An Optical Algorithm to Estimate Downwelling Diffuse Attenuation Coefficient in the Red Sea
Type
ArticleAuthors
Tiwari, Surya Prakash
Sarma, Yellepeddi V. B.
Kürten, Benjamin

Ouhssain, Mustapha
Jones, Burton

KAUST Department
Red Sea Research Center (RSRC)Biological and Environmental Sciences and Engineering (BESE) Division
Marine Science Program
Date
2018-07-19Online Publication Date
2018-07-19Print Publication Date
2018-12Permanent link to this record
http://hdl.handle.net/10754/631638
Metadata
Show full item recordAbstract
An optical algorithm is developed for the retrieval of the downwelling diffuse attenuation coefficient K (490) in the Red Sea using a comprehensive hydrolight simulated data set (N = 5000). We found a robust relationship between the K (490) and the ratio of remote sensing reflectance R (443)/R (555), with an excellent determination coefficient (R = 0.999) and a low root-mean-square error (RMSE = 0.00033). The performance of the developed algorithm is evaluated with in situ data collected in the Red Sea by comparing obatined model output with existing empirical (NASA, Morel et al., Zhang and Fell, Tiwari and Shanmugam) and semianalytical (Lee et al.) algorithms. On the used in situ data from the Red Sea, the new algorithm shows good retrievals of $K_{d}$ (490) with a low bias, and a low RMSE compared to that of the existing algorithms. For satellite application, we applied our algorithm to selected MODIS-Aqua images acquired over the Red Sea, which captured spatial features of phytoplankton blooms and physical processes (e.g., cyclonic and anticyclonic circulations) in the Red Sea. The new algorithm has the potential to improve our understanding of water transparency and photosynthetic processes that rely on the availability of solar radiation.Citation
Tiwari SP, Sarma YVB, Kurten B, Ouhssain M, Jones BH (2018) An Optical Algorithm to Estimate Downwelling Diffuse Attenuation Coefficient in the Red Sea. IEEE Transactions on Geoscience and Remote Sensing 56: 7174–7182. Available: http://dx.doi.org/10.1109/TGRS.2018.2849026.Sponsors
This work is supported by the King Abdullah University of Science and Technology, Thuwal, Saudi Arabia.Additional Links
https://ieeexplore.ieee.org/document/8415747ae974a485f413a2113503eed53cd6c53
10.1109/TGRS.2018.2849026