We present a new gridded sea surface height and current dataset
produced by combining observations from nadir altimeters and drifting buoys.
This product is based on a multiscale and multivariate mapping approach
that offers the possibility to improve the physical content of gridded
products by combining the data from various platforms and resolving a
broader spectrum of ocean surface dynamic than in the current operational
mapping system. The dataset covers the entire global ocean and spans from
1 July 2016 to 30 June 2020. The multiscale approach
decomposes the observed signal into different physical contributions. In the
present study, we simultaneously estimate the mesoscale ocean circulations
as well as part of the equatorial wave dynamics (e.g. tropical instability
and Poincaré waves). The multivariate approach is able to exploit the
geostrophic signature resulting from the synergy of altimetry and drifter
observations. Sea-level observations in Arctic leads are also used in the
merging to improve the surface circulation in this poorly mapped region. A
quality assessment of this new product is proposed with regard to an
operational product distributed in the Copernicus Marine Service. We show
that the multiscale and multivariate mapping approach offers promising
perspectives for reconstructing the ocean surface circulation:
observations of leads contribute to improvement of the coverage in delivering gap-free maps
in the Arctic and observations of drifters help to refine the mapping in regions
of intense dynamics where the temporal sampling must be accurate enough to
properly map the rapid mesoscale dynamics. Overall, the geostrophic
circulation is better mapped in the new product, with mapping errors
significantly reduced in regions of high variability and in the equatorial
band. The resolved scales of this new product are therefore between 5 %
and 10 % finer than the Copernicus product (https://doi.org/10.48670/moi-00148, Pujol et al., 2022b)....

Improved global sea surface height and current maps from remote sensing and in situ observations

10.5194/essd-15-295-2023