A semianalytical algorithm for quantitatively estimating sediment and atmospheric deposition flux from MODIS-derived sea ice albedo in the Bohai Sea, China

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Abstract

Quantitative estimates of particulate matter [PM) concentration in sea ice using remote sensing data is helpful for studies of sediment transport and atmospheric dust deposition flux. In this study, the difference between the measured dirty and estimated clean albedo of sea ice was calculated and a relationship between the albedo difference and PM concentration was found using field and laboratory measurements. A semianalytical algorithm for estimating PM concentration in sea ice was established. The algorithm was then applied to MODIS data over the Bohai Sea, China. Comparisons between MODIS derived and in situ measured PM concentration showed good agreement, with a mean absolute percentage difference of 31.2%. From 2005 to 2010, the MODIS-derived annual average PM concentration was approximately 0.025 g/L at the beginning of January. After a month of atmospheric dust deposition, it increased to 0.038 g/L. Atmospheric dust deposition flux was estimated to be 2.50 t/km2/month, similar to 2.20 t/km2/month reported in a previous study. The result was compared with on-site measurements at a nearby ground station. The ground station was close to industrial and residential areas, where larger dust depositions occurred than in the sea, but although there were discrepancies between the absolute magnitudes of the two data sets, they demonstrated similar trends.

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Xu, Z., Hu, S., Wang, G., Zhao, J., Yang, Y., Cao, W., & Lu, P. (2016). A semianalytical algorithm for quantitatively estimating sediment and atmospheric deposition flux from MODIS-derived sea ice albedo in the Bohai Sea, China. Journal of Geophysical Research: Oceans, 121(5), 3450–3464. https://doi.org/10.1002/2015JC011067

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