Paper Info
Title
Satellite Remote Sensing Observations Of Trans-Atlantic Dust Transport And Deposition: A Multi-Sensor Analysis
Abstract
We analyze the decade-long (2007-2016) record of aerosol measurements from four distinctive sensors, namely CALIOP, MODIS, MISR, and IASI, to quantify the trans-Atlantic dust transport and deposition. These satellite sensors use different techniques to characterize particle size and shape properties; and we have developed sensor-specific methods (broadly categorized into size based and shape-based method) to derive dust optical depth (DOD). The size-based DOD from MODIS and IASI generally agrees better with AERONET-derived DOD than the shape-based DOD from CALIOP and MISR does. Overall, the shape-based DOD is smaller than the size-based DOD by about 25%, which is consistent with distinctive ways of accounting for coarse-spherical particles of dust-pollution internal mixture. While such dust-pollution mixtures are counted as dust in the size-based DOD, they are excluded in the shape-based DOD. DOD is not a good proxy for dust deposition. Instead, the dust deposition depends strongly on the gradient of DOD on a monthly basis and can be derived by calculating the meridional and zonal dust mass flux based on the three-dimensional distributions of dust. Among the remote sensing measurements, difference in dust deposition is smaller than that of DOD, suggesting that different satellites characterize the DOD gradient more consistently than DOD itself. Satellite measurements of dust deposition and DOD also provide an accurate estimate of the dust loss frequency (LF) that measures how efficient the dust is removed from the atmosphere. We found that these remote sensing measurements yield similar LF values of 0.078 - 0.102 d(-1), which however is factors of 2-5 smaller than model simulations. This analysis provides valuable insights into potential deficiencies in models' emission and transport/removal processes and hence helps guide model improvement.
Year
DOI
Venue
2020
10.1109/IGARSS39084.2020.9324325
IGARSS 2020 - 2020 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM
Keywords
DocType
Citations 
remote sensing, dust, transport, deposition, dust optical depth
Conference
0
PageRank 
References 
Authors
0.34
0
6
Name
Order
Citations
PageRank
Hongbin Yu100.34
Qian Tan200.34
Mian Chin300.34
Dongchul Kim400.34
Zhibo Zhang521.06
Qianqian Song600.34