A Model Intercomparison of CCN-Limited Tenuous Clouds in the High Arctic

Abstract

. 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, 5 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 (CDNC) 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 concen-10 trations (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 on 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 15 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 5 clouds, surface temperatures and atmospheric stability need to be considered for weather and climate predictions in this region.

Cloud Ice Processes Enhance Spatial Scales of Organization in Arctic Stratocumulus

“…In our LowCCN simulation we test this mechanism and its relevance for cloud organization by lowering the ambient CCN concentration by a factor of 5 from 100 to 20 cm −3 . As a result of fewer CCN, LWP and IWP are reduced (Figures 3a and 3b), which agrees with previous results of an increased (decreased) LWP and IWP for increased (decreased) CCN concentrations, respectively Possner et al, 2017;Stevens et al, 2018). In addition, cloud droplets are larger (15 μm in LowCCN compared to 10 μm in Control; not shown), as expected from the Twomey effect.…”

“…A low availability of CCN is leading to fewer and larger cloud droplets according to the Twomey effect and thus potentially increased precipitation rates (Albrecht, 1989). As a result of fewer CCN, LWP and IWP are reduced (Figures 3a and 3b), which agrees with previous results of an increased (decreased) LWP and IWP for increased (decreased) CCN concentrations, respectively Possner et al, 2017;Stevens et al, 2018). As a result of fewer CCN, LWP and IWP are reduced (Figures 3a and 3b), which agrees with previous results of an increased (decreased) LWP and IWP for increased (decreased) CCN concentrations, respectively Possner et al, 2017;Stevens et al, 2018).…”

“…As a consequence of ice formation within the Control simulation, LWP (defined as vertically integrated in-cloud rain and cloud liquid water) is reduced by 35 g/m 2 on average compared to NoIce (Figure 3a). The averaged IWP (in-cloud ice, snow, and graupel) is 26.3% of the LWP in Control (Figure 3b), which is within the range of Arctic MPCs Klein et al, 2009;Ovchinnikov et al, 2014;Possner et al, 2017;Stevens et al, 2018;Young et al, 2017). The presence of cloud ice does indeed increase the total cloud base precipitation in our Control simulation compared to NoIce in the spatial average (0.70 mm/hr in Control and 0.44 mm/hr in NoIce; not shown) and in the spatial extremes, that is, grid points of cloud base precipitation exceeding the 85th percentile determined over the simulation domain (2.4 mm/hr in Control and 1.4 in NoIce; Figure 3f).…”

“…To investigate the importance of the ice phase on the organization of MPCs, we altered our Control simulation by omitting all ice processes in the NoIce simulation (implying that all clouds only contain supercooled liquid), similar to simulations in Stevens et al (2018). To provide one scenario with intensified ice processes, we increased the INPs in the Control simulation by a factor of 4 (HighINP).…”

Simulated and observed horizontal inhomogeneities of optical thickness of Arctic stratus

“…Here, results from the COSMO (COnsortium for Small-Scale MOdeling) model, which is adjusted to a LES setup with a high horizontal and vertical resolution to resolve the cloud structures of Arctic stratus Stevens et al, 2017) are evaluated. For that, data measured by dropsondes served as input for semi-idealized simulations of clouds using COSMO-LES (Sec.…”