The Ocean Color Component of the Aerosol Robotic Network (AERONET-OC) supports activities related to ocean color such as validation of satellite data products, assessment of atmospheric correction schemes, and evaluation of bio-optical models through globally distributed standardized measurements of water-leaving radiance and aerosol optical depth. In view of duly assisting the AERONET-OC data user community, this work (i) summarizes the latest investigations on a number of scientific issues related to above-water radiometry, (ii) emphasizes the network expansion that from 2002 until the end of 2020 integrated 31 effective measurement sites, (iii) shows the equivalence of data product accuracy across sites and time for measurements performed with different instrument series, (iv) illustrates the variety of water types represented by the network sites ensuring validation activities across a diversity of observation conditions, and (v) documents the availability of water-leaving radiance data corrected for bidirectional effects by applying a method specifically developed for chlorophyll-a-dominated waters and an alternative one that is likely suitable for any water type.

This letter summarizes a regional assessment of radiometric data products from the Ocean and Land Colour Instrument operated onboard Sentinel-3A. The assessment is supported by in situ reference measurements from the Ocean Colour component of the Aerosol Robotic Network and the Bio-optical mapping of Marine Properties Program. Results indicate a systematic underestimate of the water-leaving radiance at the blue and red spectral bands. Conversely, the aerosol optical depth at 865 nm exhibits overestimate, while the Ångström exponent shows a narrow distribution of values confined below a maximum of approximately 1.7. These findings suggest difficulty in separating water and atmospheric radiance contributions, which results in a poor determination of aerosol load and type and, consequently, an overestimate of atmospheric effects.

Two regional bio-optical algorithms are combined to retrieve the Chlorophyll-a (Chl-a) concentration in the Black Sea. The first is a band-ratio algorithm that computes Chl-a as a function of the slope of Remote Sensing Reflectance (RRS) values at two wavelengths using a polynomial regression that captures the overall data trend, enhancing extrapolation results. The second algorithm is a Multilayer Perceptron neural net based on RRS values at three individual wavelengths that features interpolation capabilities helpful to fit data non-linearities. A new merging scheme is then designed to benefit from the complementarity of the two approaches. Remote sensing data employed to demonstrate the merging of regional results for the Black Sea are those acquired by the Ocean and Land Color Instrument on board Sentinel-3A to acknowledge the need for data products of higher accuracy within the long-term Copernicus program.

The response to temperature of sample hyperspectral radiometers commonly used to support the validation of satellite ocean color data was characterized in the 400–800-nm spectral range. Measurements performed in the 10°–40°C interval at 5°C increments showed mean temperature coefficients varying from −0.04 × 10⁻² (°C)⁻¹ at 400 nm to +0.33 × 10⁻² (°C)⁻¹ at 800 nm, which are largely explained by the temperature coefficient of the photodetector array constituting the core of the sensor. Overall, the results indicate the possibility of applying temperature corrections with an uncertainty of approximately 0.03 × 10⁻² (°C)⁻¹ for the class of hyperspectral radiometers investigated in the study.

The potential for applying in situ multispectral $R_{\mathrm{ rs}}$ data from the Ocean Color component of the Aerosol Robotic Network (AERONET-OC) to validate satellite-derived ocean color hyperspectral $R_{\mathrm{ rs}}$ products was investigated in the 400–700 nm interval. The analysis was performed using a comprehensive dataset of simulated hyperspectral $R_{\mathrm{ rs}}$ in combination with an algorithm designed to reconstruct hyperspectral $R_{\mathrm{ rs}}$ from multispectral ones. Results were assessed using in situ hyperspectral $R_{\mathrm{ rs}}$ representative of diverse water types. Excluding waters dominated by a high concentration of colored dissolved organic matter, results indicate the capability of determining hyperspectral $R_{\mathrm{ rs}}$ from AERONET-OC multispectral data with mean relative and absolute uncertainties generally lower than 2% and $5 \times 10^{-5} \text { sr}^{-1}$ , respectively, at a number of the key center-wavelengths of the Ocean Color Instrument (OCI) onboard the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) spacecraft.

Quality control (QC) practices are a fundamental requirement for any measurement program targeting the delivery of high-quality data. In agreement with such a need, the Ocean Color component of the Aerosol Robotic Network (AERONET-OC) includes a number of QC steps ensuring the delivery of normalized water-leaving radiance L_WN spectra at incremental accuracy levels identified as level 1.0, level 1.5, and level 2.0. Currently, the final QC step allowing for rising level 1.5 L_WN spectra to level 2.0 implies the execution of an expert-based procedure, which is extremely time consuming and naturally undergoes subjective decisions on dubious cases. These limitations solicited the development of an automated procedure, so-called , mimicking the steps supporting an expert analyst during the final QC of AERONET-OC L_WN spectra. applies hierarchical tests to check (i) the relative consistency of level 1.5 L_WN spectra (called candidates) with respect to L_WN reference spectra (called prototypes) constructed using L_WN spectra formerly and independently quality controlled; (ii) the absence of any pronounced spectral feature in portions of each L_WN candidate spectrum expected to exhibit a regular shape; and additionally, when applicable, (iii) the temporal consistency of the L_WN candidate spectrum with respect to close-in-time spectra as a criterion to further strengthen the quality of data. performance has been verified using L_WN spectra from AERONET-OC measurement sites representative of various water types embracing oligotrophic/mesotrophic waters dominated by chlorophyll-a concentration and coastal waters exhibiting increasing levels of optical complexity. has shown an acceptance rate of AERONET-OC level 1.5 L_WN candidate spectra varying between approximately 89% and 93% with agreement in the range of 88%–93% with respect to the L_WN spectra independently quality controlled through the expert-based procedure. The additional capability of to rank the fully quality-controlled L_WN spectra combining weights depending on the various tests, anticipates the possibility to best support applications with diverse accuracy needs. Finally, acceptance rates of for L_WN prototype spectra built using level 1.5 data, an alternative to fully quality-controlled level 2.0, have shown values generally increased by less than 1%. This indicates the possibility to lessen the constraint implying the existence of reference level 2.0 L_WN data for the relative-consistency test at the expense of a fairly low reduction in accuracy.