3D reconstruction of ocean velocity from high-frequency radar and acoustic Doppler current profiler: a model-based assessment study
Authors: Manso-Narvarte Ivan , Fredj Erick , Jordà Gabriel , Berta Maristella , Griffa Annalisa , Caballero Ainhoa , Rubio Anna 
Published: May 2020

Abstract. The effective monitoring and understanding of the
dynamics of coastal currents is crucial for the development of
environmentally sustainable coastal activities in order to preserve marine
ecosystems as well as to support marine and navigation safety. This need is
driving the set-up of a growing number of multiplatform operational
observing systems, aiming for the continuous monitoring of the coastal
ocean. A significant percentage of the existing observatories is equipped
with land-based high-frequency radars (HFRs), which provide real-time
currents with high spatio-temporal coverage and resolutions. Several
approaches have been used in the past to expand the surface current velocity
measurements provided by HFR to subsurface levels, since this can expand the
application of the technology to other fields, like marine ecology or
fisheries. The possibility of obtaining 3D velocity current fields from the
combination of data from HFRs with complementary data, such as the velocity
current profiles provided by in situ acoustic Doppler current profiler
(ADCP) moorings is explored here. To that end, two different methods to
reconstruct the 3D current velocity fields are assessed by a standard
approach conceptually similar to OSSEs (observing system simulation
experiments), where 3D numerical simulations are used as true ocean in
order to evaluate the performance of the data-reconstruction methods. The
observations of currents from a HFR and ADCP moorings are emulated by
extracting the corresponding data from the 3D true ocean, and used as
input for the methods. Then, the 3D reconstructed fields (outputs of the
methods) are compared to the true ocean to assess the skills of the
data-reconstruction methods. These methods are based on different
approaches: on the one hand, the reduced order optimal interpolation uses an
approximation to the velocity covariances (which can be obtained from
historical data or a realistic numerical simulation) and on the other hand,
the discrete cosine transform penalized least square is based on penalized
least squares regression that balances fidelity to the data and smoothness
of the solution. This study, which is based on the configuration of a real
observatory located in the south-eastern Bay of Biscay (SE-BoB), is a first
step towards the application of the data-reconstruction methods to real
data, since it explores their skills and
limitations. In the SE-BoB, where the coastal observatory includes a
long-range HFR and two ADCP moorings inside the HFR footprint area, the
results show satisfactory 3D reconstructions with mean spatial (for each
depth level) errors between 0.55 and 7 cm s−1 for the first 150 m depth
and mean relative errors of 0.07–1.2 times the rms value for most of the cases.
The data-reconstruction methods perform better in well-sampled areas, and
both show promising skills for the 3D reconstruction of currents as well as
for the computation of new operational products integrating complementary
observations, broadening the applications of the in situ observational data
in the study area.