Cloud cover introduces extensive gaps in sea-surface temperature (SST) fields derived from infrared satellite measurements, and gap frequency rises further when differencing data to compute an SST-based upwelling index. Averaging can eliminate gaps but degrades spatio-temporal resolution, whereas interpolation preserves resolution but requires robust methodology. The CoRTAD database — a 21-year global ocean satellite SST dataset, gap-free, at 4 km resolution and weekly averaged — in which missing observations were mitigated by merging night- and day-passes from the Pathfinder V5.3 satellite record and computing weekly means. Residual SST gaps were filled first with a 3 × 3-pixel spatial median and, where necessary, with a piecewise cubic Hermite interpolating polynomial. The resulting spatial and temporal resolution supports observation of sub-mesoscale to mesoscale coastal-ocean processes. From CoRTAD, SSTs at near- and offshore locations for West Iberia (37°–44° N) were extracted and a coastal upwelling index (UI^sst) calculated for the period January 1982 to December 2021. The nearshore (midshelf) climatology derived from this dataset successfully identifies established recurrent upwelling centres along the West Iberian coast, which were previously detectable only in cloud-free synoptic SST imagery, thereby supporting the validity of the dataset. Monthly climatology reveals no north-south differences in upwelling intensity or season end-date, but shows that the central region between Cabo Carvoeiro (~39° N) and the River Douro (~41° N) has a notably later upwelling season onset (July/August versus June/July). With continuous satellite scatterometer winds available since 1999, the stage is set to compare an Ekman-derived upwelling index with the SST-derived index. This study demonstrates that a high-resolution, gap-free satellite SST dataset combined with targeted interpolation enables robust characterisation of coastal upwelling dynamics over multi-decadal timescales.