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Chlorophyll a concentration (Chl) product validation off the Western Iberian coast is here undertaken by directly comparing remote sensing data with in situ surface reference values. Both standard and recently developed alternative algorithms are considered for match-up data analysis. The investigated standard products are those produced by the MERIS (algal 1 and algal 2) and MODIS (OC3M) algorithms. The alternative data products include those generated within the CoastColour Project and Ocean Color Climate Change Initiative (OC-CCI) funded by ESA, as well as a neural net model trained with field measurements collected in the Atlantic off Portugal (MLP ATLP ). Statistical analyses showed that satellite Chl estimates tend to be larger than in situ reference values. The study also revealed that a non-uniform Chl distribution in the water column can be a concurring factor to the documented overestimation tendency when considering larger optical depth match-up stations. Among standard remote sensing products, MODIS OC3M and MERIS algal 2 yield the best agreement with in situ data. The performance of MLP ATLP highlights the capability of regional solutions to further improve Chl retrieval by accounting for environmental specificities. Results also demonstrate the relevance of oceanographic regions such as the Nazaré area to evaluate how complex hydrodynamic conditions can influence the quality of Chl products. [ABSTRACT FROM AUTHOR]