Abstract
Abstract. The concept of cloud radiative forcing (CRF) is commonly applied to quantify the impact of clouds on the surface radiative energy budget (REB). In the Arctic, specific radiative interactions between microphysical and macrophysical properties of clouds and the surface strongly modify the warming or cooling effect of clouds, complicating the estimate of CRF obtained from observations or models. Clouds tend to increase the broadband surface albedo over snow or sea ice surfaces compared to cloud-free conditions. However, this effect is not adequately considered in the derivation of CRF in the Arctic so far. Therefore, we have quantified the effects caused by surface-albedo–cloud interactions over highly reflective snow or sea ice surfaces on the CRF using radiative transfer simulations and below-cloud airborne observations above the heterogeneous springtime marginal sea ice zone (MIZ) during the Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) campaign. The impact of a modified surface albedo in the presence of clouds, as compared to cloud-free conditions, and its dependence on cloud optical thickness is found to be relevant for the estimation of the shortwave CRF. A method is proposed to consider this surface albedo effect on CRF estimates by continuously retrieving the cloud-free surface albedo from observations under cloudy conditions, using an available snow and ice albedo parameterization. Using ACLOUD data reveals that the estimated average shortwave cooling by clouds almost doubles over snow- and ice-covered surfaces (−62 W m−2 instead of −32 W m−2), if surface-albedo–cloud interactions are considered. As a result, the observed total (shortwave plus longwave) CRF shifted from a warming effect to an almost neutral one. Concerning the seasonal cycle of the surface albedo, it is demonstrated that this effect enhances shortwave cooling in periods when snow dominates the surface and potentially weakens the cooling by optically thin clouds during the summertime melting season. These findings suggest that the surface-albedo–cloud interaction should be considered in global climate models and in long-term studies to obtain a realistic estimate of the shortwave CRF to quantify the role of clouds in Arctic amplification.
Highlights
Interdisciplinary research conducted within the last decades has led to a broader, but not yet complete, understanding of the rapid and, compared to midlatitudes, enhanced warming in the Arctic (Gillett et al, 2008; Overland et al, 2011; Serreze and Barry, 2011; Stroeve et al, 2012; Jeffries et al, 2013; Cohen et al, 2014; Wendisch et al, 2017)
Since the numerous interactions of physical processes, responsible for Arctic amplification, are intertwined and difficult to observe, climate models are needed to quantify the individual contributions of feedback processes to Arctic climate change (Screens and Simmonds, 2010; Pithan and Mauritsen, 2014)
The satellite-observed cloud-free conditions are in general more stable and drier compared to the cloudy regimes assumed to be cloud free, which affects the obtained longwave cloud radiative forcing (CRF) values and results in inconsistencies when compared to climate model longwave CRF estimates (Allan and Ringer, 2003), where the cloud-free irradiances are calculated by neglecting clouds in the radiation scheme
Summary
Interdisciplinary research conducted within the last decades has led to a broader, but not yet complete, understanding of the rapid and, compared to midlatitudes, enhanced warming in the Arctic (so-called Arctic amplification) (Gillett et al, 2008; Overland et al, 2011; Serreze and Barry, 2011; Stroeve et al, 2012; Jeffries et al, 2013; Cohen et al, 2014; Wendisch et al, 2017). The clouds modify the surface energy budget by the two competing effects of longwave warming and shortwave cooling This results in two typical states of thermodynamic profiles (Tjernström and Graversen, 2009) and longwave radiative irradiances (Stramler et al, 2011; Wendisch et al, 2019) observed in the Arctic winter. Radiative transfer simulations enable us to evaluate in detail the processes involved in the cloud-related surface albedo changes Both processes (i and ii) have been parameterized for snow and ice, e.g., by Gardner and Sharp (2010) based on simulations. This allows us, in combination with the derived longwave CRF, to analyze the general concept of a warming or cooling effect of clouds on the sea ice during the campaign and to illustrate the impact of the surface-albedo– cloud interaction for the total balancing effect of clouds in the springtime MIZ This allows us, in combination with the derived longwave CRF, to analyze the general concept of a warming or cooling effect of clouds on the sea ice during the campaign and to illustrate the impact of the surface-albedo– cloud interaction for the total balancing effect of clouds in the springtime MIZ (Sect. 6)
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