A Critical Evaluation of Deep Blue Algorithm Derived AVHRR Aerosol Product Over China. Issue 22 (19th November 2019)
- Record Type:
- Journal Article
- Title:
- A Critical Evaluation of Deep Blue Algorithm Derived AVHRR Aerosol Product Over China. Issue 22 (19th November 2019)
- Main Title:
- A Critical Evaluation of Deep Blue Algorithm Derived AVHRR Aerosol Product Over China
- Authors:
- Mei, Linlu
Zhao, Chuanxu
de Leeuw, Gerrit
Burrows, John P.
Rozanov, Vladimir
Che, HuiZheng
Vountas, Marco
Ladstätter‐Weißenmayer, Annette
Zhang, Xiaoye - Abstract:
- Abstract: The Deep Blue (DB) aerosol retrieval algorithm has recently been applied to Advanced Very High Resolution Radiometer (AVHRR) data to produce a first version (V001) of a global aerosol optical thickness (AOT) data set. In this paper, we critically evaluate these AVHRR AOT data over China by comparison with ground‐based reference data from China Aerosol Remote Sensing Network for the period 2006–2011. The evaluation considers the impact of the surface (type and reflectance) and the aerosol properties (aerosol loading, aerosol absorption) on the quality of the retrieved AOT. We also compare the AVHRR‐retrieved AOT with that from Moderate Resolution Imaging Spectroradiometer over major aerosol source regions in China. We further consider seasonal variations and find, in general, a good agreement between AVHRR AOT and the reference data sets. The AVHRR retrieval algorithm performs well over dark vegetated surfaces, but over bright surfaces (e.g., desert regions) the results are less good. The AVHRR algorithm underestimates the AOT, with 32.1% of the values lower than the estimated error envelope of ±0.05 ± 0.25τ. In particular over the desert, the AVHRR‐retrieved AOT is frequently underestimated and for AOT ≤ 0.6 the values are on average 0.05 too low due to the pixel filtering, and dust storms are missed. The comparison of the AVHRR AOT with MODIS collection 6 and CARSNET data indicates that improvements are needed for, for example, AVHRR calibration and cloud/aerosolAbstract: The Deep Blue (DB) aerosol retrieval algorithm has recently been applied to Advanced Very High Resolution Radiometer (AVHRR) data to produce a first version (V001) of a global aerosol optical thickness (AOT) data set. In this paper, we critically evaluate these AVHRR AOT data over China by comparison with ground‐based reference data from China Aerosol Remote Sensing Network for the period 2006–2011. The evaluation considers the impact of the surface (type and reflectance) and the aerosol properties (aerosol loading, aerosol absorption) on the quality of the retrieved AOT. We also compare the AVHRR‐retrieved AOT with that from Moderate Resolution Imaging Spectroradiometer over major aerosol source regions in China. We further consider seasonal variations and find, in general, a good agreement between AVHRR AOT and the reference data sets. The AVHRR retrieval algorithm performs well over dark vegetated surfaces, but over bright surfaces (e.g., desert regions) the results are less good. The AVHRR algorithm underestimates the AOT, with 32.1% of the values lower than the estimated error envelope of ±0.05 ± 0.25τ. In particular over the desert, the AVHRR‐retrieved AOT is frequently underestimated and for AOT ≤ 0.6 the values are on average 0.05 too low due to the pixel filtering, and dust storms are missed. The comparison of the AVHRR AOT with MODIS collection 6 and CARSNET data indicates that improvements are needed for, for example, AVHRR calibration and cloud/aerosol flagging. The analysis presented in this paper contributes to a better understanding of the AVHRR AOT product over China. Key Points: The 53.5% of the AOT values are within the estimated error envelop of ±0.05 ± 0.25τ The AVHRR‐retrieved AOT is frequently underestimated over the desert regions AOT biases at 550 and 660 nm are −0.057 and −0.093, respectively … (more)
- Is Part Of:
- Journal of geophysical research. Volume 124:Issue 22(2019)
- Journal:
- Journal of geophysical research
- Issue:
- Volume 124:Issue 22(2019)
- Issue Display:
- Volume 124, Issue 22 (2019)
- Year:
- 2019
- Volume:
- 124
- Issue:
- 22
- Issue Sort Value:
- 2019-0124-0022-0000
- Page Start:
- 12173
- Page End:
- 12193
- Publication Date:
- 2019-11-19
- Subjects:
- Atmospheric physics -- Periodicals
Geophysics -- Periodicals
551.5 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)2169-8996 ↗
http://www.agu.org/journals/jd/ ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1029/2018JD029929 ↗
- Languages:
- English
- ISSNs:
- 2169-897X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4995.001000
British Library DSC - BLDSS-3PM
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- 19422.xml