testing the performance of empirical remote sensing algorithms in the baltic sea waters with modelled and in situ reflectance data

Remote sensing studies published up to now show that the performance of empirical (band-ratio type) algorithms in different parts of the Baltic Sea is highly variable. Best performing algorithms are different in the different regions of the Baltic Sea. Moreover, there is indication that the algorithms have to be seasonal as the optical properties of phytoplankton assemblages dominating in spring and summer are different. We modelled 15,600 reflectance spectra using HydroLight radiative transfer model to test 58 previously published empirical algorithms. 7200 of the spectra were modelled using specific inherent optical properties (SIOPs) of the open parts of the Baltic Sea in summer and 8400 with SIOPs of spring season. Concentration range of chlorophyll-a, coloured dissolved organic matter (CDOM) and suspended matter used in the model simulations were based on the actually measured values available in literature. For each optically active constituent we added one concentration below actually measured minimum and one concentration above the actually measured maximum value in order to test the performance of the algorithms in wider range. 77 in situ reflectance spectra from rocky (Sweden) and sandy (Estonia, Latvia) coastal areas were used to evaluate the performance of the algorithms also in coastal waters. Seasonal differences in the algorithm performance were confirmed but we found also algorithms that can be used in both spring and summer conditions. The algorithms that use bands available on OLCI, launched in February 2016, are highlighted as this sensor will be available for Baltic Sea monitoring for coming decades.