Inter-satellite calibration for decadal observations and operational forecasting of cyanobacterial blooms

Timothy Wynne, National Oceanic and Atmospheric Administration, National Centers for Coastal Ocean Science, Silver Spring, United States, Richard P Stumpf, NOAA, National Centers for Coastal Ocean Science, Silver Spring, United States, Sachidananda Mishra, CSS Inc., Fairfax, United States and Andrew Meredith, CSS Inc., Under Contract to NCCOS, NOAA, Fairfax, United States
Satellite imagery has been used by NOAA to monitor and assess cyanobacterial blooms in Lake Erie for ten years, and this capability has been operational for the last two years. The key algorithm is the cyanobacterial index (CI), which is a proxy for chlorophyll-a found in cyanobacterial blooms. The CI is a “spectral shape” algorithm, which is quite robust and objective and does not require atmospheric correction, allowing reliable use for many more scenes than analytical algorithms. Monitoring began with the European Space Agency’s (ESA) MERIS sensor (2002 - 2011). With the loss of MERIS in the spring of 2012, we shifted to NASA’s MODIS sensor (which can extend bloom observations back to 2000). In 2016, the OLCI was launched by ESA on the Copernicus Sentinel-3A satellite as the replacement for MERIS. MODIS has more limited bands and resolution than MERIS and OLCI but is still capable of providing a critical data set for the bloom years between 2012-2016 which lack coverage from OLCI and MERIS. Here we are establishing that the algorithm is self-consistent across the three sensors to maintain what will soon be a 20-year record of blooms in the Great Lakes which is available for operational forecasting as well as creating an extended bloom climatology.