Automated Quality Control of AERONET-OC LWN Data
Giuseppe Zibordi, Davide D’Alimonte, Tamito Kajiyama
Abstract
Abstract 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.