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Webinar: Sensing global primary production: Why we should go beyond the empirically- estimated Chl from ocean color?
Wednesday, 08 September 2021, 3:00
Wednesday, September 8, 2021. 3:00 PM. Webinar: Sensing global primary production: Why we should go beyond the empirically- estimated Chl from ocean color? ZhongPing Lee, University of Massachusetts, Boston. Sponsored by NOAA Ocean Color Coordinating Group. Register here.
Primary production (PP) in the aquatic environment is a measure of inorganic carbon converted to particle organic carbon via phytoplankton photosynthesis (the biological pump), which is at the core to support fishery and carbon dynamics studies. It has long been desired to have an accurate account of the spatial distribution and temporal variation of PP in the global oceans, which is one of the major goals to launch ocean color satellites. Many studies have been carried out in the past decades for the estimation of PP based on ocean color measurements, which resulted in numerous models. One thing in common among these models is that the concentration of chlorophyll (Chl) is at the center, so no surprise to see Chl as a key standard product for all satellite ocean color missions. However, this Chl product, a biological parameter, is estimated using empirical algorithms developed via regressions, while a critical requirement for photosynthesis is photons absorbed by phytoplankton, thus there is a gap between Chl and this demand. In this presentation, we will talk about the schemes to estimate global PP from ocean color, why this empirically-estimated Chl is not a good parameter, and the more robust approaches.
Speaker Bio - ZhongPing Lee got his Ph.D in 1994 from the University of South Florida. Dr. Lee is currently a Professor at the School For the Environment of the University of Massachusetts Boston, and a Fellow of the Optical Society of America. Dr. Lee's main research interests are in optical oceanography and ocean color remote sensing. He led the development of the widely used Quasi-Analytical Algorithm (QAA) and the hyperspectral algorithm (HOPE) for processing both optically deep- and shallow- waters, along with various applications of satellite ocean color products including absorption-based model for primary production. His theoretical work (2015) on the interpretation of Secchi disk depth (underwater visibility) corrected the 70-year long classical theory adopted by the ocean optics community, and his recent work (2019) on the remote sensing of stratified waters provided an in-depth understanding regarding the remote sensing products of stratified waters. He has authored or co-authored more than 160 peer- reviewed journal articles; and was a member of NASA’s MODIS/PACE/GEO-CAPE/HyspIRI and NOAA’s VIIRS science teams for ocean color remote sensing.