Abstract. We perform a model intercomparison of summertime high Arctic (> 80∘ N) clouds
observed during the 2008 Arctic Summer Cloud Ocean Study (ASCOS) campaign,
when observed cloud condensation nuclei (CCN) concentrations fell below
1 cm−3. Previous analyses have suggested that at these low CCN
concentrations the liquid water content (LWC) and radiative properties of the
clouds are determined primarily by the CCN concentrations, conditions that
have previously been referred to as the tenuous cloud regime. The
intercomparison includes results from three large eddy simulation models
(UCLALES-SALSA, COSMO-LES, and MIMICA) and three numerical weather prediction
models (COSMO-NWP, WRF, and UM-CASIM). We test the sensitivities of the model
results to different treatments of cloud droplet activation, including
prescribed cloud droplet number concentrations (CDNCs) and diagnostic CCN
activation based on either fixed aerosol concentrations or prognostic aerosol
with in-cloud processing. There remains considerable diversity even in experiments with prescribed
CDNCs and prescribed ice crystal number concentrations (ICNC). The
sensitivity of mixed-phase Arctic cloud properties to changes in CDNC depends
on the representation of the cloud droplet size distribution within each
model, which impacts autoconversion rates. Our results therefore suggest
that properly estimating aerosol–cloud interactions requires an appropriate
treatment of the cloud droplet size distribution within models, as well as
in situ observations of hydrometeor size distributions to constrain them. The results strongly support the hypothesis that the liquid water content of
these clouds is CCN limited. For the observed meteorological conditions, the
cloud generally did not collapse when the CCN concentration was held constant
at the relatively high CCN concentrations measured during the cloudy period,
but the cloud thins or collapses as the CCN concentration is reduced. The CCN
concentration at which collapse occurs varies substantially between models.
Only one model predicts complete dissipation of the cloud due to glaciation,
and this occurs only for the largest prescribed ICNC tested in this study.
Global and regional models with either prescribed CDNCs or prescribed aerosol
concentrations would not reproduce these dissipation events. Additionally,
future increases in Arctic aerosol concentrations would be expected to
decrease the frequency of occurrence of such cloud dissipation events, with
implications for the radiative balance at the surface. Our results also show
that cooling of the sea-ice surface following cloud dissipation increases
atmospheric stability near the surface, further suppressing cloud formation.
Therefore, this suggests that linkages between aerosol and clouds, as well as
linkages between clouds, surface temperatures, and atmospheric stability need
to be considered for weather and climate predictions in this region.