Estimating the effect of clouds on the arctic surface energy budget

Abstract

Abstract. The relationship between cloudiness and sea ice thickness over the Arctic Ocean is examined using an idealized equilibrium energy budget model and a singlecolumn model (SCM) forced by incoming solar radiation, atmospheric poleward energy flux, oceanic heat flux, and sea ice divergence. The sensitivity of ice thickness to cloud perturbations in the SCM is qualitatively different from previous modeling studies, which did not allow the atmospheric temperature profile to respond to perturbations in cloudiness. It is shown that this restriction implicitly changes the poleward energy flux in model experiments and obscures the intrinsic effect of clouds on the arctic climate. In the present model, equilibrium ice thickness has a strong negative correlation with cloud radiative forcing at the top of the atmosphere and no correlation with cloud radiative forcing at the surface. The results demonstrate how local processes, such as the surface albedo feedback, affect the sensitivity of ice thickness to cloud perturbations and reduce its predictability. Exploratory model experiments suggest that interactions between the Arctic and the lower latitudes (via the poleward energy flux) could strongly influence the dependence of ice thickness on cloudiness. The impact of these interactions in the model was predicted qualitatively by considering how the radiative effect of clouds is partitioned between the atmosphere and the surface. The results demonstrate the importance of using cloud radiative forcing at both the surface and the top of the atmosphere when estimating the climatic effect of perturbation in cloudiness.

The effect of surface heat fluxes on interannual variability in the spring onset of snow melt in the central Arctic Ocean

“…This points out on the importance of clouds and air moisture. The difference in downward longwave radiation between overcast and clear skies is typically 70–100 W/m 2 [ Beesley , 2000; Intrieri et al , 2002; Wang and Key , 2005]. It is, however, not only the cloud fraction and thickness that control longwave radiation, but also the phase of clouds; water clouds have a significantly higher longwave emissivity than ice clouds [ Wang and Key , 2005; Pinto et al , 1997].…”

Ground-based remote sensing of thin clouds in the Arctic

“…Changes in Arctic cloudiness can have discernible effects on the surface energy budget (Wang and Key, 2003;Beesley, 2000;Kay et al, 2008Kay et al, , 2012. Lower level Arctic stratiform clouds are regarded as an especially important target for improved numerical simulations (Smith and Kao, 1996;Harrington et al, 2000;Francis and Hunter, 2007;Fridlind et al, 2007;Klein et al, 2009;Morrison et al, 2011).…”

“…While limited to thinner clouds, this approach is appealing because, from a climatological standpoint, it is downwelling thermal emission that plays a dominant role in the Arctic surface radiation balance (Beesley, 2000;Francis and Hunter, 2006). Retrievals are based on the part of the electromagnetic spectrum that is coupled to the physics in question.…”

An annual cycle of Arctic surface cloud forcing at SHEBA

“… Curry et al [1993] conducted sensitivity studies in which they varied the properties of clouds and found that the mean thickness of Arctic sea ice was very sensitive to cloud characteristics. Beesley [2000] also examined the relationship between clouds and Arctic ice thickness using an energy budget and a single column model in which he incorporated thermodynamic coupling of the atmosphere and surface. He showed this coupling was essential and that local feedbacks can affect the dependence of ice thickness on cloud perturbations.…”