ABSTRACTS

Oral Session 12 | Friday, October 7, 11:00–11:20 | Abstract 579

Validation of remote-sensing algorithms for diffuse attenuation of downward irradiance using radiometry collected from BGC-Argo floats

The spectral diffuse attenuation coefficient of downward irradiance (Kd(λ)) is an important parameter in regulating physical and biogeochemical processes in the upper oceanic layer. Accurate retrieval of Kd(λ) from Ocean Color sensors is therefore of interest in constraining ocean models. Estimates of Kd(λ) and Kd(PAR) from 5 different published algorithms spanning from explicit-empirical, semi-analytical to implicit-empirical over 5 satellites sensors (MODIS-aqua, MODIS-terra, VIIRS–SNPP, VIIRS-JN, and Sentinel-3) were compared to autonomous profiling floats (BGC-Argo) measurements of Kd(λ), Ed(λ, 0-) and PAR. BGC-Argo provide multiple advantages compared to ship-born measurements such as 1. Uniform sampling throughout the year, 2. Unprecedented spatial coverage and 3. Lack of shading. Over 5,000 matchups between Floats and Satellites retrieved Kd(λ) values ranging from ~0.01 to 0.53 m^–1. All 3 algorithms are overall good predictors of Kd(λ), but results diverged the most for low Kd values, i.e., for the clearest waters. The biases in the retrieval of Rrs-Kd(λ) were associated with the limited range of in-situ Kd(λ) that some algorithms were constrained with, as well as the impact of the sun angle and were confirmed by Radiative transfer simulations. New coefficients for empirical and semi-analytical algorithms were computed and significantly improved Kd retrieval. This study shows the value of using BGC-Argo floats as validation for remote sensing products, as well as the need to take sun angle into consideration for algorithm improvement. Instrumenting the fleet with hyperspectral radiometers should be encouraged, as it will provide better constraints on algorithms associated with the hyperspectral NASA PACE mission.

*Charlotte Begouen Demeaux, University of Maine, 0000-0003-0471-5022

Emmanuel Boss, University of Maine