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\begin{document}

\title{Mapping altimetry in the forthcoming SWOT era by back-and-forth nudging
a one-layer quasi-geostrophic model}



\author[1,1]{Florian Le Guillou}%
\author[1,1]{Sammy Metref}%
\author[1,1]{Emmanuel Cosme}%
\author[2,2]{Clément Ubelmann}%
\author[3,3]{Maxime Ballarotta}%
\author[2,2]{Jacques Verron}%
\author[1,1]{Julien Le Sommer}%
\affil[1]{Université Grenoble Alpes, CNRS, IRD, Grenoble INP, IGE; Grenoble, France}%
\affil[2]{Ocean Next}%
\affil[3]{Collecte Localisation Satellites}%


\vspace{-1em}



  
  \date{May 20, 2024}


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\begin{abstract}
During the past 25 years, altimetric observations of the ocean surface
from space have been mapped to provide two dimensional sea surface
height (SSH) fields which are crucial for scientific research and
operational applications. The SSH fields can be reconstructed from
conventional altimetric data using temporal and spatial interpolation.
For instance, the standard DUACS products are created with an optimal
interpolation method which is effective for both low temporal and low
spatial resolution. However, the upcoming next-generation SWOT mission
will provide very high spatial resolution but with low temporal
resolution. The present paper makes the case that this temporal-spatial
discrepancy induces the need for new advanced mapping techniques
involving information on the ocean dynamics. An algorithm is introduced,
dubbed the BFN-QG, that uses a simple data assimilation method, the
back-and-forth nudging, to interpolate altimetric data while respecting
quasigeostrophic dynamics. The BFN-QG is tested in an observing system
simulation experiments and compared to the DUACS products. The
experiments consider as reference the high-resolution numerical model
simulation NATL60 from which are produced realistic data: four
conventional altimetric nadirs and SWOT data. In a combined nadirs and
SWOT scenario, the BFN-QG substantially improves the mapping by reducing
the root-mean-square errors and increasing the spectral effective
resolution by 40km. Also, the BFN-QG method can be adapted to combine
large-scale corrections from nadirs data and small-scale corrections
from SWOT data so as to reduce the impact of SWOT correlated noises and
still provide accurate SSH maps.%
\end{abstract}%



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