Advancing Ocean Remote Sensing with Spaceborne Lidar

Global estimates of phytoplankton biomass (C_phyto) and particulate organic carbon (POC) have traditionally been made using passive ocean color measurements. Recently, data from the CALIOP sensor on the CALIPSO satellite have provided the first measurements of these two key carbon cycle stocks from a space-based lidar despite the fact that CALIOP was not designed for subsurface ocean retrievals. This success suggests a potentially important future role for space lidar measurements in global ocean plankton research, particularly for a lidar system optimized for water column profiling. In this presentation we focus on the advantages of the more advanced, high spectral resolution lidar (HSRL) technique for ocean profiling. This technique enables independent vertically-resolved retrievals of the diffuse attenuation coefficient (K_d) and particulate backscatter (b_bp), providing more information with greater accuracy and fewer assumptions than the CALIOP retrievals. These advanced retrievals were recently demonstrated using data from the NASA Langley ocean-optimized aircraft-based HSRL deployed on the 2014 Ship-Aircraft Bio-Optical Research Experiment (SABOR). We will summarize results from CALIOP and SABOR and focus on the potential applications and advantages of an ocean-optimized satellite-based HSRL. Such an instrument would provide global depth-resolved profiles of plankton distributions in a range of conditions that are highly complementary to ocean color observations: e.g., under any lighting conditions, night or day; between broken cloud and through tenuous cloud; and through significant overlying aerosol loading with no need for complex correction algorithms. A satellite-based HSRL would enable characterization of annual cycles in plankton communities in currently under-sampled polar oceans, reduce uncertainty in global estimates of biomass and net primary productivity, provide new tools for assessing phytoplankton physiology and iron stress, and provide a global data set of independent measurements for assessing and improving passive ocean color retrievals. We will also present estimates of achievable retrieval uncertainties and averaging scales from a spaceborne HSRL and results from sampling studies comparing lidar coverage to ocean color observations.