Global and regional sea level changes are the subject of public and scientific concern. Sea level data from satellite radar altimetry rely on precise knowledge of the orbits. We assess the orbit-related uncertainty of sea level on seasonal to decadal timescales for the 1990s from a set of TOPEX/Poseidon orbit solutions. Orbit errors may hinder the estimation of global mean sea level rise acceleration. The uncertainty of sea level trends due to orbit errors reaches regionally up to 1.2 mm yr⁻¹.

Tide gauges observe sea level changes, but are also affected by vertical land motion (VLM). Estimation of absolute sea level requires a correction for the local VLM. VLM is either estimated from GNSS observations or indirectly by subtracting tide gauge observations from satellite altimetry observations. Because altimetry and GNSS observations are often not made at the tide gauge location, the estimates vary. In this study we determine the best approach for both methods.

The Genealogical Evolution Model (GEM) is an efficient logical model used to track dynamic evolution of mesoscale eddies in the ocean. It can distinguish different dynamic processes (e.g., merging and splitting) within a dynamic evolution pattern with a two-dimensional vector. All of the computational steps are linear and do not include iteration. It is very fast and is potentially useful for studying dynamic processes in other related fields, e.g., the dynamics of cyclones in meteorology.

We use satellite and in situ data to elucidate global-mean sea level (GMSL) changes related to El Niño-Southern Oscillation (ENSO) over 2005–2015. Steric and mass effects make comparable contributions to the GMSL budget during ENSO, in contrast to previous interpretations based largely on hydrological models, which emphasize mass contributions. Results exemplify the usefulness of the Global Ocean Observing System for understanding the Earth's radiation imbalance and hydrological cycle.