In the project, FMI researchers are working to produce a coherent near-coastal sea surface temperature (SST) dataset using two different satellite data products and machine-learning algorithms. The goal is to take the advantage of high-resolution (100 m) but seldom SST observations done by TIRS 1/2 instrument on board the USGS/NASA operated Landsat 8/9 satellites and train the Climate Reconstruction AI (CRAI) algorithm such that it can extrapolate the coarser (1 km) but more frequently available SLSTR instrument (on board Sentinel-3 satellite) SST data closer to the coastline. The resulting high-resolution near-coastal SST data allows researchers to monitor temperature extremes, that can be harmful for marine ecosystems, also in complex archipelago settings. The project is funded by the European Maritime, Fisheries and Aquaculture Fund (EMFAF), also known as Euroopan meri-, kalatalous- ja vesiviljelyrahasto (EMKVR).