Intercomparison of desert dust optical depth from satellite measurements
MetadataShow full item record
This article is published under the Open Access publishing model and distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0/ Please refer to the licence to obtain terms for any further reuse or distribution of this work.
This work provides a comparison of satellite retrievals of Saharan desert dust aerosol optical depth (AOD) during a strong dust event through March 2006. In this event, a large dust plume was transported over desert, vegetated, and ocean surfaces. The aim is to identify the differences between current datasets. The satellite instruments considered are AATSR, AIRS, MERIS, MISR, MODIS, OMI, POLDER, and SEVIRI. An interesting aspect is that the different algorithms make use of different instrument characteristics to obtain retrievals over bright surfaces. These include multi-angle approaches (MISR, AATSR), polarisation measurements (POLDER), single-view approaches using solar wavelengths (OMI, MODIS), and the thermal infrared spectral region (SEVIRI, AIRS). Differences between instruments, together with the comparison of different retrieval algorithms applied to measurements from the same instrument, provide a unique insight into the performance and characteristics of the various techniques employed. As well as the intercomparison between different satellite products, the AODs have also been compared to co-located AERONET data. Despite the fact that the agreement between satellite and AERONET AODs is reasonably good for all of the datasets, there are significant differences between them when compared to each other, especially over land. These differences are partially due to differences in the algorithms, such as assumptions about aerosol model and surface properties. However, in this comparison of spatially and temporally averaged data, it is important to note that differences in sampling, related to the actual footprint of each instrument on the heterogeneous aerosol field, cloud identification and the quality control flags of each dataset can be an important issue.
Showing items related by title, author, creator and subject.
Modern urbanization has reshaped the bacterial microbiome profiles of house dust in domestic environmentsShan, Yifan; Guo, Jing ; Fan, W.; Li, H.; Wu, H.; Song, Yong ; Jalleh, Geoffrey; Wu, W.; Zhang, Brad (2020)Background: The prevalence of allergy and other common chronic diseases is higher in developed than developing countries, and higher in urban than rural regions. Urbanization through its modification of environmental ...
Campbell, T.; Fearns, Peter (2018)© Authors 2018. CC BY 4.0 License. Recent studies have shown that in the spectral space there is often a better spectral separation between leaves and flowers and even between flowers of different species than between ...
Detection of linear trends in multi-sensor time series in the presence of autocorrelated noise: Application to the chlorophyll-a SeaWiFS and MERIS datasets and extrapolation to the incoming Sentinel 3-OLCI missionSaulquin, B.; Fablet, R.; Mangin, A.; Mercier, G.; Antoine, David; Fanton d'Andon, O. (2013)The detection of long-term trends in geophysical time series is a key issue in climate change studies. This detection is affected by many factors: the size of the trend to be detected, the length of the available data ...