Validation of aerosol products from AATSR and MERIS/AATSR synergy algorithms—Part 1: Global Evaluation.
Journal article
Che, Yahui, Mei, Linlu, Xue, Yong, Guang, Jie, She, Lu and Li, Ying 2018. Validation of aerosol products from AATSR and MERIS/AATSR synergy algorithms—Part 1: Global Evaluation. Remote Sensing. https://doi.org/10.3390/rs10091414
| Authors | Che, Yahui, Mei, Linlu, Xue, Yong, Guang, Jie, She, Lu and Li, Ying |
|---|---|
| Abstract | The European Space Agency’s (ESA’s) Aerosol Climate Change Initiative (CCI) project intends to exploit the robust, long-term, global aerosol optical thickness (AOT) dataset from Europe’s satellite observations. Newly released Swansea University (SU) aerosol products include AATSR retrieval and synergy between AATSR and MERIS with a spatial resolution of 10 km. In this study, both AATSR retrieval (SU/AATSR) and AATSR/MERIS synergy retrieval (SU/synergy) products are validated globally using Aerosol Robotic Network (AERONET) observations for March, June, September, and December 2008, as suggested by the Aerosol-CCI project. The analysis includes the impacts of cloud screening, surface parameterization, and aerosol type selections for two products under different surface and atmospheric conditions. The comparison between SU/AATSR and SU/synergy shows very accurate and consistent global patterns. The global evaluation using AERONET shows that the SU/AATSR product exhibits slightly better agreement with AERONET than the SU/synergy product. SU/synergy retrieval overestimates AOT for all surface and aerosol conditions. SU/AATSR data is much more stable and has better quality; it slightly underestimates fine-mode dominated and absorbing AOTs yet slightly overestimates coarse-mode dominated and non-absorbing AOTs. |
| Keywords | Big Data analytics |
| Year | 2018 |
| Journal | Remote Sensing |
| Publisher | MPDI |
| ISSN | 2072-4292 |
| Digital Object Identifier (DOI) | https://doi.org/10.3390/rs10091414 |
| Web address (URL) | http://hdl.handle.net/10545/623009 |
| hdl:10545/623009 | |
| Publication dates | 06 Sep 2018 |
| Publication process dates | |
| Deposited | 02 Oct 2018, 14:58 |
| Rights | Archived with thanks to Remote Sensing |
| Contributors | University of Derby, Chinese Academy of Sciences, University of Chinese Academy of Sciences, University of Bremen and Ningxia University |
| File | File Access Level Open |
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