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\begin{document}

\title{Arctic Ocean in CMIP6 Models: Historical and projected temperature and
salinity in the deep basins}



\author[1]{Narges Khosravi}%
\author[1]{Qiang Wang}%
\author[2]{Nikolay V. Koldunov}%
\author[3]{Claudia Hinrichs}%
\author[4]{Tido Semmler}%
\author[1]{S. Danilov}%
\author[5]{Thomas Jung}%
\affil[1]{Alfred Wegener Institute for Polar and Marine Research}%
\affil[2]{Alfred Wegener Institute}%
\affil[3]{Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research}%
\affil[4]{Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research}%
\affil[5]{AWI}%


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  \date{May 15, 2024}


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\begin{abstract}
We examine the historical and projected hydrography in the deep basin of
the Arctic Ocean in 23 climate models participating in the sixth phase
of the Coupled Model Intercomparison Project (CMIP6). The comparison
between historical simulations and observational climatology shows that
the simulated Atlantic Water (AW) layer is too deep and too thick among
the majority of the models and in the multi-model mean (MMM). Moreover,
the halocline is too fresh in the MMM. These issues indicate that there
is no visible improvement in the representation of Arctic hydrography in
the CMIP6 compared to the CMIP5. The climate projections reveal that the
sub-Arctic seas are outstanding warming hotspots, supplying a strong
warming trend in the Arctic AW layer. The MMM temperature increase
averaged in the upper 700 m till the end of the 21st century in the
Arctic Ocean is about 40\% and 60\% higher than the global mean in the
SSP245 and SSP585 scenarios, respectively. Comparing the AW temperature
in the present day with its future change among the models shows that
the temperature climate change signals are not sensitive to the model
biases in the present-day simulations. The upper-ocean salinity is
projected to become fresher in the Arctic deep basin in the MMM.
However, the salinity spread is rather large and the tendency toward
stronger upper ocean stratification in the MMM is not shared among all
the models. The identified hydrography biases and spread call for a
collective effort for systematic improvements of coupled model
simulations.%
\end{abstract}%



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