Autonomous in situ radiometric observations are increasingly used to constrain bio-optical processes and validate satellite ocean-color products, such as remote sensing reflectance and diffuse attenuation coefficients. Because these observations are collected independently of weather and sea-state conditions, their application critically depends on robust quality control. Starting in 2012, the BioGeoChemical-Argo (BGC-Argo) program has measured downwelling irradiance (Ed) at three wavelengths on autonomous floats. Since 2022, a pilot array of 12 BGC-Argo floats equipped with TriOS-RAMSES hyperspectral radiometers measuring Ed and upwelling radiance (Lu) has been deployed across open-ocean regions with diverse biooptical properties. To date, these floats have acquired hundreds of hyperspectral profiles from 0 to 300 m at ~10-day intervals near local noon. This study presents an automated quality-control (QC) method for hyperspectral Ed and Lu profiles measured by BGC-Argo floats, building upon previous QC procedures designed for multispectral radiometry. The method flags perturbations in the light field caused by self-shading, large tilt angles, passing clouds, wave focusing, and spikes and corrects for dark current signals. The QC is first applied at five key wavelengths (380, 443, 490, 555, and 620 nm) to generate wavelength-specific flags along each vertical profile, which are then combined into a final global classification for each spectral profile as good, questionable, or bad. This paper, along with its Python code and data files, provides the community with a robust and computationally efficient approach for assessing hyperspectral BGC-Argo data quality, preparing it for further bio-optical applications.
A Quality-Control Procedure for Bio-Optical Applications of Hyperspectral Radiometric Upwelling Radiance and Downwelling Irradiance Profiles Measured by BioGeoChemical-Argo Floats
Organelli E.;La Forgia G.;
2026
Abstract
Autonomous in situ radiometric observations are increasingly used to constrain bio-optical processes and validate satellite ocean-color products, such as remote sensing reflectance and diffuse attenuation coefficients. Because these observations are collected independently of weather and sea-state conditions, their application critically depends on robust quality control. Starting in 2012, the BioGeoChemical-Argo (BGC-Argo) program has measured downwelling irradiance (Ed) at three wavelengths on autonomous floats. Since 2022, a pilot array of 12 BGC-Argo floats equipped with TriOS-RAMSES hyperspectral radiometers measuring Ed and upwelling radiance (Lu) has been deployed across open-ocean regions with diverse biooptical properties. To date, these floats have acquired hundreds of hyperspectral profiles from 0 to 300 m at ~10-day intervals near local noon. This study presents an automated quality-control (QC) method for hyperspectral Ed and Lu profiles measured by BGC-Argo floats, building upon previous QC procedures designed for multispectral radiometry. The method flags perturbations in the light field caused by self-shading, large tilt angles, passing clouds, wave focusing, and spikes and corrects for dark current signals. The QC is first applied at five key wavelengths (380, 443, 490, 555, and 620 nm) to generate wavelength-specific flags along each vertical profile, which are then combined into a final global classification for each spectral profile as good, questionable, or bad. This paper, along with its Python code and data files, provides the community with a robust and computationally efficient approach for assessing hyperspectral BGC-Argo data quality, preparing it for further bio-optical applications.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
