithm against the ground-based AERONET observations ... |
title_full |
Global validation of columnar water vapor derived from EOS MODIS-MAIAC algorithm against the ground-based AERONET observations ... |
title_fullStr |
Global validation of columnar water vapor derived from EOS MODIS-MAIAC algorithm against the ground-based AERONET observations ... |
title_full_unstemmed |
Global validation of columnar water vapor derived from EOS MODIS-MAIAC algorithm against the ground-based AERONET observations ... |
title_sort |
global validation of columnar water vapor derived from eos modis-maiac algorithm against the ground-based aeronet observations ... |
publisher |
Elsevier |
publishDate |
2019 |
url |
https://dx.doi.org/10.13016/m2kgvg-vjye https://mdsoar.org/handle/11603/28817 |
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/m2kgvg-vjye |
_version_ |
1775350927472984064 |