TY - JOUR
T1 - A model intercomparison of CCN-limited tenuous clouds in the high Arctic
AU - Stevens, Robin G.
AU - Loewe, Katharina
AU - Dearden, Christopher
AU - Dimitrelos, Antonios
AU - Possner, Anna
AU - Eirund, Gesa K.
AU - Raatikainen, Tomi
AU - Hill, Adrian A.
AU - Shipway, Benjamin J.
AU - Wilkinson, Jonathan
AU - Romakkaniemi, Sami
AU - Tonttila, Juha
AU - Laaksonen, Ari
AU - Korhonen, Hannele
AU - Connolly, Paul
AU - Lohmann, Ulrike
AU - Hoose, Corinna
AU - Ekman, Annica M. L.
AU - Carslaw, Ken S.
AU - Field, Paul R.
N1 - Funding Information:
Acknowledgements. We thank the two anonymous reviewers for their comments on this paper. We gratefully acknowledge support from the European Union’s Seventh Framework Programme (FP7/2007-2013) with the project Impact of Biogenic versus Anthropogenic emissions on Clouds and Climate: towards a Holistic UnderStanding (BACCHUS; grant no. 603445) and the European Research Council projects ECLAIR (grant no. 646857) and C2Phase (grant no. 714062). We acknowledge the use of the MONSooN system, a collaborative facility supplied under the Joint Weather and Climate Research Programme, a strategic partnership between the UK Met Office and the Natural Environment Research Council. We also acknowledge the use of the JASMIN system operated by Centre for Environmental Data Archival (CEDA) as well as the Swiss National Supercomputing Centre (CSCS). Birgit Wehner, Douglas Orsini, Maria Martin, and Staffan Sjögren are much appreciated for providing the size-resolved particle number and the CCN observations. Caroline Leck and Michael Tjernström are specifically thanked for their coordination of ASCOS. The Swedish Polar Research Secretariat provided access to the icebreaker Oden and logistical support. We would like to thank Joseph Sedlar, Thorsten Mauritsen, and Matthew Shupe for the observational data reprinted in this paper and for their comments on an early version of the paper.
Publisher Copyright:
© 2018 Author(s).
PY - 2018
Y1 - 2018
N2 - 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 1cm−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.
AB - 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 1cm−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.
UR - http://www.scopus.com/inward/record.url?scp=85051253863&partnerID=8YFLogxK
UR - http://www.mendeley.com/research/model-intercomparison-ccnlimited-tenuous-clouds-high-arctic
U2 - 10.5194/acp-18-11041-2018
DO - 10.5194/acp-18-11041-2018
M3 - Article
SN - 1680-7316
VL - 18
SP - 11041
EP - 11071
JO - Atmospheric Chemistry and Physics
JF - Atmospheric Chemistry and Physics
IS - 15
ER -