Measuring Surface Currents from Space

Measurements of the powerful, complex and highly variable ocean surface currents and surface waves are fundamental to our understanding of ocean circulation and air—sea interaction.

The motivation for better knowledge and understanding of ocean surface currents has its foundation in maritime activities serving society at all levels including: shipping, maritime safety, marine operations, increasing maritime activities with sea-ice, fisheries, renewable energy, pollution events, environmental management, resource exploitation, ports and harbour operations, recreation, numerical weather prediction, ocean forecasting, and climate monitoring, amongst others.

These marine activities are also strongly impacted by surface waves, either as a disturbing influence or as a useful resource to be harnessed, but the deepest motivation to improve our understanding of surface waves and our capability to predict them is in fact their influence on the Earth system as a whole as a modulating influence of atmosphere-ocean interactions, at time scales ranging from wind waves weather all the way to climatic time scales (GCOS, 2016).

The actual velocity of a water parcel in contact with the atmosphere at any given location and time (i.e. the surface ocean current) is called the Total Surface Current Velocity (TSCV).

At large scales and away from the Equator, the dynamics of ocean currents are mainly dominated by the so-called geostrophic balance, as the Coriolis and pressure forces acting on water parcels almost balance each other. This underpins the well-established method, currently a component of the global ocean-observing system, of estimating ocean surface current from a combination of satellite sea level and gravimetry measurements (Rio et al., 2018). This technique relies on a constellation of platforms in low inclination 66° orbits (e.g. the Jason satellites), complemented by polar-orbit satellites including Copernicus Sentinel-3, CryoSat and SARAL-AltiKa. The altimeters measure Sea Surface Height Anomalies (SSHA) relative to the WGS84 ellipsoid, which are then corrected using a model of the Earth gravity field to yield the Absolute Dynamic Topography, a measure of the elevation of the sea surface with respect to the geoid (Bruinsma et al., 2013). From these measurements, the horizontal pressure gradient force acting on surface water particles is estimated. The approximation of geostrophic balance is then invoked to give access to the large scale and slowly evolving component of TSCV.

However, these geostrophic altimetry-derived currents are only part of the story, and the TSCV also includes ageostrophic components, that often dominate at the surface. In fact, even the tidal currents and the surface currents associated to Near-Inertial Oscillations (NIOs) are not invisible to satellite altimetry. Transport of pollutants, biological agents, internal ocean or coupled ocean–atmosphere instabilities cannot be well predicted if the full ocean surface velocity field (i.e. the TSCV) is not observed. This is particularly a problem at the equator where geostrophic balance fails, and even state-of-the-art numerical models cannot reproduce the variability at monthly time scales (Foltz et al., 2019).

Besides the tidal and NIO-related currents, the best known and most important non-geostrophic components of the TSCV are the Stokes drift, the average motion of water particles due to waves, and the Ekman drift, the component of the quasi-Eulerian current that is directly due to wind.

As the figure above (adapted from Onink et al, 2019) shows, all these components are important influences in the drift and aggregation of floating material such as plastic litter, but also in cross-shelf exchanges, including the export of carbon from land to the deep ocean.

All these components have different dependencies on the level of turbulent mixing and density stratification of the surface boundary layer of the ocean. Depending on these characteristics, the vertical profile of the Ekman drift can for instance vary strongly, the surface angle with respect to the wind ranging between 45 and 80°. The depth profile of the Stokes drift, on the other hand, depends on the detailed characteristics of the sea surface wave spectrum. Stratification can lead to effective de-coupling of the upper-ocean water from that at depth (e.g. during strong diurnal heating or shallow halocline conditions leading to a ‘slippery’ shallow layer where water at the surface can flow freely over that at depth (see Kudryavtsev and Soloviev, 1990).

Thus, only measurements in the top few metres of the ocean, such as provided by un-drogued and shallow-drogued drifters (e.g. Lumpkin et al., 2017) that follow the surface-water motion (Novelli et al., 2017) or coastal HF-radars, can currently be representative of the surface mixed layer in most conditions and provide good estimates of the TSCV.

While state-of-the-art circulation models do provide estimates of some or all of these components of the TSCV, our understanding of the accuracy and limitations of these estimates is very uneven. While the geostrophic component, which benefits from validation against (and, indeed, assimilation of) the global and consistent satellite altimetry dataset, is now well understood, validation of the Ekman and Stokes components has to rely on much smaller datasets, none of which covers appropriate time and space domains with an appropriate resolution.

Obtaining global, reliable and consistent measurements of the ageostrophic components of the TSCV is thus a key step in the development of our understanding of oceanic processes of utmost importance for the sustained inhabitability of our planet.

To address this need, the EE-9 SKIM concept proposes to implement the SKIM Ka-band Radar (SKaR), a conically scanning pencil-beam microwave radar capable of performing direct Doppler measurements of the TSCV as well as measurements of the sea surface wave directional spectrum. SKIM is also intended to carry a state-of-the-art nadir altimeter, to provide concurrent measurements of the geostrophic TSCV component, and to fly in formation with MetOp-SG(1B), to benefit from its Surface Wind Vector measurements.