Microphysical sensitivity of coupled springtime Arctic stratocumulus to modelled primary ice over the ice pack, marginal ice, and ocean

Abstract

<p><strong>Abstract.</strong> This study uses large eddy simulations to test the sensitivity of single-layer mixed-phase stratocumulus to primary ice number concentrations in the European Arctic. Observations from the Aerosol-Cloud Coupling and Climate Interactions in the Arctic (ACCACIA) campaign are considered for comparison with cloud microphysics modelled using the Large Eddy Model (LEM, UK Met. Office). We find that cloud structure is very sensitive to ice number concentrations, N_ice , and small increases can cause persisting mixed-phase clouds to glaciate and break up. <br><br> Three key sensitivities are identified with comparison to in situ cloud observations over the sea ice pack, marginal ice zone (MIZ), and ocean. Over sea ice, we find deposition-condensation ice formation rates are overestimated, leading to cloud glaciation. When ice formation is limited to water-saturated conditions, we find microphysics comparable to the aircraft observations over all surfaces considered. We show that warm supercooled (−13 °C) mixed-phase clouds over the MIZ are simulated to reasonable accuracy when using both the DeMott et al. (2010) and Cooper (1986) parameterisations. Over the ocean, we find a strong sensitivity of Arctic stratus to ice number concentrations. Cooper (1986) performs poorly at the lower ambient temperatures, leading to comparatively higher ice number concentrations (2.43 L<sup>−1</sup> at the cloud top temperature, approximately −20 °C) and cloud glaciation. A small decrease in the predicted N<sub>ice</sub> (2.07 L<sup>−1</sup> at −20 °C), using the DeMott et al. (2010) parameterisation, causes mixed-phase conditions to persist for 24 h over the ocean. However, this representation leads to the formation of convective structures which reduce the cloud liquid water through snow precipitation, promoting cloud break up. Decreasing the ice crystal number concentration further (0.54 L<sup>−1</sup>, using a relationship derived from ACCACIA observations) allows mixed-phase conditions to be maintained for at least 24 h with more stability in the liquid and ice water paths. Sensitivity to N<sub>ice</sub> is also evident at low number concentrations, where 0.1×N<sub>ice</sub> predicted by the DeMott et al. (2010) parameterisation results in the formation of rainbands within the model; rainbands which also act to deplete the liquid water in the cloud and promote break up.</p>

Relating large-scale subsidence to convection development in Arctic mixed-phase marine stratocumulus

“…The set up is the same as that used by Young et al (2017), whose study gives further details on the model itself. Momentum is conserved using the Piacsek-Williams (PW; Piacsek and Williams, 1970) centred difference scheme, whilst the total variation diminishing (TVD) monotonicity-preserving scheme of Leonard et al (1993), known as ULTIMATE, is used for scalar advection (Gray et al, 2001;Shipway and Hill, 2012).…”

“…Vertical profiles of potential temperature ( ), water vapour mixing ratio (Q vap ), and wind speed (U and V ) were implemented to initialise the model ( Fig. 1): these profiles were extracted from previous LEM runs of Arctic mixed-phase Sc, specifically from 10 h in the ocean case detailed by Young et al (2017), where a primary ice parameterisation derived from observations from the Aerosol-Cloud Coupling and Climate Interactions in the Arctic (ACCACIA) campaign was implemented. These fields give a stable BL experiencing strong (approximately 10-15 m s −1 ) N-S winds.…”

“…The control simulations apply no large-scale subsidence, apply a prescribed droplet number concentration (N drop ) of 100 cm −3 , and use the DeMott et al (2010) (hereafter, D10) parameterisation for primary ice nucleation. As in Young et al (2017), an approximation of the D10 parameterisation is used, where we assume an aerosol particle number concentration of 2.20 cm −3 (for implementation in the parameterisation) throughout the domain. (test 3,Sect.…”

“…Heterogeneous primary ice formation is represented using the D10 parameterisation with aerosol number concentrations calculated during the study by Young et al (2017). Previous studies (Harrington et al, 1999;Harrington and Olsson, 2001;Prenni et al, 2007;Morrison et al, 2012;de Boer et al, 2011;Young et al, 2017) have shown that the lifetime of springtime single-layer mixed-phase clouds at high latitudes is strongly dependent on N ice . Here, a lower (N ice = D10 × 0.5) and higher (N ice = D10 × 2) threshold are implemented to change the number concentration of modelled ice, and snow, particles.…”

“…In numerical models, mechanisms affecting the break-up of these Sc clouds -including glaciation (e.g. Harrington et al, 1999;Prenni et al, 2007;Young et al, 2017) or break-up into convective cumulus (as occurs in cold-air outbreaks, CAOs) -are often too efficient, leading to radiative biases in the polar regions (Trenberth andissue of premature glaciation of modelled mixed-phase Sc, often concluding that the cause is an overactive ice phase and strong influence of the Wegener-Bergeron-Findeisen (WBF) mechanism. The WBF mechanism causes a constantly changing, unstable microphysical structure; however, these clouds have been observed to persist for long periods of time, and thus they have the opportunity to move geographically.…”