Title
Developing A Daily Composite Product for Water Quality Parameters in the Great Lakes
Document Type
Conference Paper/Presentation
Publication Date
2017
Abstract
The Color Producing Agent Algorithm (CPA-A) is a bio-optical model used to estimate water quality parameters in the Great Lakes from satellite reflectance data. The algorithm's output products include chlorophyll, suspended minerals, CDOM, dissolved organic carbon, Kd, photic zone, bulk absorption, and bulk scattering. These products have been used to track spatial and temporal variability in the lakes, which has been corroborated by in situ data. Since 2013, MTRI has been sharing maps of these products derived from MODIS data for each Great Lake on multiple online data portals. Cloud cover limits the viable images to approximately one per week during the growing season (April-October), though occasionally several weeks go by without a good look at a lake. Using a particle tracking algorithm and the water circulation models developed by NOAA-GLERL, MTRI has developed a data assimilation technique that incorporates all satellite images within a given time period to generate a near-complete daily composite of the above-mentioned water quality products for the Great Lakes. These products will be shared on the online portals allowing stakeholders to visualize current conditions and study past behavior.
Publication Title
IAGLR's 60th annual Conference on Great Lakes Research
Recommended Citation
Bosse, K.,
Shuchman, R. A.,
Sayers, M. J.,
Schwab, D. J.,
&
Leshkevich, G.
(2017).
Developing A Daily Composite Product for Water Quality Parameters in the Great Lakes.
IAGLR's 60th annual Conference on Great Lakes Research.
Retrieved from: https://digitalcommons.mtu.edu/mtri_p/255
Publisher's Statement
Publisher's version of record: http://iaglr.org/conference/downloads/2017_abstracts.pdf