Sea level rise poses an imminent threat to coastal communities worldwide. We introduce the Dynamic Search Radius (DSR) algorithm, that chooses altimetry observations within the coastal shelf to represent sea level variability at the coast. DSR-applied coastal altimetry product agree well with tide gauges, with the largest improvements at narrow-shelf coasts, indicating reliable coastal sea level monitoring at monthly or longer scales.

Altimeter satellites have transformed our understanding of the ocean, but small-scale features represented by sea level anomaly observations can be weakened when observations are combined into maps. Using observations from the Surface Water and Ocean Topography mission, we characterized how ocean features change across space and time and used this information to improve mapping. The resulting maps better preserve small-scale features and provide improved estimates of ocean currents and energy.

The Global Ocean Data Analysis Project (GLODAP) collects oceanographic datasets from research cruises that are needed to study the marine carbon cycle. The datasets are quality controlled and adjusted where necessary to ensure consistency between cruises, and published as a global data product. Here, we present a new method for calculating the consistency adjustments called ‘furthest-first inversion’ which has been developed for the newest version of the data product.

The Surface Water and Ocean Topography satellite gives high-resolution sea surface height data, yet converting these data into accurate ocean current maps is difficult. We compared three mapping products over the North Atlantic. The results show a scale-dependent trade-off: one product is best for large-scale currents, another captures finer details, and a third performs steadily overall. These insights help users in selecting the right product for their work.